University of Southern California Dissertations and Theses

Parental mediation of adolescents' technology use at home

(USC Thesis Other)

Parental mediation of adolescents' technology use at home

PDF

Download a page range

Download transcript

Copy asset link

Request this asset

Transcript (if available)

Content Running head: PARENTAL MEDIATION OF TECHNOLOGY USE 1

PARENTAL MEDIATION OF ADOLESCENTS’ TECHNOLOGY USE AT HOME

By

Wanchanit Vongkulluksn

A Dissertation Presented to the
FACULTY OF THE USC GRADUATE SCHOOL
UNIVERSITY OF SOUTHERN CALIFORNIA
In Partial Fulfillment of the
Requirements for the Degree
DOCTOR OF PHILOSOPHY
(EDUCATION)

December 2016

PARENTAL MEDIATION OF TECHNOLOGY USE 2
DISSERTATION COMMITTEE MEMBERS
Robert Rueda, Ph.D.
Dissertation Chair
Rossier School of Education
University of Southern California

Gale Sinatra, Ph.D.
Rossier School of Education
University of Southern California

David Schwartz, Ph.D.
Dornsife College of Letters, Arts and Sciences; Department of Psychology
University of Southern California

PARENTAL MEDIATION OF TECHNOLOGY USE 3
TABLE OF CONTENTS
ABSTRACT....……………………………………………………………………………………………..7
CHAPTER 1: INTRODUCTION….........………………………………………………………………….8
CHAPTER 2: LITERATURE REVIEW….……….....………………………………………………….. 14
CHAPTER 3: METHODOLOGY.……..………………………………………………….…………….. 61
CHAPTER 4: RESULTS…………………………………………………………………………….……76
CHAPTER 5: DISCUSSION….…………………………………………………………………………115
REFERENCES………………………………………………………………………………...…………124
TABLES AND FIGURES……………………………………………………………………………….145
APPENDICES…………………………………………………………………………………………...176

PARENTAL MEDIATION OF TECHNOLOGY USE 4
LIST OF TABLES
Table 1: Descriptive Demographic Data…………………………………………………………………145
Table 2: Descriptive Statistics of Parental Mediation Behaviors, Restrictive Mediation…………..........146
Table 3: Descriptive Statistics of Parental Mediation Behaviors, Monitoring and Technical Mediation.147
Table 4: Descriptive Statistics of Parental Mediation Behaviors, Supportive Mediation……………….148
Table 5: Confirmatory Phase, Regulatory Mediation Measurement Models Fit Indices………………..150
Table 6: Exploratory Phase, Principal Factor Analysis with Oblique Promax Rotation of Monitoring
and Technical Mediation Items………………………………………………………………………….153
Table 7: Exploratory Phase, Regulatory Mediation Measurement Models Fit Indices…………………154
Table 8: Confirmatory Phase, Supportive Mediation Measurement Models Fit Indices………………..156
Table 9: Exploratory Phase, Principal Factor Analysis with Oblique Promax Rotation of Supportive
Items……………………………………………………………………………………………………..158
Table 10: Exploratory Phase, Supportive Mediation Measurement Models Fit Indices...…….………..159
Table 11: Chi-square Difference Test………………………………………………………….………..159
Table 12: Interviewed Parents Characteristics………………………………………………….……….161
Table 13: Measurement Invariance Omnibus Test of Covariance Matrices Equality………….……….162
Table 14: Measurement Invariance Analysis of Configural, Metric, Scalar, and Strict Invariance….....162
Table 15: Reliability Statistics of Measures…..………………………………………………………...167
Table 16: Pearson’s Correlations………………………………………………………………………..168
Table 17: Direct Effects Only Model Parameters (Standardized Regression Coefficients)…………….169
Table 18: Path Analysis Effect Decomposition, Restrictive Mediation model…………………………170
Table 19: Path Analysis Effect Decomposition, Monitoring model…………………………………....172
Table 20: Path Analysis Effect Decomposition, Supportive Mediation model………………………....174

PARENTAL MEDIATION OF TECHNOLOGY USE 5
LIST OF FIGURES
Figure 1: Restrictive Mediation Measurement Model………..…………………………………….……151
Figure 2: Scree Plot of Monitoring and Technical Mediation Items…………………………………….152
Figure 3: Monitoring Measurement Model………………………………………………………………155
Figure 4: Scree Plot of Supportive Mediation Items……….,.…………………………………………...157
Figure 5: Supportive Mediation Measurement Model…………………………………………………...160
Figure 6: Fisher Information and Standard Error Plot, Restrictive Mediation Scale…………………….163
Figure 7: Fisher Information and Standard Error Plot, Monitoring Scale……………………………….164
Figure 8: Fisher Information and Standard Error Plot, Supportive Mediation Scale……………………165
Figure 9: Fisher’s Information and Standard Error Plot, Technology Knowledge Measure…….………166
Figure 10: Path Model with Restrictive Mediation as IV (Standardized Loadings)…………….……….171
Figure 11: Path Model with Monitoring as IV (Standardized Loadings)………………………………..173
Figure 12: Path Model with Supportive Mediation as IV (Standardized Loadings)…………………….174

PARENTAL MEDIATION OF TECHNOLOGY USE 6
LIST OF APPENDICES
Appendix A: Domains of Digital Literacy…………………………………………………….176
Appendix B: Definitions of Active Co-use and Related Constructs…………………………..178
Appendix C: Positive Uses of ICT…………………………………………………………….180
Appendix D: Supportive Technology Mediation…………………….………………………...181
Appendix E: Survey Items……………………………………….…………………………….188
Appendix F: Confirmatory Factor and Path Models……………..…………………………….200
Appendix G: Interview Questions………………………………..…………………………….203

PARENTAL MEDIATION OF TECHNOLOGY USE 7
Abstract

Technology has become an indispensable tool for learning, with technology integration
widespread in classrooms throughout the US. However, research in educational technology has
consistently pointed to the disadvantaged position of low SES students in terms of how they use
and benefit from technology. Researchers have attributed the differential benefits of technology
access to low SES parents’ lack of effective technology mediation strategies at home. There is
little empirical support for such claims, suggesting that research is needed. In addition, there is a
need to investigate motivational and contextual factors that influence these mediation behaviors,
above and beyond social and economic constraints. In response to this gap, the purpose of this
study was to examine ways in which low income parents support adolescents’ digital literacy
development and how these mediation choices are related to motivational (including self-
efficacy for mediation and role beliefs) and contextual (including perception of the child’s
technical expertise, as well as parents’ technology knowledge and usage) factors. Using factor
analysis (n=291), results suggest a three-factor solution for technology mediation behaviors,
including (1) restrictive mediation, (2) technical and non-technical monitoring, and (3)
supportive mediation. Additionally, path analysis (n=291) shows that contextual factors such as
parents’ technology knowledge are mediated by motivational factors in their predictive
relationship on monitoring and supportive mediation behaviors, whereas these contextual factors
only have direct relationships with restrictive mediation. Analyses of parent interview data (n=8)
also illustrates that low SES parents in the sample are active mediators of technology, engaging
in diverse mediation strategies. This study provides some evidence to counter current deficit-
oriented narratives regarding the influence of home environments on adolescents’ digital literacy
development in low SES populations.
PARENTAL MEDIATION OF TECHNOLOGY USE 8
CHAPTER 1: INTRODUCTION
With an ever increasing presence of technology, the skills students need to successfully
navigate the demands of higher education, workplaces, and civic engagement are also changing.
The so-called industrial economy has been replaced by the information economy, with
technology replacing routine manual tasks and requiring most workers to master various
information systems as well as to face the challenge of learning new ones as technologies are
continually being upgraded (Levy & Murnane, 2007; Kay, 2010). At the same time, a working
knowledge of information and communication technologies (ICTs)
1
is also required for citizens
to make informed decisions about technology-related political issues as well as to participate in
civic engagement activities that are recruited and/or carried out over the internet (National
Research Committee, 2000). These demands require children to develop new digital literacy
2

skills in order to become successful in today’s technology-driven culture. In response, a new
model is now advocated in education, where acquisition of traditional content knowledge is
integrated with 21
st
century skills such as global awareness, information and media literacy, and
problem solving competence using digital tools. These demands are also reflected in increased
spending on technology in schools, as well as on the digital literacy focus of the current
Common Core State Standards (Johnson, 2013; National Governors Association, 2010).

1
ICTs as defined in this paper are related to the definition given by Warschauer and Matuchniak (2010), which
includes technologies that enabled communication between people and retrieval of information from remote
resources. However, this paper excludes television as an ICT resource because of the conceptual distinction between
parents’ mediation of television and those of other ICTs (Livingstone & Helsper, 2008). Also, the decision to define
new technologies in terms of ICT instead of “new media” is deliberate as the definition of “new media” entails novel
usages of media that is often ambiguous and value-laden (Warschauer & Matuchniak, 2010; also see definition of
new media in Jenkins, 2009).
2
The term digital literacy as used in this paper refers to technical skills as well as dispositions and values that
facilitate constructive uses of ICTs (Lankshear & Knobel, 2011). Appendix A includes different types of literacy
skills related to ICT usage. Digital literacy is used in this paper in the broad sense that also includes new media
literacy.
PARENTAL MEDIATION OF TECHNOLOGY USE 9
In addition to shifting skill demands, the rapid proliferation of technology is also
revolutionizing the way knowledge is taught and learned. Learners now assume greater control in
what, where, when, and how they learn, as educational opportunities and knowledge sources
abound in digital platforms (Collins & Halverson, 2009). To the extent that was not possible in
traditional classrooms, students can decide what content is valuable for learning, how much time
they want to spend learning it, as well as the type of help they need to reach learning goals. In
addition, technology can often provide scaffolding and interactive feedback that enhances
learning above and beyond what one teacher can do in a crowded classroom (Belland, 2014).
Information technology also allows new avenues of content production and self-expression, as
students are able to create multimedia projects that could be disseminated to a real audience and
to receive authentic feedback from diverse experts and consumers (Collins & Halverston, 2009).
Even ICT-related activities traditionally regarded as unproductive such as game play (e.g.
through educational simulations and Massively Multiplayer Online Games, or MMOGs) have
been demonstrated to increase critical thinking, literacy skills, and collaborative behaviors.
(Horwitz & Christie, 2000; Dede et al., 2004, Gee, 2003). Furthermore, recreational uses of
technology have the possibility to engage youths in civic culture, develop their personal
identities, and encourage social connection and contribution through communication with others
across the world who share the same interests and values (Livingstone, 2003; Jenkins, 2009).
However, the potential of technology to positively influence cognitive and social
development is made complex by issues of inequity. On the one hand, technology has the
capability to level out the playing field, as traditionally disadvantaged students such as those
from minority or low-income homes can access the same information society as their more
advantaged peers (Warschauer, Knobel, & Stone, 2004). On the other hand, unequal access and
PARENTAL MEDIATION OF TECHNOLOGY USE 10
usage of technology may perpetuate existing gaps in both academic and social domains. Recent
research has lent support to the latter scenario, with social stratification apparent in the
differential benefits of ICT usage. Even as access issues are mitigated (in reality through falling
prices of technologies and in research studies through experimental design in which technology
access was granted to some or all student participants from low income families), research
showed that low SES students benefit less from home computer access compared to more
affluent peers (Attewell & Battle, 1999; Sharley et al. 2007), with some showing a negative
association between access and academic achievement for students from low income homes
(Vigdor & Ladd, 2010; Malamud and Pop-Eleches 2011). This adverse trend is supported by
data on differentiated usage of technology, with low SES students shown to use computers less
frequently for homework (Becker, 2000), spend more class time on nonacademic computer use
(Warschauer, Knobel, & Stone, 2004), use word-processing and multimedia software less
frequently (DeBell & Chapman, 2006), and pursue interest-driven activities online through
consumption rather than creation (Attewell & Winston, 2003; Jenkins 2009) when compared to
their high SES counterparts. The digital divide issue is particularly salient for children in their
adolescent years, given research showing a wide gap in the ICT usage of children in this age
group (Ito et al., 2010).
While research in ICT usage have consistently pointed to the disadvantaged position of
low SES students in terms of technology usages and benefits, these results need to be interpreted
with caution because they tended to treat the low income population as a monolithic group and
overlook additional complexities that may be present within these homes. In particular, past
researchers have attributed the differential benefits of technology access on low SES parents’
PARENTAL MEDIATION OF TECHNOLOGY USE 11
lack of effective mediation
3
strategies, citing that in more advantaged homes “student computer
use [may be] more effectively monitored and channeled toward productive ends” (Vigdor &
Ladd, 2010, p. 29). But, far from providing support for such claims, past studies that directly
examined low SES parents’ technology mediation have defined it in terms of technology
supervision and, unlike those sampling from high SES communities, have not identified
mediation practices related to digital literacy development. Despite this lack of empirical
support, the prevailing narrative seems to cast low income parents as poor mediators of
technology, with their supposed ineptitude leading their children to use ICTs in ways that are
ineffective for academic and digital literacy growth. In contrast to these views, studies in a
related field of traditional literacy have found that there is variability in the extent to which low
SES parents provide home environments conducive to literacy development (Foster, Lambert,
Abbott-Shim, McCarty, & Franz, 2005; Farver, Xu, Lonigan, & Eppe, 2012) as well as
variability in the literacy achievement of children from low SES homes (Justice & Ezell, 2001;
Welsch, Sullivan, & Justice, 2003; Cabell, Justice, Konold, & McGinty, 2011). In the same vein,
researchers need to take into account the possibility that low SES parents are not homogenous
with regards to how and how much they mediate their children’s technology use.
To further illuminate the interplay between parents, children, and technology, there is
also a need to examine parental factors that influence their mediation behaviors, above and
beyond social and economic constraints. In particular, motivation factors such as parents’ self-
efficacy and role construction have been shown to influence parental behaviors, with numerous

3
The term “mediation” as used here is consistent with the definition of parental technology mediation behaviors as
defined by parental mediation theory (Livingstone & Helsper, 2008). It refers to the ways parents regulate and
support children’s technology use at home. This term is unrelated to the statistic term “mediation” that is used to
describe relationships among variables. The word “mediation” in the statistic sense will also be used later on in the
paper when relationships among variables of interest are discussed.
PARENTAL MEDIATION OF TECHNOLOGY USE 12
studies citing the importance of these motivational constructs on parents’ literacy practices at
home (Drummond & Stipek, 2005; Waanders, Mendez, & Downer, 2007; Weigel, Martin, and
Bennett, 2006). Empirical studies on how motivational factors influence parental technology
mediation is glaringly absent in educational technology research at present. This represents a
crucial gap to be filled in order to look beyond social stratifications as sufficient explanations for
disparities in technology mediation. A more nuanced perspective also allows mediation
differences within this disadvantaged group to be traced back to their motivational roots,
shedding light on the inherent resiliency of many parents who have traditionally been labeled as
ineffective or neglectful in their technology mediation behaviors. This issue is especially salient
for parents of adolescents due to the vastly different usage profiles of children in this age group
(Ito et al., 2010).
Statement of Purpose
In response to this gap in current research, the overall purpose of this study is to examine
ways in which parents from low income communities support adolescents’ digital literacy
development and how these mediation choices are related to motivational and contextual factors.
Two sub-objectives underlie this goal. First of all, this study aims to make theoretical
contributions to our collective knowledge about digital literacy development and home factors
that enhance this process by examining how parents from low income communities who may
have little monetary and/or technical resources support their adolescent children’s ICT usage.
Particularly, the present study intends to investigate the extent to which parents in this
sociocultural context execute technology mediation behaviors found by previous research, as
well as how these different behaviors can be grouped to form broad categories of mediation
types for this population. The second objective is to investigate motivational and contextual
antecedents of these technology mediation behaviors. Specifically, the purpose is to analyze how
PARENTAL MEDIATION OF TECHNOLOGY USE 13
parents’ technical knowledge, frequency of ICT usage, perception of their child’s technical
expertise, self-efficacy for technology mediation, and perception of their role in digital literacy
education predict their mediation behaviors. These objectives reflect an effort to investigate the
possible heterogeneity with which parents from similar socioeconomic backgrounds support their
children’s ICT usage as well as the nuance of how different parental factors influence these
mediation choices. This study aims to look beyond social stratification as justification for the
unrealized potential of ICT access, moving towards the view of technology mediation as a
complex process that encompasses antecedents at the parent, child, and institutional levels.
This dissertation outlines a study that addressed this need to study low SES parents’
mediation of adolescents’ technology use as well as how motivational and contextual factors
predict these behaviors. The following chapter begins by describing relevant theoretical
foundations and current empirical studies that have addressed this issue. The next chapter then
outlines methods that were used to examine how low income parents mediate technology at
home as well as how different factors predict the extent and nature of parental technology
mediation behaviors. Finally, results found from data analysis are presented and implications of
these findings are discussed.

PARENTAL MEDIATION OF TECHNOLOGY USE 14
CHAPTER 2: LITERATURE REVIEW
Theoretical Foundations
Sociocultural Theory
Sociocultural theory is relevant to adolescents’ technology learning at home because it
posits that learning takes place in the social sphere through interactions with others in
meaningful cultural practices (Vygotsky, 1980; Rogoff, 1998). The process of learning is viewed
not as a passive reception of information from others or as an individual endeavor to acquire
outside knowledge, but as “the transformation of socially shared activities into internalized
processes” (Rogoff, 1998; John-Steiner & Mahn, 1996, p. 193). That is, developmental processes
have origins in the social realm. Practices are observed, practiced, and experienced in social
engagements with others before being internalized within the individual. This internalization
process is mediated by cultural tools such as language, through a process in which social verbal
interactions (i.e. external speech) that represent culturally situated systems of thought are
internalized into an individual’s psychological realm via inner speech (Mahn, 1999). This
process is also made additionally complex as the self-world interface not only occurs within the
immediate social environment, but also with past historical contexts since cultural activities in
the present are reflections of past activities performed by countless preceding generations
(Kozulin, 1998). Learning is, then, not a process whereby individuals reinvent solutions to
problems, but one in which people appropriate “methods of action” and tools already existing in
a particular culture (p.59). It should be noted also that this learning process is not only a
transmission of knowledge from the social to the psychological realm, but also a transformation
of culture as individuals engage in co-constructing the meanings and methods of social practices
(Gutierrez, 2002).
PARENTAL MEDIATION OF TECHNOLOGY USE 15
Guided participation and legitimate peripheral participation. An important facet of
sociocultural theory especially salient to home-based learning environments is the view that
learning is not an isolated, reified process, but occurs through participation in social practices
(Rogoff, 1998; Lave & Wenger, 1991). Rogoff (1990) likened the sociocultural development
process to a model of apprenticeship, in which children play active roles in organizing their
development, with their more expert partners providing support and arranging tasks that foster
both cognitive development as well as a growing sense of being embedded in a community of
practice. The apprenticeship system entails guided participation in which masters provide
supportive structures for novices to perform activities that expose them to the sociocultural order
of their world. The masters possess “a broader vision” of the tacit processes, rules, and values
within their shared sociocultural context and seek to gradually assimilate novices to these
perspectives by allowing them to participate in parts of social activity they can handle (p. 39).
Lave and Wenger (1991) also described a related process of “legitimate peripheral
participation,” which emphasizes that children’s “peripheral” participation in cultural practices
retains the full legitimacy in terms of access to resources and social structures. In this
framework, the master-novice relationship is recast as the relationship between “old-timers” and
“new-comers,” where learning is not a structured activity but occurs through growing
involvement with the everyday, routine practices of life. Similar to the process of guided
participation, new-comers gradually become full-participants in sociocultural practice as they
learn the structures, interactions, and values embedded within their particular culture.
The concepts of guided and legitimate peripheral participation have been used to view
children’s technology learning, in particular by Plowman and associates (2008; 2010a; 2010b) in
their examination of preschool children’s learning with and about technology at home. They
PARENTAL MEDIATION OF TECHNOLOGY USE 16
found that parents characterized their children’s technology learning as “just picking it up”
(Plowman, McPake, & Stephen, 2008, p. 2). Parents engaged in technology use with children in
real life activities, providing examples for imitation while children participate in some aspects of
technology use they can perform themselves (e.g. turning items on, clicking links to navigate
websites). These learning processes occurs within natural parent-child exchanges and are so
seamless that many parents express surprise in how much their children pick up in the process of
participating in routine family activities. In addition, the researchers documented that parents
impart four areas of knowledge related to technology: (1) acquiring operational skills; (2)
extending knowledge of the world such as using technology for development of print literacy and
numeracy; (3) developing dispositions to learn through opportunities for independent learning
and accomplishments that lead to increased confidence; and (4) gaining cultural awareness of the
roles of technology in the family context and the outside world. These findings parallel the
sociocultural model of learning where discrete technical knowledge is not learned in isolation but
are internalized alongside culturally situated beliefs about how technology fits into the fabric of
life.
Another body of literature that sheds light on how children learn about technology
through participating in parents’ cultural milieu is from media studies which reference parental
mediation theory. According to this theory, parents engage in four types of mediation behaviors,
including (1) active co-use, or parents using technology with the child while providing guidance
for appropriate behaviors and media interpretations; (2) interaction restriction, or imposing rules
regarding the child’s communicative activities on ICT platforms; (3) technical restriction, or
restricting access to certain activities using specialized software programs; and (4) monitoring, or
checking up on the child’s ICT activities after use (Livingstone & Helsper, 2008). Building on
PARENTAL MEDIATION OF TECHNOLOGY USE 17
these categories of mediation behaviors, Clark (2013) elaborated on how parents’ technology
mediation behaviors vary in different sociocultural environments. For example, she found that
low SES parents often co-use technology with their children in a manner that maintains positive
relationships within the family, while high SES parents tend to discourage nonproductive
technology use. In this way, children’s technology learning is viewed from a sociocultural
perspective as occurring alongside a guided exploration of how technology should be used
within one’s cultural context. Parents can be said to possess a broader view of how technology
fits into everyday life and they gradually impart this perspective to their children by means of
mediation.
Higher mental functions and psychological tools. In addition to its ability to explain
development within situated cultural contexts, another aspect of sociocultural theory that makes
it directly relevant to the issue of parental technology mediation is how it accounts for
psychological processes in relation to cultural tools. According to Lev Vygotsky, there are two
classes of psychological processes: lower and higher mental functions (Kozulin, 1998; Mahn,
1999). Lower or natural functions consist of biological processes such as perception,
spontaneous attention, and memory that predispose the child to development (Mahn, 1999). In
contrast, higher mental functions are those that consist of conscious, cultivated psychological
processes such as abstract reasoning, decision making, and voluntary attention. The goal of
development is to transform lower into higher mental processes through internalization of social
activities.
The transformation of lower to higher mental processes is mediated by the appropriation
and use of culturally-built psychological tools. The concept of psychological tool is made distinct
from what is referred to as material tool, such that material tools are used to control external
PARENTAL MEDIATION OF TECHNOLOGY USE 18
objects whereas psychological tools are used to control individuals’ behavior and cognition
(Kozulin, 2001). Psychological tools have physical manifestations as “symbolic artifacts,” like
signs, symbols, mnemonic devices, and language (p.14). For example, a material tool like an axe
is used to change the properties of a tree through the act of cutting, while a psychological tool
like finger counting is used to aid the abstract processes of addition and subtraction.
In relating the concept of higher mental processes to digital literacy, thriving in today’s
technology-driven society requires higher psychological functions that did not exist before the
vast explosion of ICTs. One such mental process is the novel ways in which individuals leverage
distributed cognition by recognizing that knowledge is distributed across platforms and
possessing the ability to utilize devices like external memory and databases to access such
knowledge (Jenkins, 2009; Pea, 1993). Although distributed cognition arguably existed before
the advent of technology, especially as sociocultural theory posits that social and cognitive
functions are interdependent (Rueda & Moll, 1994), successful functioning in modern societies
requires new ways of tapping into distributed knowledge resources. Thinking and creating new
content rely on one’s ability to pull information from remote artifacts that expands human’s
cognitive capacity. Accessing distributed cognition today involves connecting with remote
expert practitioners via communication technologies as well as leveraging non-human tools like
the spell-checker, calculator, and information databases. The key to this process is for people to
understand when they need experts as well as how to access and use them to accomplish
cognitive tasks. Leveraging distributed cognition is a conscious activity that is learned through
interactions with others within a particular sociocultural context. As such, it can be viewed as a
higher mental process that needs to be mediated through new psychological tools
4
.

4
For a full list of other potential higher mental processes required in a technology-driven world, see Jenkins et al.
2006, p.4
PARENTAL MEDIATION OF TECHNOLOGY USE 19
As technology creates new social environments that require new mental processes, it also
provides the psychological tools needed to mediate these higher functions. Although yet to be
explored in past literature, I posit that technology usage needs to be conceived in terms of
whether it is used as a material or psychological tool. For example, technology can be used to
enhance external processes such as allowing faster communication between people and quicker
production of goods. In contrast, technology can also be used as a psychological tool through the
ways in which it mediates higher mental functions as well as transforms how people think and
behave. For example, websites like dictionary.com and Wikipedia can mediate mental processes
related to distributed cognition, helping people extend their cognitive capabilities and leverage
outside expert knowledge in their thinking. The distinction between the use of technology as
material vs. psychological tools is necessary because it informs how parents and educators can
teach children and new users of technology the way to use ICTs appropriately for different
purposes. For example, the way we teach children about how to use technology to leverage faster
communication should be different from how we teach them to use distributed cognition
resources since effective use of the latter requires more than operational skills. It also requires an
understanding of how information provided by these tools can extend and transform their
knowledge as well as a discernment of how and when these tools should be used. It is also
important to note that the reinterpretation of technology as possible psychological tools extends
Vygotsky’s conception of psychological tool as symbolic devices. Instead, technologies as
psychological tools are specialized means of disseminating symbolic devices in ways that can
also impact cognition. This extension is necessary in order to perceive technology as offering
limitless possibilities for use as psychological tools, possibilities that are realized within
sociocultural contexts as individuals appropriate them in culturally specific ways.
PARENTAL MEDIATION OF TECHNOLOGY USE 20
However, although technology can be used as psychological tools, technology access
does not always translate to its use as mediators of cognitive processes. Just as performing math
drills does not directly translate to the type of problem solving ability that generalizes to solving
unfamiliar math problems, access to online databases, for example, does not directly translate to
its use as a psychological tool to mediate the effective use of distributed resources. It is at this
junction between the availability of psychological tools and its appropriation as such that human
mediators play a role in cognitive development.
Noting Vygotsky’s lack of elaboration on the specific activities of human mediators,
Kozulin (2001) explained the role of human mediators in assisting children’s appropriation of
cultural tools. According to Kozulin, psychological tools are cultural artifacts that can only be
acquired with the help of human mediators in mediated learning experiences (MLEs)
characterized by three criteria: (1) intentionality, psychological tools are acquired only with
intentional action by the human mediator or else learners will perceive the use of tools only at
the rote, operational content level (akin to the ability to complete math drills); (2) transcendence,
psychological tools need to be taught as “generalized instruments” capable of being applied to
different tasks and contexts; and (3) mediation of meaning, psychological tools need to be
perceived as behaviors performed with a specific purpose and meaning rather than consisting of
a series of unconnected steps (p. 86-7). For example, online databases can mediate effective uses
of distributed resources when a human mediator intentionally demonstrates that databases are
one of many ICT instruments that can be used to pool and leverage expertise across time and
space, with the end goal of allowing individuals to synthesize knowledge from these resources.
With repeated exposure and chances to perform some components of the task in social practice,
children can come to use databases as an instrument that allows access to distributed cognition.
PARENTAL MEDIATION OF TECHNOLOGY USE 21
Without such intentional MLE, the child may only perceive databases in the narrow sense that
they provide information. Such unmediated view may manifest as the rote memorization that, to
use a database, one needs to click on a specific icon, type the prompt as given in the task, and
copy verbatim the answer that appears first on the screen.
From the sociocultural view, the lack of mediation for some psychological tools may not
be the result of oversight or neglect by human mediators, but rather a result of misalignment
between culturally specific modes of thinking and learning (Kozulin, 2001). Kozulin gave an
example of Hmong women whose education prior to entering the United States consists of
learning how to sew the textile art “paj ntaub” through a process of imitation, copying, and
correcting mistakes (p. 104). When these women enter language classrooms in the US where
decontextualized problem solving and spontaneous writing are valued, they find themselves
lacking the mediated learning experiences that support using language as a psychological tool to
fulfill such culturally-distant tasks. This distinct contrast between the cultural milieus of the
Hmong people and the United States serve to point out that psychological tools are cultural
artifacts and depend on the values and methods of functioning in a particular culture.
In relation to parental technology mediation, a benefit of using concepts of psychological
tools and the associated higher mental functions as lens through which to study technology
learning is due to the way that these concepts are less value-laden than the concept of digital
literacy. Just as the term “literacy” has always been imbued with values of the culturally
dominant group in a diverse setting like the United States, the concept of digital literacy is also
culturally charged as competencies aligned with those valued by the mainstream group and
educational institutions are regarded as necessary for full participation in society (Heath, 1991).
Thus, it is not surprising that the extent to which children possess these digital literacy skills and
PARENTAL MEDIATION OF TECHNOLOGY USE 22
contribute to the ICT participatory culture differ across socioeconomic lines (Jenkins et al.,
2009). In contrast, the notion of psychological tools makes explicit that how parents mediate (i.e.
as human mediators) children’s appropriation of technology is dependent on their own modes of
interaction with technology and how they have adapted technology use to thrive in their
particular social context.
Socially constructed affordances. The idea that technology usage is tied to culturally
situated practice is directly related to the concept of socially constructed affordances of
technology. The term affordance is first used by Gibson (1989) to refer to the relationship
between organisms and objects that is based on the organisms’ needs as well as their perception
of opportunities provided by the object (Hammond, 2010). The capability to use an object,
therefore, depends not only on the physical properties of the object, but also on the user’s
perceptions of its applicative possibilities (Carr, 2000). Hammond (2010) offered an example in
which a tree may afford sustenance for some animals and a hiding place for others according to
their needs. However, if the animal is too short to reach leaves and branches, its perception of the
opportunities that the tree affords changes. It may not perceive that the tree can provide leaves as
food, for example. So, although the physical properties of the tree remain the same, but the
animal’s utilization of the tree changes according to its needs and affordance perception.
Viewing the concept of affordance through a sociocultural lens, theorists have pointed
out that affordances not only refer to an individual’s perception of an object’s applicability but
also the cultural and historical contexts that shape such perception (Carr, 2000; Greeno, 1994). In
relation to technology use, the affordances of technology are socially constructed and negotiated
through how it is used in social practice (Rowe & Miller, 2015). Socially constructed
affordances, then, influence how people use technological tools in their everyday business of
PARENTAL MEDIATION OF TECHNOLOGY USE 23
living. In relation to parental mediation of technology, children participate in the social practice
of technology usage with parents and come to perceive affordances of technology in ways that
parallel their parents’ perception. Meanwhile, parents’ affordance perception influence how they
provide the mediated learning experience needed to utilize technology as psychological tools.
Parents’ own perception of how technology can support higher mental functions directly impacts
how they mediate these tools to their children. For example, while high SES parents may
mediate the use of technology as a tool to support the type of network thinking previously
mentioned, low SES parents may mediate ICT usage to support other higher mental functions
like the type of community in-group support some researchers have found to be prevalent in low
income communities (Clark, 2013).
Scaffolding by more knowledgeable others. In addition to differences in the perceived
affordance of technology, the way in which parents mediate their children’s use of technology is
also made additionally complex by the fact that some parents possess less digital competence
compared to their adolescent children (Katz, 2010; Plowman, McPake, & Stephen, 2010). This
challenges the traditional view that “masters” or “old-timers” possess both a broader view of
how social practices fit within the culturally-specific ways of living as well as the skills to
perform the tasks within those social practices. In contrast to this view, parents may possess
broader perspectives of how technology should be used in social practice, but children may in
fact possess more technical knowledge (i.e. ICT literacy skills).
Related to this issue, a more in depth examination of how “more knowledgeable” others
support, or scaffold, learners’ development reveal that this process entails more than
transmission of knowledge (Wood et al., 1976). In their original conception of scaffolding,
sociocultural researchers Wood and associates listed six aspects in the scaffolding process,
PARENTAL MEDIATION OF TECHNOLOGY USE 24
including (1) recruitment of interest in the task as well as adherence to task requirements; (2)
reduction of degrees of freedom by simplifying the task to fit the learner’s ability level; (3)
direction maintenance by keeping learners’ attention on task; (4) marking critical features
through helping learners recognize the difference between their self-made products and the
desirable outcome; (5) frustration control through verbal encouragements and assurance of
learners’ capabilities; and (6) demonstration by modelling the idealized outcome or completing
leaners’ partially worked out product (p.98). Other researchers have since added additional
aspects, including the shared understanding of instructional goal (intersubjectivity), dynamic
adjustment of the task according to the learner’s ability, fading of support, and transfer of
responsibility from the teacher to the learner (Puntambekar & Hubscher, 2005; Belland, 2014).
In examining these scaffolding aspects, it becomes clear that the scaffolding process
includes practices that do not require knowledge of the target content, such as recruiting and
maintaining learners’ attention, demarcating goals to be achieved, and highlighting salient
features of the task to be worked on. In relation to parental technology mediation, it is in fact
possible for parents with less technical skills than their children to carry out certain aspects of the
scaffolding process. Specifically, parents can encourage children to participate in technology-
related activities that parents themselves do not have the capability to perform. After children’s
interest and attention are recruited by parents, other resources such as online experts and tools,
school resources, and peer knowledge can be tapped to provide cognitive support for learning.
The role of parents in partially scaffolding learning tasks is akin to the process of distributed
scaffolding as examined in museum or blended learning environments where the role of the
teacher or parent is to help point out which task is important and should be taken up as an
objective for learning (Tabak, 2004; Pea, 2004). The cognitive support via demonstration and
PARENTAL MEDIATION OF TECHNOLOGY USE 25
transfer of responsibility are instead carried out by other agents (such as computer programs in
blended learning and signage or models in the museum environment). By garnering children’s
interest to participate in specific technology practices, parents gradually convey value
perceptions of tasks and how technology currently fits into the lives of the modern person.
Although parents can also be viewed as the “new-comer” to the technology-laden world in a
sense that some do end up learning more about technology usage in the scaffolding process (i.e.
technology brokering; Katz, 2010), children still gain important perspectives about the
sociocultural context in which they are embedded. This more complex variation of scaffolding
can be seen as a necessary way that parents adapt to the changing cultural landscape due to rapid
technological evolution.
Strengths and limitations of sociocultural theory. A major strength of sociocultural
theory in its application to parental technology mediation is how it provides a framework for
understanding informal learning contexts like the home environment. The emphasis of
development occurring through social practice parallels the way many parents interact with their
children and technology, focusing less on direct instruction and more on learning by doing
(Plowman, McPake, & Stephen, 2008; Barron et al., 2009). Another major contribution of
sociocultural theory is the way in which the concept of psychological tools can be applied to
technology use. The concept of psychological tools explicitly represents tools that are culturally
built and mediated, which directly applies to how digital technologies are created and used.
Sociocultural theory, therefore, lends a useful theoretical lens for examining how technology is
differentially used in a traditionally disadvantaged population, such as those from low income
communities.
PARENTAL MEDIATION OF TECHNOLOGY USE 26
However, some limitations stem from the exclusive use of sociocultural theory to explain
parental technology mediation. Sociocultural theory is limited in its ability to explain cognitive
and motivational processes that affect how parents choose certain mediation activities. Although
some sociocultural theorists have added to the view of learning as social practice by pointing out
that cognitive functions are constructed and distributed in the social realm (Rueda & Moll,
1997), sociocultural theory offers a limited scope to study the ways that parents reason for one
mediation task over another, set goals to be achieved in their mediation practices, and perceive
that one mediation activity is more important than another. The study of parental technology
mediation, therefore, needs to be supplemented with social cognitive theory in order to fill this
gap.
Social Cognitive Theory
Social Cognitive theory can be used to examine motivation, or “the process whereby
goal-directed activities are instigated and sustained” (Schunk, Meece, & Pintrich, 2014, p. 5).
While other theories of motivation may focus on overt behaviors (behavioral theories) or
cognition (cognitive theories), social cognitive theory highlights social influences on cognition,
motivation, and behavior (Bandura, 1986). This process is modeled by a framework of triadic
reciprocality, where environmental variables, personal factors such as cognition and motivation,
and behaviors are related in a pattern of reciprocal interactions (Schunk, 2008; Schunk, Meece,
& Pintrich, 2014). For example, the environment influences personal factors like cognition and
motivation as outside sources of information from verbal feedback or observations of
consequences to others inform individuals’ goals, values, and ability perceptions. At the same
time, these personal factors can also alter the environment because they influence the type of
settings individuals choose to be in. Cognition and motivation at the personal level also
PARENTAL MEDIATION OF TECHNOLOGY USE 27
determine the types of behavior an individual chooses to engage in, the amount of effort and
persistence expended, as well as the self-regulation strategies employed. In reverse, performing a
task provides information about individuals’ progress and abilities, thereby altering how they
view the current and similar future tasks. Unlike sociocultural theory that focuses on the
interpersonal interactions, social cognitive theory focuses on how social processes change
individuals’ cognition and motivation, which in turn influence behavior.
An important perspective of social cognitive theory is the view that individuals possess
the agency to organize their social environments and act to achieved goals (Bandura, 2001). This
perspective reflects an important paradigm shift from the preceding era of behaviorism and
cognitive psychology based on the information processing model, where people are thought of as
passive recipients of external stimuli or actors who act reflexively according to preset rules (For
more on this view, see Harre, 1983). In contrast, Bandura (2001) contended that humans are
agentic beings who act purposefully through four processes closely tied to motivation, including
intentionality, forethought, self-reactiveness, and self-reflection. Intentionality refers to the
purposefulness of actions that are chosen to be performed for specific outcomes. Intentions and
actions can be thought of as distinct, temporally-separated aspects of performance. Thus,
intentions are grounded in how individuals are motivated to act in the future. Forethought, the
second aspect of agency, extends this motivated forward planning well into the future as people
anticipate consequences of actions and act in ways that produce desired courses of events. Due to
these outcome expectations, the future is cognitively represented and acts as a motivator for
current actions. And whereas intentionality and forethought refers to the planning phase of
action, self-reactiveness refers to the process of self-regulation embedded within the act itself as
individuals self- monitor and self-correct in order to perform activities according to plan. The
PARENTAL MEDIATION OF TECHNOLOGY USE 28
last agentic aspect, self-reflectiveness, refers to the post-hoc cognitive process when individuals
adjust their motivations and goals to assimilate new information about consequences of actions
and perceived capabilities. These four aspects of agency reveal the fact that, in the social
cognitive view, motivation is the arbiter between goals, actions, and outcomes. People are
motivated by envisioned outcomes and consequently act and evaluate the best ways to achieve
them. Two such motivational variables that have been shown to influence parents’ home
educational practices are self-efficacy and role construction, as discussed in the next sections.
Self-efficacy. Self-efficacy is defined as “beliefs in one's capabilities to organize and
execute the courses of action required to produce given attainments” (Bandura, 1997, p. 3). In
relation to parents’ technology mediation, self-efficacy refers to parents’ belief about their ability
to mediate children’s technology usage in the near future through engaging in specific supportive
and regulatory behaviors that change their children’s usage patterns. Self-efficacy not only
reflects how parents view their current abilities, but also takes into account perceived task
difficulty based on environmental features (Bandura, 1997). For example, parents’ self-efficacy
to mediate children’s technology use depends on their technology knowledge as well as on such
factors as the receptivity of the child and how much the home environment is conducive to
salient parent-child interactions (e.g. space, number of other siblings, etc.; Hoover-Dempsey,
Bassler, & Brissie, 1992). These appraisals then lead parents to form goals and to subsequently
organize the environment and plan actions to achieve them (Bandura, 1986). Self-efficacy is
particularly important in the agentic process of self-reflectiveness, as parents evaluate possible
goals and adjust courses of actions that will bring about the best outcome (i.e. their children’s
technology usage) given their perceived capabilities. Although parental self-efficacy has not
been examined in the context of technology mediation, parental self-efficacy was shown to have
PARENTAL MEDIATION OF TECHNOLOGY USE 29
powerful implications for other home teaching practices because it affects parents’ selection of
achievement-related tasks, the effort they expend, and the degree to which they persist when
facing difficulties (Bandura, 1981).
In addition to reflecting self-evaluations of ability and the environmental context, self-
efficacy is also task- and domain- specific (Bandura, 1986). In particular, parents likely have
different efficacy profiles for restricting versus supporting children’s ICT usage because these
tasks require distinct abilities and behaviors. For example, parents who lack technology
competence but are typically engaged in setting rules for their children may have high self-
efficacy for regulatory mediation but low self-efficacy for supportive mediation.
Antecedents of self-efficacy. Self-efficacy is informed by four sources of information
(Schunk, Meece, & Pintrich, 2014). The most influential source is mastery experience, in which
prior performance on a task influences an individual’s self-efficacy for similar tasks in the future.
Another source of efficacy information is vicarious experience, or observing others performing a
similar task. Vicarious experience information is influenced by how similar the model is to the
observer. For example, parents from low SES communities may have increased self-efficacy for
technology mediation after they observed others in their community engaging in mediation
practices, but may not be as affected when observing more affluent parents performing the same
task. A third source of self-efficacy is verbal persuasion by others, which has been shown to have
short-term effects before mastery experience provides additional information on perceived ability
(Milner, 2002). The last source of self-efficacy is physiological or emotional states experienced
while performing a task. Reactions such as joy and stress are associated with outcomes of tasks
and inform efficacy beliefs.
PARENTAL MEDIATION OF TECHNOLOGY USE 30
Role Construction. Researchers who have studied the parents’ motivated behaviors
noted that parents’ self-efficacy is closely tied to another motivational construct called role
construction. Parental role construction is their beliefs about the responsibilities, rights, and
obligations of parents in their child’s education (Walker et al., 2005). These beliefs are formed
from socially-constructed perspectives on expected behavioral patterns related to one’s position
in a particular social context (i.e. as a parent of a school-age child; Whitaker & Hoover-
Dempsey, 2013). Both structural demands of perceived expectations by others as well as
personal understanding of these expectations inform how parents conceive of the range of
behaviors that are expected and appropriate in their role as a parent (Hoover-Dempsey & Jones,
1997). Role construction affects parental behavior, especially as demonstrated in the domain of
parental involvement in schools, because it establishes “the basic range of activities that parents
will construe as important, necessary, and permissible for their own actions on behalf of their
children” (p. 4). In relation to technology mediation, role construction informs parents about the
part they are supposed to play in children’s digital literacy development.
Because of its conception in relation to parental involvement in schools, patterns of
beliefs and behaviors are categorized as (1) parent-focused role construction reflecting the belief
that parents have the primary responsibility for children’s education, (2) school-focused role
construction reflecting that schools have the primary responsibility, and (3) partnership-focused
role construction reflecting that both parents and schools share primary responsibility (Walker et
al., 2011). Therefore, parents’ beliefs about their role in children’s technology education are
related to the extent to which they believe it is the school’s responsibility to teach children about
technology.
PARENTAL MEDIATION OF TECHNOLOGY USE 31
Antecedents of role construction. Role construction was conceptualized by Hoover-
Dempsey and associates (1997) based on social cognitive theory, which is reflected in its explicit
modeling of the connections between the social context, personal psychological factors, and
patterns of behavior. Thus, role construction shares the social cognitive emphasis on the parts
enactive and vicarious experiences play in shaping one’s psychological processes. Roles are
developed from childhood experiences with one’s parents as well as those of peers (Hoover-
Dempsey & Jones, 1997). Values, goals, and expectations are also further defined as individuals
become parents themselves and have to respond to the expectations of other agents in their social
environment such as extended family members, teachers, friends, and their own children. In this
way, parents construct roles from both cultural expectations and interactions with others in their
social group.
In addition to enactive and vicarious experiences, role construction also links expected
behaviors to the goals held by the social group parents belong to as well as parents’
interpretations of these goals (Whitaker & Hoover-Dempsey, 2013; Hoover-Dempsey & Jones,
1997). Situated within social cognitive theory, the concept of role construction emphasizes how
individuals interpret socially-derived goals by negotiating them with characteristics of their
context. This is akin to the agentic processes of forethought, during which individuals form
cognitive constructions of the “ideal” functioning based on socially-derived expectations and
plan courses of action to achieve that ideal. In addition, individuals are also self-reflective in
negotiating socially-expected roles within their own context and evaluate courses of action that
most closely match the ideal role given contextual constraints (e.g. limited time or technical
knowledge in the case of parental technology mediation). However, it should be noted that role
construction emphasizes how individuals respond to social expectations situated within particular
PARENTAL MEDIATION OF TECHNOLOGY USE 32
cultural milieus as opposed to Bandura’s view that individuals appraise the environment and set
goals that maximize their potential for success (Hoover-Dempsey & Jones, 1997; Bandura,
2001). As such, in role construction, appraisals of anticipated outcomes include a perception of
how these outcomes match social expectations, a social emphasis that is not explicit in Bandura’s
conception of outcome appraisal.
Relationship to self-efficacy. Role construction in the parent involvement framework is
inextricably tied to parents’ self-efficacy to positively influence their child’s educational
outcomes. Researchers working from the parent involvement model considered role construction
and invitations by valued others as more proximal to parents’ decisions to perform certain
activities, compared to the important but more distal effects of self-efficacy (Reed et al., 2000).
That is, parents respond directly to social and personal expectations derived from their role as
parent, and subsequently evaluate behaviors consistent with these expectations in relation to their
perceived ability. Consistent with this assumption, research has shown that parental self-efficacy
is mediated by role construction (Reed et al. 2000; Chrispeels & Rivero, 2001). For example,
parents were willing to try new practices after receiving role information from school even when
they felt they lacked the specific skills necessary for the recommended tasks (Chrispeels &
Rivero, 2001). These parents subsequently expressed frustration in performing the suggested
tasks, which could lead to decreased efficacy beliefs for future similar tasks. However, this
relationship between role construction and self-efficacy was found when parents received
explicit role information from schools and it is unclear whether this finding will also apply in the
absence of such an intervention.
Addressing low-income and ethnic minority students. In accounting for socially-situated
expectations, the role construction construct explicitly deals with the ways in which role beliefs
PARENTAL MEDIATION OF TECHNOLOGY USE 33
may differ across socioeconomic and ethnic lines. Research with Latino parents has found that
although they valued and expressed high expectations for their children’s education, some Latino
parents tend to believe that academic learning is the school’s domain (i.e. school-focused role
construction) and their involvement may be interpreted as disrespect for teachers’ knowledge and
expertise (Goldenberg et al., 2001; Resse et al., 1995). Instead, some Latino parents view their
primary role as providing moral education, ensuring children’s school attendance, encouraging
good behavior, providing shelter and necessities, and socializing children about family
responsibilities (Reese et al., 2000; Chrispeels & Rivero, 2001). These role beliefs lead to
parenting behaviors that are in opposition to those expected by schools, engendering negative
school-home relationships and resulting in lower academic achievement of many minority
children (Valdes, 1996).
In parallel, parental role construction regarding technology mediation is also socially
constructed and may differ across different communities. The ways in which parents perceive
their role as mediators or educators of digital literacy, and complementarily the extent to which
they believe that it is the school’s role, have important implications for their technology
mediation strategies. In addition, examining role construction for technology mediation of low
SES parents may reveal trends different from those of more affluent parents and shed light on the
complexity of the digital divide issue (Jenkins, 2009).
Strengths and limitations of social cognitive theory. In relating behaviors to
motivational constructs such as self-efficacy and role construction, social cognitive theory
provides a useful lens for understanding how parents become motivated to engage in specific
technology mediation behaviors. Social cognitive theory highlights parents’ agency for choosing
specific mediation methods over others as they evaluate the best means to help socialize their
PARENTAL MEDIATION OF TECHNOLOGY USE 34
children on appropriate technology usage behaviors given contextual circumstances such as their
own technical ability, resource access, and socially expected roles. As such, this theory adds to
understandings provided by sociocultural theory by describing how goal-directed behaviors are
evaluated and enacted.
While offering useful insights on how parents become motivated to engage in technology
mediation behaviors, social cognitive theory differs from sociocultural theory in its lack of focus
on social interactions. In social cognitive theory, the primary interface between an agent and the
social world is vicarious and personal experiences of consequences due to particular actions.
Thus, sociocultural and social cognitive theories offer complimentary perspectives for
understanding how and why parents from low income households mediate their children’s
technology use. Sociocultural theory is particularly useful in framing social interactions between
the child and the parent, and the ways in which these interactions lead to the acculturation of
technology use as cultural tools. Supplementing this view, social cognitive theory offers
additional insights to how parents become motivated to engage in particular mediation practices.
Empirical Literature Review
In addition to addressing theoretical foundations, reviewing insights from relevant prior
research is the next important step to understanding how parents mediate adolescents’
technology usage. Research reviewed below begins with a focus on how adolescents use
technology out of school, followed by descriptions of how parents support or restrict these usage
behaviors. Finally, related research on the ways in which contextual variables influence parents’
technology mediation are discussed.

PARENTAL MEDIATION OF TECHNOLOGY USE 35
Children’s Technology Use Profiles
The latest report from the National Telecommunications and Information Administration
(2013) indicated that computer usage and broadband internet connection are growing. More
importantly, households with school-age children are more likely to have computers than those
without children (84% compared to 73%) as well as more likely to have broadband connection
(79% compared to 66%). The report also suggests that the access divide is narrowing but still
exists across socioeconomic lines, as home computer and broadband access vary widely between
the highest and lowest income categories as of 2011 (52% vs. 95% for computer ownership and
43% vs. 93% for broadband connection). However, another recent national report suggested that
the issue of computer and internet access is more complex and may relate to children’s
developmental trajectories, with only about 52% of children online in third grade and 97%
reported being online by the time they reached 8
th
grade (Flanagin, 2010). This highlights the
fact that parents from low income households may perceive home computer and internet access
as more important as children grow older, prompting later investments in technology. In
addition, children from low income families often find access in other locations, such as at the
library, community center, or relative’s house (Warschauer & Matuniak, 2010; Clark, 2013).
As these statistics suggested, the access divide appears to be narrowing, and even more so
among adolescent youths (Livingstone & Bober, 2005; Lenhart, 2015). The new divide, the so-
called “second digital divide,” is now focused on how adolescents use ICT technologies to
contribute to the push and pull of online information. Ito and associates (2010) characterized
adolescents’ recreational digital technology usages in their ethnographic study as hanging out,
messing around, and geeking out. Hanging-out activities includes friendship-driven activities that
youths engage in with people they have relationships with offline. These activities usually occur
PARENTAL MEDIATION OF TECHNOLOGY USE 36
via social networking sites, instant messaging tools, and online games. This type of activities is
primarily consumption-oriented, consisting of activities such as chatting, downloading and
sharing digital content, viewing online profiles, as well as playing games (Attewell &
Winston,2003; Ito et al., 2010). On the other hand, messing around and geeking out involve
activities that are interest-driven, during which adolescents explore, experiment, and create with
media or technology formats. And although the latter two usage categories sometimes involve
the same consumption activities as hanging out, they are distinct from hanging out activities
because online interactions are motivated by shared interests instead of personal familiarity.
Messing around activities involve explorations of interests through the use of technology as
children extend understandings through online searches, media experimentation, and advanced
game play. Geeking out builds on these early interests into more sophisticated forms of
participation, including activities such as content creation and active navigation within online
communities of experts.
Media researchers contend that these geeking out activities are (or should be) a vital part
of a young person’s education because they position youths as creators and innovators, involving
them in the ICT participatory culture necessary for success in contemporary societies (Ito et al.,
2010; Gee, 2004; Jenkins, 2009). Such activities also recruit and maintain children’s interests in
ways that are not only personally relevant, but also improve career potentials through increasing
expertise, creative dispositions, and professional networks. However, only a fraction of
adolescents was shown to engage in such sophisticated forms of ICT participation (Ito et al.,
2010). In particular, a survey study by Livingstone and Helsper (2007) found four profiles of
ICT usage, with only 27% of preteens and teens (ages 9-19) identified as “all rounders” who
engage in forms of media production. This finding supports results from the latest survey results
PARENTAL MEDIATION OF TECHNOLOGY USE 37
by the Pew Internet and American Life (Lenhart et al. 2010) on teen content creation, which
showed that only 38% of teens create and share media content online, 21% remix online content,
and 14% have online blogs. These percentages have held relatively constant from 2004 to 2009,
in contrast to the increasing access of ICT technologies across socioeconomic groups.
The relationship between adolescents’ content creation activities and socioeconomic
factors is also more complex than initially thought. In contrast to previous studies on the
relationship between content creation and socio-demographic factors (Attewell & Winston,
2003; DeBell & Chapman, 2006), the Pew study (Lenhart et al., 2010) found that household
income and race did not significantly predict to teens’ content sharing and remixing activities. In
addition, teens from low income homes are actually more likely to create online blogs compared
to teens from more affluent communities. These statistics reveal that adolescents’ use of digital
technology maybe transforming with the ICT landscape and that usage profiles are more
complex than as a product of socioeconomic circumstances. They also suggest the need for more
careful examination of different contexts behind these usage data, particularly how parents
mediate these activities at home.
Parental Technology Mediation of Young Children.
Research on parents’ technology mediation for young children is primarily conducted
through case studies and painted a portrait of children as active learners who learn through self-
selected observations and recruit parents’ help when needed. In particular, Plowman and
associates (2008; 2010a; 2010b) conducted a survey of 326 parents and case studies of 24
families in Scotland to examine the ways in which preschoolers learn through and about
technology at home. They pointed to the permeation of media in young children’s lives, which
allows children to observe parents, relatives, and older siblings engaging in ICT-related activities
PARENTAL MEDIATION OF TECHNOLOGY USE 38
in daily routines, such as making FaceTime calls, shopping online, and downloading family
photos.
In addition to modeling behaviors, parents also engage in both proximal and distal guided
interaction patterns (Plowman et al., 2010a). Proximal guided interactions consist of parents’
explicit instructions aimed at developing children’s operational skills. These proximal
interactions are seen as a way to help children become independent users of technology and able
to occupy themselves while parents engage in other household or personal tasks. Relatedly,
distal interactions include parents overseeing children’s safety and usage progression from afar
(i.e. while performing other tasks), as well as responding to children’s call for help. These
mediation behaviors are largely echoed by other case studies of older children (up to nine years
old) and their parents, in which parents mainly foster children’s operational knowledge and view
technology mainly as a mean of entertaining children in their free time (Takeuchi, 2012;
Livingstone et al., 2015; Kerawalla & Crook, 2002). As a result, parents often cite children’s
operational capabilities when asked about what their children learn through technology although
other learning processes are also occurring, such as the development of dispositions to learn,
improvement of literacy and numeracy, and gains in understanding of the role of technology in
daily life (Plowman, Stephen, & McPake, 2010). Works by Plowman and associates were able
to provide a detailed picture of how preschool children develop digital literacy skills at home and
what aspects of digital literacy they acquire (For more on Plowman et al.’s report of the digital
literacy skills preschool children gain at home, refer to pg. 13). However, the researchers did not
focus on specific ways in which parents support children’s digital literacy development, which
could in part be a result of the targeted age range (i.e. parents of preschool children do not
engage in many qualitatively different mediation practices and/or are not often conscious that
PARENTAL MEDIATION OF TECHNOLOGY USE 39
they are contributing to children’s digital literacy development) as well as the intentional focus
of their study. And although they collected family income data, they did not distinguish
mediation practices that may be different across low and high socioeconomic groups.
Another way in which parents support young children’s technology usage is through
resource provision. The majority of resources available for young children are those that are
already present in the household, or are intentionally purchased for multiple users (i.e. for
parents and siblings; Plowman, Stephen, &McPake, 2010). Parents negotiate young children’s
access to technology with the needs of others in the family as well as the extent to which young
children can take care of these ICT tools. As such, young children are often barred from using
expensive or fragile equipment that parents use for work, especially in more affluent families.
Another aspect of resource provision is the perceived educational benefits of computer software
and games purchased for children. Interestingly, some parents are not concerned with
educational potentials of the software they purchased for their preschool children. Many parents
of young children are also unsure of technology-related activities, websites, or games they want
to promote as means for the child’s social or cognitive development (Livingstone et al., 2015).
And even when parents report that their motive for purchasing a computer is to support their
children’s education, many exhibit mismatched software purchasing behavior by evaluating
software based on their children’s preference instead of its educational potential. In contrast to
these trends, other parents do cite learning potential as the primary reason for software purchase,
especially for older children who are in school (Plowman, Stephen, & McPake, 2010; Takeuchi,
2010). These different perspectives on resource provision reflect the dual nature of ICT tools,
with capabilities to both entertain and educate. And although parents of young children mainly
PARENTAL MEDIATION OF TECHNOLOGY USE 40
view technology as recreational tools, some parents endeavor to infuse these leisure activities
with academic-oriented learning.
A type of technology mediation that is closely related to resource provision is how
parents control and guide young children’s ICT usage. Many studies on parents of young
children found convergent evidence that parents’ main concern is to ensure that their children
participate in other recreational activities besides technology usage, balancing time between
indoor and outdoor activities, as well as between individual and social pursuits (Plowman,
Stephen, & McPake, 2010; Livingstone, 2015; Takeuchi, 2012; Kerawalla & Crook, 2002). This
concern manifests as requiring children to ask for permission to use the computer and placing
limits on the amount of time children are allowed to spend using technology. In contrast, most
parents of preschool children do not offer suggestions or guidance on children’s ICT activities,
such as promoting certain games and websites (Livingstone, 2015; Kerawalla & Crook, 2002).
Parents of young children also tend not to co-use or closely supervise children’s technology
usage. Even when parents engage in co-use behaviors, they are more inclined to co-use
traditional media such as television and books with young children rather than ICT technologies
as defined in the present study (Connell, Lauricella, & Wartella, 2015). These behaviors reflect
parents’ views of ICTs as recreational tools for children, and as a parenting tool to help keep
children occupied as parents engage in other tasks. Using time limits instead of content
restrictions also parallel the use of distal mediation strategies in which parents provide reactive
support and remote supervision while their children choose for themselves the type of ICT
activities to engage in. Additionally, distal mediation patterns reflect many parents’ view that
ICT usage possesses little risk for their young children due to preschoolers’ limited ICT
operational knowledge, as well as limited reading and writing skills (Livingstone, 2015).
PARENTAL MEDIATION OF TECHNOLOGY USE 41
In addition to research on parents of young preschool children, Takeuchi (2012)
conducted qualitative case studies of two pre-adolescent children (age 8) and their families,
which included parent and child interviews as well as home observations. She also found that
parents of these children still largely exhibited the hands-off attitudes that characterized parents
of preschool children as mentioned above, although their pre-adolescent children were much
more digitally savvy than preschool children. Parents often allowed children to play computer
and handheld digital games (Nintendo DS) on their own, interfering mainly to help children
balance their time with other non-digital activities. However, the distinct difference between
these parents and parents of preschool children is the additional focus of helping children see the
educational and functional uses of technology. These parents suggested digital software that are
meant to either help expand knowledge of content areas their children are interested in like
Webkins and Cooking Mama (i.e. Encouragement-Expansion of Interests
5
; See a list of
supportive mediation behaviors in Appendix D), or help their children perform daily tasks like
Hello Kitty Daily (i.e. Instilling Cultural Roles of Technology). In addition to these educational
and functional foci, parents of pre-adolescent children also co-use technology more often with
their children compared to parents of preschool children, mixing music or playing games
together in their spare time (i.e. Collaborative Co-use). This increase in co-use behaviors might
reflect an increasing match in technical skills and interests between the parent and the pre-
adolescent child. Interestingly, these shifts in parental mediation behaviors as the child grows
from preschool to pre-adolescent age may reflect the path to more involved technology
mediation as the child enters adolescence. Although this study provides an in-depth portrayal of
how parents mediate technology for an older child, generalization from this study remains

5
Italicized parental mediation behaviors link to categories of behaviors that can be found in Appendix D.
PARENTAL MEDIATION OF TECHNOLOGY USE 42
limited because of its small sample size. The study’s main focus was also on documenting
recreational uses of ICTs, with a lack of attention to how these parents address technology
education demands from school or how they view their mediation behaviors as contributing to
their child’s digital literacy development.
The studies cited above show a shift in parents’ technology mediation behaviors in
response to children’s growing skills, both in traditional and digital literacy domains. Therefore,
supportive technology mediation found in parents with young children may not be directly
transferable to those with adolescent children. Regardless, understanding ICT mediation patterns
of parents with young children is useful in the present examination of how parents mediate
adolescent children’s ICT usage because it provides a contextual backdrop of how parental
mediation behaviors change as the child grows older, as well as how the mediation process plays
out in homes with multiple children (e.g. one adolescent child and one preschool-age child). In
addition, parental support of their adolescent child’s digital literacy development may overlap
with strategies they used when the child was younger, especially with mediation behaviors found
in parents of pre-adolescent children as in the Takeuchi (2012) study.
Parental Mediation Theory: Mediating Negative Effects of Media
As children grow older, they become increasingly capable and inclined to engage in
online activities such as socializing with others and interacting with media contents via
electronic mediums (Livingstone & Helsper, 2008). In response, parents become more concerned
with mitigating possible negative effects of media and online socialization. This concern is the
basis of parental mediation theory discussed in the previous section (p. 13). Parental mediation is
traditionally used to examine parents’ mediation of television viewing, but recent developments
by Livingstone and Helsper (2008) have elaborated this framework to other technologies.
PARENTAL MEDIATION OF TECHNOLOGY USE 43
Through factor analysis of data collected from a national survey of 1511 children (12-17 years
old) and 906 parents, they examined parents’ technology mediation behaviors that minimized
children’s encounters of online risks and therefore focused on parents’ regulation of children’s
ICT activities rather than supportive behaviors. In particular, the researchers found three
regulatory mediation strategies parents use to control their children’s ICT usage, including
interaction mediation, technical mediation, and monitoring. Interaction mediation includes
restricting activities that parents find problematic such as online chats and games, while
monitoring and technical mediation involve checking up on children ‘s ICT usage and using
filtering software, respectively. Recent researchers have also combined interaction mediation
with other restrictions of use (such as imposing time limits) into a mediation technique termed
restrictive mediation (Sonck et al. 2013; Schaan & Melzer, 2015).
Survey studies in the US and other countries using these regulatory mediation categories
found that a majority of parents engage in some type of restrictive mediation and monitoring
(Duad, 2014; Haddon, 2012; Livingstone et al. 2011; Liau et al. 2008; Eastin et al., 2006).
Parents reported that they engage more in restrictive mediation when their children’s friends are
visiting (Amarach Consulting, 2004). And while many parents engage in monitoring, they are
more likely to check websites their children visited, rather than personal profiles on social
networking websites and email accounts (Haddon, 2012; Daud, 2014). In contrast, technical
mediation is less prevalent and is dependent on parents’ ICT skills (Duad, 2014; Haddon, 2012).
The last type of mediation from this framework is active co-use. Active co-use is more
supportive of children’s technology use than other strategies based on parental mediation theory.
But, whereas regulatory mediation strategies are clearly defined, active co-use is more
ambiguous and includes widely different mediation practices such as giving technical and
PARENTAL MEDIATION OF TECHNOLOGY USE 44
content selection guidance, using technology with children, as well as providing instructive and
evaluative comments on media content (Livingstone & Helsper, 2008). This ambiguity is a result
of the fact that active co-use is a descendant of television co-viewing, a strategy parents use to
mediate children’s television consumption. Because television viewing is a narrowly defined
activity, television co-viewing can be clearly delineated as parents watching television with
children and providing commentary on contents that appear on screen. However, because ICT
technologies often feature smaller screens, are more often used by one person at a time, and
include many types of activities other than viewing, the definition of co-use in relation to ICT
technologies have become imprecise (Valkenburg et al., 2013). This problem is also related to
the mismatch between the traditional perspective of parental mediation as a mean to mitigate
negative effects of media and co-use as a primarily supportive strategy, which deters theoretical
exploration and expansion of this construct.
The imprecision of active co-use have also been noted by other media researchers, who
have found that this construct extends far beyond its original conception by Livingstone and
Helsper
6
. For example, researchers have separated co-use and active mediation strategies, with
the former referring to parents engaging in online activities with children and the latter to
discussion of content (Pasquier, Simoes, & Kridens, 2012). In addition, Haddon (2012) found
that parents use distinct strategies to guide children’s ICT usage compared to those used to
inform children about online risks (i.e. active content vs. active safety mediation
7
), a result that is
supported by a recent principal component analysis of strategies that are traditionally thought to
be active co-use (Sonck et al., 2013). Another recent study also found that parental empathy-

6
For a list of active co-use strategies used by previous literature, refer to Appendix B.
7
Active content mediation and active safety mediation are included as supportive mediation behaviors in this study.
See Appendix D.
PARENTAL MEDIATION OF TECHNOLOGY USE 45
oriented discussion of media content (i.e. active-emotional co-use) is distinct from other active
mediation behaviors (Schaan & Melzer, 2015). Furthermore, Clark (2011, 2013) added
participatory learning as an additional dimension of co-use, in which parents and children are
thought to use digital media to learn something new together. Examining dimensions of
supportive strategies like active mediation and co-use is an important avenue for future research
because parental supportive mediation is found to increase adolescents’ constructive uses of ICT
technologies and online opportunities (Daud, 2014; Garmendia et al., 2012; for a complete list of
supportive mediation behaviors, including Active Content Mediation, Active Safety Mediation,
and Participatory Learning Co-use, refer to Appendix D).
Parents’ Technology Mediation as Socialization Tools
The increase in attention on parents’ supportive technology mediation coincides with the
recent critique of parental mediation theory and its over-emphasis on media effects (Clark,
2011). Parental mediation is traditionally viewed as a way to minimize risk from media exposure
(Flanagin & Metzger, 2010; Valkenburg & Peter, 2013). Citing the limitation of this narrow
view of existing parental mediation research, recent media researchers have used parental
mediation theory to examine ways in which technology plays a role in helping parents cultivate
family values in children. Clark (2013) embarked on a large-scale, 11-year ethnographic study of
343 parents of adolescents aged 11-18, in which she found that parents from different
socioeconomic backgrounds mediate children’s ICT usage according to different ethics they
perceive as essential for their children’s success. Parents from higher socioeconomic
backgrounds tend to mediate technology usage from an ethic of expressive empowerment, with
parents encouraging children to participate in many different extracurricular activities in order to
maximize their future potential as well as to foster their ability to express views and preferences.
PARENTAL MEDIATION OF TECHNOLOGY USE 46
As such, using technology for solely entertainment purposes or to pass time is discouraged,
especially when it interferes with other, more constructive activities. In contrast, low SES parents
tend to mediate technology from an ethic of respectful connectedness. They emphasize how
technology can be used to maintain family connection as family members find content that
engages their mutual interest, and to build relationships with similar others within the community
who can provide additional social resources. These parents view media as avenues for fostering
respectful relationships both between parents and children as well as between their children and
community members, relationships which are thought to help counteract negative influences
from their environment. In addition, many parents from low income communities believe that in-
home technology usage is a safer alternative to other potentially more dangerous activities their
teens may engage in outside the home.
The difference in technology mediation ethics between these two socioeconomic groups
undoubtedly influences the types and nature of parents’ mediation. Because of the importance
they place on constructive activities, parents with the expressive empowerment ethic are likely to
discourage prolonged recreational uses of technology, either by imposing time limits or by
engaging children in other cultivating activities (Clark, 2013). For example, these parents tend to
encourage their children to engage in other activities outside the home, automatically limiting the
time their children spend on ICT devices in the process. This practice can be thought of as
another example of restrictive mediation because parents restrict the time adolescents are
allowed to use ICTs (Restrictive Mediation; Appendix D). In contrast, entertainment-oriented
uses of ICTs are accepted and encouraged as means for building family relationships in homes
where parents hold the connectedness ethic (Promotion of ICTs for Family Connectedness).
Parents in these homes also encourage adolescents to reach out to friends in their local and ethnic
PARENTAL MEDIATION OF TECHNOLOGY USE 47
communities in order to foster their native ethnic identities (Promotion of ICTs for Community
Connectedness). In addition, the nature of how parents talk to adolescents about media content
(Active Content Mediation) likely differs in these two types of home environments. Parents
working from the empowerment ethic tend to use media content as a starting point for
discussions that empower adolescents to express their ideas and interests. In contrast, parents
working from the connectedness ethic likely discuss media contents in ways that bridge
children’s interests with their own and strengthen ties within the family. These nuances highlight
the complexity of parental technology mediation, reflecting that the ways technology mediation
are carried out also depends on goals parents have for child-rearing. These goals are shaped by
parents’ perception of the best way to help children succeed in their particular sociocultural
context.
In addition to enacting technology mediation as socialization tools, Clark (2013) also
found additional mediation behaviors in her ethnographic study that could be linked to digital
literacy development. For example, she found that some parents from low income communities
encouraged their adolescent children to use technology as means to explore personal interests
(Encouragement-Expansion of Interests). In these interactions, parents communicate their views
that ICTs can be used to leverage expert knowledge on topics that their children are already
interested in. Additionally, parents help children notice how information offered by ICT
resources can be the gateway to new academic avenues that can lead to better jobs (Instilling
Cultural Roles of Technology). Verbal encouragement behaviors such as these have also been
found in other studies, particularly in relation to helping children gain new ICT operational
knowledge. In particular, one study found that parental encouragement was a key factor that
persuaded adolescent girls to expand their technical knowledge by taking elective technology
PARENTAL MEDIATION OF TECHNOLOGY USE 48
classes typically dominated by boys (Barron, 2004; Encouragement-Expansion of Operational
Skills).
In addition to verbal encouragement behaviors, Clark also found that parents provided
technology resources in response to school’s demands (Resource Provision), ask their adolescent
children to teach younger children how to use technology (Recruitment of Child’s Technical
Guidance), help children see how technology can be used to improve everyday living (Instilling
Cultural Roles of Technology), help children gain access to technology classes offered at school
(Brokering Digital Learning), and participate in learning episodes with their children about and
through technology mediums (Participatory Learning Co-use). While these findings provided
new ideas about how parents from low income community support adolescents’ ICT usage,
Clark’s focus was not on the relationship between these mediation behaviors and digital literacy
development. Rather, her study concentrated on the ways in which parents mediate technology as
means to negotiate different types of family relationships that correspond to values inherent in
their socioeconomic communities. Therefore, it remains unclear how parents perceive of these
supportive mediation strategies in relation to their children’s digital literacy development and
how these behaviors may or may not lead to beneficial ICT usage by their children.
Parents’ Mediation of Constructive Technology Usage
In response to the increasing focus on digital literacy development and the benefits of
engaging in ICT participatory culture, some scholars recently focused on how parents can
support children’s ICT participation. Still working within the confines of parental mediation
theory and its associated mediation categories, quantitative studies using SEM and correlation
analyses found that interaction mediation was most severe in limiting adolescents’ online
PARENTAL MEDIATION OF TECHNOLOGY USE 49
opportunities, or what Daud and colleagues have termed “positive uses of the internet”
8

(Garmendia et al., 2012; Daud, 2014). In their confirmatory factor analysis of data from a survey
of 384 children (ages 9-16) and 334 parents, Daud and associates (2014) found that interaction
mediation in particular reduces adolescents’ opportunities to communicate with others who share
the same interests, tap into distributed cognition resources, and share their self-created media
content. In contrast, technical restriction was the only type of mediation found to be associated
with increased positive uses of ICTs because they afford children relative freedom to explore and
use internet resources (Daud, 2014). Interestingly, active co-use was found not to have a
significant relationship (Garmendia, 2012), and even a slightly negative relationship (Daud,
2014), with positive ICT usage. I contend that this is a result of the imprecision of the co-use
construct as previously mentioned, particularly as active co-use was primarily represented by
regulatory behaviors in the Daud study (See Appendix B). In addition, while these studies help
us understand how parents can support children’s ICT participation, they do not examine
additional ways that parents provide this support above and beyond the limited scope of active
co-use.
Educational scholars working from a framework of digital literacy and ICT participatory
culture have tried to fill this gap by exploring different ways that parents support children’s
constructive uses of ICTs. Most notable is an interview study conducted in the Silicon Valley by
Barron and associates (2009) on families of eight adolescents chosen for their exceptional ICT
participatory activities. They found that parents of these children play a variety of roles in
supporting ICT participation. These roles include: (1) teacher, teaching their child some aspects

8
Positive usage was defined by Daud and associates (2014) as children’s use of the internet to gain new knowledge
and skills. These usage domains are reproduced in Appendix C. The present study uses this definition in referring to
“constructive” uses of ICTs.
PARENTAL MEDIATION OF TECHNOLOGY USE 50
of technology operation; (2) project collaborator, working together with their child on a
technology-related project; (3) learning broker, seeking learning opportunities to help their child
develop new technology competence; (4) resource provider, providing resources in support of
their child’s technology learning and usage; (5) nontechnical consultant, providing advice not
related to technology on their child’s ICT activities; (6) employer, recruiting their child to help
with technical services; and (7) learner, asking their child for help with technology-related
issues
9
. This study focused on parental technology mediation at the very highest echelon of
participatory culture, with child-participants who engage heavily in content creation activities
and parents who possess high degrees of technical knowledge and social capital (i.e. friends and
co-workers who also have high levels ICT technical knowledge and access). Because of the
study context, the authors contend that the roles exhibited by parents in their study provide a
range of possible ways that parents can help foster children’s ICT participation. However,
parents from less advantaged families possess significantly less knowledge, monetary, and/or
social resources compared to parents in the Barron study. So, while some of the mediation
behaviors found in the Barron study have also been found in low SES contexts in other studies
(such as the collaborator role/Collaborative Co-use behavior, learning broker role/Brokering
Digital Learning behavior, and learner role/Recruitment of Child’s Technical Guidance behavior
found in Clark, 2013 and Takeuchi, 2012), it remains to be seen whether other mediation
behaviors this study reported can be generalized to parents from lower socioeconomic groups.
In summary, a host of possible technology mediation strategies has already been
uncovered by previous research. These behaviors can roughly be separated into two categories:

9
Parental roles found in the Barron 2009 study are recast into supportive mediation behavior categories in order to
make the language consistent with other behavioral categories, all of which can be found in Appendix D. The
nontechnical consultant role was converted to Encouragement-Expansion of Operational Skills to align the category
with similar behaviors found in the low SES context from the Clark 2013 study.
PARENTAL MEDIATION OF TECHNOLOGY USE 51
regulatory and supportive mediation. Regulatory mediation involves restricting children’s ICT
usage and parallels the behaviors outlined by parental mediation theory (See Appendix D for a
detailed list). Supportive mediation, on the other hand, includes parental behavior that supports
children’s ICT usage and aid in their digital literacy development. But, although much is already
known about these behaviors, there are still gaps in the present knowledge regarding mediation
behaviors specific to parents from low income communities. As previously mentioned,
supportive technology mediation has thus far been studied almost exclusively in the high SES
context, and even those that were found in low SES homes were not explicitly linked to digital
literacy development as the outcome of interest. In addition to this knowledge gap, there has also
been less focus on factors that influence how parents mediate children’s ICT usage, an area of
research that will be reviewed next.
Factors of Parental Technology Mediation
In contrast to the large number of existing studies on parental technology mediation and
its relationship with children’s technology usage and online risk encounters, less research has
focused on antecedents of different mediation behaviors. Studies that have examined these
factors primarily defined parental mediation in terms of regulatory mediation as described in
parental mediation theory. These literatures are reviewed below.
Parents’ technical skills. Research has shown that parents’ regulatory mediation
behaviors are partly determined by their technical expertise. Parents who have more confidence
using technology themselves are more likely to monitor children’s usage history (Sonck, Nikken,
& de Haan, 2013). This reflects that monitoring requires more technical knowledge than
restrictive behaviors such as setting technology-related rules and imposing time limits for
children’s ICT usage. Another mediation behavior that requires technology knowledge is
PARENTAL MEDIATION OF TECHNOLOGY USE 52
technical mediation, which is related to the fact that higher skilled parents are more likely to use
this method of mediation (Nikken & Jansz, 2011). Complementarily, studies have also found that
parents who use ICTs less often themselves and those who have lower internet literacy skills are
more likely to use restrictive means in mediating their children’s ICT usage as opposed to using
monitoring or technical mediation strategies (Lou et al., 2010; Nikken & Jansz, 2011). Although
the extent to which parents use technology as well as their technical knowledge also likely
influence their use of supportive mediation strategies, this relationship has not been investigated
by previous research.
Parents’ demographic characteristics. Some demographic characteristics of parents
are also linked to specific technology mediation practices. For example, mothers are found to
mediate children’s technology usage more often than fathers (Sonck et al., 2013; Kirwil et al.,
2009). More education and higher income are also linked to the use of more varied mediation
behaviors (Eastin et al., 2006). However, more nuanced understandings such as how the
relationship between SES markers and parental technology mediation is likely mediated by
factors like parents’ technical skills have largely been overlooked. In addition, the way that these
personal factors likely influence supportive mediation behavior via parents’ perception of how
well they can mediate children’s technology use is yet to be explored. Examining how
heterogeneities in parents’ technical skills influence parents’ self-efficacy for mediation and,
relatedly, the types of mediation behaviors they engage in is one of the first steps towards a more
complex view of parental factors that affect mediation decisions.
Child factors. Some child-related factors are also related to how parents mediate their
technology usage. Because boys and girls tend to use ICTs in different ways, parents are also
likely to mediate their technology usage differently. Research showed that, compared to girls,
PARENTAL MEDIATION OF TECHNOLOGY USE 53
boys are more confident about their ICT knowledge (Barron, 2009), use ICTs more frequently
(Rees & Noyes, 2007), spend more time on the computer for recreational activities as opposed to
school-related activities (Epstein, 2012), play games more often and for longer periods (Epstein,
2012; Andrews, 2008), engage in more online interactions with strangers (Andrews, 2008), as
well as engage in more illegitimate ICT activities such as hacking (Taylor & Mounfield, 1994).
In response, parents tend to place more time and content restriction on boys compared to girls
(Sonck et al., 2013; Nikken & Jansz, 2011). They also set more restrictions when adolescents
spend more time online regardless of gender. On the other hand, some parents express more
concern about the negative effects of media for girls than for boys, which contributed to parents
engaging in more active safety mediation (i.e. talking about online risks) with girls (Valkenburg
et al., 1999; Sonck et al. 2013). But, while these studies highlight parents’ reactions to gendered
profiles of ICT usage by children, some scholars cautioned that these profiles are overly
simplistic (Jenkins et al.,2009; Barron, 2009). These works found that many girls are just as
active and digitally savvy as boys in their ICT participation, although they tend to gravitate
towards artistic-oriented and writing production activities. Therefore, more focus should be on
how parents’ mediation behaviors differ according to children’s ICT usage profiles and,
relatedly, their technical expertise rather than general gender categories.
Another child factor that appears to influence parents’ technology mediation is the child’s
age, which is also likely a result of developmental patterns of use. Adolescents reported more
engagement with ICT usage but less videogame-playing as they grow older (Witt, Massman, &
Jackson, 2011). Older adolescents also engage in more communicative activities online (Lenhart
et al., 2010). Relatedly, parents tend to set more general rules regarding ICT usage for older
adolescents compared to the younger group, with household rules regarding time limits and
PARENTAL MEDIATION OF TECHNOLOGY USE 54
acceptable activities online (Livingstone & Haddon, 2009). In addition, researchers have found
that parents engage in more active mediation with older adolescents, but are less likely to
monitor or co-use technology with older teens (Nikken & Jansz, 2011). These mediation
behaviors have important implications for adolescents’ constructive ICT activities because
adolescents are shown to progress through developmental stages of ICT participation as they
grow older, from “basic user to all-rounders” according to Livingstone and Helsper (2007) and
from engaging in “hanging out” to “geeking out” activities online according to Ito and associates
(2010). But, although it is well documented that adolescents engage in increasingly sophisticated
profiles of ICT usage as they grow older, the way that child’s age and digital expertise influence
parental mediation behaviors through parents’ perception of their mediation abilities has yet to
be explored by past research. It is likely that the more digitally sophisticated the child becomes,
parents also become increasingly unsure of their ability to mediate the child’s ICT activities.
Motivational Factors in Parental Technology Mediation
Review of existing literatures revealed that research investigating factors of parental
technology mediation tend to focus on how parents’ mediation behaviors are affected by
children’s characteristics and relatively fixed parental characteristics such as parents’
socioeconomic indicators. But, as was briefly introduced in the last section, the influence of
context-related motivational variables such as parents’ self-efficacy and role construction has not
been examined. The research reviewed below highlight how these motivational factors have been
shown to affect behaviors in related domains, as well as how they are relevant to the issue of
parental technology mediation.
Self-efficacy. In the field of emergent literacy, parental self-efficacy to engage in literacy
practices is shown to predict the frequency of home learning and cognitive activities (Downer &
PARENTAL MEDIATION OF TECHNOLOGY USE 55
Mendez, 2005; Grolnick, Benjet, Kurowski & Apostoleris, 1997; Machida, Taylor, & Kim,
2002; Waanders, Mendez, & Downer, 2007). Waanders and associates (2007) also pointed out
that parental engagement in home learning activities requires more initiative than school
involvement and is thus highly dependent on parents’ self-efficacy to carry out activities situated
within their particular home contexts. Additionally, Machida and associates (2002) found that
parental self-efficacy is a mediator between family background characteristics and the home
learning environment. Parents from low socioeconomic backgrounds who have high self-efficacy
engage in literacy activities similar to their more affluent counterparts. Other scholars also
suggest that high levels of literacy skills associated with more education not only act as the raw
materials for knowledge transmission, but also influence parents’ behaviors by increasing their
self-efficacy to carry out specific literacy activities (Hoover-Dempsey, Bassler, & Brissie, 1992).
Considering this evidence, self-efficacy likely plays a large role in determining what parents do
at home to mediate their children’s technology use. Specifically, the extent to which parents use
technology and their technical skills likely inform their self-efficacy to mediate children’s ICT
usage. Self-efficacy in turn influences the nature and the extent to which parents engage in
mediation behaviors. The relationships among socioeconomic status, technology usage, technical
skills, and self-efficacy for technology mediation also reflect a more nuanced view of how
technology mediation is carried out in different home contexts, as opposed to the overly
simplistic view of socioeconomic factors as determinants of effective mediation behaviors.
Another body of literature that provides evidence for the relationship among technical
skills, self-efficacy, and teaching practices is the research on teacher self-efficacy. Researchers
found that teachers’ computer ability, self-efficacy for using computers, and self-efficacy for
teaching with technology are associated with positive attitudes towards technology integration
PARENTAL MEDIATION OF TECHNOLOGY USE 56
(Lee & Tsai, 2010), intentions to use technology in the classroom (Anderson & Maninger, 2007;
Sang et al., 2010), as well as student-centered technology integration (Chen, 2010). In addition,
teachers’ self-efficacy for technology integration increased after participating in a professional
development workshop that systematically included antecedents of self-efficacy such as
vicarious learning experiences (Wang et al., 2004; Watson, 2006). Drawing parallels to parents’
technology mediation, technical skills are expected to be particularly salient in informing self-
efficacy for mediation activities that require operational knowledge such as giving direct
instruction about ICT usage and installing filtering software. However, as evident in the teacher
self-efficacy literature, targeted workshops aimed at improving specific operational skills needed
for mediation and fostering perceived mediation ability will likely improve parents’ self-efficacy
for technology mediation. Informing parents about supportive mediation behaviors that do not
require technical skills may also improve self-efficacy beliefs by expanding their mediation
repertoires to include specific activities parents with low technical abilities can perform.
Role construction. In addition to self-efficacy, role construction is another variable
demonstrated by literacy researchers to impact parent behavior. Role construction is related to
parents’ beliefs regarding whether specific domains of their children’s development are the
parent’s or the school’s responsibility. Its prominence in the literacy field is linked to its
influence on the types and frequency of literacy activities parents choose to engage in at home as
well as on parents’ active participation at children’s schools (Chrispeels & Rivero, 2001;
Drummond & Stipek, 2005; Gonzalez & Chrispeels, 2004; Sheldon, 2002). In addition,
researchers have found that role information given by schools as well as intervention programs
aimed at aligning role beliefs with school’s expectations help parents engage in new and more
frequent literacy activities at home (Chrispeels & Rivero, 2001; Gonzalez & Chrispeels, 2004).
PARENTAL MEDIATION OF TECHNOLOGY USE 57
In this respect role construction is similar to self-efficacy in that they are empirically
demonstrated to be changeable after exposure to targeted intervention programs.
Related to technology mediation, parents likely hold different beliefs about their role in
teaching children about technology usage and associated risks. In fact, recent media studies have
found that many parents believed that computer education should be taught at school (Ortiz,
Green, & Lim, 2011) and expressed that they would like schools to offer more information to
both parents and students about internet safety (Livingstone et al., 2011). Moreover, parents
often engage in technology mediation practices that are related to schools, such as providing ICT
resources as suggested by their children’s school (Clark, 2013) and encouraging their children to
take classes at school to improve their ICT skills (Barron, 2004; Barron et al. 2009). The strong
presence of parent-school relationships in children’s technology education suggests that parents’
perception of their role in relation to what they perceive to be the school’s role is likely an
important factor in parents’ mediation decisions. Furthermore, just as parents’ role construction
about home literacy practices was demonstrated to be changeable, providing additional role
information regarding parents’ expected involvement in children’s digital literacy development
will likely help parents conceive their roles in ways that support children’s constructive ICT
participation. Like self-efficacy, role construction as a changeable motivational construct offers a
less deterministic view regarding the influence of socioeconomic circumstance on parents’
technology mediation behaviors.
Summary
As shown in the previous sections, the increasing proliferation of ICTs in the home has
led to an increase in research on parents’ technology mediation behaviors in recent years. At the
same time, other studies have documented large gaps in how adolescents use technology at
PARENTAL MEDIATION OF TECHNOLOGY USE 58
home, from passive uses to highly sophisticated content creation and online socialization.
However, these two areas of research offered mismatched views because the majority of research
on parents’ technology mediation referenced parental mediation theory, which emphasized
avoidance of risks from ICT usage instead of digital literacy development. In addition, the
handful of studies on the ways that parents support children’s constructive ICT usage tended to
focus on higher socioeconomic populations, with parents who possess extraordinary amounts of
resource access and technical knowledge. There is a gap in the field at present for a better
understanding of how supportive strategies found in the high SES context translate to less
advantageous sociocultural contexts. As suggested by sociocultural theory and existing
mediation research, parents’ supportive strategies are products of how parents socialize their
children to match technology usage behaviors with demands from their sociocultural contexts
(Kozulin, 2001; Clark, 2013). Previous qualitative studies of parents in low income communities
also suggest that these parents engage in some supportive mediation behaviors that are similar to
their more affluent counterparts (such as resource provision) and others that are unique to their
socioeconomic group (such as encouragement of technology use for maintaining family
connectedness; Plowman et al., 2010; Clark, 2013; Takeuchi, 2012; Plowman, Stephen,
&McPake, 2010). As such, additional research is presently needed to examine the extent to
which low income parents engage in different types of supportive mediation behaviors found by
previous research.
In addition, research documenting the ICT participation divide has repeatedly noted the
lower returns of ICT access for adolescents from lower socioeconomic communities. Some
researchers have thus concluded that low SES parents do not mediate their adolescents’ ICT
usage in ways that contribute to their digital literacy development. However, as works in other
PARENTAL MEDIATION OF TECHNOLOGY USE 59
fields have suggested, parents from these so-called “disadvantaged” backgrounds possess
different motivation profiles that lead to variability in how they support their children’s
development (For example, Waanders, Mendez, & Downer, 2007; Drummond & Stipek, 2005).
Examining how key motivational variables like self-efficacy and role construction influence
parents’ technology mediation behaviors is an important step toward overcoming the view of
effective mediation behaviors as a byproduct of socioeconomic circumstances.
Despite the importance of understanding key antecedents of parents’ technology
mediation behaviors, there are still many unanswered questions in this area of research. Although
literacy research supports that self-efficacy and role construction influence parents’ behaviors, it
is unclear whether these effects are also applicable for a different domain like technology
mediation. And while evidence exist that contextual factors such as parents’ technical knowledge
influence parents’ regulatory technology mediation, it is still unclear how these factors influence
parents’ engagement in supportive mediation. In addition, we do not yet know whether these
contextual factors also affect parents’ perception of their ability and responsibility to mediate
their children’s technology usage, and thereby exerting both direct and indirect effects on
parenting behaviors. Answers to these questions will provide a more nuanced understanding of
the interplay among contextual limitations, parental motivation, and parental technology
mediation behaviors.
Research Questions
In light of gaps in existing research, the proposed study aims to examine how parents
from low-income communities support and regulate adolescents’ technology usage as well as
how motivational and contextual factors predict these behaviors. Two main research questions
guide this study:
PARENTAL MEDIATION OF TECHNOLOGY USE 60
1) How do parents from low socioeconomic communities support and regulate
adolescents’ ICT usage?
a. What is the prevalence of each type of behavior in the sample?
b. Do supportive mediation behaviors found from previous research represent
different facets of the same underlying construct? For regulatory mediation
behaviors?
2) How do motivational and contextual factors influence parents’ supportive and
regulatory technology mediation behaviors?
a. What are the influence of parental self-efficacy and role construction on
supportive and regulatory mediation behaviors?
b. What are the direct effects of parents’ technology usage, parents’ technology
knowledge, and perceived child’s technical expertise on parental mediation
behaviors, and what are their indirect effects as mediated by self-efficacy and
role construction?
c. What are the effects of other contextual factors on parents’ technology
mediation, including the effects of lunch status (an income indicator), parent
education, parents’ English proficiency, and child’s age?

PARENTAL MEDIATION OF TECHNOLOGY USE 61
CHAPTER 3: METHODOLOGY
To answer research questions posed in the previous chapter, the present study utilized an
exploratory sequential mixed methods design consisting of quantitative data collection and
analysis followed by a qualitative phase (Creswell & Clark, 2011). This research design is
advantageous in term of the researcher’s ability to supplement quantitative findings with in-depth
participants’ perspectives. The goals of the first phase were to collect and analyze survey data to
answer the two research questions guiding this study. The purpose of the second, qualitative
phase was to supplement quantitative findings as well as to gain a more in-depth understanding
of how parents carry out different mediation strategies in real world settings and the factors
parents take into account when they mediate adolescents’ technology use at home.
Phase One: Quantitative Data Collection and Analysis
Participants
Participants for this study were recruited from schools, community centers, and
community fairs in low-income neighborhoods throughout Southern California. Two-hundred
and ninety-one participants were recruited, consisting of parents of children aged 9-18. The
majority of participating parents self-reported to be of Latino ethnic origin (67.7%, n=197),
followed by African-American (10.0%, n=29), White/Caucasian (7.6%, n=22), and Asian (6.5%,
n=19). Small percentages of parents also reported to be Native American (<1%, n=1), Pacific
Islander (1.0%, n=3), or Middle-eastern (<1%, n=2). About 3 percent of parents (n=10) reported
that they are of mixed or other ethnic origins and another 3% omitted a response. Parents ranged
in age from 25 to 62 years old, with a mean age of 41 years old. Indicative of the sampling
context, 74 percent of parents (n=215) indicated that their child receives free or reduced-priced
PARENTAL MEDIATION OF TECHNOLOGY USE 62
lunch, and 47% of parents reported an education level of high school completion or lower (For
additional demographic description of participants, refer to Table 1).
Data Collection Procedure
Data collection for this study occurred between March and May, 2016. At five
participating schools, parents were invited to a workshop on adolescents and technology use,
with an incentive raffle to win an iPad for all attending parents used as a part of the recruitment
strategy. At the workshop, parents were asked for their willingness to participate in the study,
with the researcher making an explicit announcement that their participation would not affect
their ability to attend the workshop. After parents gave their consent, they were asked to fill out a
paper survey about their technology mediation practices, motivational characteristics, and
relevant personal information before any instructive information was given. Parents were given a
choice to take the survey in English or Spanish.
The researcher also set up a table at community fairs and community centers and asked
parents to fill out a paper survey as part of a research project. Parents were offered a five-dollar
Starbucks gift card or a raffle to win an iPad mini at the end of the study for their participation.
Parents were asked to fill out a survey on site (no remote participation or returning survey via
mail was allowed). Parents at these sites were also given a choice to take the survey in English or
Spanish.
The parent survey lasted approximately 15 minutes. In the case that parents had multiple
children, parents were asked to provide information about their ICT mediation behaviors for one
adolescent child only.

PARENTAL MEDIATION OF TECHNOLOGY USE 63
Materials
Surveys were adapted from those used by previous studies or created from synthesis of
past literature (Appendix E). A list of measures is included below.
Supportive technology mediation. The supportive technology mediation scale was
created from supportive mediation behaviors found from previous empirical research. Fourteen
supportive behaviors were included (using a total of 25 items), comprising of seven behaviors
found in the high SES contexts, and seven found in low or mixed SES contexts (See Appendix
E). Parents were asked the extent to which they engage in the specified behaviors (with
endpoints from never to very often). IRT analysis of supportive mediation items were carried out
as part of the study, and the expected a posteriori (EAP) scores were used to represent each
parent’s score on this latent trait (Embretson & Reise, 2000).
Regulatory technology mediation. The regulatory technology mediation scale was
adapted from Daud and associates (2014; α=0.86-0.95). Three categories of regulatory mediation
were measured, including restrictive mediation (11 items), technical mediation (4 items), and
monitoring (6 items). Some items were presented with dichotomous response options (yes/no)
and others were presented with frequency response options (with end points from never to very
often) as appropriate. IRT analysis of regulatory mediation items were carried out as part of the
study, and the expected a posteriori (EAP) scores were used to represent each parent’s score on
this latent trait (Embretson & Reise, 2000).
Supportive and regulatory mediation self-efficacy. Self-efficacy items were created
using guidelines provided by Bandura (2006). Parents’ self-efficacy for performing supportive
and regulatory mediation behaviors were measured in two different scales due to the domain-
specific nature of self-efficacy. In particular, parents were expected to have different perceptions
PARENTAL MEDIATION OF TECHNOLOGY USE 64
of how well they can carry out regulatory as opposed to supportive mediation behaviors. The
scales were in Likert formats with five response options (1=strongly disagree, 2=disagree,
3=neither agree nor disagree, 4=agree, 5= strongly agree). Similar scales of self-efficacy have
shown good reliability (α=0.80-0.86; Mendez et al., 2013). Consistent with previous literature,
sum scores from these two scales were used to represent parents’ supportive and regulatory
mediation self-efficacy.
Parent-focused and school-focused role construction. Role construction was assessed
through two related scales, including parent-focused and school-focused role constructions. This
scale was adapted from Sheldon (2002, α=0.90). Parents respond to statements with the stem “It
is the parents’ responsibility to…” and “It is the school’s responsibility to…” The scale was in a
Likert format with five response options (1=strongly disagree, 2=disagree, 3=neither agree nor
disagree, 4=agree, 5= strongly agree). Consistent with previous literature, sum scores from these
two scales were used to represent participants’ parent role and school role beliefs.
Technical knowledge. Parents’ technical knowledge was assessed with ten true/false
items. Items were converted from self-report items in Hargittai (2005, original α=0.89). In
particular, self-report items with the highest correlations to computer task performance were
converted into knowledge assessment items. Because these knowledge items were newly created
for this study, IRT analysis of these items were carried out and expected a posteriori (EAP)
scores were used to represent each parent’s score for technical knowledge.
Technology usage. Parents’ technology usage was assessed using items adapted from
Wartella (2013). Parents were asked about the amount of time they use technology at home and
at work (with endpoints from 0-1 hour to more than 7 hours) as well as the technology
PARENTAL MEDIATION OF TECHNOLOGY USE 65
involvement in the nature of their work (from requiring a lot of knowledge about technology to
does not require knowledge about technology at all).
English proficiency. Parents’ report of their English proficiency was assessed with five
items adapted from the Home Language Survey administered by the California Department of
Education (CA Department of Education, 2010; no reliability information found). The scale
consisted of five items: (1) What is your first language(s)? (open response); (2) What language(s)
do you use most frequently at home? (open response); (3) What language(s) do you use most
frequently at work? (open response); (4) What language(s) do you most frequently read in? (open
response); (5) How would you describe how well you can use English to communicate to others?
(Likert format from 5=very well to 1= no ability at all). In addition, the participant’s choice of
survey language (English vs. Spanish) was taken as an additional data point to evaluate parents’
English proficiency. Because of the differences between metrics across items, standardized
composite scores from the aforementioned six data points were used in the final analysis.
Perception of child’s digital expertise. Parent’s perception of their child’s digital
expertise is assessed with five items adapted from categories of constructive uses of ICTs
described in the Duad et al. (2014) study: (1) I think my child is an expert at communicating with
others online; (2) I think my child is an expert at creating digital content; (3) I think that my child
is an expert at getting information from online resources; (4) I think that my child is an expert at
using technology to express themselves; (5) I think that my child is an expert at using technology
for entertainment purposes. These items were assessed with a 5-points Likert scale (1=strongly
disagree, 2=disagree, 3=neither agree nor disagree, 4=agree, 5= strongly agree).
PARENTAL MEDIATION OF TECHNOLOGY USE 66
Demographic data. A survey of demographic characteristics was also created for this
study. Data points that were collected include child’s lunch status
10
(free, reduced, or full priced
lunch), parent’s education (0=lower than high school education, 1=some high school education,
2=high school graduate, 3=some college education, 4=college graduate or received vocational
degree, 5= some graduate education, 6=received graduate degree), parent’s ethnicity (select all
that apply response options), parent’s age (numeric response), parent’s gender (0=female,
1=male), as well as the focal child’s age and gender.
Data Analysis
Analysis was conducted in two stages, with the first stage analyzing the factor structures
of supportive and regulatory mediation and the second analyzing how motivational and
contextual factors interact to influence supportive and regulatory mediation behaviors.
First stage: confirmatory factor analysis. To address the first research question, six
factor models were fitted under the Confirmatory Factor Analysis framework. This analytic
strategy is used to understand behaviors that make up supportive and regulatory technology
mediation in this population and to test the convergent validity of these behaviors. Factor models
for regulatory mediation were fitted using the Weighted Least Squares Mean and Variance
adjusted (WLSMV) estimator because this scale includes items with binary responses. The use of
the WLSMV is meant to account for the ordinal nature of data collected (Edwards, 2009;
Muthen, 1993). Factor models for supportive mediation were fitted using the Maximum
Likelihood (ML) estimator.
The first model (S1) was specified with each supportive behavior loading onto one latent
“Supportive Mediation” factor. In the second model (S2), items in each subcategory of

10
Although a numeric income item was included in the survey, most parents (over 70%) omitted a response for this
item and numeric income data was not included in the final data analysis.
PARENTAL MEDIATION OF TECHNOLOGY USE 67
supportive behavior were fitted as separate factors, with one “Supportive Mediation” latent
factor specified as a second-order factor (See Appendix F). For regulatory behaviors, one model
(R1) was specified with each regulatory behavior fitted under one latent factor similar to model
S1. As suggested by previous research, another model (R2) was specified in which each
regulatory behavior loaded onto one of three known subcategories of regulatory mediation
(Restrictive Mediation, Technical Mediation, and Monitoring) and one latent “Regulatory
Mediation” factor specified as a second-order factor.
Finally, descriptive statistics such as the mean, standard deviation, and frequency of use
were generated for each mediation behavior in order to understand the prevalence of each
behavior in the sample and low income subsample (those reported to receive free or reduced
priced lunch). These results were compared to factor analysis results to generate a clearer picture
of what types of mediation behaviors low income parents engage in.
Selection of fit indices. Multiple fit indices were used to assess model fit, based on
growing consensus for convergent evidence of fit (Hu & Bentler, 1999). Most SEM scholars now
advocate the report of other fit statistics in addition to the standard χ
2
statistic because of its
sensitivity to sample size. In particular, the χ
2
index tends to reject models with large sample
sizes even when fit is satisfactory (Loehlin, 2004). With small sample sizes, the χ
2
index can be
non-significant even when there are large amounts of model misfit. In comparison, CFI and TLI
are incremental fit indices that assess the improvement in model fit against a baseline model,
which is usually the independence model where variables are assumed to be uncorrelated.
Because the specification that observed variables have zero covariances is highly improbable in
most cases, incremental fit indices such as the CFI and TLI have received criticism for making
any model appear well-fitted when compared to a very bad null model (Loehlin, 2004). In
PARENTAL MEDIATION OF TECHNOLOGY USE 68
contrast to previously discussed absolute and incremental fit indices, the Root Mean Square
Error of Approximation (RMSEA) is a population-based index that is less sensitive to sample
size, adjusts for parsimony, and does not require baseline model specification. However, the
effectiveness of RMSEA still depends on assumptions of normality and adequate sample size.
Because of their relative strengths and weaknesses, multiple fit indices are needed to evaluate
different dimensions of fit. In this study, all of the above mentioned indices were used. The
criteria of adequate fit were defined as having CFI and TLI greater than 0.90, RMSEA less than
0.08, and χ
2
/df less than 3 (Hu & Bentler, 1999; Kline, 1998; Olivares & D’Zurilla, 1996). In
addition to global fit indices, examination of residuals was also carried out as a way to provide
additional convergent evidence of fit. The overall average size of residuals was evaluated via the
SRMR (Standard Root Mean Square Residual) and WRMR (Weighted Root Mean Square
Residual) indices as appropriate for each estimator, with SRMR ≤ 0.10and WRMR ≤ 0.10 as
indicating acceptable fit (Hu & Bentler, 1990).
Exploratory factor analysis. In instances where there were poor fit across a-priori factor
models, exploratory factor analysis techniques were used order to identify the proper factor
structure, including factor rotation and scree plot analyses.
Second stage: path analysis. Before addressing the second question regarding the
relationships among contextual factors, motivational factors, and mediation behaviors,
robustness checks were performed to evaluate the validity and reliability of relevant constructs,
including measurement invariance analysis and scale reliability analysis. These robustness
checks are discussed below, followed by a presentation of how path analytic models were
analyzed.
PARENTAL MEDIATION OF TECHNOLOGY USE 69
Measurement invariance analysis. Because surveys were given in English and Spanish,
a test of measurement invariance was necessary to test the assumption that factor relationships
found in the previous step were the same for parents who took the survey in different languages.
Factor structures above that represented the best fitting models for the Supportive Mediation
latent factor and the Regulatory Mediation latent factor were tested for invariance across the two
survey languages. Factorial invariance analysis proceeded according to recommendations by
Vandenberg and Lance (2000) as well as Horn and McArdle (1992). In particular, measurement
invariance analyses began with an omnibus test for equality of covariance matrices, followed by
a test of configural invariance (equivalent a priori pattern of factor loadings), metric invariance
(equality of item loadings), scalar invariance (equality of item intercepts), and strict invariance
(equality of residual variances). The decision rule for model invariance is a non-significant chi-
square test statistic and p-value (p<0.05), as well as a change in CFI between increasingly
restrictive models that is less than 0.01 (ΔCFI<0.01; Chen, 2007; Cheung & Rensvold, 2002).
IRT-based analysis of test functioning. In order to ensure that newly created scales
yielded a satisfactory amount test information for the study sample, best-fitting factor models
representing regulatory mediation, supportive mediation, and technology knowledge were fitted
using Graded Response Modeling (GRM) under the Item Response Theory framework allowing
both item thresholds and slopes to be estimated (Embretson & Reise, 2000). Subsequently,
Fisher’s information functions for each GRM model were calculated and graphed to determine
the range of latent factor (theta) scores for which the scale is informative.
Scale reliability analysis. Because all scales were adapted or newly created for this study,
reliability statistics were calculated for all measures. In particular, Cronbach’s alphas (Cronbach,
1951) were calculated for scales using summed and standardized composite scores, whereas
PARENTAL MEDIATION OF TECHNOLOGY USE 70
empirical reliabilities were calculated for models using IRT-scaled scores (i.e. regulatory
mediation scale, supportive mediations scale, and technology knowledge measure) (Embretson &
Reise, 2000).
Path analysis. After robustness checks were performed, the first stage of assessing the
relationship among contextual factors (parents’ technical knowledge, parents’ technology usage,
and perception of child’s digital expertise), motivational factors (self-efficacy and role
construction), and technology mediation behaviors commenced with a correlational analysis
using Pearson’s coefficients. Specifically, Pearson’s correlations between mediation behaviors
and other contextual and motivational factors of interest were examined as the first step to better
understand their empirical relationships. In addition, the empirical relationship between
supportive and regulatory mediation behaviors was examined by analyzing Pearson’s correlation
of parents’ scores on these two behaviors.
After correlational analysis, path analysis was performed to examine relationships among
variables. Two path models (P1 & P2) were specified to represent the hypothesized effect
priority (Kline, 2011)
11
. One path model specified relationships among contextual factors,
motivational factors, and supportive mediation behaviors whereas the other specified the same
relationships for regulatory mediation behaviors. Model P1 specified that parents’ technical
knowledge, technology usage, and perception of child’s expertise predict motivational factors
including supportive mediation self-efficacy, regulatory mediation self-efficacy, and parental
role construction (See Appendix F). The model also specified that each contextual variable has
both a direct effect on supportive mediation, and indirect effects as mediated by self-efficacy and
role construction variables. This model reflects the hypothesis that the more parents use

11
In the case that factor solutions showed a higher number of factors representing mediation behaviors, a
corresponding number of path models were fitted.
PARENTAL MEDIATION OF TECHNOLOGY USE 71
technology themselves and the more technically knowledgeable they are, the more self-
efficacious they tend to be about regulating and supporting their child’s ICT usage. More
technically knowledgeable parents are also hypothesized to have greater role expectations
regarding how parents should support children’s digital literacy development. In addition,
parents who believe that their child has more technical expertise are likely to have lower self-
efficacy for mediating the child’s ICT activities. These parents may also have lower expectations
regarding parents’ role in supporting children’s digital literacy growth because their children
already have well-developed skills. These motivational factors, in turn, influence the extent to
which parents engage in mediation behaviors. Model P2 specified the same relationships among
variables, with regulatory mediation behavior as the dependent variable. Control variables were
added in both models, including parents’ school role perception, focal child’s age, parents’
education level, parents’ English language proficiency, and lunch status (free, reduced, or
regular-priced lunch). Effects decomposition analysis was carried out for each path model,
similar to the technique specified in Kline (2011), Sava (2002), and Parajes & Miller (1994).
This included first fitting models with only direct effects between antecedent variables and the
dependent supportive and regulatory mediation variables, then comparing parameter estimates to
models with indirect effects included. For statistically significant indirect paths, the ratios of
indirect to direct effect (Rm) were also calculated (Preacher & Kelly, 2011).
Methodological Considerations
Power analysis. An important consideration in planning a study involving factor and
path analytic techniques is to determine the overall statistical power to reject a model. Sample
size is directly related to statistical power, where an adequate sample size is defined as that
which allows model misfits to be detected (Loehlin, 2004). Regarding this issue, Loehlin (2004)
PARENTAL MEDIATION OF TECHNOLOGY USE 72
extended the work of MacCallum and associates (1996) and offered the sample size needed for
adequate power (i.e. 1-β > 0.80) in factor analysis studies. Loehlin defined adequate power as the
study’s ability to reject the hypothesis of poor fit when there is actually good fit in the
population
12
, as dependent on the model degrees of freedom. For factor and path models
specified in this study, the lowest degrees of freedom was 18. The power for all models based on
the MacCallum et al. (1996) and Loehlin’s (2004) calculations and a sample size of 300 was
higher than 0.90. This figure is sufficiently high to allow variability of fit to be detected (i.e. 1-
β>0.80, Kline, 2011).
Sample size considerations. A related issue is the minimum sample size needed for
model convergence and accurate parameter estimation, given model complexity and the selected
estimator (WLSMV and ML for the present study). There is growing consensus that general
rules of thumb regarding sample sizes are inadequate, such as rules regarding the ratio of cases to
manifest variables (N/p) and those regarding the ratio of cases to parameters (N/q; Moshagen &
Musch, 2014). Instead, the estimation criterion used, the number of indicators per factor, as well
as the magnitude of factor loadings and communalities (i.e. R-squared statistics) are
demonstrated by simulation studies to be salient in determining adequate sample sizes (Muthen
et al., 1997; Moshagen & Musch, 2014; Beauducel & Herzberg, 2006; MacCallum & Widaman,
1999). This reflects that increases in construct reliability decreases sample size requirements
(Gagne & Hancock, 2006). The ML and WLSMV estimators that were used in this study have
been shown to perform well for moderately complex models (about 15 variables) with sample
sizes of 200 or more (Muthen et al., 1997). A Monte Carlo study conducted by Maccallum and
Widaman (1999) also found that a sample size of at least 200 yields acceptable percentages of

12
Loehlin’s (2004) calculations are based on the specification that RMSEA≥1.0 indicates poor fit and RMSEA≤0.05
indicates good fit.
PARENTAL MEDIATION OF TECHNOLOGY USE 73
convergent and admissible solutions (>95%) across all communality levels for a model with the
ratio of variables to factor close to this study’s specified models (i.e. models with at least 4
indicators per factor, 5 categories per indicator). Furthermore, a model with the projected
structure (i.e. at least 5 categories per indicator) and moderate to high factor loadings were found
to have acceptable relative percentage bias
13
using ML or WLSMV and a sample size of at least
200 (Moshagen & Musch, 2014).
Phase Two: Qualitative Data Collection and Analysis
Participants
During the survey administration process detailed above, parents were asked if they were
willing to participate in a one-on-one interview with the researcher. Participants for the
qualitative phase (n=8) were recruited from the pool of parents who expressed willingness to
participate in an individual interview. Maximal variation purposive sampling was used as the
criteria for selecting parents to participate in individual interviews (Crewell & Clark, 2011). The
conditions for maximizing differences were based on the types of mediation behaviors parents
engage in as well as the extent to which parents engage in these behaviors with their children, as
specified in survey responses. Specifically, the goal of sampling for individual interviews was to
recruit parents who engage in mediation behaviors that are qualitatively different from one
another as well as parents who engage in varying levels of mediation (i.e. recruiting those who
are exceptionally involved in their children’s digital literacy development as well as those who
are considerably less involved compared to other parents). This sampling technique was
intended to maximize the variability in the data in terms of the types of mediation behaviors
parents engage in, as parents who are less engaged in adolescents’ ICT usage may use strategies

13
Relative percentage bias is defined by Moshagen & Musch (2014) as RB
θ
=100(θ – θ), where θ is the observed fit
statistic and θ is the expected statistic. RB
θ
values less than |10%| were considered acceptable.
PARENTAL MEDIATION OF TECHNOLOGY USE 74
that are different than those of their peers. In addition, perceptions of factors that influence their
mediation decisions likely vary among parents who differ in terms of the extent of their
mediation behaviors.
Materials
Six interview questions were used to guide individual interviews, although parents were
encouraged to elaborate on topics they find especially relevant (See Appendix G). Some
questions are based on the protocol used by Barron and her associates (2009) in their study of
parents’ supportive mediation behaviors. Additional focus was placed on the types of mediation
behaviors parents engage in, what these mediation behaviors look like in practice, as well as
contextual factors that contribute to their mediation decisions.
Procedures
Data collection for this phase began after data collection in the quantitative phase was
complete. This schedule was intended to allow for maximal variation purposive sampling, such
that parents’ scores on various constructs of interest were calculated and used in making
recruitment decisions. Individual interviews were conducted in participants’ homes or at another
location agreed upon by the participant and the researcher. Each parent interview lasted
approximately 45 minutes and were audio-recorded with parents’ consent.
Data analysis
Audio recordings of interviews were transcribed, with alphanumeric codes assigned to
each participating parent. Analysis of interview data was conducted in two stages. In the first
stage, a deductive approach was used to code interviews according to specific mediation
behaviors found by previous research (i.e. from mediation categories represented in the survey
instrument), factors known to affect mediation decisions, as well as trends found from
PARENTAL MEDIATION OF TECHNOLOGY USE 75
quantitative analysis. The coding process included reading through the transcripts, recording
short memos linking data to previous mediation categories, using NVIVO software to divide
texts into small units, assigning labels to these units, and finally grouping units into themes
(Creswell & Clark, 2011).
The second stage consisted of inductive coding, with logistic steps similar to the first
deductive analysis (i.e. reading, writing memos, segmenting data, assigning themes). An
important distinction was the use of inductive analysis techniques, such as those described by
Neumann (2006). In this stage, data was explored without reference to what is already known
about what constitutes technology mediation and factors that may influence mediation behaviors.
Current understandings of parents’ mediation techniques were “held lightly” (p. 387) in order to
examine ways in which the data transforms preexisting knowledge. This stance was necessary in
order to be able to discover how qualitative data added to quantitative findings, yielding a more
complete picture of the home-based technology mediation process.
Validity Considerations
In addressing the assumption of interpretative validity, two strategies were used as
recommended by Creswell and Clark (2011). First, a triangulation process was used to ensure
that emergent themes are consistent across different participating parents. Themes found from
interview data were also triangulated with quantitative findings from the first phase. Secondly,
disconfirming evidence that represents a divergent perspective was searched for within the data.
However, the presence of some disconfirming evidence is natural and expected, and as such was
not used to discredit a theme unless disconfirmation emerged across several data sources (i.e.
interviews of different parents with varying mediation characteristics, or both qualitative and
quantitative data).
PARENTAL MEDIATION OF TECHNOLOGY USE 76
CHAPTER 4: RESULTS
Using the methods described above, the following results are found for each of the
following research questions:
Question 1a: How do parents from low socioeconomic communities support and restrict
adolescents’ ICT usage? What is the prevalence of each type of behavior in the sample?

Descriptive statistics of sample parents’ technology mediation behaviors are reported in
Table 2-4, including the mean, standard deviation, range of scores, and percent of engagement.
This report shows that this sample consisting mostly of low income parents were active
technology mediators. For restrictive mediation behaviors (RTM1-11), almost all parents
indicated that they restrict their child from giving out personal information online (95.9%) and
encourage their child to do other activities instead of using technology (94.4%). A high
percentage of parents also indicated that they restrict their child from using online chat-rooms
(84.8%) and from uploading digital content (75.5%), as well as set up time limits for technology
use (87.2%). Parents engaged in other restrictive behaviors to a lower extent, ranging from about
45-60%. For non-technical monitoring (MNT1-6), approximately 70-80% parents indicated that
they engage in these monitoring behaviors sometimes or more (scoring 3 or higher on the item).
For technical mediation (TCM1-4), more parents used parental control to block content access
(74%) and to keep track of the child’s online activities (74.8%), than to limit time spent with
technology (44.8%) or to prevent spam and viruses (67.1%). Percentages representing the
mediation behaviors of the low income subsample did not differ substantially from those for the
entire group.
For most supportive behaviors, about 70-80% of parents indicated that they execute the
behavior sometimes, often, or very often (scoring 3 or higher on the item). Some behaviors were
more popular, with about 90% of sample parents indicating that they talk to the child at least
PARENTAL MEDIATION OF TECHNOLOGY USE 77
sometimes about how to be safe when interacting with other people using technology and give
the child ideas about what to read and view online. Lower percentages of sample parents
encouraged their child to use technology to connect with others in the community (41%) and
looked for technology classes their child could take (53.6%). Notably, parents reported that they
engaged in all behaviors belonging to the proposed help recruitment factor (RTS 1&2; RTG
1&2) to a lower extent compared to most other behaviors, with about 60 to 70 percent of sample
parents indicating that they engaged in these behavior sometimes or more. This result gave an
early indication that these items may have tapped into a construct different from other supportive
behaviors.
Question 1b: Do supportive mediation behaviors found from previous research represent
different facets of the same underlying construct? For regulatory mediation behaviors?

Confirmatory factor analysis revealed that the restrictive mediation subtype (a component
of regulatory mediation) has satisfactory fit as a one factor model (Table 5; Model R3; χ
2
/df=1.85,
CFI=0.952, TLI-0.946, RMSEA=0.056, WRMR=1.087). The restrictive mediation measurement
model is illustrated in Figure 1. Other measurement models for regulatory mediation showed
poor fit, including models specifying regulatory behaviors as one factor (Model R1), regulatory
behaviors as a second-order factor (Model R2), and two models with monitoring and technical
mediation fitted as separate first order factors (Models R4 and R5). In the exploratory phase,
fitting all monitoring and technical mediation items as one factor (model R6; 10 remaining
regulatory items outside of restrictive mediation) did not result in satisfactory fit, pointing to a
possible hierarchical factor solution. Subsequent scree plot analysis of these items reveals a three
to four factor solutions (Figure 2). Using oblique promax rotation as suggested by Floyd and
Widaman (1995) because of the expected hierarchical factor relationship, items were shown to
load into four factors, with monitoring split into two factors (MNTa and MNTb) and technical
PARENTAL MEDIATION OF TECHNOLOGY USE 78
mediation split into another two factors (TCMa and TCMb; Table 6). However, modeling these
four factor as the first-order factor and regulatory behavior as the second-order factor showed
unsatisfactory fit (Table 7, Model R7; χ
2
/df=5.11, CFI=0.991, TLI-0.987, RMSEA=0.122,
WRMR=1.474).
Led by theoretical considerations, two other models were fitted, one which combined
technical mediation items and separated monitoring items (Table 7, Model R8;
MNTa+MNTb+all TCM), and another which combined monitoring items and separated
technical mediation items (Model R9; all MNT+ TCMa +TCMb). Again, regulatory mediation
was fitted as a second-order latent factor, whereas monitoring and technical mediation in their
variations served as 1
st
order factors. Of these, the model with TCM items combined under one
factor (Model R8) showed the best fit (χ
2
/df=2.14, CFI=0.997, TLI=0.996, RMSEA=0.064,
WRMR=0.969; monitoring measurement model illustration in Figure 3). Furthermore, an
additional model which included restrictive mediation, technical mediation, and two monitoring
factors as first order factors and regulatory mediation as the second-order latent factor showed
poor fit (Model R10; χ
2
/df=5.77, CFI=0.951, TLI=0.944, RMSEA=0.134, WRMR=2.05),
suggesting a separate factor solution for restrictive mediation and other regulatory behaviors.
These results support the theoretical distinction between restrictive mediation and
monitoring/technical mediation behaviors. A more in-depth examination of monitoring and
technical mediation behavioral indicators also revealed more commonalities among these
behaviors than previously noted. In particular, technical mediation (including behaviors such as
using parental control software to monitor and limit the child’s online activities) can be thought
of another facet of monitoring, albeit using technology as tools to assist with monitoring efforts.
Thus, it makes theoretical sense that monitoring and technical mediation fit well as first order
PARENTAL MEDIATION OF TECHNOLOGY USE 79
factors, each loading onto the same the second-order factor. For conceptual clarity, the factor
represented by restrictive behaviors (i.e. RTM items) will henceforth be termed restrictive
mediation, whereas the second-order factor represented by monitoring and technical mediation
behaviors (i.e. MNT and TCM items) will be termed monitoring, with the previous monitoring
and technical mediation behavioral indicators recast as non-technical monitoring and technical
monitoring, respectively.
For supportive behaviors, proposed models with all 25 items loading onto one factor
(Table 8; Model S1), supportive behaviors as a second-order factor with five subcategories of
supportive mediation as first-order factors (Model S2), and five models with each supportive
categories fitted separately (Models S3-S7) all showed poor fit
14
. During the exploratory phase,
scree plot analysis showed a possible five to six factor solutions (Figure 4). Principal factor
analysis with oblique promax rotation was then performed, resulting in clear six factor solutions
with 19 items (Table 9). When these six factors were examined, three were found to represent the
same group of behaviors as the supportive subcategories formed a-priori, including guidance
provision (GDP), resource provision (RSP) and, connectedness promotion (CNP), but with
some rearrangement of items. Items representing brokering digital learning (BDL items,
Appendix D) now loaded onto the connectedness promotion factor, representing the fact that the
act of brokering learning parents in this sample perform is related to promoting connection with
others who can provide digital learning resources, as will be discussed later when qualitative data
are presented. Also, the guidance provision factor now consists only of active content mediation
and does not include active safety mediation. One instilling cultural roles of technology item
(ICR2 I; I talk to my child about how technology can improve his/her life) now loads onto this

14
The resource provision factor (Model S7) cannot be tested because only three items were specified, giving the
model zero degree of the freedom.
PARENTAL MEDIATION OF TECHNOLOGY USE 80
same guidance provision factor. This factor structure makes theoretical sense as well, as talking
to one’s child about how technology can be used to improve his/her life can be thought of as a
form of providing guidance. Finally, the resource provision factor has the same structure as the
a-priori formulation.
Three factor solutions represented new arrangements of the supportive mediation
subcomponents. Firstly, both active safety mediation items (ASM1 & ASM2) proposed to be part
of guidance provision were shown to be grouped into their own factor, now termed active safety
mediation. Also, items related to encouraging the child to become more involved with
technology use loaded onto one factor, including looking for technology classes for the child
(BDL2), encouraging the child to learn more about technology (EES1), encouraging the child to
take a technology class (EES2), and showing the child how technology can be used in everyday
life (ICR1). These items combined to form a particular facet underlying supportive mediation
that taps into how parents encourage the child to learn about and use technology in ways that
build technical expertise and digital literacy. This factor is now called technical involvement
promotion. Finally, one additional factor is suggested by principal factor analysis to include
items involving parents using technology with the child, including doing something together
with the child (CCU1), collaborating with the child to achieve something (CCU2), learning
something together using technology (PCU1), and teaching the child how to do something using
technology (EOI1). This factor, now termed instructive co-use, goes beyond the traditional
definition of co-use defined by previous literature (Livingstone & Helsper, 2008) to include more
purpose-driven activities (i.e. include learning and achieving something through technology
rather than only consisting of passive usage). Also, it specifies more instructive actions by
PARENTAL MEDIATION OF TECHNOLOGY USE 81
parents, with parents cast as actively structuring the co-use episodes rather than as an equal
partner with the child in technology usage.
In addition to 19 supportive behaviors loading onto six factors, principal factor analysis
also suggested that two items may possess joint loading onto two factors. One brokering digital
learning item (BDL1; I find ways for my child to learn how to do new things with technology) is
proposed to also load onto the instructive co-use factor, which is in line with this factor reflecting
more intentionality on the part of the parent than the traditional co-use factor. Another brokering
digital learning item (BDL2; I look for technology classes my child could take) is proposed to
load onto the new technology involvement promotion factor. This addition is also theoretically
supported because this item is similar to other parent behaviors in the factor related to
encouraging the child to learn more about beneficial uses of technology. Because these two joint
loadings are shown in factor analysis to be smaller in magnitude compared to other items in the
factor, their relevance were tested using four models. These four models include one which
specified both two joint loadings (Model S9; BDL1 in instructive co-use and BDL2 in
technology involvement promotion), one which specified one joint loading for BDL1 in
instructive co-use (Model S10), one which specified one joint loading for BDL2 in technology
involvement promotion (Model S11), and one which specified no joint loading (Model S12). Of
these, the model that specifies two joint loadings demonstrated the best fit (Table 10, Model
R10; χ
2
/df=2.03, CFI=0.923, TLI=0.908, RMSEA=0.062, SRMR=0.056). Chi-square difference
tests comparing models with and without each joint loading following procedures outlined in
Loehlin (2004) also show that the addition of both the BDL1 and BLD2 joint loadings resulted in
significant improvement in fit (Table 11). Lastly, fitting all 19 items as one factor (Model S8)
PARENTAL MEDIATION OF TECHNOLOGY USE 82
and each subcategory as separate factors with no second-order relationships
15
(Model S13) also
resulted in unsatisfactory fit (Table 10), providing additional evidence for a hierarchical factor
solution for supportive mediation behaviors. The best fitting supportive mediation measurement
model is illustrated in Figure 5.
Qualitative Trends
Taken together, the above factor solutions provided evidence for the convergent validity
of restrictive mediation, monitoring, and supportive mediation behaviors. Qualitative data
echoed these results, with most parents naturally referring to restrictive, monitoring, and
supportive behaviors in distinct terms. Interview data also suggest that they engage in a variety
of mediation behaviors. Further, qualitative data extends quantitative trends by illustrating
parents’ effort to balance regulatory and supportive mediation behaviors, as well the
intentionality with which these parents mediate technology use for their adolescent children.
These qualitative findings are presented below.
Restrictive mediation. For follow-up parent interviews, parents were recruited according
to the maximal variation purposive sampling strategy in order to gain perspectives on how
parents with varying characteristics mediate technology. Table 12 lists these parents’ scores on
various contextual, motivational, and behavioral constructs of interests (scores are in percentiles
unless indicated). In terms of restrictive mediation, parents in the interview subsample agreed
that their restrictive behaviors stem from their worry about internet safety, particularly from their
child’s contact with strangers. Megan
16
, a thirty year-old mother who scored the highest on

15
The active safety mediation is not included in Model S13 because this factor only has two indicators and the
model is not identified when only two items load onto one first order factor.
16
All parent names are pseudonyms.
PARENTAL MEDIATION OF TECHNOLOGY USE 83
restrictive mediation engagement from this interview subsample, talked about restricting ICT
usage for her 12 year-old:
My 12-year-old, [because of] her age, she wants to get into that social media stuff. I limit
it. I'm scared of it. Because I don’t want her to talk to strangers or something when I'm
not around. Even though you put limitations, it's so hard to monitor all the time,
especially with old[er] children. I kind of don’t allow her to have it or see it if I'm not
there.

Another constant parent worry is the child’s over-dependence on technology and the limitation
this places on becoming involved in other constructive activities. Parallel to quantitative results,
all parents interviewed set up a time limit for their child’s technology use and encourage the
child to engage in other activities when they see that s/he has spent too much time using a
device. Carol, a 33-year-old mother of a ten-year-old said, “[technology is] only for three hours
max… If it's a school night, it’ll be forty-five minutes.” She also talked about how she
encourages her son to do other activities when the daily technology time limit is reached, “When
his time is up, you need something to do? Play with your Legos. You can go outside. You can go
walk the dog. Get the chalk. Our front yard is all cement so we play chalk, we do beanbag toss
and all kind of stuff with just the chalk and the ground.” All parents agreed that this type of
encouragement is what they do on a regular basis. Rather than only setting up time limits, parents
actively suggest alternative activities their child can engage in, either an activity the child can
engage in by him/herself or one in which the family can spend time together. Megan commented
on the active nature of this behavior:
I know that there's parents out there that don’t get their children involved in technology
because they think that they're making them less physical and stuff. I understand that that
could be a problem but you have to limit the time. You have to limit the time that they're
on it. You've got to make sure that they're getting physical activity. I enrolled my children
in soccer. I'm making sure that they get physical activity as well as their online education.

PARENTAL MEDIATION OF TECHNOLOGY USE 84
These results suggest that even in restrictive mediation, arguably the least involved among all
mediation types, parents from this sample demonstrated active involvement in how they limit
children’s ICT activities. With their worry about internet safety and technology over-
dependence, they co-construct with their child the right amount and type of ICT- and non-ICT
related activities the child should engage in.
Related to the active nature of parents’ restrictive mediation engagement, parents also
vary in terms of how much they engage in restrictive mediation depending on the child’s age.
This is most apparent in parents with an older adolescent child, who discussed changes in their
restrictive mediation behaviors as the child grows older. Marcy, a mother of a 17-years-old boy
who scored low on restrictive mediation engagement, said:
Well, now that he is about six months from being an adult, he pretty much has free rein. I
mean, he's almost an adult. He has his own laptop, which we don't really restrict….
[When he was younger], he had just a phone for phone calls and text and that was it. He
got that in seventh grade and that was more because of after school and making sure he
got home…We had restrictions on his browser that he could use and we had restrictions
on him during the day when he couldn't use his phone from eight to three during school
days. I refused to let him have Facebook or Instagram before the minimum age. When he
was thirteen and he joined Facebook, I said at that time he needed to be my friend and I
said I could approve whoever your friends are.

This quote sums up the extent that restrictive mediation changes throughout the child’s
adolescent years, with the parent engaging heavily in placing restrictions when the child was in
early adolescence and relaxing most restrictions by the time the child is in late adolescence. Even
with a mid-adolescent child, some parents noticed a difference in the amount of restriction
compared to when the child was younger. Hanna, a mother of a 15-year-old girl who also scored
low on the restrictive mediation survey, told the interviewer, “When [my daughter] was little we
didn't give her the phone. We would limit, we wouldn't let her have the technology that she has
right now. The rules kind of loosened up a lot.”
PARENTAL MEDIATION OF TECHNOLOGY USE 85
Further, parents expressed that these changes in restrictive mediation evolved due to
increasing trust in the child’s ability to distinguish between appropriate and inappropriate online
contents and behaviors. In addition, parents of mid- and older- adolescent children stated that
they wish to build this trust as well as the child’s self-regulation skills as s/he grows older.
Marcy, the mother of the 17-year-old, said:
I feel like he needs to build his own self-monitoring and balance and figure it out when
he goes to college. …You have restrictions and they're there. You can restrict everything.
I can find an app where I could look at where my son is right now in the house. Micro
chipping them. I do think that there is a burden as a parent, knowing when to let up a
little bit. At what point do you allow them more and more freedom because when they go
to college, you don't want them to be the kid that doesn't sleep because he has access to
the whole internet.

This portrait of parents’ restrictive mediation also illustrates parents as active mediators of
technology, constantly refining their mediation strategies to match the child’s changing abilities
as well as their own evolving goals for child-rearing. These results also suggest that low amounts
of restrictive mediation engagement do not always signal neglectful parenting, but could also be
a result of parents’ active decision to scaffold the development of the child’s ICT-related self-
regulation skills as s/he grows older.
Monitoring. Like restrictive mediation, parents engaged in a variety of technology
monitoring behaviors, which are also dependent on the child’s age. All interviewed parents of
younger adolescent children (ages 10-13, including Carol, Mary, Megan, Sandy, and Arnold)
discussed physically monitoring the child by being present when the child goes online. For
example, Carol, a mother of a 10-year-old child, stated:
When he's on my computer that's when I'm standing over his shoulder. We were doing
solar systems science experiment or whatever for his school, and I was telling him, "Just
look up the information you need," and he said he couldn't on his computer and so that
must've meant there must've been some kind of block on there. I let him use my laptop
PARENTAL MEDIATION OF TECHNOLOGY USE 86
which is unrestricted but, because of that, I'm over his shoulder making sure he's not
diddling and dabbling in other things.

Other popular strategies include asking the child to use ICTs in a central location in the home
and asking the child to “turn in” their devices before they go to bed each night, which naturally
limits ICT usage in the child’s bedroom. Although a mother to a late-adolescent child, Marcy
talked about using this strategy when her son was younger:
When he was in eighth grade, [the limit] was nine o'clock. Every night when he was done
with his net-book or with his phone he just had to turn it in to us. Really, it ended up
being downstairs in the cabinet and it just became routine. … It just became routine for
him and even now I notice that he still puts it out in the hall.

Further, a common reason parents cited for engaging in this type of mediation is to ensure
that the child does not encounter inappropriate content online and to limit exposure to online
risks that could occur from isolated usage. Marcy emphasized that “with YouTube, it was very
easy for [my son] to go to the far end and us not even realize. So we did have obviously filters
for internet searches. We did decide to the put the family computer in a very central location
where it was very visible in our house.” In addition, parents monitor because they acknowledge
that unsafe ICT interactions may not always be child-initiated, as Sandy (a mother of a 13-year-
old girl) communicated:
I don't encourage her to be isolated when she uses her technology, because things happen
and not necessarily on her side, but it could be someone that she's communicating with or
whatever the case. That's where the limitations come in, as well as me knowing exactly
who she's talking to. If it's not somebody that I agree with, then I shut it down, or if I'm
not in the room her older brother's in the room or her dad is in the room. Somebody is
always around so she can't really isolate herself, to set herself up to be in a situation that
she can't get herself out of.

These parental views indicate that both restrictive and monitoring behaviors are rooted in
ensuring that children have a safe and age-appropriate online experience. However, the reasons
parents give for monitoring their children’s ICT usage did not include curbing their child’s over-
PARENTAL MEDIATION OF TECHNOLOGY USE 87
dependence on technology, which was one of the main reasons parents cite for engaging in
restrictive mediation. This difference suggests a distinction between the intentions behind these
two types of behavior, which may account for the quantitative results pointing to separate factor
solutions for restrictive and monitoring behaviors.
Other than monitoring using physical means, other monitoring behaviors include
checking up on the child’s online activities and using software filters to limit exposure to
inappropriate content. Parents in the interview subsample indicated that they engage in all types
of monitoring behaviors listed in the survey, including checking up on the child’s usage history
and social networking profile. Further, parents explained that these monitoring efforts led them
to use ICTs in ways that they normally would not have. Hanna, a 44-year old mother of a 15-
year-old girl, told the interviewer:
I know some parents don't use social network because they see the danger and they don't
want to be [involved]. For me, I want to know where I can find information or how
people could get your information. I try to be friends with my daughter's friends so that I
could see what's going on or things that she may not be telling me. I'm kind of spying. I
try to learn everything even though I don't use it a whole lot, like Snapchat or Instagram.
I do try to sign up for an account and make sure that I follow her as well or my other kids
just so that I could see what's not being told to me.

Again, this quote and many others like it cast parents in the interview subsample as being active
in ensuring their children’s online safety. They go out of their way to become integrated into
their children’s online lives, continually exerting their physical and online presence all the time,
and not only in a retroactive way when troublesome behaviors occur.
In addition to becoming more active ICT users themselves in the process of engaging in
monitoring behaviors, many parents also cited that they use technology tools to help in both
technical and non-technical monitoring efforts. This echoes quantitative results, which suggest a
one-factor solution for non-technical and technical monitoring. Most parents reported using
PARENTAL MEDIATION OF TECHNOLOGY USE 88
internet filters to block the child’s exposure to unsuitable content, as well as using a software to
set limits on the amount of time the child can spend on a device. Furthermore, more technically
savvy parents also use available tools to help them monitor the types of online activities their
child engages in, a behavior that is traditional regarded as a type of non-technical monitoring.
For example, Randy, a 36-year-old father who scored at the 94
th
percentile on the technology
knowledge measure, said of his monitoring behavior:
Can I check on what they're doing? Yes, I can. I can easily just turn my phone on and
check what's going on on the laptop. We have them synchronized like that. Once in a
while, I'll get online and I'll check to see what they're doing and what they're chit-chatting
about. … I'll check the phones once in a while and they don't have anything that they're
not supposed to. I have this chip on the SIM card that I can go to a website and it tells me
exactly where they've been on the phone.

Related to the use of technology tools to help with their monitoring efforts, parents also talked
about the having the technology knowledge necessary to effectively monitor children’s ICT
activities. For example, Sandy expressed:

I can go in and I can check at any given moment and see who she's talking to, when, and
I know how to go in through cookies and search so that I can verify if she tries to erase
anything, whatever the case. I pretty much know how to maneuver my way through it so
I'll know exactly what's going on.

Comments like these reflect a theme in parents’ interviews that parents need to be well-versed in
technology knowledge in order to effectively monitor children’s usage. Some parents also
emphasized that oftentimes parents need to have advance enough skills to overcome children’s
efforts to conceal inappropriate behaviors, such as deleting usage history illustrated in Sandy’s
quote. Because technology knowledge is closely tied to both technical and non-technical
monitoring (i.e. monitoring done by a software vs. those done manually by the parent such as
checking usage history), it is not surprising that factor analysis results show these two highly
PARENTAL MEDIATION OF TECHNOLOGY USE 89
related constructs as loading onto the same second-order monitoring factor. Relatedly, the
technology-focused nature of monitoring makes it distinct from restrictive mediation, which is
also reflected in quantitative results from factor analysis.
Supportive mediation. In addition to regulatory mediation like restrictive and
monitoring behaviors, parents in the interview subsample also indicated that they engage in a
wide variety of supportive behaviors. The sections below focused on each different type of
support parents provide for their adolescents’ technology use.
Resource provision. The two most common supportive behaviors that all parents with
varying contextual and motivation characteristics engage in are resource provision and active
safety mediation. For example, Arnold, a 52-year-old father who arguably has the least adaptive
contextual and motivational characteristics among those in the interview subsample, immediately
replied after he was asked how he supported his son’s technology usage:
I bought the computer because I thought they will need it. And really, they need it
because they need to learn more [about] how to get more information, more everything.

His sentiment is echoed by all parents in the interview subsample, all of whom cited that they
provide technology devices to their children to help them learn more about how to use
technology as well as to help support their academic work. With the latter reason in mind, Hanna
also talked about providing the technology that would benefit her daughter in school:
They have Chromebooks at school in the classroom. They can't take it home. [The
school] issued them one at school they can use. They don't take it home. We try to buy
the same technology so that they could use it at home and be familiar with it. As soon as
we found out our school opted for the Chromebook instead of the iPad for their
classrooms, then we bought the Chromebook.

Active safety mediation. In addition to providing resources, all parents in the interview
subsample agreed that another basic supportive parental role is to ensure the child’s safety when
using ICTs, which includes having conversations with the child about being safe online. When
PARENTAL MEDIATION OF TECHNOLOGY USE 90
asked about parent’s responsibilities in helping children learn about technology use compared to
schools’ responsibilities, Sandy answered:
I think there's a fine line there because certain things as a whole, the parents are going to
do regardless of what the school does anyway. Like safety, a responsible parent would. I
wouldn't just leave it up to a school to teach my child how to be safe on the internet. I
would definitely share that information with my children.

This quote demonstrates a consistent theme from parent interviews, with parents citing that
talking to their children about being safe while using ICTs is an essential mediation strategy.
They cast this mediation behavior as a natural part of parenting because the first goal of child-
rearing is to keep the child safe. In particular, parents of mid- and late- adolescent children who
are allowed to use social media especially noted their engagement in this type of mediation. For
instance, Hanna, a mother of a 15-year-old girl, explained how she encourages her daughter to be
safe online:
I sometimes look at her things and I would say, "Oh my gosh, you have x number of
followers on Instagram. Do you even know who they are?" I always talk to her. I don't try
to control who is her friend on Facebook or Snapchat or something but I would give
examples. I said, "I just read this news. This girl sent a nude photo to the boyfriend, but
now it's all over the internet." I just say examples of how people have done crazy things
that they shouldn't have. I said, "I hope you're not doing stupid things like this." Kind of
using an example of other people instead of telling her, "You shouldn't do this, you
shouldn't do this." I don't think they'll listen. I don't think it would stick.

Because the child’s involvement in social media outlets presents increased risks, parents of these
older adolescent children who use social media tend to perceive active safety mediation as even
more crucial compared to parents of younger adolescents. Again, this illustrates parents as active
mediators who constantly refine their support of their child’s technology use to fit the child’s
needs and development.
Instructive co-use. Another important theme that emerged from quantitative data related
to supportive mediation is the intentionality with which parents co-use technology with
PARENTAL MEDIATION OF TECHNOLOGY USE 91
adolescent children. The origin of the co-use construct as a descendent of television co-viewing
tended to cast co-use as a passive strategy, with parents responding to their child’s needs or
reacting to what the child encounters through media. However, parents in the interview
subsample demonstrated that their co-use of ICT devices is mostly done with a purpose. Carol
talked about the co-use of technology in her household, which are aimed at increasing her son’s
technology skills:
[We got him] like the new age Richter set where you’re building a computer. Like a little
hand-held one. It’s going to be like a mini one but it’s everything, you know, all the little
soldering pieces and stuff. When we got him the package, it looked a little advanced and
my boyfriend [the father] said, when he has time to do it side by side with him, we’ll let
him start it. We’ve been looking for advances for him.

This quote shows that parents are active in looking for opportunities for their children to gain
new technical skills and would use technology with the child to achieve this goal. In addition,
parents are also active in encouraging children to increase their knowledge about the world by
looking for information together with the child online. Again, this theme is consistent across
parents with differing characteristics. For instance, Mary, a 45-year-old mother who scored at the
16
th
percentile in supportive mediation, talked about her co-use with her daughter and how she
looked for information together with the child:
Mary: Sometimes they have questions, ‘What is this?’ And you don’t know what
it is. You can’t answer. And sometimes I say to my daughter, ‘Let me look
on google what it means or what is there.’ … I remember she asked me,
‘What is meningitis?’ I say, ‘Let’s find out what it means.’
Interviewer: So, right there you just looked on google with her?
Mary: Yes, we looked on google.

On the other hand, parents who engage highly in supportive mediation also co-use ICTs with
their children by searching for information online together. Sandy, a mother who scored at the
91
st
percentile in supportive mediation described her co-use:

PARENTAL MEDIATION OF TECHNOLOGY USE 92
There have been times in the past where if she was doing research on a subject, and she
didn't uncover as much information as she'd like to, then I would give her tips on how to
narrow the search in terms of getting more concise information so that it's not so broad.
It's more focused on the area of which she's interested in getting information on.

Although both co-use, information searching behaviors are centered around helping children gain
new knowledge using communication technologies, parents who provide greater support tend to
show the child more effective ways to retrieve online information. In both cases, however,
parents show intentionality in their co-use episodes, modeling through their use of technology
with the child how technology tools can be a gateway for learning. This finding parallels
quantitative trends demonstrating instructive co-use as a factor that encompasses parents
teaching the child new aspects of technology use while using technology together with the child.
Guidance provision. In addition to instructive co-use, many parents also discussed how
they encourage their child to independently use technology for gaining new knowledge. Parents
in the interview subsample reported that they encouraged their child to look online for
information when the child has a question, rather than relying on the parent to provide an answer.
For example, Sandy explained:
If we're having a conversation, or if we're watching something on TV, and then they'll see
[the word] hierarchy, and then she'll say, "what is that?" I say well, instead of me telling
her, I'll tell her to research it and then come back and tell me what it means. Or if we talk
about an era for example, she'll say, "oh what does that mean, the Renaissance era? What
are you talking about? What is that all about?" Okay, well look it up, come back to me
and tell me what it means.

Like Sandy, many parents reported that they encourage their children to use online resources to
learn more about content the child encountered through the media, or about topics the child
learned in school. Many parents in the interview sample also reported that they suggest online
content for their child. For instance, Hanna expressed that she would suggest online content for
her 15-year-old daughter, explaining that “if I read a news article about something or watch a
PARENTAL MEDIATION OF TECHNOLOGY USE 93
good YouTube video, I try to send it to [my daughter].” Other parents go beyond suggesting
online content they’ve encountered and are more active in seeking ways to encourage their
children to learn more about how to use online informational resources. Randy, a father of a 15-
year-old boy explained:
I encouraged them sometimes. I usually have a question every week. Today's question for
all the kids was why do they make the holes on a golf ball? I'll give them $10. Every
week, I give them something like that. I encourage them to get on the internet and try to
see or ask people. … I encourage him to do it because if it’s up to him, he’d be playing
video games.

The above quotes represent varying degrees of behaviors that are part of the guidance provision
factor. As shown by these parents’ insights, this type of mediation behavior is focused on
guiding children towards an understanding of how informational resources can be leveraged for
independent learning, as well as encouraging more constructive ICT behaviors in which children
explore what information technologies have to offer.
Technology involvement promotion. Another type of supportive mediation parents
engage in is encouraging more involvement with technology tools, including encouraging the
child to learn more about new technology tools and to use these tools in daily life. For example,
parents expressed that they would encourage their child to take more technology-related classes.
For instance, Megan expressed, “I would encourage her to take probably a typing class or like a
graphic design class or something like that. That would probably be good because she's artistic.”
Other parents also mentioned coding classes as a type of class they would encourage their child
to take, especially if the child already has an interest in computer programming. As represented
by the above quote, some parents in the interview subsample also expressed balancing their
desire for their child to learn more about technology tools with the child’s existing interest.
Because her daughter enjoys creating art, Megan would work to infuse technology tools into
PARENTAL MEDIATION OF TECHNOLOGY USE 94
what her daughter is already engaging in by suggesting a graphic design class. However, it
should be noted that a lower number of parents in the interview subsample reported that they
would encourage their child to take a technology class compared to other types of supportive
behaviors, with some stating that the school already provides the type of classes that would give
their child the technical knowledge they need. This trend echoes quantitative data, which
indicated that only 53.6% of parents who took the survey reported looking for technology classes
their child could take at least occasionally (Table 4). On the other hand, this trend could be
another facet of parents responding to their children’s interest, such that only parents who have
children with an interest related to technology would encourage their children to take a
technology class outside of those provided by the school.
In addition to encouraging the child to expand their technical skills, parents also reported
that they suggest a variety of ways in which technology can help manage or ease daily tasks.
This typically occurs when parents suggest software programs that provide homework assistance,
help manage school work, assist with scheduling, or organize family activities. For example,
Randy talked about a program he suggested for his children:
My three oldest ones on their phone, I downloaded an app for them. I forgot
what it's called. It's an app where they have their schedule from the first period to
second, third, fourth and they write in the homework they need to do. After school
when they get home, it just reminds them from this time to this time, you’ve got to do
this. This time to this time, you do that.

These encouragements can be seen as a way that parents socialize children to understand the
ways in which technology can be leveraged as tools for daily living. When asked about the
conversation around technology in her house, Carol said that she tells her children that, “you use
your technology tools to make your life easier. You’re not going to take a spoon and try and use
it as a hammer.” This shows parents’ efforts to help children perceive technology as tools that
PARENTAL MEDIATION OF TECHNOLOGY USE 95
can be used in all aspects of life. Further, parents also discussed during interviews that they make
this explicit effort to introduce helpful tools for their children because their children are not
likely to learn to use the tools on their own. As Megan noted:
I'm teaching my oldest right now how to use it for organization. I had her write her
notes in a program. There's this program that she has downloaded, it has reminders
easily pop up on your screen and stuff. [These programs are] really permitting that type
of using the technology in that way. Setting her alarm to wake up. She didn’t know
that stuff. She just knew the fun part.

Again, these parent comments show that parents are active in supporting their children’s
technology usage, purposefully integrating technology into their children’s lives in ways they
perceive as appropriate for their social context.
Connectedness promotion. Lastly, parents also discussed that one of their roles as
supporters of their children’s technology use involve encouraging their children to use
technology to connect with their family and community. As previously mentioned, parents are
concerned about their children becoming isolated while using technology. In addition to limiting
the time children spend on independent technology usage, another strategy parents use is to
encourage technology use in ways that promote connectedness. One way parents achieve this
goal is to recommend programs that allow families to keep updated on each other’s activities or
to connect with family members who live in remote locations. For instance, Hanna mentioned:
We chat, we have a group for their grandparents from out of state and
relatives and cousins. We can share pictures. I try to put our calendar on Google so
that you can see it. They don't usually follow my calendar. We email, text, have a
common group on Facebook as well. We chat, that's how we communicate information.

Similarly, Marcy explained that she also uses a technology tool that helps keep her family
connected:

We have cozy. It's a family organizer. We are able to put our schedules, now that [my
son] just got a new job. (Scrolling and reading out from the app) He starts next week.
PARENTAL MEDIATION OF TECHNOLOGY USE 96
You can see I scheduled our interview here. After this, we have a barbecue. (Turns to the
interviewer) Now we know who goes where.

These are examples of how parents are leveraging technology tools to help keep the family
connected, rather than as an agent of isolation.
Related to connectedness promotion, parents in this interview sample also reported their
perception that brokering digital learning is closely related to connectedness promotion, as also
shown by factor analysis results. Whereas the traditional notion of parents brokering digital
learning involve parents looking for technology classes for their children, parents who were
interviewed not only talked about looking for formal digital learning opportunities, but also
about learning opportunities that arise from family and community members who have technical
expertise. For example, Carol talked about the type of technology learning her son receives from
his father:
They're both actually making a video game. My husband's not using Scratch (a kid-
friendly programming platform that can be used to create games), he's using a real
platform and shooting it with green screen, getting actual characters in it. But, they're
both making a video game, so my son learns from him. It's interesting. That's their
connection really.

A little bit later, she also explained:

Interviewer: In terms of him playing his games, like the Minecraft and the building,
would he do it by himself because he's pretty self-sufficient?
Carol: That, yes. He does that by himself or with dad or with family who plays it
too online because you can play together. So they'll go into each other
game and help each other build stuff.
Interviewer: Oh, so that would be with other family members?
Carol: His uncle but his uncle is two years older than him.

These quotes illustrate a theme in qualitative data in which parents perceive that their child gains
technical knowledge by interacting with family members who have more knowledge. So, parents
are leveraging connections within the family to help their child improve their technology skills.
PARENTAL MEDIATION OF TECHNOLOGY USE 97
In addition, when talking about digital learning, some parents naturally refer to resources from
their social circle rather than a formal class. As Sandy mentioned:
Well I have pretty much the basics of all the programs. Some I use more than others, but
I'm not that good with formulas in Excel so I wouldn't able to help her in that regard, but
then of course, wherever my weaknesses are, I would be encouraged to point her in the
direction of someone who could help her or try to figure out how to get it done so that
she would be successful in that area.

This quote again points to the tendency some parents have in resorting to social resources when
looking for digital learning opportunities for their children. However, it should be noted that this
theme is not pervasive across parents with differing characteristics in the interview sample. This
may be due to the disparities in access to social resources that different parents have, particularly
as the study context is situated in low income neighborhoods. However, the connection that
exists between promoting connectedness and brokering digital learning for the child parallels
qualitative trends, as the connectedness promotion factor included aspects referring to
encouraging ICTs usage to connect with family and community members as well as looking for
digital learning opportunities for the child.
Balance between regulatory vs. supportive technology mediation. In addition to
providing nuanced insights on how parents restrict, monitor, and support children’s technology
use, qualitative data also support and extend factor analysis results by providing a better
understanding about the distinct nature between regulatory-oriented (i.e. restrictive mediation
and monitoring) and support-oriented parental behaviors, as well as the relationship parents
perceive between these two types of mediation. Qualitative results support modeling regulatory-
oriented and support-oriented behaviors, with parents naturally referring to these two types of
behaviors in distinct terms. In particular, all parents talk about how they actively try to achieve
PARENTAL MEDIATION OF TECHNOLOGY USE 98
balance between regulating their children’s technology usage while at the same time encouraging
them to use technology in productive ways. For instance, Hanna explained:
If I have my way, or I have the time, I would like to monitor more. How much is
appropriate? Would preventing her from using technology help her or not help her is
where we have a problem with right now.

Many parents echoed this sentiment, trying to achieve the perfect balance between setting limits
and encouraging more constructive uses of technology. In addition, parents also discussed an
additional concern of helping their child not to become too technologically-reliant. Marcy talked
about this issue during her interview:
I think it’s finding a balance of encouragement also making it not necessarily a
bad thing and not making it too alluring. We don't want to limit it too much. I
think it's something that families need to work on as a whole because I do think
as adults we're too dependent. I feel like people can't drive without using technology. I
think my husband and I are working on that, too.

This quote represents an additional concern that many parents expressed, which is not only
finding the balance between restricting and supporting their kid’s technology use, but also
allowing them to enjoy the benefits of technology while not becoming over-dependent on
technology in all aspects of life. Another additional consideration parents make is to follow what
their children are interested in when it comes to encouraging them to expand their technical
skills. For example, Sandy expressed,
If it's something she's interested in I'll tell her, like I said before, to do the research on it.
If it's something that you, after having done that research, you decide that you definitely
want to do it then, yeah, I would say to that degree. But as far as saying, "oh my
goodness, pick up your laptop and let's go on an adventure" I don't do anything like that,
but I do encourage her because it's at her fingertips. She doesn't have to go to the library
or do a lot of different things to find out simple information that could be found at her
fingertips.

This set of discussions shows the pervasive parent concern with balance. Parents are continually
thinking and adjusting the ways in which they can encourage their children’s technology use at
PARENTAL MEDIATION OF TECHNOLOGY USE 99
the right level and with the right avenues that are also of interest to the child. This finding is
related to the overall theme in qualitative findings, with parents reporting that they are active
mediators of technology for their adolescent children.
Question 2: How do motivational and contextual factors influence parents’ supportive and
regulatory technology mediation behaviors?

Measurement invariance analysis. After factor solutions were reached and qualitative
data analysis provided a clearer picture of how parents mediate technology at home, the next
research question addressed how contextual and motivational factors influence these behaviors.
To this end, a series of statistical tests were performed to address assumptions of validity and
reliability of relevant constructs in preparation for the second phase of quantitative analysis,
which aimed to test the relationships among these contextual, motivation, and behavioral
constructs. The first of these is a test for measurement invariance. In accordance with procedures
outlined by Vandenberg and Lance (2002) as well as Horn and McArdle (1992), the test for
measurement invariance began with omnibus tests for equality of covariance matrices among
restrictive mediation, monitoring, and supportive mediation indicators. Fit statistics showed that
models constraining covariance matrices demonstrated relatively poor fit. In particular, the
monitoring model with covariance matrices constrained showed high residual variance (Table
13; WRMR=1.199 compared to the WRMR<1.0 cutoff) and poor RMSEA statistic
(RMSEA=0.098 compared to the RMSEA<0.08 cutoff). The restrictive and supportive mediation
models with equality of covariance matrices specified also demonstrated high residual variance
(WRMR=1.027 and SRMR=1.132, respectively)
17
.

17
WLSMV estimator and WRMR residual fit index were used for Restrictive Mediation and Monitoring models due
to presence of ordinal data. ML estimator and SRMR residual fit index were used for Supportive Mediation model.
PARENTAL MEDIATION OF TECHNOLOGY USE 100
Because the omnibus tests failed, the test of measurement invariance proceeded as
recommended by Vandenberg and Lance (2002), first with testing configural invariance (i.e.
equality of a-priori pattern of factor loadings) of the restrictive mediation model using factor
patterns established from confirmatory factor analysis in the previous step. This test yielded
satisfactory fit, with χ2 p-value less than 0.001 and CFI=0.955 (Table 14). The subsequent test of
metric invariance (i.e. equality of item loadings) still showed good fit, demonstrating that the
metric invariant model is not statistically different compared to the configural invariant model (Δ
χ2 p-value = 0.523 and ΔCFI=0.006). However, the test for scalar invariance demonstrated that
constraining item intercepts resulted in a model that is statistically different than the metric
invariant model, since the change in CFI exceeded the 0.01 cutoff (Δ χ2 p-value = 0.208 and
ΔCFI=0.027). The conclusion from this analysis was that the restrictive mediation model meets
the assumption of invariance at the level of metric invariance across the two survey language
groups, with factor patterns and item loadings taken to be equal.
Next, the test for measurement invariance continued with the monitoring model, which
found configural invariance tenable for this model across the two survey language groups (χ2 p-
value <0.001, CFI=0.918). The metric invariant monitoring model also showed good fit, with fit
indices showing that it was not statistically different from the configural invariant model (Δ χ2 p-
value = 0.085 and ΔCFI=0.006). However, the scalar invariant monitoring model was found not
to be tenable and was statistically different from the metric invariant model (Δ χ2 p-value =
0.001 and ΔCFI=0.038). Lastly, the supportive mediation model was tested for measurement
invariance. The first test of configural invariance supported the specification that factor patterns
were consistent across two survey language groups (χ2 p-value <0.001, CFI=0.911). The test of
metric invariance also held (Δ χ2 p-value = 0.444 and ΔCFI=0.001), whereas the specification of
PARENTAL MEDIATION OF TECHNOLOGY USE 101
scalar invariance was not supported (Δ χ2 p-value = 0.000 and ΔCFI=0.017). Taken together,
these analyses supported the assumption of invariance for the monitoring and supportive
mediation at the level of metric invariance, with assumptions of equivalent factor patterns and
item loadings found to be consistent with the data. This result suggests that each indicator
measures the latent trait with the same unit scale across groups, allowing for meaningful analysis
of the relationships among latent variables across groups (Widaman & Reise, 1997). Since our
interest is to analyze regression relationships and not to compare mean mediation scores across
survey language groups (which would require scalar invariance), metric invariance suffices for
meaningful incorporation of these latent constructs for further analysis.
Item-response analysis and measurement reliability. An additional assumption for
valid regression analysis is that the instruments used are effective in measuring the constructs of
interest. For the present study, this is a particular concern for the parental technology mediation
measures (including scales for restrictive mediation, monitoring, and supportive mediation), as
well as the technology knowledge measure
18
because these have not been vetted by previous
research. Item-response analysis was performed to examine the test- level functioning of these
scales using graded response modeling. For the restrictive mediation scale, Fisher’s information
plot showed that the scale yielded sufficient information for respondents from two standard
deviations below the mean latent factor (theta) score to one standard deviation above the mean
theta score (Figures 6). The supportive scale was shown to yield sufficient information for
respondents scoring two standard deviations above and below the mean theta score (Figure 8),
whereas the monitoring and technology knowledge scales were shown to yield sufficient

18
To address the unidimensionality assumption for IRT analysis, the technology knowledge measure was fitted as a
one factor model using confirmatory analysis. Results show goodness of fit (χ2/df=2.05, CFI=0.964, TLI=0.954,
RMSEA=0.060, WRMR=0.062). The restrictive mediation, monitoring, and supportive mediation were already
shown to have unidimensionality from factor analysis in the previous step.
PARENTAL MEDIATION OF TECHNOLOGY USE 102
information for those scoring one standard deviation above and below the mean (Figures 7 and
9). Taken together, the restrictive mediation and technology knowledge measures were found to
be most informative for samples of parents whose score lies around the mean theta score, but
may not be as effective for those with very high or low levels of these constructs. However, the
supportive mediation and monitoring scales were found to be informative for parents across a
wider range of the latent trait. In the final step, parents’ scores on these latent constructs were
IRT-scaled using expected a posteriori (EAP) factor scores in preparation for path analysis in the
next step.
To further assess the psychometric properties of the measures used in this study,
reliability statistics were calculated for all scales used. Empirical reliabilities were reported for
measures that underwent IRT analysis and are IRT-scaled (i.e. restrictive mediation, monitoring,
supportive mediation, and technology knowledge measures; Table 15). Cronbach’s alphas were
calculated for all remaining measures. All measures were shown to have good reliability, except
for the technology usage scale. This could be due to the low number of items in this measure.
Path analysis. After factor and psychometric analyses, the next phase of quantitative
analysis sought to analyze the relationships among contextual factors, motivational factors, and
parental mediation behaviors. Firstly, Pearson’s correlations were calculated in order to assess
bivariate relationships among variables of interest (Table 16). Results show that supportive
mediation was significantly and positively related to monitoring behaviors, but was not
significantly correlated to restrictive mediation. This result gave evidence that supportive and
regulatory behaviors such as monitoring are not mutually exclusive, with this correlation data
indicating that parents who support their child’s technology use to a greater extent also engage in
more monitoring. However, restrictive mediation was only significantly related to monitoring
PARENTAL MEDIATION OF TECHNOLOGY USE 103
and not supportive mediation, which gave indication that restrictive and supportive behaviors are
conceptually distinct. As such, restrictive and supportive mediation may be influenced by a
different set of factors.
Further examination of Pearson’s correlations revealed that all motivational factors of
interest, including parent role belief, supportive self-efficacy, and restrictive self-efficacy were
significantly related to supportive mediation and monitoring, but not restrictive mediation. In
term of contextual factors, parents’ technology usage, technology knowledge, and perception of
child’s technical expertise are positively correlated with supportive mediation, but negatively
correlated with restrictive mediation. Other contextual factors were also found to influence
parents’ mediation behaviors, with parents who reported more technology usage, scored higher
on the technology knowledge measure, and perceived their child to have more digital expertise
also more likely to engage in supportive mediation behaviors but less likely to engage in
restrictive mediation. Also, parents’ English proficiency, education level, and child’s age are also
negatively correlated with restrictive mediation, but have no significant correlational relationship
with supportive mediation. These results corresponded to earlier trends pointing to the
distinctiveness between restrictive and supportive mediation behaviors.
Analyses of relationships among contextual factors, motivational variables, and parents’
technology mediation behaviors continue with direct effects regression modeling, with
contextual and motivational factors specified as predictors for mediation behaviors (Table 17).
Results showed that several contextual factors were significant predictors of restrictive
mediation, including technology knowledge (standardized ß= -0.17, p<0.01), perception of
child’s expertise (standardized ß= -0.28, p<0.001), child’s age (standardized ß= -0.27, p<0.001),
and English proficiency (standardized ß= -0.24, p<0.001). In contrast, no motivational factor was
PARENTAL MEDIATION OF TECHNOLOGY USE 104
found to significantly predict restrictive mediation. For the monitoring regression model,
supportive self-efficacy (standardized ß= 0.30, p<0.01), child’s age (standardized ß= -0.13,
p<0.05), and parent education level (standardized ß= -0.15, p<0.05) were found to be significant
predictors of monitoring behavior. Finally, for supportive mediation, parents’ technology usage
(standardized ß= 0.22, p<0.001), parental role construction (standardized ß= 0.15, p<0.05), and
supportive self-efficacy (standardized ß= 0.28, p<0.01) were found to significantly predict
parents’ supportive mediation.
The last step of quantitative analysis consisted of path model analysis. In total, three path
models were fitted, each with a different type of mediation behavior as the dependent variable
(i.e. restrictive mediation, monitoring, and supportive mediation). For each model, contextual
factors (including parent’s technology knowledge, technology usage, and perception of child’s
expertise) were modeled to have direct effects on mediation behavior as well as an indirect effect
through motivational factors (including parental role construction, supportive self-efficacy, and
restrictive self-efficacy; for model illustration, refer to Appendix F). A number of control
variables were also included in all path models, including parents’ school role perception, child’s
age, English proficiency, education level, and lunch status.
Effect decomposition analysis of the restrictive mediation path model showed that
parents’ technology knowledge (standardized ß= -0.180, p<0.001; Table 18), perception of
child’s technical expertise (standardized ß= -0.265, p<0.001), English proficiency (standardized
ß= -0.238, p<0.001), and the focal child’s age (standardized ß= -0.279, p<0.001) all have
significant direct effects on restrictive mediation behavior. Echoing results from the direct effects
only model, no motivational variable was found to have predictive effects on restrictive
mediation. These results suggest that contextual factors exert more influence on restrictive
PARENTAL MEDIATION OF TECHNOLOGY USE 105
mediation behaviors than the motivational variables of interest in this study. This path model was
found to account for 31.3% of the variance in parents’ restrictive mediation behavior. A path
model representing significant predictors of restrictive mediation is illustrated in Figure 10.
In contrast, contextual factors appeared to have less direct influence on monitoring
behavior. Effect decomposition analysis showed that parents’ knowledge, technology usage, and
perception of child’s digital expertise did not have significant direct effects on monitoring
behaviors. Instead, these contextual factors’ influence on monitoring behavior was mediated by
supportive self-efficacy. In particular, the indirect effect of parents’ technology knowledge on
monitoring behavior as mediated by supportive self-efficacy was found to be statistically
significant (standardized ß= 0.045, p<0.05; Table 19). This result suggests that parents with more
technology knowledge tend to have higher self-efficacy for supportive mediation, which in turn
increases their monitoring behavior. Likewise, the indirect effect of the perception of child’s
digital expertise on monitoring behavior as mediated by supportive self-efficacy was also found
to be statistically significant (standardized ß= 0.087, p<0.01). This result suggests that the more
parents perceive their child as technology experts, the more self-efficacy they have for
supporting their child’s technology usage, which in turn increases monitoring behavior. Since
these two contextual factors did not have significant direct effects on monitoring behavior, but
rather only indirect effects through self-efficacy, parents’ technology knowledge and perception
of child’s technical expertise can be said to be completely mediated by supportive self-efficacy in
their predictive roles on monitoring. These relationships are illustrated in a path model
representation in Figure 11.
One last path model was fitted with supportive mediation as the dependent variable.
Effect decomposition analysis showed that contextual factors have direct effects on supportive
PARENTAL MEDIATION OF TECHNOLOGY USE 106
mediation behaviors, as well as indirect effects via motivation behaviors. In particular, parents’
technology usage has a direct relationship with supportive behavior (standardized ß= 0.221,
p<0.01; Table 20), such that parents who reported more frequent technology usage also reported
more supportive mediation behaviors. As expected, supportive self-efficacy (standardized ß=
0.279, p<0.01) and parental role beliefs (standardized ß= 0.161, p<0.05) also demonstrated to
have direct relationships with supportive mediation behaviors. These results suggest that parents
with higher self-efficacy and higher parental role construction also tend to engage in more
supportive mediation behaviors. In addition to these direct effects, parents’ technology
knowledge (standardized ß= 0.042, p<0.05) and perception of child’s expertise (standardized ß=
0.087, p<0.01) also have indirect effects on supportive mediation via their relationships with
supportive self-efficacy. That is, parents with more technology knowledge and those who
perceive that their child has more technology expertise are more likely to have higher self-
efficacy, which in turn increases their engagement in supportive behaviors. In addition,
perception of child’s expertise also has indirect effects on supportive behaviors as mediated by
parental role beliefs (standardized ß= 0.057, p<0.05), such that parents who perceive that their
child has more technology expertise also tend to believe that parents have a higher responsibility
in the child’s technology education, which in turn increases their engagement in supportive
mediation behaviors. It is interesting to note that although parental technology usage is a direct
predictor of supportive mediation behavior, this contextual factor does have an indirect effect on
supportive mediation via any of the specified motivation variables. This finding supports that
parents’ technology usage and knowledge, though related, are different in their relationship with
supportive mediation behaviors.

PARENTAL MEDIATION OF TECHNOLOGY USE 107
Qualitative Trends
Analysis of parents’ interviews extended our understanding of previously reported
quantitative trends, as parents consistently pointed to technology knowledge as a gateway to
effective mediation, the balance between schools’ and parents’ roles in children’s digital literacy
development, and children’s natural interest as a main contributor to successful supportive
efforts by parents. These emergent themes from qualitative data are discussed below.
Technology knowledge as mediation gateway. One of the most consistent theme that
emerged from qualitative data is the regard for technology knowledge as the main gateway for
effective mediation. In the previous presentation of qualitative data, technology knowledge was
described as closely related to parents’ professed abilities to monitor children’s technology use.
Building on this trend, all parents also referred to their own technology knowledge as the main
factor influencing their effectiveness as a technology mediator when asked to reflect on how well
they are able to mediate technology for their children. Arnold, a 52-year-old father who reported
one of the lowest scores on technology knowledge, supportive self-efficacy, and supportive
mediation (at the 28
th
, 2
nd
, and 16
th
percentile, respectively; refer to Table 12) discussed his lack
of technology skills impacting his mediation ability:
[The school] told me [the kids] don't have to use the computer too much time, to play in
something that is not really needed, but, I cannot do anything because I don't know how I
can control. …I think some parents, they explain more because, in my case, I don't have
too much level of school. I don’t know too much about technology. I think some parent
who has high levels, they teach their kids more than me. (Grammatical errors retained.)

This quote shows that parents’ lack of technology knowledge not only impacts parents’ ability to
monitor children’s technology use, but also their ability to enact supportive mediation strategies.
Relatedly, parents with higher technology knowledge also perceived that they are able to support
PARENTAL MEDIATION OF TECHNOLOGY USE 108
their children’s technology use because of this knowledge. Randy, a father who scored at the 94
th

percentile in technology knowledge, reflected on his mediation ability:
For instance, I know this family they don't have a computer and they always come
over to the house because they need to do homework but the mom doesn't know
anything about technology. I think she's illiterate. How is she going to help her son with
it? If she doesn't have the knowledge to show her kids, how is she going to help them
progress? …I already know a little bit of technology. I already know how to use it. One
day, they get stuck when they have a paper that they got to send somewhere, they can't do
it, then they come to me and I help them. I guess that's the way, me being
skilled or with the knowledge on a computer or a tablet or whatever device, then
that helps me help them improve their skills.

As Randy compared his own ability as a technology mediator to another, less technologically
knowledgeable parent, it became clear that he attributed much of his ability to support his
children’s technology usage to his technology knowledge. Many parents with high technology
knowledge in the interview subsample also regarded their mediation ability in similar ways.
These qualitative trends support path model results, in which technology knowledge was found
to influence parents’ monitoring and supportive behaviors through its effect on supportive self-
efficacy. Parents with higher technical skills are more confident about their abilities to mediate
technology, thereby also increasing the extent to which they engage in monitoring and supportive
mediation strategies.
In addition to referring to technology knowledge as a crucial requirement for effective
technology mediation, parents also pointed to the need for them to learn more about certain
technologies in order to be able to continue supporting their children’s technology involvement.
For instance, Marcy talked about her interest in learning more about coding as her younger
daughter is taught the subject at school:
Well like the coding thing, I don't get it, I'll be honest. I have complete trust in what
they're taught and how they're going to utilize those so I don't mind Minecraft and those
types of games. But, [the game] utilizes a lot of coding. I don't know how to do coding, I
PARENTAL MEDIATION OF TECHNOLOGY USE 109
don't understand it. I guess there's going to be some homework on my end if I want to
give them free rein in that regard.

Other parents also reported interest in learning more about social media and technology
programs their children use for school in order to become more effective technology mediators.
In addition, many parents expressed the necessity for schools to hold workshops for parents,
informing parents about what types of technology their children are using in the classroom and
teaching parents to use the same tools. As Hanna explained:
I think the parents should learn the technology too so that they know what's being used. I
always download the same apps they do so I could see what they're using it for. … I
guess if [the school] have something new, if they're going to train the kids maybe have a
session for the parents as well.

Parents in the interview subsample also agreed that having knowledge about the technology tools
their child uses at school will help them extend the child’s academic development at home and
allows them to monitor that the child is meeting school’s expectations when working at home.
Again, these trends support the close relationship among technology knowledge, monitoring
behaviors, and supportive mediation behaviors. These results also suggest that the variabilities in
mediation behaviors that were found in previous research as well as in the present study could in
large parts be due to parents’ technology knowledge and, relatedly, their self-efficacy for
mediating their children’s technology use.
Perceptions of parents’ and school’s responsibilities. Another important trend that
emerged from qualitative data is parents’ perception that their role as a technology mediator
mainly consists of ensuring the child’s online safety and extending technology education
initiated by schools. As shown through qualitative results presented in the last section, parents
see keeping their child safe online as part of the basic function of a parent, akin to keeping
children physically safe and maintaining their well-being. In addition to this role, parents also
PARENTAL MEDIATION OF TECHNOLOGY USE 110
perceive that children’s technology skills development should be a shared responsibility between
the parent and the school. Many parents discussed that it is the parent’s responsibility is to pick
up where the school leaves off with regards to technology education. Parents’ views range from
perceptions that parents should “reinforce the technology education here at home” (Megan), to
“school shows them and we fill in the gaps,” (Marcy), and finally that parents should “continue
from whatever is left off in school. (Saying,) you talked about this? Let’s explore it some more.”
(Carol). These sentiments range on a continuum from repeating and reinforcing what is taught in
school to extending what children learned in school and exploring new avenues of using the
same technology tools. But, despite this range, one common thread is the sense that the school’s
role is to initiate the type of technology education that should occur, whereas the parent’s job is
to support the development of these skills and build off the basic knowledge that the school
provides. In addition, parents also noted that the shared responsibility are structured in this way
because schools are already taking major initiatives in helping children learn about technology.
As Marcy explained:
If [the school] didn't teach technology, I think it would fall on my shoulders a lot more.
But, I trust that schools are teaching them. If they weren't then it would be something I
would take an active role in rather than supplementary role.

We see yet again that parents actively respond to their children’s needs in terms of technology
education, assessing what types of supportive mediation is appropriate given the social context,
which in this case refers to the type of support that is already given at school. In addition, it is
apparent that most parents in the interview subsample do not leave the school in charge of their
children’s technology education, but see themselves as having shared responsibility in this aspect
of their children’s development. These trends also support and extend our understanding of
PARENTAL MEDIATION OF TECHNOLOGY USE 111
quantitative results showing parental role construction as an important motivational antecedent
of how much parents engage in supportive technology mediation.
Parental response to children’s natural affinities. Another way that qualitative data
extended our understanding of quantitative results is related to path model results showing that
parents’ perception of children’s technical expertise significantly predicts parents’ engagement in
supportive behaviors. During interviews, parents pointed to their child natural ability to learn
skills related to technology. For example, Megan talked about when she introduced her daughter
to a new program:
I taught my daughter how to use PowerPoint. She wasn't very familiar with it but then I
was familiar with it because we used it a lot in college. When I introduced her to it, it
looks like she just got better at it fast, when it took me like easily half a year.

Like Megan, many parents discussed how effortless and natural technology learning is for their
children. In addition to children’s natural capability to learn how to maneuver technology tools,
many parents also pointed to their child’s natural affinity for technology usage as one factor that
influences their mediation behavior. When asked about what role she has in encouraging her
child to learn more about technology, Marcy replied, “I do encourage, but I feel like, with him, it
was self-driven.” Carol also replied that when it comes to encouraging her son to learn more
about technology, “the interest is there so [my job] is just keeping that fire it.” Given perceptions
regarding children’s natural ability and affinity to learn about technology, parents may perceive
that it is easier to support their child’s technology use when the child already has some technical
expertise since their supportive role would neither take much direct instruction nor
encouragement. When the child has digital expertise, further technology learning can become
much like a domino effect, with the parents only needing to provide guidance to ensure that the
learning is heading in the right course. In essence, parents’ supportive tasks may become easier
PARENTAL MEDIATION OF TECHNOLOGY USE 112
and parents’ self-efficacy may become higher as the child gains more technical expertise. These
qualitative trends suggest one explanation for why parents who perceive that their child has more
technical expertise also reported higher self-efficacy for mediation and higher engagement in
supportive mediation.
An additional way that children’s natural affinities play a role in how parents are able to
mediate technology is related to some children’s natural tendency to learn independently using
information technology. As Randy describes:
Randy: My son, he'll get online and he'll just search about what happened in 1820
or what happened in 1800 or he'll just type in some random stuff like that.
Interviewer: Not from homework, but just because he wants to know?
Randy: He's more that type of person [who says], "Why does a car do what it
does?" He's that type of person.
Interviewer: Do you feel like that's something that you have a role in helping him or do
you think that it’s just natural?
Randy: No, he just does it.

This exchange shows that when the child possesses a disposition to learn independently through
information technology, the parents’ supportive task may also become easier, raising supportive
self-efficacy and supportive mediation engagement. However, it should be noted that only a few
parents of older adolescent children professed to this disposition in their children (i.e. Randy
with a 15-year-old child and Marcy with a 17-year-old child). This could mean that this
disposition may become more apparent as children become independent technology users, and
may not be present in every child. In any case, this qualitative trend helps transform the way we
think about how parents’ perception of children’s digital expertise may influence their self-
efficacy and technology mediation behaviors.
Summary
As a response to the lack of research on how parents from low income communities
mediate their adolescent children’s technology usage, the purpose of this study was to gain a
PARENTAL MEDIATION OF TECHNOLOGY USE 113
deeper understanding of how parents in this socioeconomic context enact mediation strategies
found in previous research, as well as to understand the relationships among contextual factors,
motivational factors, and mediation behaviors. Through the use of mixed methods, including
factor analysis, path modeling, and open thematic coding of parent interviews, the present study
found that parents in the study sample are active mediators of technology who engage in a wide
variety of mediation behaviors. Factor analysis of both regulatory and supportive behaviors show
that mediation behaviors can be grouped into three main categories, including (1) restrictive
mediation, (2) monitoring, including technical and non-technical monitoring, and (3) supportive
mediation. Further quantitative and qualitative analyses suggest intricate relationships among
these behaviors, with correlation analysis showing that monitoring behaviors are positively
correlated with both restrictive and supportive mediation, whereas restrictive and supportive
mediation show no relationship. This suggests that parents who restrict their child’s usage to a
greater extent are not less likely to engage in supportive mediation. Qualitative results echoed
this trend, with parents reporting that one of their main goals as a technology mediator is to find
the right balance between limiting and supporting their children’s technology usage.
In terms of the relationships among contextual factors, motivational factors, and
mediation behaviors, path model results show a difference in how the two types of antecedent
variables (i.e. contextual and motivational variables) relate in their predictive relationships on
three categories of mediation behaviors. For restrictive mediation, contextual factors play large
and direct roles in shaping how much parents restrict their children’s technology use. In
particular, parents who had more technology knowledge, perceived their children as having more
technical expertise, had an older focal child, and reported higher English proficiency were less
likely to engage in restrictive mediation. There was no significant effect of motivation variables
PARENTAL MEDIATION OF TECHNOLOGY USE 114
on restrictive mediation behaviors. On the other hand, motivation variables play important
mediating roles in how contextual factors influence monitoring and supportive behaviors. In
particular, parents who had more technology knowledge and viewed that their child has more
technical expertise tended to have higher supportive self-efficacy, which indirectly increased
monitoring behavior. In addition, parents’ technology knowledge and perception of child’s
digital expertise also influenced supportive mediation solely through their relationships with
supportive self-efficacy and parental role construction. Qualitative data also extends these
quantitative trends, with parent interviews highlighting technology knowledge as an important
gateway towards effective mediation, parents’ perception of the shared responsibility between
the parent and the school in educating children about technology, and children’s natural ability
and affinity for technology usage possibly making parents’ supportive tasks easier for parents
whose child already possess some technical expertise.

PARENTAL MEDIATION OF TECHNOLOGY USE 115
CHAPTER 5: DISCUSSION
Overall, the findings from this study added to the collective knowledge about how
parents from low income communities mediate technology at home. In particular, results from
this study countered the current deficit-oriented narratives, which often cast low SES parents as
ineffective and neglectful in their technology mediation behaviors (Vigdor & Ladd, 2010;
Malamud and Pop-Eleches, 2011). Opposite from these traditional notions, quantitative results
showed that parents in this sample engaged in all of the mediation behaviors found in previous
research, with about 70 to 80 percent indicating that they engage in most behaviors sometimes,
often, or very often. Qualitative analysis also showed that these parents are purposeful and
reflective in their technology mediation efforts, mediating technology with the explicit intention
to build their children’s technology skills, support social development, and build academic
competencies. As such, the present study represents one of the first shift that should occur in the
current research directions within the field of parental technology mediation, towards less focus
being placed on what parents don’t do and more on the types of mediation behaviors parents do
engage in and why.
The study’s results supporting the view of parents as intentional mediators of technology
also validates the use of sociocultural theory as the theoretical lens for studying parental
technology mediation. According to sociocultural theory, parents purposefully mediate
children’s usage of cultural tools such as ICTs in order to socialize them on the appropriate
integration of these tools into daily life (Kozulin, 2001; Rogoff, 1998). Parents in this sample
have shown that they are continually mindful about mediating technology in ways that help their
children learn how to leverage these tools for their distinct benefits, while balancing negative
side effects such as increased isolation and over-dependence. In addition, parents in this sample
PARENTAL MEDIATION OF TECHNOLOGY USE 116
demonstrated multiple scaffolding strategies found in previous sociocultural research, including
recruiting and maintaining children’s attention on technology learning through verbal
encouragement, demarcating learning goals to be achieved by suggesting to their children what
technology-related activities to engage in, and (for those with high enough technology
knowledge) demonstrating how goals can be reached through modeling correct usage (Wood et
al., 1976). These findings provide additional support for the use of sociocultural theory as the
lens to study informal learning interactions in general, and parental technology mediation at
home in particular.
Moreover, results from the present study supported trends from previous parental
technology mediation research, which pointed to connectedness promotion as one main goal that
low income parents have for mediating technology use (Clark, 2013). That is, low income
parents were found in previous studies to help children use technology primarily in ways that
strengthen ties within the family and community. This strategy reflects parents’ explicit effort to
shield their children from potentially harmful influences outside the home or social circle.
Echoing these previous results, factor analysis showed connectedness promotion to be one facet
of how parents in this sample support their child’s technology use. More importantly, qualitative
data also showed that the focus on connectedness is more pervasive than initially indicated by
quantitative data. In asking parents about how they promote their children’s technology use,
parents reported that they encourage their children to use programs that keeps family members
updated with one another (an example of technology involvement promotion), use ICTs with
their children in order to help them increase content and/or technology knowledge (an example
of instructive co-use), and reaching out to family or community members in brokering digital
learning for their children (part of connectedness promotion). The fact that mediation activities
PARENTAL MEDIATION OF TECHNOLOGY USE 117
related to increasing connections within the child’s family and social circle span three different
supportive mediation categories provides additional empirical support for Clark’s (2013) work,
which found this focus to be prevalent among low income parents.
Also, like Clark’s study, results from the present study suggests that low income parents
may engage in similar types of technology mediation as their more affluent counterparts, but
differ in how they carry out specific mediation behaviors in practice. For instance, while parents
in high SES contexts discussed finding technology classes as part of their effort to broker digital
learning for their child (Barron et al., 2009), parents in this sample also listed reaching out to
social resources as an additional way they find new technology learning opportunities for their
child. Additionally, while giving explicit technology training to their children is one common
supportive role parents in high SES contexts perform, parents in this primarily low income
sample often situated their instructive technology-related conversations with their children within
the context of instructive co-use, during which the parent and the child use technology together.
These differences in the execution of mediation behaviors may be due to low income parents’
intentional focus on promoting connectedness, but could also be due to parents adapting how
they carry out these mediation behaviors to compensate for contextual constraints. For example,
parents may be inclined to reach out to technical experts in their social circle as a way of
brokering digital learning for their child in order to avoid the high monetary and time cost of
enrolling the child in formal technology classes. Similarly, parents with limited technology
knowledge themselves may be more inclined to give instructive guidance while using technology
with the child in order to leverage the child’s growing technical expertise. But, although this
study’s results suggest these trends, a full examination of the nuances in how the execution of
PARENTAL MEDIATION OF TECHNOLOGY USE 118
mediation behaviors may vary between high and low income parent samples is outside the scope
of the present study, and would present an interesting avenue for future research.
Furthermore, this study also extends current research by examining how parents support
children’s technology use, in addition to the focus of the majority of existing research that tended
to investigate how parents regulate children’s technology usage (Clark, 2013). Results from this
study show that parents execute a variety of supportive behaviors in helping to develop
children’s digital literacy skills, offering opportunities for future research to study how these
supportive behaviors function to increase children’s digital literacy gains. Also, similar to trends
found in previous studies, a major theme in this study’s qualitative data suggests that parents
today constantly endeavor to achieve balance between limiting and supporting children’s
technology usage (Plowman, Stephen, & McPake, 2010; Livingstone, 2015; Takeuchi, 2012;
Kerawalla & Crook, 2002). Thus, studying restrictive mediation and monitoring behaviors
without concurrently examining supportive mediation behaviors would surely generate an
incomplete picture of the extent to which parents are engaged in mediating technology for their
children. Instead, a more complete focus on both regulatory and supportive behaviors, as well as
a focus on examining the right balance between these two types of mediation which maximizes
positive outcomes for children, are fruitful avenues for research that will be useful for parents
given their existing concerns.
In addition, findings from this study transforms existing knowledge by giving empirical
support for the important role motivation plays in influencing parents’ technology mediation
behaviors. Whereas existing research on parental mediation have focused solely on demographic
and contextual factors such as parents’ age, socioeconomic status, and technology knowledge
(Sonck, et al., 2013; Nikken & Jansz, 2011; Kirwil et al., 2009), the present study provides
PARENTAL MEDIATION OF TECHNOLOGY USE 119
empirical support for the importance of motivational variables like self-efficacy and role
construction in predicting parents’ engagement in technology mediation. Also, while results from
this study parallel trends found in previous studies that parents’ contextual limitations (such as
having less technology knowledge and lower English proficiency) increases restrictive mediation
behaviors and may have negative impacts on their child’s ICT involvement (Lou et al., 2010;
Nikken & Jansz, 2011), this study adds to the existing research base by pointing out that these
contextual factors have less direct impact on monitoring and supportive behaviors. The
implications for these findings are three-fold. Firstly, these results again point to the importance
of examining both regulatory-oriented and support-oriented mediation concurrently in order to
gain a complete picture of how parents mediate technology in a particular socio-cultural context.
Secondly, understanding how contextual factors influence mediation behaviors through their
effects on motivation help scholars gain deeper perspectives on the factors that are involved in
the parent-led, technology education children receive at home. These results echo previous
parent research that have found motivation to be an important predictor of parents’ literacy-
promoting interactions with children (Waanders et al., 2007; Sheldon, 2002; Weigel, Martin, &
Bennett, 2006). Akin to similar research on parental literacy-promoting behaviors, contextual
factors such as parents’ technology knowledge were found to impact mediation behaviors not
only directly by providing the raw materials for instruction, but also indirectly through their
influence on how parents become motivated to engage in these instructive behaviors. By
executing initial explorations on the relationships contextual and motivational factors have with
mediation behaviors, this study opens up new avenues for theoretical explorations related to the
additional roles motivational variables may play in influencing how and how much parents
educate their children about technology use. The third important implication for results
PARENTAL MEDIATION OF TECHNOLOGY USE 120
supporting motivational factors as predictors of technology mediation behaviors is related to the
changeable nature of these constructs. Unlike focusing on relatively static characteristics such as
the effects of parents’ socioeconomic status on mediation behaviors, a shift in attention to
malleable motivational variables translate to our ability as a scholarly community not to relegate
a doomed fate for parents and children with less advantageous social characteristics. When
parental technology mediation and its associated motivational antecedents are treated as those
that can be positively impacted, we can begin to move forward in identifying the right type of
interventions that can shape these beliefs and behaviors into more adaptive ones. Results from
the present study as well as previous research suggest that giving parents more information on
different types of mediation behaviors they can engage in, increasing their technical skills related
to executing monitoring behaviors, as well as providing more information and workshops on
technology tools their child uses at school may help increase parents’ self-efficacy and parental
role beliefs for mediation (Lee & Tsai, 2010; Gonzales & Chrispeels, 2004). These intervention
possibilities are also avenues for future research in this area. And while we may be far from
leveling the playing field in terms of equalizing children’s home-based technology education,
this type of research is the first step in the right direction towards this goal.
Limitations
Similar to other research carried out in social settings, the present study has several
limitations due to contextual and logistic constraints. These are presented below.
Issue of Self-report
One limitation of this study is due to its reliance on self-report during the quantitative
phase, a data collection method which has recently been reexamined for potential validity
problems (Elsevier, 2015). The main disadvantage of self-report stems from the fact that people
PARENTAL MEDIATION OF TECHNOLOGY USE 121
do not always report the truth, with biases stemming from both limitations in their conscious
self-knowledge as well as the tendency to align reported behaviors and perspectives with what
they viewed to be socially desirable (Barker et. al., 2002; Pintrich, 2004). However, scholars
have noted that other methods of data collection also suffer from validity issues stemming from
different types of biases (e.g. observer bias in observation studies). In order to offset these
distinct validity concerns, many scholars and educational psychology journals now recommend a
combination data collection methods in a research program, such as combining knowledge
assessments with self-reports in education research (Pintrich, 2004; Greene, 2015; Elsevier,
2015). As a study focusing on motivation constructs, the current research employed primarily
self-report measures derived from existing studies. While recognizing potential issues from the
use of self-reports, this data collection method is argued to be appropriate because (1) it is
logistically practical to administer, (2) motivational constructs require personal perspectives that
could only be collected via self-reports, (3) no clear social desirability is yet attached to different
mediation behaviors, and (4) the issue of parental technology mediation is not sensitive,
providing no incentive to report falsely (Sinatra, 2015, personal communication; Barker et al.,
2002).
In order to ameliorate the effects of self-report bias, a knowledge measure (technology
knowledge) was included as part of the survey battery for this study and behavioral measures
were adapted to target specific behaviors instead of solely relying on perceived frequency of
broadly defined restrictive or supportive mediation engagement (See Appendix E). Qualitative
data from individual parent interviews were also collected and analyzed in order to supplement
quantitative data and further ensure that trends found from parents’ self-report responses
matched actual practices and perspectives. Parents’ perspectives given during interviews were
PARENTAL MEDIATION OF TECHNOLOGY USE 122
shown to both support and extend understandings about parental technology mediation behaviors
offered by quantitative data analysis.
Issue of Selection Bias
This study is also limited because its sampling procedures contributed to selection bias.
In particular, participating parents are those that chose to attend a seminar on how to support
their children’s technology use, or chose to stop by a parenting and technology booth at a
community center. Thus, they are likely to be more concerned about their role in mediating
children’s ICT usage and more inclined to mediate technologies at home compared to other
parents. However, the chosen sampling procedure provided a unique context for countering the
current narrative of low income parents as ineffective mediators of technology. Participating
parents, as demonstrated by their choice to join the study, are likely active mediators who seek
different avenues to support their children’s technology usage despite more limited monetary,
knowledge, and/or social resources compared to affluent peers.
Issue of Generalizability
This study is also limited in terms of its generalizability due to the fact that data
collection occured in Los Angeles County, a site with recent technology-related reforms within
its school district. In particular, the Common Core Technology Project is currently underway,
with one-to-one iPads and Chromebooks being distributed to students in schools throughout the
county (Margolin et al., 2014). The school’s provision of a new technology resource may
influence parents’ beliefs about the school’s role in children’s technology education as well as
their perceived ability to mediate children’s usage of a new device. These changes in beliefs are
expected to directly influence parents’ role construction and self-efficacy related to technology
mediation, as well as the types of mediation behaviors they engage in. Indeed, qualitative data
PARENTAL MEDIATION OF TECHNOLOGY USE 123
suggests that the active nature with which schools in this county educate children about
technology influenced many parents to view that their responsibility for their child’s technology
education is secondary to that of the school’s. As such, findings from this study cannot be
generalized to other contexts, such as communities where schools play a less dominant role in
technology education. On the other hand, this policy context in which one-to-one technology
provision is intended to close the access gap provides rich grounds for examining how low
income parents mediate their children’s usage of these tools, and how these mediation behaviors
may differ from more affluent parents.
Conclusion
Despite its limitations, this study is one of the first to examine how parents from low
income communities support adolescents’ usage of technology, as well as how motivational and
contextual factors influence parents’ technology mediation behaviors. Results from this work
supplemented current theories on how parents with different contextual constraints support
adolescents’ digital literacy development. These findings can help researchers and educators
inform other parents similarly constrained by socioeconomic circumstances the various ways that
they can support children’s development in this literacy domain. Furthermore, by addressing
mediation behaviors as resulting from parents’ motivational characteristics instead of
socioeconomic factors, this work aimed to counter current deficit-oriented narratives regarding
the influence of home environments on adolescents’ digital literacy development in low SES
populations.

PARENTAL MEDIATION OF TECHNOLOGY USE 124
References
Amarach Consulting. (2004). The Use of New Media by Children: A Research Report for the
Internet Advisory Board. Ireland: Amarach
Ananiadou, K., & Claro, M. (2009). 21st century skills and competences for new millennium
learners in OECD countries, OECD Education Working Papers,41, 4-33.
Anderson, J. C., & Gerbing, D. W. (1988). Structural equation modeling in practice: A review
and recommended two-step approach. Psychological Bulletin, 103(3), 411.
Anderson, S. E., & Maninger, R. M. (2007). Preservice teachers' abilities, beliefs, and intentions
regarding technology integration. Journal of Educational Computing Research, 37(2),
151-172.
Andrews, G. G. (2008b). Gameplay, gender, and socioeconomic status in two American high
schools. E-Learning, 5, 199-213.
Attewell, P., & Battle, J. (1999). Home computers and school performance. The Information
Society, 15, 1-10.
Attewell, P., & Winston, H. (2003). Children of the digital divide. In P. Attewell, & N. M. Seel
(Eds.), Disadvantaged teens and computer technologies (pp. 117-136). Münster,
Germany: Waxmann.
Austin, E. W. (1993). Exploring the effects of active parental mediation of television content.
Journal of Broadcasting & Electronic Media, 37, 147 – 158.
Bandura, A. (1981). Self-referent thought: A developmental analysis of self-efficacy. In J.H.
Flavell & L. Ross (Eds.), Social cognitive development frontiers and possible futures.
Melbourne: Cambridge.
Bandura, A. (1986). Social foundations of thought and action: A social cognitive theory.
PARENTAL MEDIATION OF TECHNOLOGY USE 125
Bandura, A. (1997). Self-efficacy: The exercise of control. New York: Freeman.
Bandura, A. (2001). Social cognitive theory: An agentic perspective. Annual Review of
Psychology, 52(1), 1-26.
Bandura, A. (2006). Guide for constructing self-efficacy scales. Self-efficacy beliefs of
adolescents, 5, 307-337.
Barker, C., Pistrang, N., & Elliott, R. (2002). Research Methods in Clinical Psychology: An
Introduction for Students and Practitioners, Second Edition. Hoboken, NJ: John Wiley
and Sons.
Baron, R. M., & Kenny, D. A. (1986). The moderator–mediator variable distinction in social
psychological research: Conceptual, strategic, and statistical considerations. Journal of
personality and social psychology, 51(6), 1173.
Barron, B. (2004). Learning ecologies for technological fluency: Gender and experience
differences. Journal of Educational Computing Research, 31(1), 1-36.
Barron, B., Martin, C. K., Takeuchi, L., & Fithian, R. (2009). Parents as learning partners in the
development of technological fluency. International Journal of Learning and Media,
1(2), 55-77.
Barton, A.C., Drake, C., Perez, J.G., Louis, K.S., & George, M. (2004). Ecologies of parental
engagement in urban education. Educational Researcher, 33(4), 3-12.
Baumrind, D. (1971). Current patterns of parental authority. Developmental Psychology
Monographs, 4(1), 1–103.
Bawden, D. (2008). Origins and concepts of digital literacy. In C. Lankshear & M. Knobel
(Eds.), Digital Literacies: Concepts, Policies, and Practices (pp.17-32). New York, NY:
Peter Lang.
PARENTAL MEDIATION OF TECHNOLOGY USE 126
Beauducel, A., & Herzberg, P. Y. (2006). On the performance of maximum likelihood versus
means and variance adjusted weighted least squares estimation in CFA. Structural
Equation Modeling, 13, 186–203.
Becker, H. J. (2000). Who’s wired and who’s not? Future of Children, 10(2), 44-75.
Belland, B. R. (2014). Scaffolding: Definition, current debates, and future directions. In J.M.
Spector, M.D. Merrill, J.Elen, & M.J.Bishop (Eds.), Handbook of Research on
Educational Communications and Technology (pp. 505-518). New York, NY: Springer.
Bentler, P. M. (1990). Comparative fit indexes in structural models. Psychological bulletin,
107(2), 238.
Bers, M. U. (2010). Beyond computer literacy: supporting youth's positive development through
technology. New directions for youth development, 128, 13-23.
Bers, M., Doyle-Lynch, A., & Chau, C. (2012). Positive technological development: The
multifaceted nature of youth technology use towards improving self and society. In M.
Bers (Ed.), Technology, learning, and identity: Research on the development and
exploration of selves in a digital world (pp. 123-145). Cambridge: Cambridge University
Press.
Bronfenbrenner, U. (1986). Ecology of the family as a context for human development: Research
perspectives. Developmental psychology, 22(6), 723.
Cabell, S.Q., Justice, L.M., Konold, T.R., & McGinty, A.S. (2011). Profiles of emergent literacy
skills among preschool children who are at risk for academic difficulties. Early
Childhood Research Quarterly, 26, 1-14.
PARENTAL MEDIATION OF TECHNOLOGY USE 127
Carr, M. (2000). Technological affordance, social practice and learning narratives in an early
childhood setting. International Journal of Technology and Design Education, 10(1), 61-
80.
Chen, F. F. (2007). Sensitivity of goodness of fit indexes to lack of measurement invariance.
Structural equation modeling, 14(3), 464-504.
Chen, R. (2010). Investigating models of preservice teachers’ use of technology to support
student-centered learning. Computers & Education, 55(1), 32-42.
Cheung, G. W., & Rensvold, R. B. (2002). Evaluating goodness-of-fit indexes for testing
measurement invariance. Structural equation modeling, 9(2), 233-255.
Chrispeels, J.H., & Rivero, E. (2001). Engaging Latino families for student success: How parent
education can reshape parents' sense of place in the education of their children. Peabody
Journal of Education, 76(2), 119-169.
Clark, L. S. (2013). The parent app: Understanding families in the digital age. New York, NY:
Oxford University Press.
Clark, L.S. (2011). Parental mediation theory for the digital age. Communication Theory, 21(4),
323-343.
Cohen, J. & Cohen, P. (1983). Applied Multiple Regression/Correlation Analysis for the
Behavioral Sciences. Hillsdale, New Jersey: Lawrence Erlbaum.
Cohen, J., Cohen, P., West, S. G., & Aiken, L. S. (2003). Applied multiple regression/correlation
analysis for the behavioral sciences. New York, NY: Routledge.
Cole, D. A., & Maxwell, S. E. (2003). Testing mediational models with longitudinal data:
questions and tips in the use of structural equation modeling. Journal of Abnormal
Psychology, 112(4), 558.
PARENTAL MEDIATION OF TECHNOLOGY USE 128
Collins, A., & Halverson, R. (2009). Rethinking education in the age of technology: The digital
revolution and schooling in America. New York: Teachers College Press.
Creswell, J. W., & Clark, V. L. P. (2011). Designing and conducting mixed methods research,
2
nd
edition. Thousand Oaks, CA: SAGE Publications.
Crockett, L., Jukes, I., & Churches, A. (2011). Literacy is not enough: 21st century fluencies for
the digital age. Newbury Park, CA: Corwin Press.
Cronbach, L.J. (1951). Coefficient alpha and the internal structure of tests. Psychometricka, 16,
297-334.
Cumming, G. (2013). Understanding the new statistics: Effect sizes, confidence intervals, and
meta-analysis. New York, NY: Routledge.
Daud, A., Omar, S.Z., Hassan, M.S., Bolong, J., & Teimouri, M. (2014). Parental mediation of
children’s positive use of the Internet. Life Science Journal, 11(8), 360-369.
DeBell, M., & Chapman, C. (2006). Computer and Internet use by students in 2003. Washington,
DC: National Center for Education Statistics.
Dede, C. (2010). Comparing frameworks for 21st century skills. In J. Bellanca & R. Brandt
(Eds.), 21st Century Skills: Rethinking How Students Learn (pp. 51-76). Bloomington,
IN: Solution Tree Press.
Downer, J.T., & Mendez, J.L. (2005). African American father involvement and preschool
children's school readiness, Early Education and Development, 16, 317–340.
Drummond, K.V., & Stipek, D. (2005). Low-income parents' beliefs about their role in children's
academic learning. The Elementary School Journal, 104(3), 197-213.
Eastin, M.S., Greenberg, B.S., & Hofschire, L. (2006). Parenting the internet. Journal of
Communication, 56(3), 486-504.
PARENTAL MEDIATION OF TECHNOLOGY USE 129
Edwards, M. C. (2009). An introduction to item response theory using the need for cognition
scale. Social and Personality Psychology Compass, 3(4), 507-529.
Eklund, L., & Helmersson Bergmark, K. (2013). Parental mediation of digital gaming and
internet use. Proceedings from FDG 2013: the 8th International Conference on the
Foundations of Digital Games (pp. 63-70).
Elsevier. (2015). Contemporary educational psychology. Retrieved from
http://www.journals.elsevier.com/contemporary-educational-psychology/
Embretson, S. & Reise (2000). Item response theory for psychologists. Mahwah, NJ: Erlbaum
Associates.
Epstein, J. A. (2011). Factors related to adolescent computer use and electronic game use.
International Scholarly Research Network Public Health, 2012, 1-6.
Fairlie, R. W., & Robinson, J. (2013). Experimental evidence on the effects of home computers
on academic achievement among schoolchildren (No. w19060). Washington,
DC:National Bureau of Economic Research.
Farver, J.A.M., Yiyuan, X., Lonigan, C.J., & Eppe, S. (2013). The home literacy environment
and Latino Head Start children’s emergent literacy skills. Developmental Psychology,
46(4), 775-791.
Feuerstein, R. (1990). The theory of structural cognitive modifiability. In B. Presseisen (Ed.)
Learning and Thinking Styles: Classroom Interaction, pp. 68-134. Washington, D.C.:
National Education Association.
PARENTAL MEDIATION OF TECHNOLOGY USE 130
Finney, S. J., & DiStefano, C. (2006). Non-normal and categorical data in structural equation
modeling. In G.R. Hancock & R.O. Mueller (Eds.), Structural equation modeling: A
second course (pp.269-314). Greenwich, CO: Information Age Publishing.
Flanagin, A. J., Metzger, M. J., & Hartsell, E. (2010). Kids and credibility: An empirical
examination of youth, digital media use, and information credibility. Cambridge, MA:
MIT Press.
Foster, M., Lambert, R., Abbott-Shim, M., McCarty, F., & Franz, S. (2005). A model of home
learning environment and social risk factors in relation to children’s emergent literacy
and social outcomes, Early Childhood Research Quarterly, 20, 13–36.
Gagne, P., & Hancock, G. R. (2006). Measurement model quality, sample size, and solution
propriety in confirmatory factor models. Multivariate Behavioral Research, 41, 65–83.
Garmendia, M., Garitaonandia, C., Martínez, G., & Casado, M. Á. (2012). The effectiveness of
parental mediation. In S. Livingstone, L. Haddon, A.Gorzig (Eds.), Children, risk and
safety on the internet: Research and policy challenges in comparative perspective (pp.
231-244). Chicago, IL: The Policy Press.
Gee, J. P. (2001). Reading as situated language: A sociocognitive perspective. Journal of
Adolescent & Adult Literacy, 44(8), 714-725.
Gee, J. P. (2004). Situated language and learning: A critique of traditional schooling. New
York: Routledge.
Gefen, D., Straub, D., & Boudreau, M. C. (2000). Structural equation modeling and regression:
Guidelines for research practice. Communications of the association for information
systems, 4(1), 1-77.
PARENTAL MEDIATION OF TECHNOLOGY USE 131
Gentile, D. A., Nathanson, A. I., Rasmussen, E. E., Reimer, R. A., & Walsh, D. A. (2012). Do
you see what I see? Parent and child reports of parental monitoring of media. Family
Relations, 61(3), 470-487.
Goldenberg, C., Gallimore, R., Reese, L., & Garnier, H. (2001). Cause or effect? A longitudinal
study of immigrant Latino parents’ aspirations and expectations, and their children’s
school performance. American Educational Research Journal, 38(5), 547–582.
Gonzalez, M., & Chrispeels, J. (2004, April). Do educational programs increase parenting
practices at home? Factors influencing Latino parent involvement. Paper presented at the
annual meeting of the American Educational Research Association, San Diego, CA.
Greene, B. A. (2015). Measuring cognitive engagement with self-report scales: Reflections from
over 20 years of research. Educational Psychologist, 50(1), 14-30.
Grolnick, W.S., Benjet, C., Kurowski, C.O., & Apostoleris, N.H. (1997). Predictors of parent
involvement in children's schooling. Journal of Educational Psychology, 89(3), 538-548.
Gutiérrez, K. D. (2002). Studying cultural practices in urban learning communities. Human
Development, 45(4), 312-321.
Haddon, L. (2012). Parental mediation of internet use: evaluating family relationships. In E.
Loos, L. Haddon, & E. Mante-Meijer (Eds.), Generational Use of New Media (pp. 13-
30). Farnham, UK: The Editors.
Hammond, M. (2010). What is an affordance and can it help us understand the use of ICT in
education? Education and Information Technologies, 15(3), 205-217.
Hargittai, E. (2005). Survey measures of web-oriented digital literacy. Social Science Computer
Review, 23(3), 371-379.
Harré, R. (1983). Personal being: A theory for individual psychology. Oxford: Blackwell.
PARENTAL MEDIATION OF TECHNOLOGY USE 132
Heath, S. (1991). The sense of being literate: Historical and cross-cultural features. In R. Barr,
M. Kamil, R. Mosenthal, P.D. Pearson (Eds.), Handbook of Reading Research, (Vol. 3,
pp. 3-25). White Plains, New York: Longman.
Hoogland, J. J., & Boomsma, A. (1998). Robustness studies in covariance structure modeling An
overview and a meta-analysis. Sociological Methods & Research, 26(3), 329-367.
Hoover-Dempsey, K. V., & Sandler, H. M. (1995). Parental involvement in children's education:
Why does it make a difference? Teachers College Record, 95, 310-331.
Hoover-Dempsey, K.V., & Jones, K.P. (1997, March). Parental role construction and parental
involvement in children’s education. Paper presented at the annual meeting of the
American Educational Research Association, Chicago, IL.
Hoover-Dempsey, K.V., Bassler, O.C., & Brissie, J.S. (1992). Explorations in parent-school
relations. Journal of Educational Research, 85(5), 287- 294.
Hu, L., & Bentler, P.M. (1999). Cutoff criteria for fit indexes in covariance structure analysis:
Conventional criteria versus new alternatives. Structural Equation Modleing, 6, 1-55.
Ito, M., Baumer, S., Bittanti, M., boyd, d., Cody, R. , Herr, B. … Yardi, S. (2010). Hanging out,
messing around, geeking out: Living and learning with new media. Cambridge: MIT
Press.
Jenkins, H. (2009). Confronting the challenges of participatory culture: Media education for the
21st century. Cambridge: MIT Press.
John-Steiner, V., & Mahn, H. (1996). Sociocultural approaches to learning and development: A
Vygotskian framework. Educational Psychologist, 31(3), 191-206.
PARENTAL MEDIATION OF TECHNOLOGY USE 133
Justice, L. M., & Ezell, H. K. (2001). Written language awareness in preschool children from
low-income households: A descriptive analysis. Communication Disorders Quarterly, 22,
123–134.
Katz, V. S. (2010). How children of immigrants use media to connect their families with the
community. Journal of Children and Media, 4(3), 28-315.
Kay, K. (2010). 21
st
century skills: Why they matter, what they are, and how we get there. In J.
Bellanca & R. Brandt (Eds.), 21st Century Skills: Rethinking How Students Learn (pp.
51-76). Bloomington, IN: Solution Tree Press.
Kirwil, L. (2009). Parental mediation of children's internet use in different European countries.
Journal of Children and Media, 3(4), 394-409.
Kline, R. B. (2011). Principles and practices of Structural Equation Modeling. New York, NY:
The Guildford Press.
Kozulin, A. (2001). Psychological tools: A sociocultural approach to education. Cambridge, MA:
Harvard University Press.
Lankshear, C., & Knobel, M. (2011). New Literacies: Everyday Practices and Social Learning
(3rd Edition). Maidenhead, GBR: McGraw-Hill Education.
Lave, J., & Wenger, E. (1991). Situated learning: Legitimate peripheral participation. New
York, NY: Cambridge university press.
Lee, M. H., & Tsai, C. C. (2010). Exploring teachers’ perceived self-efficacy and technological
pedagogical content knowledge with respect to educational use of the World Wide Web.
Instructional Science, 38(1), 1-21.
Lenhart, A., Purcell, K., Smith, A., & Zickuhr, K. (2010). Social Media & Mobile Internet Use
among Teens and Young Adults. Washington, DC: Pew Research Center.
PARENTAL MEDIATION OF TECHNOLOGY USE 134
Leu, D. J., Everett-Cacopardo, H., Zawilinski, J., Mcverry, G., & O'Byrne, W. I. (2013). New
literacies of online reading comprehension. In C.A. Chapelle (Ed.), The Encyclopedia of
Applied Linguistics (pp. 1-9). Oxford: Blackwell Publishing.
Liau, A. K., Khoo, A., & Ang, P. H. (2008). Parental awareness and monitoring of adolescent
internet use. Current Psychology, 27(4), 217-233.
Livingstone, S. (2003). The Changing Nature and Uses of Media Literacy. Working paper.
London: London School of Economics.
Livingstone, S., & Bober, M. (2006). Regulating the internet at home: contrasting the
perspectives of children and parents. In D. Buckingham & R. Willett (Eds.), Digital
Generations: Children, Young People, and New Media (pp. 93-113). Mahwah, NJ:
Lawrence Erlbaum.
Livingstone, S., & Haddon, L. (2009). Kids online: Opportunities and risks for children.
Chicago, IL: The Policy Press.
Livingstone, S., & Helsper, E. (2007). Gradations in digital inclusion: children, young people
and the digital divide. New media & society, 9(4), 671-696.
Livingstone, S., & Helsper, E. J. (2008). Parental mediation of children's internet use. Journal of
broadcasting & electronic media, 52(4), 581-599.
Livingstone, S., Haddon, L., Görzig, A., & Ólafsson, K. (2011). Risks and safety on the internet:
the perspective of European children: Full findings and policy implications from the EU
Kids online survey of 9-16 year olds and their parents in 25 countries. London, UK: EU
Kids Online Network.
Loehlin, J. C. (2004). Latent variable models: An introduction to factor, path, and structural
equation analysis. New York, NY: Routledge.
PARENTAL MEDIATION OF TECHNOLOGY USE 135
MacCallum, R. C., Browne, M. W., & Sugawara, H. M. (1996). Power analysis and
determination of sample size for covariance structure modeling. Psychological methods,
1(2), 130-149.
MacCallum, R. C., Widaman, K. F., Zhang, S., & Hong, S. (1999). Sample size in factor
analysis. Psychological methods, 4(1), 84-99.
Machida, S., Taylor, A.R., & Kim, J. (2002). The role of maternal beliefs in predicting home
learning activities in head start families. Family Relations, 51, 176-184.
Mahn, H. (1999). Vygotsky's methodological contribution to sociocultural theory. Remedial and
Special Education, 20(6), 341-350.
Malamud, O., & Pop-Eleches, C. (2010). Home computer use and the development of human
capital (No. w15814). Washington, DC: National Bureau of Economic Research.
Margolin, J., Haynes, E., Heppen, J., Ruedel, K., Meakin, J., Hauser, A., ... & Hubbard, A.
(2014). Evaluation of the Common Core Technology Project. Washington, DC: American
Institutes for Research.
Martin, A. (2008). Digital literacy and the ‘digital society.’ In C. Lankshear & M. Knobel (Eds.),
Digital Literacies: Concepts, Policies, and Practices (pp.151-76). New York, NY: Peter
Lang.
McDonald, R. P. (1999). Test theory: A unified treatment. Mahwah, New Jersey: Lawrence
Erlbaum.
Milner, H.R. (2002). A case study of an experienced English teacher's self-efficacy and
persistence through “crisis” situations: Theoretical and practical considerations. The High
School Journal, 86(1), 28-35.
PARENTAL MEDIATION OF TECHNOLOGY USE 136
Moje, E. B., Ciechanowski, K. M., Kramer, K., Ellis, L., Carrillo, R. & Collazo, T. (2004).
Working toward third space in content area literacy: An examination of everyday funds
of knowledge and Discourse. Reading Research Quarterly, 39, 38-70.
Moshagen, M., & Musch, J. (2014). Sample size requirements of the robust weighted least
squares estimator. Methodology. European Journal of Research Methods for the
Behavioral and Social Sciences, 10(2), 60-70.
Muthén, B., Du Toit, S. H., & Spisic, D. (1997). Robust inference using weighted least squares
and quadratic estimating equations in latent variable modeling with categorical and
continuous outcomes. Psychometrika, 75, 1-45.
Muthen, B.O.(1993). Goodness of fit with categorical and other nonnormal variables. In K. A.
Bollen & J. S. Long (Eds.), Testing Structural Equation Models (pp. 205–243). Newbury
Park, CA: Sage.
Myers, N. D., Ahn, S., & Jin, Y. (2011). Sample size and power estimates for a confirmatory
factor analytic model in exercise and sport: a Monte Carlo approach. Research quarterly
for exercise and sport, 82(3), 412-423.
Nathanson, A. (2001). Parent and child perspectives on the presence and meaning of parental
television mediation. Journal of Broadcasting and Electronic Media, 45, 201-220.
Neumann, A. (2006). Professing passion: Emotion in the scholarship of professors at research
universities. American Educational Research Journal, 43(3), 381-424.
Nikken, P. Jansz, J. & Schouwstra, S. (2007). Parents’ interest in videogame ratings and content
descriptors in relation to game mediation. European Journal of Communication, 22, 315-
336.
PARENTAL MEDIATION OF TECHNOLOGY USE 137
Nikken, P., & Jansz, J. (2006). Parental mediation of children’s videogame playing: A
comparison of the reports by parents and children. Learning, Media and Technology,
31(2), 181-202.
Nikken, P., & Jansz, J. (2011). Parental mediation of young children’s Internet use. Netherlands:
Erasmus University Rotterdam.
Njoroge, W. F., Elenbaas, L. M., Garrison, M. M., Myaing, M., & Christakis, D. A. (2013).
Parental cultural attitudes and beliefs regarding young children and television. JAMA
pediatrics, 167(8), 739-745
Notten, N., & Kraaykamp, G. (2009). Parents and the media: A study of social differentiation in
parental media socialization. Poetics, 37(3), 185–200.
Olivares, A.M. & D’Zurilla, T.J. (1996). A factor-analytic study of the social problem-solving
inventory: An integration of theory and data. Cognitive Therapy and Research, 20(2),
115-133.
Ortiz, R. W., Green, T., & Lim, H. (2011). Families and home computer use: Exploring parent
perceptions of the importance of current technology. Urban Education, 46(2), 202-215.
Padilla-Walker, L. M., & Coyne, S. M. (2011). “Turn that thing off!” parent and adolescent
predictors of proactive media monitoring. Journal of adolescence, 34(4), 705-715.
Pajares, F., & Miller, M. D. (1994). Role of self-efficacy and self-concept beliefs in
mathematical problem solving: A path analysis. Journal of educational psychology,
86(2), 193.
Pasquier, D., Simões, J. A., & Kredens, E. (2012). Agents of mediation and sources of safety
awareness: a comparative overview. In S. Livingstone, L. Haddon, A.Gorzig (Eds.),
PARENTAL MEDIATION OF TECHNOLOGY USE 138
Children, risk and safety on the internet: Research and policy challenges in comparative
perspective (pp. 219-230). Chicago, IL: The Policy Press.
Pea, R. (1993). Practices of Distributed Intelligence and Designs for Education. In G. Salomon
(Ed.), Distributed Cognitions: Psychological and Educational Considerations.
Cambridge, MA: Cambridge University Press.
Pea, R. D. (2004). The social and technological dimensions of scaffolding and related theoretical
concepts for learning, education, and human activity. The Journal of the Learning
Sciences, 13(3), 423-451.
Pekrun, R. (2006). The control-value theory of achievement emotions: Assumptions, corollaries,
and implications for educational research and practice. Educational Psychology Review,
18(4), 315-341.
Pintrich, P. R. (2004). A conceptual framework for assessing motivation and self-regulated
learning in college students. Educational psychology review, 16(4), 385-407.
Plowman L, McPake, J., Stephen C. (2010). The technologisation of childhood? Young children
and technology in the home. Children and Society, 24(1) 63-74.
Plowman L, Stephen C., McPake, J. (2010). Supporting young children’s learning with
technology at home and in preschool. Research Papers in Education, 25(1) 93-113.
Plowman, L., McPake, J., & Stephen, C. (2008). Just picking it up? Young children learning with
technology at home. Cambridge Journal of Education, 38(3), 303-319.
Puntambekar, S., & Hubscher, R. (2005). Tools for scaffolding students in a complex learning
environment: What have we gained and what have we missed? Educational psychologist,
40(1), 1-12.
PARENTAL MEDIATION OF TECHNOLOGY USE 139
Reed, R.P., Jones, K.P., Walker, J.M., & Hoover-Dempsey, K.V. (2000, April). Parents'
motivations for involvement in children’s education: Testing a theoretical model. Paper
presented at the annual meeting of the American Educational Research Association. New
Orleans, LA.
Rees, H., & Noyes, J. M. (2007). Mobile telephones, computers, and the internet: sex differences
in adolescents' use and attitudes. CyberPsychology & Behavior, 10(3), 482-484.
Reese, L., Balzano, S., Gallimore, R., & Goldenberg, C. (1995). The concept of educacion:
Latino family values and American schooling. International Journal of Educational
Research, 23, 57–81.
Reese, L.J., &Gallimore, R. (2000). Immigrant Latinos’ cultural model of literacy development:
An alternative perspective on home-school discontinuities. American Journal of
Education, 108(2), 103–134.
Rogoff, B. (1990). Apprenticeship in thinking: Cognitive development in social context. New
York, NY: Oxford University Press.
Rosen, L. D., Cheever, N. A., & Carrier, L. M. (2008). The association of parenting style and
child age with parental limit setting and adolescent MySpace behavior. Journal of
Applied Developmental Psychology, 29, 459–471.
Rowe, D.W., & Miller, M.E.(2015, April). Preschoolers’ construction of the sociocultural
affordances of iPads as tools for multimodal, multilingual composing. Paper presented at
the annual meeting of the American Educational Research Association, Chicago, IL.
Rueda, R., & Moll, L. C. (1994). A sociocultural perspective on motivation. In H.F. O’Neil & M.
Drillings (Eds.), Motivation: Theory and research (pp.117-137). New York, NY:
Psychology Press.
PARENTAL MEDIATION OF TECHNOLOGY USE 140
Saklofske, D. H., Michayluk, J. O., & Randhawa, B. S. (1988). Teachers' efficacy and teaching
behaviors. Psychological Reports, 63(2), 407-414.
Sang, G., Valcke, M, van Braak, J., & Tondeur, J. (2010). Student teachers’ thinking processes
and ICT integration: Predictors of prospective teaching behaviors with educational
technology. Computers & Education, 54, 103-112.
Sava, F. A. (2002). Causes and effects of teacher conflict-inducing attitudes towards pupils: A
path analysis model. Teaching and teacher education, 18(8), 1007-1021.
Schaan, V. K., & Melzer, A. (2015). Parental Mediation of Children's Television and Video
Game use in Germany: Active and Embedded in Family Processes. Journal of Children
and Media, 9(1), 58-76.
Schunk, D. H., & Zimmerman, B. J. (2006). Competence and control beliefs: Distinguishing the
means and ends. In P. A. Alexander & P. H. Winne (Eds.), Handbook of Educational
Psychology (2nd ed., pp. 349–367). Mahwah, NJ: Erlbaum.
Schunk, D.H. (2008). Learning theories: An educational perspective. New Jersey: Pearson
Schunk, D.H., Meece, J.R., & Pintrich, P.R. (2014). Motivation in education: Theory, research,
and applications. Upper Saddle River, NJ: Pearson Education.
Shapley, K., Sheehan, D., Maloney, C., Caranikas-Walker, F., Huntsberger, B., & Sturges, K.
(2007). Evaluation of the Texas Technology Immersion Project: Findings from the
Second Year. Austin, Texas: Texas Center for Educational Research.
Sheldon, S. B. (2002). Parents’ social networks and beliefs as predictors of parent involvement.
The Elementary School Journal, 102(4), 301–316.
PARENTAL MEDIATION OF TECHNOLOGY USE 141
Shell, D. F., Murphy, C. C., & Bruning, R. H. (1989). Self-efficacy and outcome expectancy
mechanisms in reading and writing achievement. Journal of Educational Psychology,
81(1), 91-100.
Sinatra, G. M., Heddy, B. C., & Lombardi, D. (2015). The challenges of defining and measuring
student engagement in science. Educational Psychologist, 50(1), 1-13.
Smagorinsky, P. (2013). What does Vygotsky provide for the 21st century language arts teacher?
Language Arts, 90(3), 192-204.
Sonck, N., Nikken, P., & de Haan, J. (2013). Determinants of internet mediation: a comparison
of the reports by Dutch parents and children. Journal of Children and Media, 7(1), 96-
113.
Tabak, I. (2004). Synergy: A complement to emerging patterns of distributed scaffolding. The
Journal of the Learning Sciences, 13(3), 305-335.
Takahashi, A. (2009). Self-perception of English Ability: Is it related to proficiency and/or class
performance. Studies in Foreign Languages and Cultures, 14, 39-48.
Takeuchi, L. (2012). Kids closer up: Playing, learning, and growing with digital media.
International Journal of Learning and Media, 3(2), 37-59.
Taylor, H. G., & Mounfield, L. C. (1994). Exploration of the relationship between prior
computing experience and gender on success in college computer science. Journal of
Educational Computing Research, 11, 291-306.
Tschannen-Moran, M., Woolfolk-Hoy, A., & Hoy, W. (1998). Teacher efficacy: Its meaning
and measure. Review of Educational Research, 68(2), 202-248.
Valdes, G. (1996). Con respeto: Bridging the distances between culturally diverse families and
schools. New York: Teachers College Press.
PARENTAL MEDIATION OF TECHNOLOGY USE 142
Valkenburg, P. M., & Peter, J. (2013). The differential susceptibility to media effects model.
Journal of Communication, 63(2), 221-243.
Valkenburg, P. M., Piotrowski, J. T., Hermanns, J., & Leeuw, R. (2013). Developing and
Validating the Perceived Parental Media Mediation Scale: A Self-Determination
Perspective. Human Communication Research, 39(4), 445-469.
Valkenburg, P., Krcmar, M., Peeters, A. & Marseille, N. (1999). Developing a scale to assess
three styles of television mediation: “instructive mediation,” “restrictive mediation,” and
“social coviewing.” Journal of Broadcasting and Electronic Media, 43, 52-66.
Valsiner, J. (1997). Culture and the development of children's action: A theory of human
development. Hoboken, NJ: John Wiley & Sons.
Vigdor, J. L., & Ladd, H. F. (2010). Scaling the digital divide: Home computer technology and
student achievement (No. w16078). Washington, DC: National Bureau of Economic
Research.
Voogt, J., & Roblin, N. P. (2010). 21st century skills: Discussion paper. Enschede, the
Netherlands: University of Twente.
Vygotsky, L. S. (1980). Mind in society: The development of higher psychological processes.
Cambridge, MA: Harvard university press.
Waanders, C., Mendez, J.L., & Downer, J. (2007). Parent characteristics, economic stress, and
neighborhood context as predictors of parent involvement in preschool children’s
education. Journal of School Psychology, 45, 619-636.
Walker, J.M.T., Ice, C. L., Hoover-Dempsey, K. V., & Sandler, H. M. (2011). Latino parents'
motivations for involvement in their children's schooling: An exploratory study. The
Elementary School Journal, 111(3), 409-429.
PARENTAL MEDIATION OF TECHNOLOGY USE 143
Walker, J.M.T., Wilkins, S.W., Dallaire, J.R., Sandler, H.M., & Hoover-Dempsey, K.V. (2005).
Parental involvement: Model revision through scale development. The Elementary School
Journal, 106(2), 85-104.
Wang, L., Ertmer, P. A., & Newby, T. J. (2004). Increasing preservice teachers’ self-efficacy
beliefs for technology integration. Journal of Research on Technology in Education,
36(3), 231-250.
Warschauer, M., & Matuchniak, T. (2010). New technology and digital worlds: Analyzing
evidence of equity in access, use, and outcomes. Review of Research in Education, 34(1),
179-225.
Warschauer, M., Knobel, M., & Stone, L. (2004). Technology and equity in schooling:
Deconstructing the digital divide. Educational Policy, 18(4), 562-588.
Wartella, E., Rideout, V., Lauricella, A., & Connell, S. (2013). Parenting in the age of digital
technology. Report for the Center on Media and Human Development School of
Communication. Evanston, IL: Northwestern University.
Weigel, D.J., Martin, S.S, & Bennett, K.K. (2006). Mothers’ literacy beliefs: Connections with
the home literacy environment and pre-school children’s literacy development. Journal of
Early Childhood Literacy, 6(2), 191-211.
Welsch, J. G., Sullivan, A., & Justice, L. M. (2003). That’s my letter!: What preschoolers’ name-
writing representations tell us about emergent literacy knowledge. Journal of Literacy
Research, 35, 757–776.
Whitaker, M., & Hoover-Dempsey, K. (2013). School influences on parents' role beliefs. The
Elementary School Journal, 114(1), 73-99.
PARENTAL MEDIATION OF TECHNOLOGY USE 144
Widaman, K. F., & Reise, S. P. (1997). Exploring the measurement invariance of psychological
instruments: Applications in the substance use domain. The science of prevention:
Methodological advances from alcohol and substance abuse research, 281-324.
Witt, E. A., Massman, A. J., & Jackson, L. A. (2011). Trends in youth’s videogame playing,
overall computer use, and communication technology use: The impact of self-esteem and
the Big Five personality factors. Computers in Human Behavior, 27(2), 763-769.
Wood, D., Bruner, J. S., & Ross, G. (1976). The role of tutoring in problem solving. Journal of
child psychology and psychiatry, 17(2), 89-100.
Zhao, X., Lynch, J. G., & Chen, Q. (2010). Reconsidering Baron and Kenny: Myths and truths
about mediation analysis. Journal of consumer research, 37(2), 197-206.

PARENTAL MEDIATION OF TECHNOLOGY USE 145
Tables and Figures

Table 1: Descriptive Demographic Data
Indicators
# of participants
(% of total)
Ethnicity (283 responses)
Latino 197 (67.7%)
African-American 29 (10.0%)
White/Caucasian 22 (7.6%)
Asian 19 (6.5%)
Native American 1 (<1%)
Pacific Islander 3 (1.0%)
Middle-Eastern 2 (<1%)
Mixed and Other Race 10 (3.4%)
Lunch (282 responses)
Free Lunch 195 (67.0%)
Reduce-priced Lunch 20 (6.9%)
Regular-priced Lunch 67 (23%)
Education Level (273 responses)
Less than High School 74 (25.4%)
High School Graduate 63 (21.6%)
Some College Education 50 (17.2%)
College Graduate 46 (15.8%)
Some Graduate Education 13 (4.5%)
Graduate Degree 27 (9.3%)
Gender (281 responses)
Male 55 (18.9%)
Female 226 (77.7%)
Age (273 responses)
21-30 20 (6.9%)
31-40 123 (42.3%)
41-50 106 (36.4%)
51-60 22 (7.6%)
More than 60 20 (6.9%)
PARENTAL MEDIATION OF TECHNOLOGY USE 146

Table 2: Descriptive Statistics of Parental Mediation Behaviors, Restrictive Mediation
Restrictive Items
Entire Sample (N=291) Low Income Subsample (n=215)
Mean (SD) Range % executed
sometimes or
more Ɨ
Mean
(SD)
Range % executed
sometimes
or more
RTM1: I restrict my child from using instant
messaging
0.59 0-1 58.8% 0.64 0-1 63.6%
RTM2: I restrict my child from downloading
music or films on the internet
0.62 0-1 61.7% 0.64 0-1 64.0%
RTM3: I restrict my child from using e-mail 0.51 0-1 51.2% 0.58 0-1 57.7%
RTM4: I restrict my child from playing
online games
0.48 0-1 47.9% 0.53 0-1 52.8%
RTM5: I restrict my child from watching
video clips on the internet
0.46 0-1 46.0% 0.50 0-1 50.2%
RTM6: I restrict my child from using online
chat-rooms
0.85 0-1 84.8% 0.85 0-1 84.5%
RTM7: I restrict my child from having
his/her own social networking profile
0.67 0-1 67.1% 0.68 0-1 68.1%
RTM8: I restrict my child from giving out
personal information to others on the
internet
0.96 0-1 95.9% 0.96 0-1 95.8%
RTM9: I restrict my child from uploading
photos, videos, or music to share with
others
0.76 0-1 75.5% 0.78 0-1 77.6%
RTM10: I set up rules about the amount of
time my child can spend using technology.
0.87 0-1 87.2% 0.90 0-1 89.7%
RTM11: I encourage my child to do other
activities instead of using technology.
3.97 1-5 94.4% 3.95 1-5 93.4%
Ɨ % Executed sometimes or more refers to the percent of parents who indicated they used this strategy sometimes (score =3), often
(score = 4), or very often (score = 5). For dichotomous items, this number would reflect the percent of parents who indicated that they
execute that particular mediation behavior (i.e. answering 1= Yes).
PARENTAL MEDIATION OF TECHNOLOGY USE 147

Table 3: Descriptive Statistics of Parental Mediation Behaviors, Monitoring and Technical Mediation
Regulatory Items
Entire Sample (N=291) Low Income Subsample (n=215)
Mean (SD) Range
% executed
sometimes or
more Ɨ
Mean
(SD)
Range
% executed
sometimes
or more
MNT1: I check the websites my child
visited after s/he is done.
3.66
(1.26)
1-5 82.3%
3.79
(1.27)
1-5 82.7%
MNT2: I check messages in my child’s
email or instant messaging account
3.27
(1.32)
1-5 72.9%
3.28
(1.33)
1-5 72.9%
MNT3: I check my child’s profile on
social network websites (like Facebook)
or online community
3.27
(1.42)
1-5 72.6%
3.33
(1.41)
1-5 73.8%
MNT4: I check which friends or contacts
my child has added to his/her social
networking profile or instant messaging
service
3.33
(1.37)
1-5 74.7%
3.42
(1.36)
1-5 76.2%
MNT5: I remain close by to monitor my
child when s/he uses technology.
3.49
(1.17)
1-5 82.9%
3.55
(1.20)
1-5 83.1%
MNT6: I make sure my child uses
technology in a public space at home
(living room, dining room, etc.).
3.71
(1.21)
1-5 85.4%
3.78
(1.20)
1-5 86.9%
TCM1: I use parental control or other
means of blocking my child’s content
access
0.75
(0.43)
0-1 74.8%
0.75
(0.44)
0-1 74.8%
TCM2: I use parental control or other
means of keeping track of my child’s
online activities
0.75
(0.43)
0-1 74.8%
0.75
(0.43)
0-1 75.2%
TCM3: I use a software to limit the time
my child spends with technology
0.45
(0.50)
0-1 44.8%
0.50
(0.50)
0-1 50.5%
TCM4: I use a software to prevent spam,
junk mail, or viruses in my child’s email
0.67
(0.47)
0-1 67.1%
0.73
(0.45)
0-1 72.6%
Ɨ % Executed sometimes or more refers to the percent of parents who indicated they used this strategy sometimes (score =3), often
(score = 4), or very often (score = 5) for frequency-related questions. For dichotomous items, this number would reflect the percent
of parents who indicated that they execute that particular mediation behavior (i.e. answering 1= Yes).
PARENTAL MEDIATION OF TECHNOLOGY USE 148
Table 4: Descriptive Statistics of Parental Mediation Behaviors, Supportive Mediation
Supportive Items
Entire Sample (N=291) Low Income Subsample (n=215)
Mean
(SD)
Range
% executed
sometimes
or more Ɨ
Mean
(SD)
Range
% executed
sometimes
or more
CCU1: My child and I do something together
using technology.
3.34
(0.97)
1-5 88.3%
3.33
(1.03)
1-5 87.0%
CCU2: I collaborate with my child to achieve
something using technology
3.37
(0.99)
1-5 86.6%
3.39
(1.02)
1-5 86.5%
PCU1: My child and I learn something new
together using technology.
3.55
(0.99)
1-5 88.9%
3.57
(1.03)
1-5 88.7%
PFC1: I encourage my child to use technology
to connect with people in our family.
3.06
(1.15)
1-5 67.7%
3.10
(1.19)
1-5 67.9%
PCC1: I encourage my child to use technology
to connect with other people in our
community.
2.35
(1.23)
1-5 41.6%
2.40
(1.27)
1-5 41.9%
BDL1: I find ways for my child to learn how to
do new things with technology.
3.23
(1.05)
1-5 81.1%
3.24
(1.06)
1-5 80.9%
BDL2: I look for technology classes my child
could take.
2.65
(1.24)
1-5 53.6%
2.67
(1.22)
1-5 55.3%
EEI1: I encourage my child to use online
resources to increase their knowledge about
something they’re interested in
3.61
(1.08)
1-5 88.6%
3.55
(1.12)
1-5 86.4%
EEI2: I encourage my child to create
something they’re interested in using
technology.
3.34
(1.03)
1-5 83.5%
3.35
(1.03)
1-5 83.7%
EES1: I encourage my child to learn more
about how to use technology.
3.47
(1.03)
1-5 87.2%
3.47
(1.04)
1-5 86.9%
EES2: I encourage my child to take a
technology class.
3.14
(1.22)
1-5 72.2%
3.16
(1.22)
1-5 73.4%
ICR1: I show my child how technology can be
used in everyday life.
3.38
(1.05)
1-5 83.3%
3.40
(1.09)
1-5 83.1%
ICR2: I talk to my child about how technology
can improve his/her life.
3.45
(1.06)
1-5 84.3%
3.47
(1.05)
1-5 85.8%
PARENTAL MEDIATION OF TECHNOLOGY USE 149

Supportive Items
Entire Sample (N=291) Low Income Subsample (n=215)
Mean
(SD)
Range
% executed
sometimes
or more Ɨ
Mean
(SD)
Range
% executed
sometimes
or more
ACM1: I give my child ideas about what’s
good to read or view online.
3.62
(0.98)
1-5 92.0%
3.66
(1.00)
1-5 91.5%
ACM2: I talk to my child about online content
that we both are interested in.
3.49
(1.01)
1-5 88.5%
3.53
(0.99)
1-5 90.1%
ASM1: I talk to my child about how to be safe
when interacting with others people using
technology.
3.93
(1.07)
1-5 90.7%
3.90
(1.05)
1-5 90.7%
ASM2: I talk to my child about what s/he
would do if something on the internet
bothered her/him
3.84
(1.09)
1-5 89.6%
3.85
(1.10)
1-5 88.8%
EOI1: I teach my child how to do something
new using technology.
3.29
(1.11)
1-5 80.1%
3.32
(1.13)
1-5 79.9%
RTS1: I ask my child to help perform
technology-related tasks around the house.
3.03
(1.22)
1-5 67.5%
3.05
(1.24)
1-5 68.2%
RTS2: I ask my child to help fix something
related to technology when it does not work.
3.02
(1.29)
1-5 64.2%
3.06
(1.28)
1-5 67.1%
RTG1: I ask my child to show me how to do
something using technology.
3.10
(1.21)
1-5 73.4%
3.15
(1.19)
1-5 76.2%
RTG2: I ask my child to help another family
member understand how to use technology.
3.12
(1.27)
1-5 70.3%
3.17
(1.26)
1-5 72.1%
RSP1: I give my child the technology tools
he/she needs.
3.54
(1.04)
1-5 88.1%
3.53
(1.09)
1-5 85.4%
RSP2: I let my child borrow my technology
device.
3.32
(1.22)
1-5 79.2%
3.27
(1.25)
1-5 76.2%
RSP3: I find ways for my child to access the
technology tool he/she needs
3.53
(1.09)
1-5 86.2%
3.53
(1.11)
1-5 84.7%
Ɨ % executed sometimes or more refers to the percent of parents who indicated they used this strategy sometimes (score =3), often
(score = 4), or very often (score = 5). For dichotomous items, this number would reflect the percent of parents who indicated that
they execute that particular mediation behavior (i.e. answering 1= Yes).

PARENTAL MEDIATION OF TECHNOLOGY USE 150

Table 5: Confirmatory Phase, Regulatory Mediation Measurement Models Fit Indices
Models
# of
items
χ
2
df
χ
2
p-value
χ
2
/df CFI TLI RMSEA
RMSEA
90%CI
WRMR
R1: Regulatory mediation
one factor
21 2451.14 189 0.000 12.97 0.873 0.859 0.212 0.204.219 3.106
R2: Regulatory mediation
2
nd
order factor
21 1038.04 186 0.000 5.58 0.952 0.946 0.131 0.123-0.139 2.022
R3: Restrictive mediation
(RTM)
11 81.48 44 0.001 1.85 0.985 0.982 0.056 0.036-0.074 1.087
R4: Monitoring (MNT) 6 176.75 9 0.000 19.64 0.988 0.980 0.256 0.224-0.289 2.076
R5: Technical mediation
(TCM)
4 19.71 2 0.000 9.85 0.986 0.957 0.178 0.112-0.253 1.404
Note: Grayed field indicates best fit among comparable models.
PARENTAL MEDIATION OF TECHNOLOGY USE 151
Figure 1: Restrictive Mediation Measurement Model

PARENTAL MEDIATION OF TECHNOLOGY USE 152
Figure 2: Scree Plot of Monitoring and Technical Mediation Items

0 1 2 3 4
Eigenvalues
0 2 4 6 8 10
Number
Scree plot of eigenvalues after factor
PARENTAL MEDIATION OF TECHNOLOGY USE 153

Table 6: Exploratory Phase, Principal Factor Analysis with Oblique Promax Rotation of Monitoring and Technical Mediation Items
Items
Factor 1
(MNTa)
Factor 2
(MNTb)
Factor 3
(TCMa)
Factot 4
(TCMb)
MNT1: I check the websites my child visited after s/he is done.
0.1821 0.4209 -0.0615
-0.0048
MNT2: I check messages in my child’s email or instant messaging account
0.6690 0.1344 0.0172
0.0124
MNT3: I check my child’s profile on social network websites (like Facebook) or online
community
0.9196 -0.0303 0.0047
-0.0599
MNT4: I check which friends or contacts my child has added to his/her social
networking profile or instant messaging service
0.8862 0.0518 -0.0138
0.0304
MNT5: I remain close by to monitor my child when s/he uses technology.
0.1513 0.7255 -0.0430
0.0520
MNT6: I make sure my child uses technology in a public space at home (living room,
dining room, etc.).
-0.0450 0.7866 0.0563
-0.0553
TCM1: I use parental control or other means of blocking my child’s content access
0.0582 -0.0499 0.7479
0.0703
TCM2: I use parental control or other means of keeping track of my child’s online
activities
-0.0656 0.0532 0.7461
0.0280
TCM3: I use a software to limit the time my child spends with technology
-0.0940 0.0346 0.0286
0.6022
TCM4: I use a software to prevent spam, junk mail, or viruses in my child’s email
0.0676 -0.0588 0.1018
0.5843
Note: Grayed field indicates items presumed to load on labeled factors.
PARENTAL MEDIATION OF TECHNOLOGY USE 154

Table 7: Exploratory Phase, Regulatory Mediation Measurement Models Fit Indices
Models
# of
items
χ
2
df
χ
2
p-value
χ
2
/df CFI TLI RMSEA
RMSEA
90%CI
WRMR
R6: All MNT and TCM items
one factor
10 645.77 35 0.000 18.45 0.958 0.946 0.253 0.236-0.270 2.947
R7: Regulatory 2
nd
order;
MNTa + MNTb + TCMa + TCMb
10 158.51 31 0.000 5.11 0.991 0.987 0.122 0.104-0.141 1.474
R8: Regulatory 2
nd
order;
MNTa+ MNTb + all TCM
10 68.52 32 0.000 2.14 0.997 0.996 0.064 0.043-0.085 0.969
R9: Regulatory 2
nd
order;
all MNT + TCMa + TCMb
10 169.14 32 0.000 5.29 0.991 0.987 0.125 0.106-0.143 1.522
R10: Regulatory 2
nd
order;
RTM+MNTa+MNTb+all TCM
21 1066.63 185 0.000 5.77 0.951 0.944 0.134 0.126-0.141 2.049
Note: Grayed field indicates best fit among comparable models.
PARENTAL MEDIATION OF TECHNOLOGY USE 155
Figure 3: Monitoring Measurement Model

PARENTAL MEDIATION OF TECHNOLOGY USE 156

Table 8: Confirmatory Phase, Supportive Mediation Measurement Models Fit Indices
Models
# of
items
χ
2
df
χ
2
p-value
χ
2
/df CFI TLI RMSEA
RMSEA
90%CI
SRMR
S1: Supportive mediation one
factor
25 1614.91 275 0.000 5.87 0.643 0.610 0.136 0.130-0.143 0.099
S2: Supportive mediation 2
nd

order factor
25 1012.67 270 0.000 3.75 0.802 0.780 0.102 0.096-0.109 0.088
S3: Connectedness (CNN) 5 66.03 5 0.000 13.21 0.887 0.773 0.206 0.163-0.251 0.096
S4: Knowledge expansion (KNE) 6 142.01 9 0.000 15.78 0.788 0.646 0.227 0.195-0.261 0.089
S5: Help recruitment (HRM) 4 21.76 2 0.000 10.88 0.966 0.897 0.186 0.121-0.260 0.036
S6: Guidance provision (GDP) 7 94.43 14 0.000 6.74 0.906 0.859 0.145 0.118-0.173 0.058
S7: Resource provision (RSP) 3 Zero degree of freedom

PARENTAL MEDIATION OF TECHNOLOGY USE 157
Figure 4: Scree Plot of Supportive Mediation Items

0 2 4 6 8
10
Eigenvalues
0 5 10 15 20 25
Number
Scree plot of eigenvalues after factor
PARENTAL MEDIATION OF TECHNOLOGY USE 158

Table 9: Exploratory Phase, Principal Factor Analysis with Oblique Promax Rotation of Supportive Items
Items
Factor 1
(GDP)
Factor 2
(RSP)
Factor 3
(TIP)
Factor 4
(ICU)
Factor 5
(CNP)
Factor 6
(ASM)
CCU1: My child and I do something together using
technology.
0.0436 -0.0512 0.0146 0.8418 -0.0259 0.0500
CCU2: I collaborate with my child to achieve
something using technology
-0.0800 -0.0258 0.0977 0.7637 0.0644 0.0031
PCU1: My child and I learn something new
together using technology.
0.0979 0.0710 0.0213 0.5351 0.0514 -0.0360
EOI1: I teach my child how to do something new
using technology.
0.1898 0.0510 0.0407 0.2709 0.0137 0.0331
PFC1: I encourage my child to use technology to
connect with people in our family.
0.0348 -0.0077 -0.0311 0.0580 0.6760 0.0935
PCC1: I encourage my child to use technology to
connect with other people in our community.
-0.0044 0.0513 -0.0657 0.0285 0.6127 -0.1143
BDL1: I find ways for my child to learn how to do
new things with technology.
-0.0759 0.0215 -0.0424 0.2138 0.3917 0.0064
BDL2: I look for technology classes my child could
take.
0.0853 -0.0134 0.2405 -0.0365 0.2902 0.0878
EES1: I encourage my child to learn more about
how to use technology.
0.0251 -0.0430 0.7533 0.0548 -0.0245 -0.0058
EES2: I encourage my child to take a technology
class.
-0.0861 -0.0227 0.8168 0.0025 0.0130 0.0024
ICR1: I show my child how technology can be
used in everyday life.
0.1580 0.1746 0.6285 0.1171 -0.0786 -0.0142
ICR2: I talk to my child about how technology can
improve his/her life.
0.5325 0.0033 0.1663 -0.0133 0.1101 -0.0859
ACM1: I give my child ideas about what’s good to
read or view online.
0.7983 -0.0386 0.0774 -0.0542 0.0258 0.0659
ACM2: I talk to my child about online content that
we both are interested in.
0.7295 0.0493 -0.1401 0.1803 -0.0706 0.0211
ASM1: I talk to my child about how to be safe
when interacting with others people using
technology.
0.0923 0.0349 0.0036 0.1066 -0.0236 0.6358
ASM2: I talk to my child about what s/he would do
if something on the internet bothered her/him.
0.0995 0.0290 -0.0147 0.0420 0.0019 0.6282
RSP1: I give my child the technology tools he/she
needs.
0.0149 0.5389 0.0767 -0.0623 0.0380 0.0712
RSP2: I let my child borrow my technology device. -0.0627 0.7298 -0.0599 0.1241 0.0254 -0.0680
RSP3: I find ways for my child to access the
technology tool he/she needs
0.0694 0.7597 0.0525 -0.0758 -0.0149 0.0536
Note: Dark gray fields indicate items presumed to load on labeled factors; Light gray field indicate items which may have joint loadings on more
than one factor (pending further statistical tests); Items with low loadings across Factors 1-6 are not included for clarity. Factor names are as
follows: GDP=Guidance Provision; RSP=Resource Provision; TIP=Technology Involvement Promotion; ICU=Instructive Co-use;
CNP=Connectedness Promotion; ASM=Active Safety Mediation
PARENTAL MEDIATION OF TECHNOLOGY USE 159

Table 10: Exploratory Phase, Supportive Mediation Measurement Models Fit Indices
Models
# of
items
χ
2
df
χ
2
p-value
χ
2
/df CFI TLI RMSEA
RMSEA
90%CI
SRMR
S8: Supportive 1
st
order; limited items 19 732.67 152 0.000 4.82 0.696 0.659 0.119 0.112-0.127 0.084
S9: Supportive 2
nd
order; GDP, RSP, TIP, ICU,
CNP, ASM 1
st
order (BDL1 in ICU & BDL2 in TIP)
19 292.09 144 0.000 2.03 0.923 0.908 0.062 0.053-0.071 0.056
S10: Supportive 2
nd
order; GDP, RSP, TIP, ICU,
CNP, ASM 1
st
order (BDL1 in ICU)
19 300.51 145 0.000 2.07 0.919 0.904 0.063 0.054-0.072 0.060
S11: Supportive 2
nd
order; GDP, RSP, TIP, ICU,
CNP, ASM 1
st
order (BDL2 in TIP)
19 310.86 145 0.000 2.14 0.913 0.898 0.065 0.056-0.074 0.061
S12: Supportive 2
nd
order; GDP, RSP, TIP, ICU,
CNP, ASM 1
st
order (no joint loading)
19 315.35 146 0.000 2.16 0.911 0.896 0.066 0.057-0.074 0.061
S13: GDP, RSP, TIP, ICU, CNP; all separate
factors* ( BDL2 in TIP & BDL1 in ICU)
17 675.56 119 0.000 5.68 0.673 0.627 0.131 0.123-0.140 0.306
Note: Grayed field indicates best fit among comparable models.
*Factor ASM not included in Model S13 because the model is not identified when only two items load onto one first order factor.
Table 11: Chi-square Difference Test
Models Compared Loading Tested ∆χ
2
∆df p value
Model S12 vs. Model S10 BDL1 onto ICU 14.84 1 0.000***
Model S12 vs. Model S11 BDL2 onto TIP 4.49 1 0.034*
PARENTAL MEDIATION OF TECHNOLOGY USE 160
Figure 5: Supportive Mediation Measurement Model

PARENTAL MEDIATION OF TECHNOLOGY USE 161

Table 12: Interviewed Parents Characteristics
Pseudonym
Parent
Gender
Age
(years)
Child’s
Age
(years)
Tech
Knowledge
Tech
Usage
Perceived
Child
Expertise
Parental
Role
Supportive
Self-
efficacy
Restrictive
Mediation
Monitoring
Supportive
Mediation
Carol Female 33 10 98
th
% 27
th
% 76
th
% 74
th
% 85
th
% 37
th
% 89
th
% 43
th
%
Hanna Female 44 15 98
th
% 82
th
% 99
th
% 63
th
% 30
th
% 2
nd
% 31
th
% 8
th
%
Marcy Female 36 17 71
th
% 61
th
% 77
th
% 57
th
% 75
th
% 6
th
% 40
th
% 57
th
%
Mary Female 45 10 37
th
% 41
th
% 60
th
% 70
th
% 17
th
% 69
th
% 29
th
% 16
th
%
Megan Female 30 12 46
th
% 82
th
% 63
th
% 74
th
% 47
th
% 78
th
% 100
th
% 98
th
%
Randy Male 36 15 94
th
% 82
th
% 63
th
% 63
th
% 38
th
% 48
th
% 64
th
% 35
th
%
Sandy Female 46 13 80
th
% 91
th
% 94
th
% 74
th
% 90
th
% 19
th
% 91
th
% 91
st
%
Arnold Male 52 13 28
th
% 10
th
% 17
th
% 1
st
% 2
nd
% 17
th
% 41
th
% 16
th
%
Note: Statistics reported are in percentiles unless indicated.
PARENTAL MEDIATION OF TECHNOLOGY USE 162

Table 13: Measurement Invariance Omnibus Test of Covariance Matrices Equality (Across Survey Language Groups)
Models
# of
items
χ
2
df
χ
2
p-value
χ
2
/df CFI TLI RMSEA
RMSEA
90%CI
WRMR SRMR
Restrictive Mediation: RTM 11 72.74 55 0.000 1.32 0.993 0.987 0.049 0.000-0.076 1.027 -
Monitoring: MNT + TCM 10 104.86 45 0.000 2.33 0.996 0.992 0.098 0.074-0.123 1.199 -
Supportive Mediation 18 266.79 190 0.000 1.40 0.963 0.933 0.055 0.041-0.067 - 1.132
Note: WLSMV estimator and WRMR residual fit index were used for Restrictive Mediation and Monitoring models due to presence of ordinal data. ML estimator and
SRMR residual fit index was used for Supportive Mediation model.
Table 14: Measurement Invariance Analysis of Configural, Metric, Scalar, and Strict Invariance
(Across Survey Language Groups)
Construct Model χ
2
(Δ χ
2
)*
Df
(Δ Df)*
p(Δ p) CFI( ΔCFI)
Restrictive Mediation: RTM
(11 items)

Configural 151.34 88 <0.001 0.955
Metric (1.81) (11) (0.523) (0.006)
Scalar (39.44) (2) (0.208) (0.027)
Monitoring: MNT & TCM
(10 items)

Configural 184.63 64 <0.001 0.918
Metric (17.4) (9) (0.085) (0.006)
Scalar (28.27) (6) (0.001) (0.038)
Supportive Mediation
(19 items)

Configural 452.87 270 <0.001 0.911
Metric (17.93) (15) (0.444) (0.001)
Scalar (48.09) (13) (0.000) (0.017)
Note: Grayed fields indicate results supporting measurement invariance of at the level labeled.

PARENTAL MEDIATION OF TECHNOLOGY USE 163
Figure 6: Fisher Information and Standard Error Plot, Restrictive Mediation Scale

PARENTAL MEDIATION OF TECHNOLOGY USE 164
Figure 7: Fisher Information and Standard Error Plot, Monitoring Scale

PARENTAL MEDIATION OF TECHNOLOGY USE 165
Figure 8: Fisher Information and Standard Error Plot, Supportive Mediation Scale

PARENTAL MEDIATION OF TECHNOLOGY USE 166
Figure 9: Fisher’s Information and Standard Error Plot, Technology Knowledge Measure

PARENTAL MEDIATION OF TECHNOLOGY USE 167

Table 15: Reliability Statistics of Measures
Measures Number of Items
α
(Empirical Reliability)
Supportive Mediation*

19 (0.93)
Restrictive Mediation*

11 (0.80)
Monitoring Mediation (TCM+MNT)

10 0.91
Supportive Self-Efficacy

7 0.91
Regulatory Self-Efficacy

6 0.91
Parent Role Construction

6 0.96
School Role Construction

6 0.96
Technical Knowledge*

10 (0.77)
Technology Usage

4 0.57
Perception of Child’s Technical
Expertise
5 0.92
*Empirical reliability statistics reported due to use of IRT-scaled scores
PARENTAL MEDIATION OF TECHNOLOGY USE 168
Table 16: Pearson’s Correlations

1. 2. 3. 4. 5. 6. 7. 8. 9. 10. 11. 12. 13. 14.
1. Supportive Mediation 1
2. Restrictive Mediation -0.04 1
3. Monitoring 0.47*** 0.13* 1
4. School role beliefs 0.24*** -0.13* 0.08 1
5. Parent role beliefs 0.35*** -0.08 0.22*** 0.65*** 1
6. Supportive Self-
Efficacy
0.43*** -0.05 0.39*** 0.28*** 0.51*** 1
7. Restrictive Self-
Efficacy
0.32*** 0.07 0.37*** 0.32*** 0.46*** 0.74*** 1
8. Parent Tech Usage 0.28*** -0.29*** 0.01 0.16** 0.16** 0.24*** 0.07 1
9. Parent Tech
Knowledge
0.13* -0.27*** 0.03 0.14* 0.17** 0.19** 0.05 0.35*** 1
10. Perception of Child’s
Expertise
0.30*** -0.39*** -0.02 0.28*** 0.27*** 0.26*** 0.10 0.43*** 0.11 1
11. English Proficiency 0.08 -0.29*** 0.01 0.06 0.08 0.20*** 0.10 0.43 0.40*** 0.09 1
12. Lunch Status -0.02 -0.15* -0.10 0.03 0.10 0.02 -0.07 0.27*** 0.37*** 0.01 0.43*** 1
13. Child’s Age -0.04 -0.33*** -0.22*** -0.01 -0.09 -0.16** -0.17** 0.02 -0.03 0.23*** -0.08 0.02 1
14. Parent’s Education 0.10 -0.17** -0.09 0.15* 0.14* 0.18 0.04 0.36*** 0.45*** 0.13* 0.49*** 0.57*** -0.07 1
* = p<0.05, ** = p<0.01, *** = p<0.001

PARENTAL MEDIATION OF TECHNOLOGY USE 169

Table 17: Direct Effects Only Model Parameters (Standardized Regression Coefficients)
IV: Restrictive
Mediation
Monitoring Supportive
Mediation
Contextual Variables: Knowledge
-0.17**
(0.06)
0.04
(0.07)
0.02
(0.06)
Usage
-0.04
(0.06)
0.03
(0.07)
0.22***
(0.04)
Child Expertise
-0.28***
(0.04)
-0.11
(0.04)
0.02
(0.04)
Motivational Variables: Parental Role
0.01
(0.07)
0.09
(0.08)
0.15*
(0.08)
Support SE
0.05
(0.01)
0.30**
(0.02)
0.28**
(0.01)
Restrict SE
0.06
(0.01)
0.12
(0.01)
0.08
(0.01)
Control Variables: School Role Perception
-0.07
(0.07)
-0.06
(0.08)
0.01
(0.08)

Child Age
-0.27***
(0.01)
-0.13*
(0.02)
-0.05
(0.02)

Language Proficiency
-0.24***
(0.03)
-0.01
(0.03)
-0.07
(0.03)

Parent Education Level
0.06
(0.04)
-0.15*
(0.04)
0.04
(0.04)

Lunch Status (Free, Reduced, Full Price)
0.01
(0.07)
-0.04
(0.08)
-0.09
(0.07)
Intercept 1.86***
(0.37)
-1.02*
(0.42)
2.90***
(0.40)
Standardized regression coefficient (standard error)
* <0.05; ** p<0.01; ***p<0.001
PARENTAL MEDIATION OF TECHNOLOGY USE 170

Table 18: Path Analysis Effect Decomposition, Restrictive Mediation Model
Effects
Parameter
Estimate
Standard
Error
Z value p
Standardized
Estimate
Direct Effects: Knowledge à RTM -0.182** 0.059 -3.076 0.002 -0.180***

Usage à RTM -0.042 0.062 -0.673 0.501 -0.041

Child Expertise à RTM -0.160*** 0.038 -4.237 0.000 -0.265***

Parental Role à RTM 0.022 0.071 0.310 0.757 0.023

Support SE à RTM 0.001 0.014 0.084 0.933 0.007

Restrict SE à RTM 0.021 0.013 1.574 0.115 0.121
Indirect Effects: Knowledge à Parental Role à RTM 0.003 0.011 0.308 0.758 0.003

Usage à Parental Role à RTM -0.000 0.002 -0.164 0.870 -0.000

Child Expertise à Parental Role à RTM 0.004 0.014 0.309 0.757 0.007

Knowledge à Support SE à RTM 0.001 0.012 0.084 0.933 0.001

Usage à Support SE à RTM 0.001 0.007 0.084 0.933 0.001

Child Expertise à Support SE à RTM 0.001 0.014 0.084 0.933 0.002

Knowledge à Restrict SE à RTM 0.006 0.008 0.660 0.509 0.006

Usage à Restrict SE à RTM -0.003 0.009 -0.407 0.684 -0.003

Child Expertise à Restrict SE à RTM 0.015 0.011 1.388 0.165 0.025
Control Variables: School Role Perception -0.064 0.069 -0.932 0.351 -0.062

Child Age -0.074*** 0.015 -5.009 0.000 -0.270***

English Proficiency -0.116*** 0.030 -3.826 0.000 -0.238***

Parent Education Level 0.027 0.039 0.706 0.480 0.049

Lunch Status (Free, Reduced, Full Price) 0.019 0.067 0.283 0.777 0.018
Ratio of Restrictive Mediation Variance Explained (R-square statistic) = 0.313
* = p<0.05, ** = p<0.01, *** = p<0.001
PARENTAL MEDIATION OF TECHNOLOGY USE 171
Figure 10: Path Model with Restrictive Mediation as IV (Standardized Loadings)

PARENTAL MEDIATION OF TECHNOLOGY USE 172

Table 19: Path Analysis Effect Decomposition, Monitoring Model
Effects
Parameter
Estimate
Standard
Error
Z value p
Standardized
Estimate
% of Effect
Mediated
Direct Effects: Knowledge à MNT 0.040 0.067 0.587 0.557 0.038

Usage à MNT 0.038 0.071 0.530 0.596 0.037

Child Expertise à MNT -0.077 0.044 -1.750 0.080 -0.124

Parental Role à MNT 0.109 0.083 1.324 0.185 0.108

Support SE à MNT 0.052** 0.015 3.375 0.001 0.305**

Restrict SE à MNT 0.026 0.015 1.714 0.087 0.146

Indirect Effects: Knowledge à Parental Role à MNT 0.016 0.014 1.160 0.246 0.016
-

Usage à Parental Role à MNT -0.002 0.007 -0.230 0.818 -0.002
-

Child Expertise à Parental Role à MNT 0.022 0.017 1.283 0.199 0.035
-

Knowledge à Support SE à MNT 0.047* 0.023 1.993 0.046 0.045*
100%

Usage à Support SE à MNT 0.025 0.022 1.170 0.242 0.025
-

Child Expertise à Support SE à MNT 0.054** 0.020 2.699 0.007 0.087**
100%

Knowledge à Restrict SE à MNT 0.007 0.010 0.687 0.492 0.007
-

Usage à Restrict SE à MNT -0.005 0.011 -0.452 0.651 -0.005
-

Child Expertise à Restrict SE à MNT 0.019 0.013 1.509 0.131 0.031
-
Control Variables: School Role Perception -0.060 0.080 -0.757 0.449 -0.057

Child Age -0.038* 0.017 -2.228 0.026 -0.134*

Language Proficiency -0.004 0.035 -0.105 0.916 -0.007

Parent Education Level -0.091* 0.044 -2.098 0.036 -0.159*

Lunch Price (Free, Reduced, Full) -0.048 0.076 -0.630 0.529 -0.045

Ratio of Monitoring Variance Explained (R-square Statistic) = 0.155

* = p<0.05, ** = p<0.01, *** = p<0.001
PARENTAL MEDIATION OF TECHNOLOGY USE 173
Figure 11: Path Model with Monitoring as IV (Standardized Loadings)

PARENTAL MEDIATION OF TECHNOLOGY USE 174

Table 20: Path Analysis Effect Decomposition, Supportive Mediation Model
Effects
Parameter
Estimate
Standard
Error
Z value p
Standardized
Estimate
% of Effect
Mediated
Direct Effects: Knowledge à SPT 0.026 0.065 0.395 0.693 0.024

Usage à SPT 0.232** 0.068 3.404 0.001 0.221**

Child Expertise à SPT 0.028 0.041 0.687 0.492 0.047

Parental Role à SPT 0.165* 0.081 2.053 0.040 0.161*

Support SE à SPT 0.048** 0.015 3.192 0.001 0.279**

Restrict SE à SPT 0.015 0.015 1.054 0.292 0.086

Indirect Effects: Knowledge à Parental Role à SPT 0.025 0.016 1.578 0.115 0.024
-

Usage à Parental Role à SPT -0.003 0.011 -0.258 0.797 -0.003
-

Child Expertise à Parental Role à SPT 0.035* 0.018 1.980 0.048 0.057*
100%

Knowledge à Support SE à SPT 0.044* 0.022 1.968 0.049 0.042*
100%

Usage à Support SE à SPT 0.023 0.020 1.133 0.257 0.022
-

Child Expertise à Support SE à SPT 0.052** 0.020 2.676 0.007 0.087**
100%

Knowledge à Restrict SE à SPT 0.004 0.007 0.624 0.533 0.004
-

Usage à Restrict SE à SPT -0.004 0.007 -0.528 0.597 -0.004
-

Child Expertise à Restrict SE à SPT 0.013 0.013 1.014 0.311 0.021
-
Control Variables: School Role Perception 0.001 0.078 0.011 0.991 0.001

Child Age -0.016 0.016 -0.984 0.325 -0.055

Language Proficiency Perception -0.041 0.033 -1.233 0.217 -0.080

Parent Education Level 0.023 0.043 0.535 0.593 0.039

Lunch Status (Free, Reduced, Full Price) -0.096 0.073 -1.321 0.187 -0.088

Ratio of Supportive Mediation Variance Explained (R-square Statistic) = 0.242

* = p<0.05, ** = p<0.01, *** = p<0.001

PARENTAL MEDIATION OF TECHNOLOGY USE 175
Figure 12: Path Model with Supportive Mediation as IV (Standardized Loadings)

PARENTAL MEDIATION OF TECHNOLOGY USE 176
Appendix A
Domains of Digital Literacy

Literacy Domains Description Sources
Computer/ICT
Literacy
• Technical knowledge related to basic
operations of information and
communication technologies.
• Ability to apply technical skills to produce
and receive communication effectively
across different domains, including for
work, school, personal, and civic purposes
• Ability to evaluate how ICT fits or could be
adapted for a specific purpose
• the capacity and confidence to learn how to
complete tasks using an unfamiliar
technology

Voogt & Roblin, 2010
OECD, 2009
Cassidy & Eachus, 2002
Information/media
Literacy
• ability to “read” information and media
sources critically in order to extract salient
knowledge, to understand intended
meanings and avoid being misled, as well as
to use this information for real world tasks
• ability to effectively produce media content,
including being able to judge the most
appropriate medium for communicating a
specific message

Lankshear & Knobel, 2011
Crockett, Jukes, & Churches,
2011
Digital/New media
Literacy
• Includes other technical literacy domains as
well as ethos-related values and dispositions
• The “epistemic” understanding of the nature
of the information society as well as
particular attitudes and dispositions towards
technology use for constructive social
actions and reflective thinking on one’s own
actions
• An awareness of the push and pull of
information within the digital realm and its
ability for providing learning opportunities
as well as an understanding of how to
independently take advantage of these
opportunities in appropriate ways.
• The disposition to use the capabilities of
ICTs to become involved in the community,
to foster sound judgment and negotiation,
and to assist in civic participation that gives
back to society.

Lankshear & Knobel, 2011
Martin, 2008
Bawden, 2008
Jenkins, 2009
Bers, 2010
Bers, Doyle-Lynch, & Chau,
2012
PARENTAL MEDIATION OF TECHNOLOGY USE 177
Twenty-first Century
Literacy/Skills
• Subsumes new literacies previously
mentioned and orients them towards the
educational preparation of students for
successful functioning in the 21st century.
• skills are embodied within educational
frameworks as the goals of formal
schooling, including such frameworks as the
Partnerships for 21st century skills (P21),
the National Educational Technology
Standards (NETS), and the National
Assessment of Educational Progress
(NAEP)
• Included additional aspects not directly
related to technology, such as the capacity
for creativity and innovation in the P21 and
NETS frameworks as well as the ability to
act autonomously in forming and carrying
out life plans in the NAEP framework (For
complete review of 21
st
century skills across
different frameworks, please refer to Dede,
2010, and Voogt & Roblin, 2010).

Voogt & Roblin, 2010
Dede, 2010
Kay, 2010

PARENTAL MEDIATION OF TECHNOLOGY USE 178
Appendix B
Definitions of Active Co-use and Related Constructs

Sources Terms Used Dimensions
Eastin et al., 2006 Interpretive
mediation
Parents discuss/evaluate online content
with child
Coviewing
mediation
The extent to which a parent experiences
online content with their child
Livingstone & Helsper,
2008
Daud, 2014
Active co-use Rules about time spent online
Parent stays nearby when child is online
Parent watches screen when child online
Parent helps when child uses the Internet
Parent talks to child about Internet use
Parent sits with child when online
Child not allowed to give out personal
info
Child not allowed to buy anything online
Child not allowed to fill out online
forms/quizzes
Kirwil 2009 Social co-use Parents sit with child when s/he is on the
internet
Haddon 2012
Livingstone et al., 2012
Pasquier et al., 2012
Sonck et al., 2015

Active content
mediation
Parents talk to child about what s/he does
on the internet
Parents stay nearby when child uses the
internet
Parents encourage child to explore and
learn things on the internet by
him/herself
Parents sit with child while s/he uses the
internet
Parents do shared activities with child on
the internet
Active safety
mediation
Parents explain why some websites are
good or bad
Parents help child when something is
difficult to do or find on the internet
Parents suggest ways to use the internet
safely
Parents suggest ways to behave towards
other people online
Parents talk to child about what to do if
something on the internet bothers
him/her
PARENTAL MEDIATION OF TECHNOLOGY USE 179
Parents help child when s/he encounter
something bothersome online
Gentile et al. 2012 Co-use Parents watch TV with child
Parents play computer and video games
with child
Active
mediation
Parents talk to child about content on TV
and movies
Parents talk to child about content on
video games
Valkenburg et al., 2013 Active
mediation
Parents explain media content
Parents convey their opinions about the
content of media
Eklund & Bergmark, 2013 Active
mediation
Parents talk about computer gaming
Parents talk about internet use/experiences
Parents play computer and console games
with child
Parents on the internet with child
Schaan & Melzer, 2015
(parents’ mediation of TV
viewing)
Patronizing co-
use
Parents explain what happens on TV
Parents pay attention to what the child is
watching
Parents watch TV together with child at
child’s suggestion
Parents explain rules of TV usage
Parents are present in the same room with
the child as s/he watches TV
Active
emotional
co-use
Parents give advice while watching TV
Parents describes what happens on TV
Parents evaluate what might happen next
on TV
Parents watches TV together with child at
parents’ suggestion
Parents tell child that films do not reflect
reality
Parents evaluate the feelings of the
protagonist
Parents encourage TV watching
Parents point to good things on TV
Clark, 2011
Clark, 2013
Participatory
learning
Parents are listeners and co-creators who
invite child to serve as a leader and a
guide into experiences with ICTs
Parents provide prompts to continue
conversations, and aim to learn from
as well as with their children.

PARENTAL MEDIATION OF TECHNOLOGY USE 180
Appendix C
Positive Uses of ICT
Usage Domains Dimensions (adapted from Daud et al., 2014)
Information Looking for information regarding education
Doing schoolwork
Looking for current news
Visiting websites to get information about hobby
Visiting websites to get information about health
Looking for information on computers
Visiting school websites
Visiting websites about protecting the environment
Visiting government websites
Looking at other people’s personal homepages
Looking for products/shops
Visiting websites about children’s rights
Visiting websites about charity organizations
Communication Using Facebook
Using Instant Messaging (IM)
Sending e-mails or text messages to a site
Sending/receiving e-mails
Using Twitter
Using chat-rooms
Using Skype
Entertainment Downloading music
Playing educational games
Downloading clips
Looking for cinema/theatre/concert listings
Downloading films
Downloading TV shows
Participation Doing a quiz
Voting for something/someone
Linking useful information
Participating in discussion forums
Collaborating with someone to produce content for YT
Creativity Planning a trip
Creating arts
Trying to set up a webpage
Creating animations
Uploading and sharing own content to YT
Expression Uploading photos or drawings
Offering advice to others
Writing updates stories on Facebook
Writing updates stories on Twitter
Writing blog posts
PARENTAL MEDIATION OF TECHNOLOGY USE 181
Appendix D
Supportive Technology Mediation

Name Description Example in High SES
Context
Example in
Low/Mixed SES
Context
Source(s) Survey Item(s)
Created
CONNECTEDNESS
Collaborative
Co-use (CCU)
Parents and child use
technology together
to accomplish a
goal.
Parent and child work
together on a computer
animation project
(Barron et al., 2009)
Parent and child mix
music together
(Takeuchi, 2012).

Parent and child play
computer games
together (Nikken &
Jansz, 2011).
Barron et al., 2009;
Takeuchi, 2012;
Clark, 2013; Nikken
& Jansz, 2011
My child and I
do something
together using
technology.

I collaborate
with my child to
achieve
something using
technology
Participatory
Learning Co-use
(PCU)
Parents and child
learn something new
together through
and/or facilitated by
a technology
medium.
- Parent and child learn
something new together
by researching
information online or
participating in online
discussion forums
(Clark, 2011).
Clark, 2011. My child and I
learn something
new together
using
technology.
Promotion of
ICT as Means of
Family
Connectedness
(PFC)
Parents promote
usage of technology
as means for family
connection
- Parent uses mobile
phone to keep in
connection with child
throughout the day
(Clark, 2013).

Clark, 2013 I encourage my
child to use
technology to
connect with
people in our
family.
PARENTAL MEDIATION OF TECHNOLOGY USE 182
Parent uses mobile
phone with child to
connect with distant
relatives (Clark, 2013).
Promotion of
ICT as Means of
Community
Connectedness
(PCC)
Parents promote
usage of technology
as means for
community
connection
- Parent encourages child
to use social networking
site to connect with
friends from Native
American youth
program (Clark, 2013).
Clark, 2013 I encourage my
child to use
technology to
connect with
other people in
our community.
KNOWLEDGE EXPANSION
Brokering
Digital Learning
(BDL)
Parents find new
ways for child to
learn new
operational
knowledge.
Parent sign up for the
child to attend a
computer programming
class (Barron et al.,
2009).
Parent petitioned the
school to allow child to
take a computer
programming class
although they do not
have access to a home
computer (Clark, 2013).
Barron et al., 2009;
Barron, 2004; Clark,
2013
I find ways for
my child to learn
how to do new
things with
technology.

I look for
technology
classes my child
could take.
Encouragement
– Expansion of
Interest (EEI)
Parents provide
verbal
encouragement for
child to use
technological
resources and/or
capabilities to
expand on personal
interests
- Parent encourages child
to look up information
about content (e.g. cars,
game design) they are
interested in online
(Clark, 2013)
Clark, 2013 I encourage my
child to use
online resources
to increase their
knowledge about
something
they’re interested
in.

PARENTAL MEDIATION OF TECHNOLOGY USE 183
I encourage my
child to create
something
they’re interested
in using
technology.
Encouragement
– Expansion of
Operational
Skills (EES)
Parents provide
verbal
encouragement for
child to expand their
technical knowledge
Parent encourage child to
learn a new programming
language (Barron et al.,
2009).

Parent encourage child to
take a computer
programming class at
school (Barron, 2004).
- Barron et al., 2009;
Barron, 2004
I encourage my
child to learn
more about how
to use
technology.

I encourage my
child to take a
technology class.
RECRUITMENT OF TECHNOLOGY HELP
Recruitment of
Child’s
Technical
Services (RTS)
Parents ask the child
to help perform
technology-related
tasks.
Parent ask child to update
the software on the
parent’s computer and
troubleshoot when the
computer crashes or fails
to print (Barron et al.,
2009).
- Barron et al., 2009. I ask my child to
help perform
technology-
related tasks
around the
house.

I ask my child to
help fix
technology when
it does not work.
Recruitment of
Child’s
Technical
Guidance (RTG)
Parents ask the child
to teach an aspect of
technology use to
the parents
themselves and/or
Parent asked child to
teach him how to use
Flash (Barron et al.,
2009).
Parent ask child to teach
her how to play a
computer game
(Takeuchi, 2012).

Barron et al., 2009;
Clark, 2013;
Takeuchi, 2012.
I ask my child to
teach me how to
do something
using
technology.

PARENTAL MEDIATION OF TECHNOLOGY USE 184
other family
members.
Parent asks older child
to teach younger child
how to use a computer
and navigate the internet
(Clark, 2013).
I ask my child to
help another
family member
understand how
to use
technology.
PROVISION OF GUIDANCE
Explicit
Operational
Instruction (EOI)
Parent teaches child
how to do something
using technology.
Parent taught child how
to use Photoshop in order
to include illustrations on
an assignment from
school (Barron et al.,
2009).
- Barron et al., 2009

I teach my child
how to do
something new
using
technology.
Instilling
Cultural Roles of
Technology
(ICR)
Parents show child
how to use and
integrate technology
with other aspects of
their lives.
Parent show child how to
use technology to help
keep track of assignment
due dates (Clark, 2013).
Parent told child that the
internet is a resource
where they can learn
something new that can
help expand their
employment
opportunities (Clark,
2013).

Parent purchased the
game software Hello
Kitty Daily, which helps
the child remembers
phone numbers, reminds
herself when home
assignments are due,
and budget money for
personal purchases
(Takeuchi, 2012).
Clark, 2013
Plowman et al., 2010
I show my child
how technology
can be used in
everyday life.

I talk to my child
about how
technology can
improve his/her
life.
PARENTAL MEDIATION OF TECHNOLOGY USE 185
Active Content
Mediation
(ACM)
Parents guide child
to view appropriate
or preferred digital
media content.
- Parent talk to child
about their internet
activities (Livingstone,
2011).

Parent talk with child
about internet content
that engages both of
their interests (Clark,
2013).
Livingstone, 2011;
Clark, 2013
I give my child
ideas about
what’s good to
read or view
online.

I talk to my child
about online
content that we
both are
interested in.
Active Safety
Mediation
(ASM)
Parents discuss/teach
child about how to
use technology
safely.
Parents point out to child
to be vigilant about
whom they allow to
access their social
network profiles (Clark,
2013).
Parents talk to child
about how to use the
internet safely
(Livingstone & Helsper,
2008).
Clark, 2013;
Livingstone &
Helsper, 2008; Sonck
et al., 2013
I talk to my child
about how to be
safe when
interacting with
other people
using
technology.

I talk to my child
about what s/he
would do if
something on the
internet bothered
her/him
RESOURCE PROVISION
Resource
Provision (RSP)
Parents provide
digital resources and
peripheral tools
(books, building
materials) the child
needs for school or
to pursue other
Parent purchased
Macromedia Flash
software for child
(Barron et al., 2009).

Parent arranged for child
to use computer at an
uncle’s house to
complete school
assignment (Clark,
2013).
Barron et al., 2009
Clark, 2013
Takeuchi, 2012
Plowman et al., 2010
I give my child
the technology
tools he/she
needs.

PARENTAL MEDIATION OF TECHNOLOGY USE 186
technology-related
interests.
Parent lend a book on
computer programming
to child (Barron et al.,
2009).
I let my child
borrow my
technology
device.

I find ways for
my child to
access the
technology tool
he/she needs

Regulatory Technology Mediation
Name Description Source(s) Survey Item(s)
Restrictive
Mediation
(RTM)
Parents impose rules
regarding the child’s
communicative activities or
time spent on ICT platforms
Livingstone &
Helsper, 2008;
Sonck et al., 2013;
Daud et al., 2014
1.) I restrict my child from using instant messaging
2.) I restrict my child from downloading music or films on
the internet
3.) I restrict my child from using e-mail
4.) I restrict my child from playing online games
5.) I restrict my child from watching video clips on the
internet
6.) I restrict my child from using online chat-rooms
7.) I restrict my child from having his/her own social
networking profile
8.) I restrict my child from giving out personal information
to others on the internet
9.) I restrict my child from uploading photos, videos, or
music to share with others
10.) I set up rules about the amount of time my child can
spend using technology.
11.) I encourage my child to do other activities instead of
using technology.
PARENTAL MEDIATION OF TECHNOLOGY USE 187
Technical
Mediation
(TCM)
Parents restrict access to
certain activities using
specialized software
programs.
Livingstone &
Helsper, 2008;
Sonck et al., 2013;
Daud et al., 2014
1.) I use parental control or other means of blocking my
child’s content access
2.) I use parental control or other means of keeping track
of my child’s online activities
3.) I use a software to limit the time my child spends with
technology
4.) I use a software to prevent spam, junk mail, or viruses
in my child’s email
Monitoring
(MNT)
Parents check up on child’s
ICT activities.
Livingstone &
Helsper, 2008;
Sonck et al., 2013;
Daud et al., 2014
1.) I check the websites my child visited after s/he is done.
2.) I check messages in my child’s email or instant
messaging account
3.) I check my child’s profile on social network websites
(like Facebook) or online community
4.) I check which friends or contacts my child has added to
his/her social networking profile or instant messaging
service
5.) I remain close by to monitor my child when s/he uses
technology.
6.) I make sure my child uses technology in a public space
at home (living room, dining room, etc.).
PARENTAL MEDIATION OF TECHNOLOGY USE 188
Appendix E
Survey Items
SUPPORTIVE MEDIATION BEHAVIORS

Promotion of Connectedness
Please check how often you do this with/for your child.
Never Rarely A few times Often Very often
CCU1: My child and I do something together
using technology.

CCU2: I collaborate with my child to achieve
something using technology

PCU1: My child and I learn something new
together using technology.

PFC1: I encourage my child to use
technology to connect with people in our
family.

PCC1: I encourage my child to use
technology to connect with other people in
our community.

Knowledge Expansion
Please check how often you do this with/for your child.
Never Rarely A few times Often Very often
BDL1: I find ways for my child to learn how
to do new things with technology.

BDL2: I look for technology classes my
child could take.

EEI1: I encourage my child to use online
resources to increase their knowledge about
something they’re interested in

EEI2: I encourage my child to create
something they’re interested in using
technology.

EES1: I encourage my child to learn more
about how to use technology.

EES2: I encourage my child to take a
technology class.

PARENTAL MEDIATION OF TECHNOLOGY USE 189
Provision of Guidance
Please check how often you do this with/for your child.
Never Rarely A few times Often Very often
ICR1: I show my child how technology can
be used in everyday life.

ICR2: I talk to my child about how
technology can improve his/her life.

ACM1: I give my child ideas about what’s
good to read or view online.

ACM2: I talk to my child about online
content that we both are interested in.

ASM1: I talk to my child about how to be
safe when interacting with others people
using technology.

ASM2: I talk to my child about what s/he
would do if something on the internet
bothered her/him

EOI1: I teach my child how to do something
new using technology.

Recruitment of Technology Help
Please check how often you do this with/for your child.
Never Rarely A few times Often Very often
RTS1: I ask my child to help perform
technology-related tasks around the house.

RTS2: I ask my child to help fix something
related to technology when it does not work.

RTG1: I ask my child to show me how to do
something using technology.

RTG2: I ask my child to help another family
member understand how to use technology.

Resource Provision
Please check how often you do this with/for your child.
Never Rarely A few times Often Very often
RSP1: I give my child the technology tools
he/she needs.

RSP2: I let my child borrow my technology
device.

RSP3: I find ways for my child to access the
technology tool he/she needs

PARENTAL MEDIATION OF TECHNOLOGY USE 190
REGULATORY MEDIATION BEHAVIORS
(adapted from Livingstone et al., 2012, Daud, 2014, and Sonck et al., 2013)

Please identify whether you have done the following activities with your adolescent child (please
pick one child for the entire survey if you have more than one adolescent children)
Restrictive Mediation
YES NO
I restrict my child from using instant
messaging

I restrict my child from downloading music
or films on the internet

I restrict my child from using e-mail
I restrict my child from playing online games
I restrict my child from watching video clips
on the internet

I restrict my child from using online chat-
rooms

I restrict my child from having his/her own
social networking profile

I restrict my child from giving out personal
information to others on the internet

I restrict my child from uploading photos,
videos, or music to share with others

I set up rules about the amount of time my
child can spend using technology.

I encourage my child to do other activities
instead of using technology
19
.
Please select how often

Never Rarely A few times Often Very often

19
On the actual survey, this item was integrated with monitoring items for formatting purposes.
PARENTAL MEDIATION OF TECHNOLOGY USE 191
Technical Mediation
YES NO
I use parental control or other means of
blocking my child’s content access

I use parental control or other means of
keeping track of my child’s online activities

I use a software to limit the time my child
spends with technology

I use a software to prevent spam, junk mail,
or viruses in my child’s email

Monitoring
Please select how often you do this with/for your child.
Never Rarely A few times Often Very often
I check the websites my child visited after
s/he is done.

I check messages in my child’s email or
instant messaging account

I check my child’s profile on social network
websites (like Facebook) or online
community

I check which friends or contacts my child
has added to his/her social networking profile
or instant messaging service

I remain close by to monitor my child when
s/he uses technology.

I make sure my child uses technology in a
public space at home (living room, dining
room, etc.).

PARENTAL MEDIATION OF TECHNOLOGY USE 192
SELF-EFFICACY FOR TECHNOLOGY MEDIATION
(adapted from Bandura, 2006 and Lee & Tsai, 2010)

The following statements are about your interactions with your adolescent child and their
technology usage (not including watching TV). Please read each statement carefully and rate
how much you agree or disagree.
Regulatory Self-Efficacy
I am confident I can set appropriate rules for my child regarding his/her technology usage.
strongly disagree disagree neither agree agree strongly agree
nor disagree
1 2 3 4 5

I think I know what types of online activities I should restrict my child from doing.
strongly disagree disagree neither agree agree strongly agree
nor disagree
1 2 3 4 5

I am certain I can check my child’s activities on a technology device after his/her use.
strongly disagree disagree neither agree agree strongly agree
nor disagree
1 2 3 4 5

I am able to use parental controls to prevent my child from encountering inappropriate contents
on a technology device.

strongly disagree disagree neither agree agree strongly agree
nor disagree
1 2 3 4 5

I am confident I can monitor what my child is doing when s/he is using technology.

strongly disagree disagree neither agree agree strongly agree
nor disagree
1 2 3 4 5

I am certain I can limit how much time my child spends using technology.

strongly disagree disagree neither agree agree strongly agree
nor disagree
1 2 3 4 5

PARENTAL MEDIATION OF TECHNOLOGY USE 193
Supportive Self-Efficacy

I am able to help my child with his/her technology usage.
strongly disagree disagree neither agree agree strongly agree
nor disagree
1 2 3 4 5

I know I can encourage my child to learn new things about how to use technology.

strongly disagree disagree neither agree agree strongly agree
nor disagree
1 2 3 4 5

I am certain I can find access to technology resources my child needs.

strongly disagree disagree neither agree agree strongly agree
nor disagree
1 2 3 4 5

I am confident I can help my child use technology in ways that will improve his/her life.

strongly disagree disagree neither agree agree strongly agree
nor disagree
1 2 3 4 5

I am able to encourage my child to use technology to learn about things they are interested in.

strongly disagree disagree neither agree agree strongly agree
nor disagree
1 2 3 4 5

I am confident I can encourage my child use technology to connect with others in our family and
community.

strongly disagree disagree neither agree agree strongly agree
nor disagree
1 2 3 4 5

PARENTAL MEDIATION OF TECHNOLOGY USE 194
ROLE CONSTRUCTION
(adapted from Sheldon, 2002)

The following statements are about your views on technology education. Please read each
statement carefully and rate how much you agree or disagree.
It is the parents’ responsibility to:
1) Teach children how to use technology
strongly disagree disagree neither agree agree strongly agree
nor disagree
1 2 3 4 5

2) Teach children how to be safe when using technology
strongly disagree disagree neither agree agree strongly agree
nor disagree
1 2 3 4 5

3) Motivate children to learn more about how to use new technology
strongly disagree disagree neither agree agree strongly agree
nor disagree
1 2 3 4 5

4) Encourage children to use technology in new and different ways
strongly disagree disagree neither agree agree strongly agree
nor disagree
1 2 3 4 5

5) Encourage children to use technology to explore and learn about their interests
strongly disagree disagree neither agree agree strongly agree
nor disagree
1 2 3 4 5

6) Provide the tools children need to use technology effectively
strongly disagree disagree neither agree agree strongly agree
nor disagree
1 2 3 4 5

PARENTAL MEDIATION OF TECHNOLOGY USE 195
It is the school’s responsibility to
1) Teach children how to use technology
strongly disagree disagree neither agree agree strongly agree
nor disagree
1 2 3 4 5

2) Teach children how to be safe when using technology
strongly disagree disagree neither agree agree strongly agree
nor disagree
1 2 3 4 5

3) Motivate children to learn more about how to use new technology
strongly disagree disagree neither agree agree strongly agree
nor disagree
1 2 3 4 5

4) Encourage children to use technology in new and different ways
strongly disagree disagree neither agree agree strongly agree
nor disagree
1 2 3 4 5

5) Encourage children to use technology to explore and learn about their interests
strongly disagree disagree neither agree agree strongly agree
nor disagree
1 2 3 4 5

6) Provide the tools children need to use technology effectively
strongly disagree disagree neither agree agree strongly agree
nor disagree
1 2 3 4 5

PARENTAL MEDIATION OF TECHNOLOGY USE 196
TECHNICAL KNOWLEDGE
(adapted from Hargittai, 2005
20
)

Please indicate whether you think each statement is TRUE or FALSE

1) In order to download something from the web, the user needs to create a new folder on
their device for the new content. (F)
2) Advance search allows the user to put in additional search information to narrow down
results. (T)
3) When viewing websites online, a user can use preference settings to change the font size
and font style of texts. (F)
4) Newsgroup is a convenient way to access news online published by major newspaper
companies such as the Wall Street Journal and the New York Times. (F)
5) PDF is a file format that allows documents to be distributed across computers. (T)
6) When looking through an email account, the user can use the refresh button to load new
incoming emails. (T)
7) MP3 is a file format used for transferring video content. (F)
8) HTML is the standard markup language used to create webpages. (T)
9) JPG is a file format used for transferring digital images. (T)
10) An internet user can only upload digital content to one person at a time. (F)

TECHNOLOGY USAGE
(adapted from Wartella, 2013)

Home usage
On an average weekday, how many hours do you spend using technology at home (not
including television)?
0-1 hours 1-3 hours 3-5 hours 5-7 hours more than 7 hours
On an average weekend day, how many hours do you spending using technology at
home? (not including watching television)?
0-1 hours 1-3 hours 3-5 hours 5-7 hours more than 7 hours

20
Self-report items with highest correlations to computer task performance were converted into knowledge
assessment items.
PARENTAL MEDIATION OF TECHNOLOGY USE 197
Work usage
On an average workday, how many hours do you spend using technology at work?
0-1 hours 1-3 hours 3-5 hours 5-7 hours more than 7 hours
How would you describe the nature of your work?
____ Requiring a lot of knowledge about technology
____ Requiring some knowledge about technology
____ Requiring a little knowledge about technology
____ Does not require knowledge about technology at all

PERCEPTION OF ENGLISH ABILITY

Please read each statement carefully and rate how much you agree or disagree.
1.) I am confident I can understand written English in most situations.
strongly disagree disagree neither agree agree strongly agree
nor disagree
1 2 3 4 5

2.) I am confident I can understand spoken English in most situations.
strongly disagree disagree neither agree agree strongly agree
nor disagree
1 2 3 4 5

3.) I am confident I can understand English written on online webpages.
strongly disagree disagree neither agree agree strongly agree
nor disagree
1 2 3 4 5

PARENTAL MEDIATION OF TECHNOLOGY USE 198
PERCEPTION OF CHILD’S DIGITAL EXPERTISE
(Created from ICT usage categories in Daud et al., 2014)

Please read each statement carefully and rate how much you agree or disagree.
1.) I think my child is an expert at communicating with others online.
strongly disagree disagree neither agree agree strongly agree
nor disagree
1 2 3 4 5

2.) I think my child is an expert at creating digital content.
strongly disagree disagree neither agree agree strongly agree
nor disagree
1 2 3 4 5

3.) I think that my child is an expert at getting information from online resources.
strongly disagree disagree neither agree agree strongly agree
nor disagree
1 2 3 4 5

4.) I think that my child is an expert at using technology to express themselves.
strongly disagree disagree neither agree agree strongly agree
nor disagree
1 2 3 4 5

5.) I think that my child is an expert at using technology for entertainment purposes.
strongly disagree disagree neither agree agree strongly agree
nor disagree
1 2 3 4 5

Please read the following question and select an appropriate response.
6.) On an average school day, how many hours does your child spend using technology at
home (not including television)?
0-1 hours 1-3 hours 3-5 hours 5-7 hours more than 7 hours
7.) On an average day off from school, how many hours does your child spending using
technology at home (not including television)?
0-1 hours 1-3 hours 3-5 hours 5-7 hours more than 7 hours 7

PARENTAL MEDIATION OF TECHNOLOGY USE 199
DEMOGRAPHIC QUESTIONS
1. What is the combined monthly income of everyone in your home?
______________________ (numeric response)

2. How many people live in your house?
______________________ (numeric response)

3. What is the highest level of education you’ve received?
□ Less than high school
□ Some high school
□ High school graduate
□ Some college education
□ College/vocational degree graduate
□ Some graduate education
□ Received graduate degree
4. What is your ethnicity? (Check all that apply)
□ American Indian/Alaskan Native
□ Native Hawaiian or Other Pacific Islander
□ Black/African American (Not of Hispanic origin)
□ Latino/Latin American (Including Cuban, Puerto Rican)
□ Mexican/Mexican American
□ Asian/Asian American
□ Middle Eastern/Middle Eastern American
□ Non-Latino White/Caucasian

5. What is your age?
______________________ (numeric response)

6. What is your chosen child’s age (the child about whom you answered the questions
above)?
______________________ (numeric response)

7. What is your gender?
□ Male
□ Female

8. What is your chosen child’s gender?
□ Male
□ Female

PARENTAL MEDIATION OF TECHNOLOGY USE 200
Appendix F
Confirmatory Factor and Path Models
Model S1

Model S2

In this model, ellipses (…) are used to
indicate that all supportive mediation
behavior items were included.
Item labels correspond to specific
behaviors detailed in Appendix D.
PARENTAL MEDIATION OF TECHNOLOGY USE 201
Model R1

Model R2

In this model, ellipses (…) are used to
indicate that all regulatory mediation
behavior items were included.
PARENTAL MEDIATION OF TECHNOLOGY USE 202
Model P1
21

21
Demographic factors including school role perception, child’s age, parents’ education level, and lunch status
were included in both path models as control variables (not shown).
PARENTAL MEDIATION OF TECHNOLOGY USE 203

Model P2

PARENTAL MEDIATION OF TECHNOLOGY USE 204
Appendix G
Interview Questions

(partially adapted from Barron et al., 2009)

1. Can you describe your involvement with your child’s technology usage?
2. Have you encouraged your child to use technology? What did you encourage them to do?
3. In what ways, if any, do you restrict your child’s technology usage?
a. Do you have rules about your child’s technology use? If so, what kind of rules do
you have?
4. What factors influence how you help your child with his/her technology usage?
5. How does your child’s school help with your child’s abilities to use technology? What do
you think about this?
a. In your opinion, what is the parents’ role in helping children learn how to use
technology?
b. In your opinion, what should be the relationship between the school and the
parent when it comes to children’s technology education?
6. What do you think about your abilities to help your child learn how to use technology?
a. Compared to other parents you know, what do you think about your abilities to
help your child use technology?

Abstract (if available)

Abstract Technology has become an indispensable tool for learning, with technology integration widespread in classrooms throughout the US. However, research in educational technology has consistently pointed to the disadvantaged position of low SES students in terms of how they use and benefit from technology. Researchers have attributed the differential benefits of technology access to low SES parents’ lack of effective technology mediation strategies at home. There is little empirical support for such claims, suggesting that research is needed. In addition, there is a need to investigate motivational and contextual factors that influence these mediation behaviors, above and beyond social and economic constraints. In response to this gap, the purpose of this study was to examine ways in which low income parents support adolescents’ digital literacy development and how these mediation choices are related to motivational (including self-efficacy for mediation and role beliefs) and contextual (including perception of the child’s technical expertise, as well as parents’ technology knowledge and usage) factors. Using factor analysis (n=291), results suggest a three-factor solution for technology mediation behaviors, including (1) restrictive mediation, (2) technical and non-technical monitoring, and (3) supportive mediation. Additionally, path analysis (n=291) shows that contextual factors such as parents’ technology knowledge are mediated by motivational factors in their predictive relationship on monitoring and supportive mediation behaviors, whereas these contextual factors only have direct relationships with restrictive mediation. Analyses of parent interview data (n=8) also illustrates that low SES parents in the sample are active mediators of technology, engaging in diverse mediation strategies. This study provides some evidence to counter current deficit-oriented narratives regarding the influence of home environments on adolescents’ digital literacy development in low SES populations.

Linked assets

University of Southern California Dissertations and Theses

Conceptually similar

PDF

Increasing parent involvement at the high school level using the gap analysis framework

PDF

Latino parental aspirations and literacy practices related to children's reading engagement

PDF

Math achievement and self-efficacy of linguistically and ethnically diverse high school students: their relationships with English reading and native language proficiency

PDF

Increase parental involvement to decrease the achievement gaps for ELL and low SES students in urban California public schools: an evaluation study

PDF

The link between maternal depression and adolescent daughters' risk behavior: the mediating and moderating role of family

PDF

Examining Latino parents' perspective on parent involvement at the secondary level: why should we care

PDF

Parenting children of affluence

PDF

Facilitating interest and out-of-school engagement in science in secondary school girls: Increasing the effectiveness of the teaching for transformative experience in science model through parent...

PDF

Eliminating the technology equity gap for students through parent support at home: an evaluation study

PDF

The parent voice: an exploratory study to understand Latino parent involvement in schools

PDF

A gap analysis of course directors’ effective implementation of technology-enriched course designs: An innovation study

PDF

The home environment and Latino preschoolers' emergent literacy skills

PDF

Mexican immigrant families with deaf and hard of hearing children: the importance of informal support structures

PDF

Innovative parental involvement: Utilizing information and communication technologies to increase parental involvement

PDF

Emirati parents of gifted students: a study of role construction and involvement

PDF

Social reproduction theory and parental involvement in Head Start: investigating the parent's perspective

PDF

The impact of parental involvement on student achievement

PDF

A needs assessment of an urban elementary school district's afterschool program

PDF

Home and school factors and their influence on students' academic goal orientation and motivation

PDF

The relationship of teachers' parenting styles and Asian American students' reading motivation

Asset Metadata

Creator Vongkulluksn, Wanchanit (author)

Core Title Parental mediation of adolescents' technology use at home

School Rossier School of Education

Degree Doctor of Philosophy

Degree Program Education

Publication Date 09/28/2016

Defense Date 09/01/2016

Publisher University of Southern California (original), University of Southern California. Libraries (digital)

Tag digital literacy,Motivation,OAI-PMH Harvest,parent involvement

Format application/pdf (imt)

Language English

Contributor Electronically uploaded by the author (provenance)

Advisor Rueda, Robert S. (committee chair), Schwartz, David (committee member), Sinatra, Gale M. (committee member)

Creator Email vongkull@usc.edu,vvongkull@gmail.com

Permanent Link (DOI) https://doi.org/10.25549/usctheses-c40-310034

Unique identifier UC11280319

Identifier etd-Vongkulluk-4833.pdf (filename),usctheses-c40-310034 (legacy record id)

Legacy Identifier etd-Vongkulluk-4833.pdf

Dmrecord 310034

Document Type Dissertation

Format application/pdf (imt)

Rights Vongkulluksn, Wanchanit

Type texts

Source University of Southern California (contributing entity), University of Southern California Dissertations and Theses (collection)

Access Conditions The author retains rights to his/her dissertation, thesis or other graduate work according to U.S. copyright law. Electronic access is being provided by the USC Libraries in agreement with the a...

Repository Name University of Southern California Digital Library

Repository Location USC Digital Library, University of Southern California, University Park Campus MC 2810, 3434 South Grand Avenue, 2nd Floor, Los Angeles, California 90089-2810, USA