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Technology integration and self-efficacy of in-service secondary teachers in an international school
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Technology integration and self-efficacy of in-service secondary teachers in an international school
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Content
Technology Integration and Self-Efficacy of In-Service Secondary Teachers in an
International School
by
Jennifer Kae Norman
Rossier School of Education
University of Southern California
A dissertation submitted to the faculty
in partial fulfillment of the requirements for the degree of
Doctor of Education
August 2022
© Copyright by Jennifer Kae Norman 2022
All Rights Reserved
The Committee for Jennifer Kae Norman certifies the approval of this Dissertation
Darline Robles
Helena Seli
Lawrence Picus, Committee Chair
Rossier School of Education
University of Southern California
2022
iv
Abstract
This study applies the social learning theory to examine the level of technology use in the
classrooms of secondary in-service teachers at an international school in Southeast Asia. This
study aimed to understand the relationships between teachers’ years of experience, level of
participation in technology professional development, technology self-efficacy, technological
pedagogical content knowledge (TPACK), and the possible influences these variables have on
integrating technology into instructional practices. Forty-three secondary teachers completed
three survey instruments that assessed their levels of TPACK, technology self-efficacy, and level
of technology use in classroom instructional practices: Concerns-Base Adoption Model (CBAM-
LoU), TPACK questionnaire, and Technology Integration Self-Efficacy scale (TISES).
Nonparametric bivariate analyses of Kruskal-Wallis and Spearman’s ranks of correlation were
used to identify relationships between the dependent variable technology integration and
independent variables years of teaching experience, level of professional development, TPACK,
and technology self-efficacy. Findings from this study showed no relationship between the
dependent and independent variables. The results did reveal a strong correlation between TPACK
and technology self-efficacy. This study begins the exploration to determine if the TPACK
framework is the right program for measuring levels of technology integration for this
international school in Southeast Asia. Professional development on pedagogy that centers on
student learning will provide teachers with meaningful learning opportunities both individually
and within the professional learning community framework to promote positive educational
equity in using technology in the classroom.
Keywords: Self-efficacy, TPACK, technology integration
v
Dedication
To my stepson David, a young Black man who calls me mom. I am honored and humbled to hold
that title.
vi
Acknowledgments
I would like to thank everyone who offered support and encouragement throughout my doctoral
journey. First, I need to thank my husband, Esteban, and my son, David, for their continued
support and love over the last 3 years. When I started this process in October 2019, I never
imagined the world would be on lockdown due to the COVID-19 pandemic, and we would be
separated for 2 ½ years. The video calls and notes of encouragement put a smile on my face and
shined a light on even the darkest days. I would like to thank my dissertation chair, Dr. Larry
Picus and Drs. Darline Robles and Helena Seli for agreeing to serve on my dissertation
committee. To the entire University of Southern California doctoral cohort #2, class of 2022. It
has been a pleasure to work and study alongside all of you. I have been inspired by your
commitment, drive, determination, courage, and generosity to be vulnerable in this shared space
and disrupt the status quo. To Drs. Dan Skimin and Adrian Price—We are the best team ever. To
Dr. Christine Demetre—The coffee and chocolate deliveries came at the right time. Your notes
of encouragement were indeed an inspiration. I looked forward to each hug and your parting
words —“You got this!” We got this! To Dr. Monica Gonzales—Words alone cannot begin to
express how proud I am of your accomplishments and that I get to call you “friend”. I want to
thank Mrs. Lee Ann Spillane for your words of wisdom and willingness to be my writing coach.
When my self-efficacy was low, you showed grace and patience and provided valuable feedback.
Because of you, I have made great strides as a writer. Finally, to my mom, Elizabeth. Thank you
for the video chats, support, and encouragement to become a life-long learner and the courage to
do things a little differently.
vii
Table of Contents
Abstract .......................................................................................................................................... iv
Dedication ....................................................................................................................................... v
Acknowledgments .......................................................................................................................... vi
List of Figures ................................................................................................................................. x
List of Tables ................................................................................................................................. xi
List of Abbreviations .................................................................................................................... xii
Chapter One: Overview of the Study .............................................................................................. 1
Background of the Problem ................................................................................................ 3
Statement of the Problem .................................................................................................... 8
Purpose of the Study ........................................................................................................... 9
Significance of the Study .................................................................................................. 11
Assumptions ...................................................................................................................... 12
Limitations ........................................................................................................................ 12
Definition of Terms ........................................................................................................... 13
Organization of the Study ................................................................................................. 15
Chapter Two: Review of the Literature ........................................................................................ 16
Factors that Influence Technology Integration ................................................................. 17
Constructivism .................................................................................................................. 24
TPACK ............................................................................................................................. 31
Self-Efficacy ..................................................................................................................... 34
Conceptual Framework ..................................................................................................... 41
Chapter Three: Methodology ........................................................................................................ 46
Sample and Population ..................................................................................................... 47
Instrumentation ................................................................................................................. 48
viii
Data Collection ................................................................................................................. 52
Data Analysis .................................................................................................................... 53
Researcher’s Positionality ................................................................................................. 54
Summary ........................................................................................................................... 55
Chapter Four: Results ................................................................................................................... 57
Demographic Data ............................................................................................................ 57
Data Analysis .................................................................................................................... 61
Summary ........................................................................................................................... 79
Chapter Five: Discussion .............................................................................................................. 81
Interpretation of Findings ................................................................................................. 82
Limitations ........................................................................................................................ 89
Delimitations ..................................................................................................................... 90
Recommendations for Practice ......................................................................................... 90
Future Research ................................................................................................................ 95
Conclusion ........................................................................................................................ 97
References ..................................................................................................................................... 99
Appendix A: Demographics ....................................................................................................... 119
Appendix B: Concerns-Based Adoption Model (CBAM) Levels of Use of an Innovation ....... 120
Appendix C: Technological Pedagogical Content Knowledge (TPACK) Questionnaire .......... 122
Appendix D: Technology Integration Self-Efficacy Scale (TISES) ........................................... 125
Appendix E: CBAM-LoU Survey Permission ............................................................................ 127
Appendix F: TPACK Questionnaire Permission ........................................................................ 128
Appendix G: TISES Survey Permission ..................................................................................... 131
Appendix H: Permission from The University of Southern California Institutional Review
Board ........................................................................................................................................... 132
Appendix I: Permission to Conduct Study .................................................................................. 134
ix
Appendix J: Participant Invitation Email .................................................................................... 136
x
List of Figures
Figure 1: TPACK Framework…………………………………………………………………...33
Figure 2: Conceptual Framework for Technology Integration…………………………………..42
xi
List of Tables
Table 1: Years of Teaching Experience 59
Table 2: Frequency of Professional Development 60
Table 3: Levels of Technology Use 61
Table 4: Years of Teaching Experience Compared to Levels of Technology Use 63
Table 5: Professional Development Training and Level of Technology Use 64
Table 6: Spearman Rank-Order Correlations Between Frequency of Professional Development,
Year of Teaching Experience, and Level of Technology Use 64
Table 7: Descriptive Statistics for Technology Knowledge (TK) 66
Table 8: Descriptive Statistics for Pedagogical Knowledge (PK) 67
Table 9: Descriptive Statistics for Content Knowledge (CK) 68
Table 10: Descriptive Statistics for Technology Content Knowledge (TCK) 68
Table 11: Descriptive Statistics for Technology Pedagogy Knowledge (TPK) 69
Table 12: Descriptive Statistics for Pedagogical Content Knowledge (PCK) 69
Table 13: Descriptive Statistics for Technology Pedagogy Content Knowledge (TPACK) 70
Table 14: Descriptive Statistics for TPACK Composite Scores 71
Table 15: Spearman Rank-Order Correlations Between Each TPACK Knowledge Domain and
Levels of Technology Use 73
Table 16: Descriptive Statistics for Technology Self-Efficacy 75
Table 17: Composite Score for Technology Self-Efficacy 77
Table 18: Spearman Rank-Order Correlation Between Technology Knowledge Domains and
Technology Self-Efficacy 78
Appendix A: Demographics 119
Appendix C: Technological Pedagogical Content Knowledge (TPACK) Questionnaire 122
Appendix D: Technology Integration Self-Efficacy Scale (TISES) 125
xii
List of Abbreviations
HISS Hillier International Secondary School
TK Technology knowledge
CK Content knowledge
PCK Pedagogical content knowledge
PK Pedagogical knowledge
TCK Technology content knowledge
TPK Technology pedagogical knowledge
TPACK Technology pedagogical content knowledge
1
Chapter One: Overview of the Study
The 2020 pandemic has forced people to change their daily routines. To slow the spread
of COVID-19, countries closed their borders and halted the daily activities of their citizens.
Forced to rely on technology for everyday experiences, people worldwide worked remotely,
changed to food delivery, and used Zoom for online schooling. The world was already
experiencing rapid technological innovation and social change driven by these new technologies
(Mir & Parrey, 2019). The digital divide existed before the pandemic and made great strides to
decrease digital inequities by providing digital resources to schools and homes (OECD, 2015).
However, the pandemic exposed the underfunded, failing digital infrastructures and the digital
inequities in distributing digital devices to students and teachers during the abrupt transition to
online learning. This pandemic has provided more advantages to privileged students who have
access to technology and digital learning spaces (Pew Research Center, 2021). According to the
Pew Research Center (2021), by 2025, innovators said people would rely more on technology for
work, health care, and education. The innovators coined the term “tele-everything” to describe
how the world will deepen its relationships with technology. As technology expands the
opportunities for innovation, it will also create new challenges (Chicioreanu et al., 2019).
A 2018 study conducted by the Pew Research Center reported that 95% of US teens ages
13 to 17 years, representing approximately 23 million teenagers, have or have access to a
smartphone, and 45% of the youth report a near-constant presence online. These figures are
almost double that of the 2014–2015 survey, that 24% of teenagers self-reporting near-constant
internet use. In addition, teenagers say they have a wide variety of technology uses in their daily
life outside of school but have limited technology uses for instructional purposes while in school
(Harrell & Bynum, 2018). These statistics reassure that access to technology is improving, yet
2
there are still problems addressing and solving digital inequities within classroom instructional
practices.
Technology is prevalent in daily life, and teachers in many countries do not utilize and
frequently use technology in their practices (OECD, 2016). Technology is rapidly changing each
day, and the need to keep pace with these rapid changes is at the forefront of national and local
educational technology plans. Addressing insufficient technology integration can be understood
by examining teachers’ reasons for technology reluctance in their instructional practices.
Technology pedagogy content knowledge (TPACK) and teacher self-efficacy will explain
educators’ perceptions of technology integration and teachers’ potential barriers when integrating
technology into instructional practices. A teacher’s TPACK knowledge will address and provide
answers to teachers’ technological pedagogical content knowledge and its influences on
technology integration. Teacher self-efficacy beliefs will inform about challenges teachers have
with instructional design choices to integrate with technology. These factors influence digital
competency and levels of confidence to make informed decisions about technology use in
different contexts.
Educators cannot predict students’ future uses of educational technology (Kimmons et
al., 2020) but are responsible for preparing students for the “tele-everything” world. Students
have basic technology skills of email, internet browsing, social media, and texting. However,
students do not have a deep knowledge of using technology for educational purposes. Educators
need to integrate technology into their instructional practices to enhance learning. It is equally
important that students have the technical skills and knowledge to improve employment
opportunities beyond high school and prepare to function digitally (Lombardi et al., 2017).
Digital immigrant teachers and native teachers have reported feeling unprepared and struggling
3
to integrate technology effectively into instructional practices (Brookfield, 2017; Gray et al.,
2010; Prensky, 2001.)
Through transformative instruction and feedback, teachers must facilitate student learning
and personal growth and challenge students to master 21st-century skills of collaboration, critical
thinking, communication, and creativity. Students need these 21st-century skills to be literate in
technology, competitive in higher education, and function in a technology-driven world (Harris,
2016). Technology use in the classroom has steadily increased over the last twenty years, but
technology in the classroom and instructional practices does not take full advantage of using
technology to enhance student learning (Brookfield, 2017; Gray et al., 2010). Meeting the needs
of the 21st-century learner has caused teachers to rethink and redesign their instructional
practices that provide students with various means to develop knowledge and demonstrate their
learning and skills (Harris, 2016; Zehra & Bilwani, 2016).
Concerning the intentional use of technology, not enough is known about why teachers
choose to use or not use digital devices, software, or applications for instructional purposes. This
lack of understanding affects students’ technical knowledge and how students learn with
technology. This may negatively contribute to the inequities that adversely affect student
learning. This study aims to understand the relationship between teacher self-efficacy and
(TPACK) and the possible influence these variables have on integrating technology into
pedagogy practices. The remainder of this chapter will be an overview and description of the
problem of inadequate technology integration into classroom instructional practices.
Background of the Problem
The Hillier International Secondary School (HISS) Instructional Technology Department
embraces the National Education Technology Plan’s recommendations and the International
4
Society of Technology Education (ISTE) standards. The HISS technology plan is rooted in
improving student learning opportunities. It uses technology integration and innovation lenses to
make learning personalized, collaborative, and relevant to current events. The most recent
Educational Plan (2021–2027) involves advancing instructional practices to meet the learning
needs of all students. This plan includes upgrading the learning environments with high-quality
digital resources, professional learning opportunities, and increasing the coaching and feedback
for teachers to grow instructional practices continuously. For educators at HISS, mandates on
technology integration are influenced by U.S. technology plans and ISTE standards implemented
at the local level. These federal guidelines have made it imperative that educators are willing and
prepared to embrace technology integration into their instructional practices.
Accredited by the Western Association of Schools and Colleges (WASC) in the United
States, the institution’s mission statement encourages all community members to strive for
excellence every day. The institution makes enormous strides through written commitments to
teaching and learning and the impact these have on student learning outcomes that foster world
learners who will have the skills and capacity to lead in their chosen fields of study and careers.
The central office guides the school, but the on-site divisional leadership teams manage the day-
to-day operations (elementary, middle, and high schools). The school’s diversity and makeup do
not reflect the local community near the school; however, the government restricts students who
hold passports from the host country from applying for admission to the school.
Hillier International Secondary School is rich in technology devices, digitally equipped
physical spaces, and an entire team dedicates time to supporting technology integration in
instructional practices. The Technology and Innovation team has collected data on the devices
used in the high school classrooms to inform which systems will best be supported by the
5
network, software, and classroom instruction. HISS has invested heavily in instructional
technology and adopted a 1:1 program in 2014. Each secondary student is required to bring a
laptop to school each day. Internal research data shows that students choose Apple® products
(90%) over Windows products (10%). Therefore, HISS and Apple® have partnered with The
Family Funded MAC Program, which provides educational discounts on laptops. In addition,
HISS has an Apple® Certified Technician onsite for consultations and simple repairs.
Before purchasing, the secondary school Technology Help Center (THC) asks parents to
consider that the specifications set forth meet or exceed their laptop choice. In addition, parents
and students are encouraged to consider laptop size, familiarity with the device, personal
preferences, design, and perceived intended use as data points to drive purchase decisions. Not
all classes use the same software and tools; therefore, most parents buy with the intent for
students to use the computer throughout their high school years.
Upon employment, teachers are afforded a new 13-inch Apple® laptop and iPad with a
pencil. At the end of 4 years, everyone can buy their current computer at a reduced cost and is
given a new laptop for the next 4 school years. However, if a teacher resigns or their contract is
terminated within those 4 years, teachers do not have the option to purchase. Therefore, the
computer is placed in the substitute teacher inventory and available for use during their daily
employment contract.
In addition to the computer laptop, teachers receive two charging cables—one for the
classroom and one for home use. Teachers are also given a terabyte external hard drive and are
taught and encouraged to perform computer backups and syncs frequently. Classrooms are
equipped with an HD projector, Apple® TV, a speaker system, and capabilities for wireless
connection. Technology support is available every day in the divisional THCs from 7:30 am to
6
4:30 pm, and most teachers are comfortable utilizing Google Chat and Zoom for immediate
assistance after hours. Personalized one-to-one consultation and small group training are
designed to meet teachers’ needs. The office employs two full-time technology and innovation
engineers, one educational technology and innovation coach, and one educational technology
and innovation coordinator. The school is committed to meeting the technology needs of the
educators to use technology in pedagogical practices.
School decision-makers believe the introduction of 1:1 technology into instructional
teaching practices will increase student interest, time on task, and improve learning (Inan &
Lowther, 2010). Students born after 1980 are millennials who have had access to technology and
are considered tech-savvy and digital natives (Prensky, 2001). The digital natives’ definition
describes learners born into an era surrounded by technology and assumes these students are
digitally literate and skilled in various technologies that enhance learning (Kirschner &
Bruyckere, 2017; Smith et al., 2020). It is assumed that students labeled as digital natives are
comfortable with a wide range of technology, innovate and produce digital content, and are
informed consumers of technology. However, digital native is a label and stereotype assigned to
this generation of learners. The research indicates that students do not know how to use
technology for educational purposes (Kirschner & Bruyckere, 2017; Smith et al., 2020). These
labels and stereotypes of digital natives have negatively impacted a teacher’s ability to integrate
technology into instructional practices.
There are so many options, opportunities, and approaches to technology integration that
in-service teachers may feel overwhelmed (Crittenden et al., 2019; Kessler, 2018). This feeling
of cognitive overload may contribute to frustration when using technology in instructional
practices effectively (Mayer, 2011). The dedicated technology department provides ongoing
7
professional development and offers technical support to assist teachers with knowing how to
use the technology and understand the benefits of technology integration (Hur et al., 2016). In
addition, when teachers add technology into the classroom and instructional practices, the
learning environment changes and invites students to own their learning (Hamilton, 2015).
Educators can focus on technology integration with the infrastructure in place and digital
needs met. However, having access to a rich selection of technology devices and infrastructure
does not ensure technology integration into instructional practices (Harrell & Bynum, 2018;
Zehra & Bilwani, 2016). There are gaps and challenges between teachers and their various uses
of technology. Technology savvy teachers with rich, successful experiences using digital devices
can maximize the benefits and design lessons that foster collaboration and deeper learning (Inan
& Lowther, 2010). Teachers who lack self-efficacy using technology opt to retain the status quo
(Harrell & Bynum, 2018).
The pedagogical argument for integrating technology has many layers. First and
foremost, the digital native students are surrounded by technology (Pew Research Center, 2021).
Second, students ask for and need technology to be used in 21st-century learning to expand their
access to knowledge (Harrell & Bynum, 2018). Third, reducing time and mental effort to teach
and design lessons with educational technology is another benefit as teachers’ self-efficacy
increases with each successful mastery or vicarious experience (George & Sanders, 2017).
Finally, technology integration adds value to student-centered learning and performance (George
& Sanders, 2017). Surprisingly, there is little research on integrating technology into educators’
instructional practices in an international school accredited using an American educational
curriculum. The use and non-use of technology in teacher instructional practices demonstrate
potential digital inequalities in students’ educational experiences (Ragnedda & Muschert, 2013).
8
This study aims to understand better teachers’ perception of using technology in instructional
practices by looking at the relationship between independent variables of the technological
pedagogical content knowledge framework (TPACK), teacher self-efficacy, and factors that may
or may not affect an educator’s instructional practices for technology integration.
Statement of the Problem
Many factors explain why educators choose to use or not use technology in their
instructional practices. Technology use in elite schools can be attributed to finance purchases,
continuous professional learning, and proactively following a well-defined plan that encourages
integration. Providing students with 1:1 technology improves teachers’ options to create learning
activities for students. Therefore, educators should be motivated to adopt and integrate
technology into the curriculum (Lowther et al., 2012; Roehl et al., 2013). However, these
explanations are not enough to ensure that technology is used effectively in classrooms for
instructional purposes (Zehra & Bilwani, 2016). In a study by the OECD (2021a), 62% of the
countries reported little or no use of technology to enhance learning. Additionally, the OECD
(2013) study said that 20% of the teachers in many countries need more professional
development in technological pedagogical skills to integrate technology successfully into their
classroom practices. Students who do not have opportunities to engage with technology to learn
21st-century skills are at risk of not being competitive in the global society unless teachers have
the technological pedagogical knowledge to create meaningful learning opportunities that
integrate technology into instructional practices (Teo & Zhou, 2017).
Teachers do not always use technology effectively to maximize the impact of teaching
and learning (Teo & Zhou, 2017). Even though there has been steady improvement over the last
15 years, there is still a large percentage of in-service teachers who do not integrate their
9
instructional practices with technology (Teo & Zhou, 2017). Institutions’ technology plans are
created and used as guidelines for schools to incorporate technology; teachers need to develop
digital competency and skills for transformative teaching to engage students in the learning
process. Digital competence ensures teachers have the confidence, technological pedagogical
skills, and knowledge to engage students in a rapidly changing educational environment. In a
recent study, researchers found that when teachers are mandated to use technology in
instructional practices, it is not guaranteed that the lessons produced will improve higher-order
thinking skills or promote constructivist learning (George & Sanders, 2017). The study results
revealed that only three out of the thirty lessons examined demonstrated that the quality of
learning could be increased using technology. As a result, teachers are not creating technology-
integrated lessons that invite students to engage with the material to create meaningful learning
experiences rooted in constructivist principles (George & Sanders, 2017; Huang et al., 2019;
Mayer, 2002; Schunk, 2020). Therefore, the problem affects students because Hiller
International Secondary School has an educational plan to demonstrate digital competency with
1:1 laptop use. Furthermore, the plan explicitly states that technology is integrated into
instructional materials to support student learning with the knowledge and skills needed to
advance in higher learning and careers of their choice (Lombardi et al., 2017).
Purpose of the Study
This study aims to understand the relationship between teacher self-efficacy and
technological pedagogical and content knowledge (TPACK) and the possible influences these
variables have on integrating technology into pedagogy practices. This research study
approaches through a constructivist paradigm, given that the problem has multiple factors used to
construct knowledge (Lochmiller & Lester, 2017). Many internal and external barriers cited in
10
the literature possibly contribute to insufficient classroom instruction use of technology (Durff &
Carter, 2019; Ertmer, 1999; Hur et al., 2016; Hsu, 2016; Sang et al., 2011). At HISS, high-
quality infrastructure, sufficient access to quality devices, and adequate funds for software and
applications eliminate external factors. However, the internal factors, including lack of consistent
professional learning, low TPACK, low teacher self-efficacy, and negative attitudes towards
technology, are still possible factors (Durff & Carter, 2019; Harrell & Bynum, 2018; Hur, 2016).
While many factors affect technology integration, researchers and the current literature have
labeled TPACK and teacher self-efficacy as the two factors that have the most significant
influence on teachers’ instructional practices and intent to integrate technology (Chicioreanu &
Ianos, 2019; Durff & Carter, 2019; Harrell & Bynum, 2018; Hur, 2016). This study examines the
factors that prevent teachers from using technologies to enhance instruction in the classroom and
will focus on the following questions to understand the relationships between the variables of
teachers’ years of experience, level of participation in technology professional development,
TPACK knowledge, technology self-efficacy, and level of technology integration.
Three research questions guided this study:
1. Is there a relationship between high school teachers’ attributes (years of experience
and level of participation in technology professional development) and their level of
technology integration?
2. Is there a relationship between high school teachers’ technological pedagogical
content knowledge (TPACK) and their level of technology integration?
3. Is there a relationship between teachers’ self-efficacy and their level of technology
integration?
11
Significance of the Study
Understanding the phenomenon of educational technology is a complex process and
requires a wide lens to capture all the components to gain a complete understanding. Researchers
and studies have discovered many themes of technology integration that range from institutional
influences, student learning outcomes, and teacher competence to identifying and using digital
tools for instructional practices (Lai & Bower, 2020). Having technology knowledge on how to
use various digital devices does not guarantee that a teacher can teach with technology or know
which tools to use to have the desired outcome (Guggemos & Seufert, 2021). It is argued that
integrating technology makes teaching more efficient and can influence instructional changes
from traditional teacher-centered approaches to more constructivist student-centered that
promotes 21st-century learning (George & Sanders, 2017; Hamilton, 2015; Harrell & Bynum,
2018).
Educators’ self-reported perceptions of using technology in the classroom for
instructional purposes are one such component that has not been explored at Hillier International
Secondary School (pseudonym). This study is driven by the realization that teacher self-efficacy
strongly influences technology use (Harrell & Bynum, 2018), and this technology integration
domain is unknown. The findings of this study will inform future technology and professional
learning needs at HISS. This study’s specific purposes will be to understand the barriers and
challenges with technology integration at an international school, analyze teachers’ self-reported
perceptions of technology use, and teachers’ self-efficacy to make informed decisions on
integrating technology into instructional practices.
12
Assumptions
For this study, anecdotal evidence from teachers is helping to define the problem with
insufficient levels of technology integration into classroom instruction practices in an
international private school and the current need to meet the technological goals and learning
aspirations of the school’s strategic plan. The literature review claims that integrating technology
into instructional practices has improved over the years yet is still underutilized in many
countries. There is also an assumption that teachers participating in this study have access to
instructional technology devices for their classrooms. In addition, it is assumed that all teachers
are aware of the strategic plans’ learning aspirations that require technology instruction in the
classrooms. Finally, there is an assumption that participants answered honestly on the
instruments used in this study. The survey instrument relies on the self-reported data of the
participants’ beliefs, perceptions, knowledge, skills, and attributes. Socially desired biases may
cause participants to overestimate or underestimate their abilities, expertise, and learning, which
is reflected in their responses. This assumption is a reasonable expectation when using surveys
for research purposes that ask participants questions about themselves, experiences, abilities,
attitudes, and beliefs (Robinson & Leonard, 2019).
Limitations
The participants are limited to those contracted employees during the period for data
collection, and the study was opened to only those secondary teachers working at this private
international school. The teachers from this school were all sent the online survey instrument and
received information on the survey’s purpose, intent, and contents. Subjects were informed that
participation in the study was voluntary and that opting out at any time was an option. The
authors granted written permission to use and adapt the survey instruments (Robinson &
13
Leonard, 2019). The surveys were revised and adapted for the international private school setting
with a well-established 1:1 technology program, and caution was exercised when applying it to
this international educational environment.
The biases I hold as an instructional technology coach are possible limitations of this
study. My instructional duties include modeling, demonstrating, leading professional
development, and working with educators to integrate technology into instructional practices.
The data collected for this study happened in November 2021, and the information gained for
this study is specific to that time. I recognize that the study’s findings were conditional, and any
knowledge gained from this study represents secondary teachers’ experiences at an international
school during this specific time frame.
Definition of Terms
Content knowledge (CK): Educators’ knowledge includes concepts, theories, ideas, and
organizational frameworks unique to each subject matter (Shulman, 1986).
Digital equality: Access to materials that are required to make use of digital tools such as
computers and infrastructure (OECD, 2015).
Digital equity: Ensure that resources (access, knowledge, and skills) are available to
have, learn, and use to move learning forward (OECD, 2015).
Digital learning: The use of a wide variety of technology tools in instructional practices
to enhance students’ learning experiences (Office of Educational Technology, 2021).
Innovation: The art of using technology to solve problems to make something new, an
invention, or better, an iteration from something that already exists (Magiera, 2017; Wagner,
2012).
14
In-Service teacher: An educator with a degree in teaching and one or more years of
experience.
Pedagogical content knowledge (PCK): The educators’ knowledge to combine what is
taught and how it is taught to discover multiple methods to present material to improve student
understanding (Koehler & Mishra, 2013).
Pedagogical knowledge (PK): The educators’ knowledge about various instructional
processes and practices to enhance student learning (Koehler & Mishra, 2013).
Preservice teacher: An educator pursuing a degree in teaching from a higher learning
institution.
Teacher self-efficacy: An educator’s perception and beliefs in their capabilities and
abilities to develop and execute plans to learn and meet personal goals (Bandura, 1989; Bandura
& Schunk, 1981).
Technological content knowledge (TCK): The educators’ understanding of which
technologies are best suited for the academic subject content (Koehler & Mishra, 2013).
Technology integration: The timely and purposeful use of digital tools in instructional
practices to enhance student learning and skills; encourages the use of those skills for learning
and problem-solving (Kimmons, 2016).
Technical knowledge (TK): Educators’ ability to continuously identify, understand, use,
communicate, problem-solve, and interact with various digital devices in everyday work and life
(Koehler & Mishra, 2013; Tondeur et al., 2019).
TPACK Technical pedagogical content knowledge: A theoretical knowledge framework
on how to develop teaching strategies that integrate technology into the teaching and learning
15
process by understanding the relationships between the core components of content, pedagogy,
and technology (Guerra et al., 2017; Koehler & Mishra, 2013).
Organization of the Study
This dissertation is organized into five chapters. Chapter One provides an overview of the
purpose of the study, research questions, and historical perspective that is unique to the study.
Chapter Two provides a literature review as it relates to the problem of practice. The chapter
topics are barriers to technology integration, TPACK technology framework, teacher self-
efficacy, and how each influences the use of technology in instructional practices. Chapter Three
discusses the research methods used for the study, including the participant selection process,
credibility and trustworthiness, limitations of the study, and ethical practices. Chapter Four will
discuss the research findings and include an analysis of the data. Finally, Chapter Five discusses
the results of the data analyses and recommendations for practice and future research.
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Chapter Two: Review of the Literature
Chapter two aims to provide a thorough review of the literature that examines
constructivist-oriented technology integration in an international school through the lens of the
technological pedagogical content knowledge framework (TPACK) and teachers’ self-efficacy.
These two topics create the base for the conceptual framework for this study of technology
integration practices in an international high school.
This study begins by examining U.S. educational policies that provide a historical
context. The context of these policies played a crucial role in shaping how schools viewed and
implemented technology integration in K–12 schools. The United States education policies frame
this study and provide context for the literature review; note that sample populations and
locations from additional studies used to support this literature review are from the United States
and non-U.S. institutions. The educational policies offer guidance, but the individual states
develop and design educational technology plans resulting in inconsistencies in American
international schools. The effectiveness of technology integration in K–12 settings is a global
concern. As states, districts, and schools continue to invest in educational technology, the
teacher's challenge is to transform their teaching practices to integrate technology (Sheffield et
al., 2018). By looking at the TPACK technology framework and technology self-efficacy, this
study will highlight relationships between these variables and teacher attributes (years of
experience and level of participation in technology professional development). These variables
affect a teacher’s self-efficacy with TPACK and influence their choices to use or not use
technology in instructional practices.
After reviewing policies, the literature review looks at the historical journey of
integrating technology in schools. This is a logical place to begin because this will reveal the
17
many technology integration barriers addressed in the second section that K–12 schools
experienced when implementing U.S. federal education policies’ guidelines. These barriers
directly impact teachers’ technology integration, self-efficacy, and instructional practice.
The third area of focus will examine the TPACK framework created by Mishra and
Koehler (2006) and how it helps teachers gain technological, pedagogical, and content
knowledge to inform their technology integration practices. Describing these framework
knowledge domains, including how each part intersects with the others, gives meaningful
opportunities to think about how the degree of teacher technology knowledge levels influences
classroom instructional practices and choices. Teachers choose to use or not use technology in
their instructional practices in each of these areas, which directly impacts students’ preparedness
for the 21st-century (Harris, 2016). Finally, the literature review concludes with a broad look at
teacher self-efficacy and how it correlates to teachers’ ability to integrate technology into
instructional practices and choices.
Factors that Influence Technology Integration
The use of technology for teaching and learning purposes has been at the forefront of
most educational lists of priorities for the past 40 years and continues to be actively debated. The
emphasis on computer literacy and skill development emerged in the 1970s and 1980s. The
United States government’s administrations have sought to improve education through
educational reform acts targeting various policies and content areas. Each reform act suggested
the United States was behind other nations and needed changes to remain competitive. The
National Defense Education Act of 1958, enacted by President Eisenhower, sought to improve
math, science, and foreign language skills. This act was the answer to keeping up with the Soviet
Sputnik satellite launch in 1957. A few years later, in 1965, President Lyndon B. Johnson
18
introduced the Elementary and Secondary Education Act (ESEA). This act recognized the needs
of disadvantaged children and was the first act that mandated federal government funds for K–12
educational programs (U.S. Department of Education, n.d.).
Over the next several years, presidents enacted educational reforms to address various
needs, attempting to overcome student learning deficits in different content areas. The United
States (1983) Commission on Excellence in Education of the Reagan administration published A
Nation at Risk: The Imperative for Educational Reform and suggested that U.S. schools were
failing. Other countries were outpacing strides made in technology innovation. This threatened
America’s future and its citizens and was considered a possible link to its economic growth.
President William Clinton reintroduced the ESEA in 1994 under the name Improving America’s
Schools Act. It promoted drug-free schools and spotlighted immigrant education. The Bush
administration continued these efforts under No Child Left Behind (NCLB) in 2001.
The revised NCLB 2002 act was the first to accommodate K–12 technology integration
in K–12 schools to improve student achievement and close the achievement gap. With this
revised 2002 NCLB act, the United States governmental education and professional
organizations have recognized that preparing students for 21st-century skills and careers include
technology integration (Harrell & Bynum, 2018). The National Council of Teachers of English
(2018) revised its technology position statement and identified technology literacy in all four
core beliefs to demonstrate that it is essential to have technology access and be informed
consumers of technology. The core beliefs state that technology is selected based on its ability to
enhance and expand deeper thinking about learning English. Educators need to have content and
technology knowledge to make informed decisions about intentional technology use and improve
the instructional practice. The National Education Technology Plan (2017) embraces the
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educational philosophy of John Dewey (1937) to produce mature learners by co-creating
alongside students. The NETP 2021 plan seeks to increase equitable access to technology and
transform learning experiences that support the practical uses of technology. This plan
recommends providing in-service teachers with the technical knowledge and skills to redesign
instructional practices to meet the technology needs of 21st-century student learners.
Finally, at nearly the same time NCLB was created, the International Society for
Technology in Education (ISTE) developed the National Educational Technology Standards for
students (NETS-S) in 1998. Then, in 2000, the NETS-T for teachers was created. These revised
standards have been rewritten to merge with changing technologies and educational spaces to
ensure students have the skills needed to live and thrive in a digital society. The invention of the
personal computer made it possible for the workplace, homes, and schools to have computers for
professional, personal, and educational use (Farr & Murray, 2016). Over the years, technology
standards have guided educators and students on what they should know and do with technology.
Recognizing that many stakeholders have an essential role in integrating 21st-century pedagogies
into educational practices, standards were developed for educational leaders (2018), coaches
(2019), and the newest, Computational Thinking Competencies for educators (2019) (ISTE
Standards, n.d.).
Barriers to Technology Integration
Integrating technology into classroom instructional practices is a slow, complex, yet
methodical process influenced by many factors (Inan & Lowther, 2010). When teachers
underutilize technology for instructional practices, various factors are cited as barriers to
technology integration (Hsu, 2016). Ertmer (1999) was the first researcher to coin the factors
affecting technology integration in classroom instruction as internal or external barriers (Durff &
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Carter, 2019; Hur et al., 2016; Sang et al., 2011). External barriers, also referred to as first-order
barriers, are described as factors that need systemwide support, such as access to technology and
professional development. Internal barriers, often referred to as second-order barriers, are those
relevant to teachers, such as confidence and self-efficacy in using technology and perceived
values that student learning is positively affected by technology integration (Hur et al., 2016;
Kim et al., 2013; Venkatesh et al., 2012). Over the past two decades, the external barriers have
decreased because of the lower cost of technology tools and increased support and training in
schools.
According to Harrell and Bynum (2018), decreasing external barriers and having access
to technology devices is not enough to eliminate barriers. The United States government, states,
and local school districts have taken steps to increase access to digital tools, yet 40% of K–12
teachers have failed to integrate technology into their instructional teaching practices (Pittman &
Gains, 2015). These teachers have also experienced difficulties overcoming internal, second-
order barriers that directly influence technology integration into classroom instructional practices
(Durff & Carter, 2019; Zehra & Bilwani, 2016). Internal barriers continue to exist and are
obstacles to integrating technology into teacher instructional practices (Ertmer, 2015; Pittman &
Gains, 2015).
The internal barriers are more difficult to overcome (Christenson & Knezek, 2016).
Technology-rich schools, such as Hillier International High School, cannot guarantee that
technology is integrated into teachers’ instructional practices (Pittman & Gaines, 2015). Self-
efficacy is seen as a second-order, internal barrier and is an influential factor that affects a
teacher’s behavior and plays a vital role in a teacher’s willingness and desire to use technology
tools in classroom instruction (Bandura, 1977; Harrell & Bynum, 2018). To leverage
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technology’s affordances, teachers who are well supported have access to consistent professional
learning and feel confident in using technology tools, such as computers, web applications, and
software programs. Teachers will use the tools to their full capacities and diminish internal
barriers with support and efforts to remove external barriers (Hur et al., 2016). Continuing to
acknowledge and address all barriers will support the use of technology in classroom instruction
and provide 21st-century future-ready skills to students (Durff & Carter, 2019; Harrell & Bynum,
2018).
Internal Barriers
An internal barrier, such as low teacher self-efficacy, has been cited by many researchers
as a strong predictor and influencer of technology integration into instructional practices (Birisci
& Kul, 2019; Hsu, 2016; & Poulou et al., 2019). Similarly, internal barriers that must be
overcome for successful technology integration include attitudes toward technology, socio-
cultural barriers, and pedagogical barriers (Durff & Carter, 2019; Ertmer, 2015). How teachers
feel about using technology, how comfortable teachers are about using technology in the
classroom, and the perceived usefulness of technology for learning purposes are internal barriers
that prevent integrating technology into instructional practices.
Educators’ attitudes about technology integration, both positive and negative, influence
whether they use technology in the classroom (Sahin et al., 2016; Tonderu et al., 2017). In a
study with 64 in-service high school teachers in South Africa, the educators explained that
integrating technology was practical. Yet, their attitude was identified as a barrier to integrating
technology (Van Der Rosee & Tsibolane, 2017). In another study of English teachers at a
Chinese university, the teachers explained that the usefulness and ease of use influenced their
decisions to use technology (Teo et al., 2017). In Southeast Asia, researchers Teo and Zhou
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(2017) discovered that gender, age, and experience using computers did not influence teacher
attitudes or their purposeful use of technology in instructional practices.
The school learning culture, administrative support, and supportive colleagues influence
technology in the classroom. Administrators are strategically positioned to positively influence
technology use in the classroom by encouraging a culture of innovation that breaks the status
quo, supporting specific use of hardware and software such as a 1:1 program, and supporting the
ideals that technology integration is a valued educational practice (Durff & Carter, 2019).
Teachers have stated that administrative support was essential and influenced their decisions to
integrate technology for instructional purposes (Weng & Tang, 2014). In a qualitative study of
twenty U.S. teachers, the researcher discovered that the administrator’s directives prompted
teachers to adopt technology and supported their beliefs that technology would enhance student
learning (Tuttle, 2012). In another study, teachers reported that the school’s mission and vision
statement shaped behavior changes to move towards a paperless environment (Zehra & Bilwani,
2016). Supportive administrators can help teachers eliminate internal barriers through actions
that encourage participation in professional development, online courses, and conferences that
showcase or model effective use of technology. In addition, administrators can influence a
positive professional learning community (PLC) culture that shares resources and ensures
teachers have access to technical support and technology coaches.
Pedagogical beliefs on how to teach students are formed early in a teacher’s career,
sometimes difficult to change, and lead to an internal barrier that impedes technology integration.
Teachers who have access to many resources but have traditional pedagogical beliefs will portray
themselves to be the barrier to classroom technology use (Ertmer, 2015). Teachers whose beliefs
are rooted in student-centered approaches will fare better using technology than those with
23
teacher-centered ideals (Tondeur et al., 2017). Teachers who adopt constructivist models adjust
their teaching approaches to help students collaborate, build knowledge, and develop student
agency through personalized learning. Change is challenging; however, teachers have overcome
pedagogical barriers by being willing to adapt and push through continuous change and finding
appropriate resources that use technology to further student growth and learning. As a result, they
prepare students for a future of utilizing technology in the workplace and higher education (Durff
& Carter, 2019).
Teacher attitudes, socio-cultural environments, and pedagogical beliefs are all intertwined
internal barriers that impede and are obstacles to technology integration (Ertmer, 2015; Teo et al.,
2017; Van Der Ross & Tsibolane, 2017; Zehra & Bilwani, 2016). Overcoming these barriers is a
challenge but can be done with support from administrators, professional development, peers
who model appropriate, timely use of technology, and PLC teams (Durff & Carter, 2019). The
success of technology integration into the classroom depends heavily on teachers’ positive
attitudes and perceptions of technology in teaching and learning. Administrators can show they
value technology by allowing time for teachers to develop skills and adopt a constructivist
teaching style that challenges the status quo of traditional lecture-based instructional practices
(Durff & Carter, 2019; Weng & Tang, 2014).
Technology Integration for 21st-century Learning
Using technology in the classroom for instructional purposes is an essential skill that all
teachers must have (Ruggiero & Mong, 2015; Birisci, 2019). For today’s students to meet 21st-
century learning standards that include communication, collaboration, critical thinking, and
creativity, didactic instructional approaches alone do not prepare students to meet these standards
(Harris, 2016). Integrating technology into 21st-century learning and instructional practices is an
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expectation for all teachers. The ISTE standards are learner-focused. While educators work to
improve their learning and technological skills, the direct impact will be improving student
learning outcomes. These standards are rooted in the philosophy that technology must be used
with purpose. For example, the ISTE standards also pave the way for personalized learning to
empower student agency and differentiated learning to meet students where they are skill-wise.
As educators become more comfortable with technology integration into instructional practices,
they can proactively design lessons to offer more equitable learning experiences. Students can
access the parts of the curriculum needed, collaborate with peers and experts, and own their
learning. This flexible environment allows teachers to respond to students’ needs rather than the
needs of the curriculum.
Constructivism
When examining how students acquire knowledge, the conversation shifts to how
learners construct knowledge (Schunk, 2020). Constructivist learning, influenced by Vygotsky’s
(1978) sociocultural theory, acknowledges that individual experiences and prior knowledge are
needed to organize and acquire knowledge. According to Vygotsky, the social environment and
social interactions were components necessary and critical for learning. For learning to happen, it
is the result of the student being active rather than passive while receiving instructions and
information (Schunk, 2020).
Constructivism embraces the idea that learning happens through active participation. The
focus is on instructional activities and the use of mediatory tools that are more non-traditional
and student-centered (Ertmer, 2015; Hamilton, 2015; Huang et al., 2019). Vygotsky (1978) states
that tools can include signs, symbols, and text; however, language is the most influential for
constructing knowledge. As teachers mediate how to use the tools, learners can begin to self-
25
regulate and transfer this knowledge to performing other activities and advance their learning.
For learners to co-construct knowledge in technology-infused collaborative spaces, there must be
equity, and learners must have self-regulation skills.
Influenced by the work of Vygotsky (1978), constructivism’s pedagogical approach to
teaching holds that learning needs collaborative connections to prior knowledge to construct new
knowledge (Schunk, 2020). Instructional practices enhanced with technology suggest that
learning is not confined to physical spaces but rather shaped by social interactions with others.
Learning can happen anywhere, anytime. Learning also signifies that the learner will do
something or know something they did not know before. Using a constructivist approach,
teachers abandon traditional teaching methods and promote meaningful learning by designing
active, constructive, and intentional lessons to encourage knowledge construction from multiple
perspectives (Koh et al., 2014; Koh et al., 2017).
Technology and education are forever connected, and one does not exist without the
other. Using technology tools in the classroom generally has positive learning outcomes (Lia &
Bower, 2020; Scott et al., 2017). However, technology tools should not drive technology
integration; pedagogy should. There has been a shift from teaching educators how to use
technology tools to discovering how technology use in classroom instruction and pedagogy
drives 21st-century learning (Ertmer, 2015). Numerous authors support the belief that a student-
centered constructivist approach is the best strategy for integrating technology (Hamilton, 2015;
Huang et al., 2019; Milner-Bolotin, 2017). Such a redesign demands teachers reorganize learning
spaces: Less sitting in rows, more sitting in flexible groups, less lecture, more inquiry, less
individual work, more collaborative work. These shifts place the learner at the heart of learning.
When designing instructional practices in a constructivist learning environment, teachers
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intentionally create paths for students to develop responsibilities for their learning and be a part
of the learning process (Morchid, 2020). Focusing on pedagogy is the framework needed to
prioritize students, content, and teaching strategies. Technology integration into instructional
practices is both the tool and catalyst for change.
A strong argument for using technology in instructional practices is the data received
from student learning and outcomes (Lai & Bower, 2020). For example, math instructors created
virtual learning environments for their learners, and the results concluded that students were
more comfortable with learning the skills and the tasks became more enjoyable (Garzón &
Bautista, 2018). Meaningful learning tells us that time on task increases with a sense of play and
joy, much as Csíkszentmihályi and Rathunde (1993) describe flow when students are
intrinsically motivated by the activity and not by the extrinsic rewards (Schunk, 2020).
While there is a place for drill and practice in a constructivist learning environment,
computers and software should be used for more than rote learning. Computers and software
assist in developing creativity and critical thinking, among other skills, through student-designed
multimedia presentations, robotics construction and challenges, research, and musical creations
(Pourhosein Gilakjani et al., 2013). Shifting the traditional teacher-centered approach to a
constructivist student-centered approach will support the meaningful selection of technology to
enhance learning (Lia & Bower, 2020). Adopting constructivist beliefs helps educators
understand how students learn, what students enjoy doing, and develop effective models of
teaching practices (Henshon, 2019; Sang et al., 2011).
In a study of 820 teachers in China with an average of 14.6 years of teaching experience,
researchers (Sang et al., 2011) found relationships between constructivist beliefs and teachers’
levels of technology integration into instructional practices. Those teachers that embrace
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constructivist beliefs are also more likely to use technology in their instructional practices and
are more likely to encourage students to use technology for educational purposes (Hermans et al.,
2008; Tondeur et al., 2008). In a constructivist learning environment, the teachers’ knowledge,
beliefs, and attitude toward technology and their technological self-efficacy affect the level of
technology use and success the student experiences.
Similarly, higher self-efficacy is positively related to intrinsic motivation (Bandura &
Schunk, 1981). As in the math example, the teacher transforms from the holder of all knowledge
to the learning process facilitator. Educators that promote student agency, voice, and choice, are
equally promoting opportunities for students to expand on their prior knowledge and
experiences. A positive outcome in a constructivist learning environment when using technology
in the classroom is the shared learning experiences and collaboration among teachers and
students. Teachers and students share computer skills knowledge, reinforcing collaborative
learning and learned skills (Pourhosein Gilakjani et al., 2013). In addition to pedagogy, various
support is needed for technology integration from administrators, coaches, information
technology teams, and professional development. Researchers also cite those teachers who have
systems of support for using technology in the classroom saw the most significant benefit to
improving student learning and their learning experiences (motivation, satisfaction, and
enjoyment) and decreasing second-order barriers (Durff & Carter,2019; Ertmer, 2015; Weng &
Tang, 2014).
Technology Integration and Professional Development for In-Service Teachers
Funding technology initiatives are discussed in the plans to integrate technology globally,
nationally, and locally has increased, but there has not been a significant impact on student
learning (Niederhauser et al., 2018). Over the last 20 years, massive infrastructure changes in
28
schools included gains in hardware and software and funding for professional development to
support technology integration. However, Harrell and Bynum (2018) have indicated that
infrastructure is not considered when purchasing devices and how these will be used for
instructional purposes. Therefore, access to and investments in technology-rich resources do not
address the absence of integrating technology (Pittman & Gaines, 2015; Sanders & George,
2017).
Efforts to place technology in the classroom are an extremely complex process and do not
guarantee that pedagogical practices will change to include technology in instructional practices
(Fullan & Langworthy, 2013; Howard & Thompson, 2016; Inan & Lowther, 2010). Professional
development that motivates in-service teachers to integrate technology into instructional
practices has not reached its full potential and has fallen short of expectations (Niederhauser et
al., 2018). Nevertheless, there are successful programs that demonstrate one-to-one laptop use,
transformative teaching, and pedagogical changes that support 21st-century learning: Apple
Teacher Learning Center (2021), Google for Education (2021), Global Online Academy, and
Intel Teach courses (2021). All these programs offer ongoing technology-related professional
development that challenges traditional teaching strategies. Technology has a vital role in
education that, without it, in-service teachers are not prepared to deliver instruction that enhances
skills in problem-solving and collaboration. From infrastructure to software to programs, all
these factors are essential for developing teachers’ self-efficacy, which leads to changes in
pedagogical practices that help students build future-ready skills (Niederhauser et al., 2018).
Inservice Training Versus Professional Development
Inservice training and professional development provide different learning experiences
for teachers (Hamilton, 2015). However, both are considered opportunities that influence
29
teaching practice (Amadi, 2013; OECD, 2021b). Inservice training is usually on-site, attendance
is required, and is used to further school-level strategic plans. These plans include new curricula,
standards, or policies such as child safeguarding (Amadi, 2013). The purpose is to promote and
grow support for the institution’s agenda. These learning programs have little to no impact on a
teacher’s pedagogical practices or purpose-driven use of technology.
On the other hand, teachers seek professional development opportunities to improve their
skills and knowledge (Amadi, 2013; Ma et al., 2018; Williams, 2017). Teachers can pursue in-
person or online learning based on interest and convenience (Zhang et al., 2017). Attending
professional development seminars and conferences is usually paid for by the school, and
teachers can qualify for continuing education credits (CEUs), credit for licensures, or salary
increases (OECD, 2021b). Gaining new knowledge and learning new skills directly impact future
actions (Merriam & Tisdell, 2016). Therefore, educators need to continuously improve skills and
update pedagogical practices that enhance 21st-century learning. Attending professional
development is a choice, and upon completion, teachers are encouraged to make pedagogical
changes to their teaching practices (Hamilton, 2015). Furthermore, when teachers add
technology into the classroom and instructional practices, the learning environment changes
(Hamilton, 2015).
Access to professional development and instructional technology support encourages
practicing teachers to use technology in the classroom (Pourhosein Gilakjani et al., 2013).
Veteran teachers of the mid-1990s were more than likely born before computers were widely
used in schools and classrooms. Therefore, unlike pre-service teachers, current teachers may not
be exposed to an appropriately taught and modeled undergraduate technology methods course.
There is a positive relationship between a teacher’s willingness to integrate technology in the
30
classroom and their level of self-efficacy with computer skills and knowledge. In a survey of 350
teachers from Silicon Valley schools located in a technology-centric region of the United States,
55% strongly agreed that being proficient with computers affects a teacher’s willingness to
integrate technology (Hernández-Ramos, 2005). There is a need for continuous learning through
PLCs, vicarious learning experiences, and continued professional development, especially as
technology continues to change and evolve.
Professional development provides many options, opportunities, and approaches to
technology integration that in-service teachers may feel overwhelmed with so many choices that
are offered (Thomas et al., 2019). This may contribute to frustration when making decisions to
use technology for instruction effectively. Providing professional development and continued
support afterward assists teachers with knowing how to use the technology and understanding
the benefits of technology integration (Hur et al., 2016). Teachers with purpose-driven pedagogy
use that knowledge to learn how to use technologies they may be unfamiliar with yet want to
know more about. The intersection of teachers’ pedagogical knowledge and technological
knowledge is supported by showing teachers real examples of technology working within their
instructional practices (Hur et al., 2016; Williams, 2017). This professional learning positively
affects technology integration (Hur et al., 2016). Positive attitudes toward technology, a culture
of learning, administrative support, and adopting a constructivist stance all influence the use of
technology in the classroom (Durff & Carter, 2019). A teacher’s deep understanding of how
technological, pedagogical, and content knowledge works together simultaneously (Koehler &
Mishra, 2009) and solid constructivist beliefs positively influence the teacher’s ability to
integrate technology into instructional practices. Constructivist teachers are also strong advocates
of students’ use of technology and create meaningful learning experiences (Mayer, 2012) and
31
positively influence their students’ use of technology in their learning (Pourhosein Gilakjani et
al., 2013).
TPACK
Technology pedagogy content knowledge (TPACK) derives from Lee Shulman’s work
(1986, 1987) about pedagogical content knowledge (PCK). The TPACK framework shows the
interconnections between technological pedagogical and content knowledge (Willermark, 2018).
Shulman discussed that students’ comprehension is linked to teachers’ understanding of the
content when integrated with appropriate pedagogical approaches (V oogt et al., 2013). In other
words, what is taught is just as important as how educators teach the content for student
understanding. In 2006 and again in 2009, Mishra and Koehler revised this work to include
technology knowledge (Koehler et al., 2013; V oogt et al., 2013). The development of the TPACK
framework helped educators visualize the importance of teaching effectively with technology.
Content knowledge (CK) refers to teachers’ understanding of their subject (Shulman 1986).
Pedagogical knowledge (PK) refers to teachers’ learning and continuous skill development to
improve lesson delivery. Technology knowledge (TK) refers to a teacher’s ability to continually
assess and select the appropriate technology and adapt as the technology changes continuously.
For teachers to move toward a student-center constructivist pedagogical approach, they need to
know how to use technology tools and how those tools are used to effectively teach their content
(George & Sanders, 2017).
The 2009 TPACK framework was revised and still includes the same three knowledge
domains of TK, PK, and CK. However, it now shows each area intersecting to produce three
additional knowledge domains: PCK, TPK, and TCK (Figure 1). The center of these intersections
offers TPACK and demonstrates the importance of supporting and developing teacher educators’
32
TPACK (Tondeur et al., 2019). An educator’s TPACK knowledge and beliefs about the three
primary knowledge domains are intertwined and determine whether or not a teacher will create
or re-design technology-infused lessons (Tondeur et al., 2019; V oogt et al., 2013). Teachers who
have a deep understanding of how the three knowledge domains work together also understand
each of these knowledge domains as separate entities. An educator with a complete experience of
the subject matter and how to present and teach that subject has a TPACK knowledge foundation
to make better decisions on the purposeful selection of technology tools to enhance their
instructional practices.
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Figure 1
TP ACK Framework
Note. From Using the TP ACK Image, by The TPACK Framework, 2011, (https://tpack.org).
Reprinted with permission of the publisher, © 2012 by tpack.org at http://tpack.org.
Understanding TPACK and the connections between content, pedagogy, and technology
can be linked to an educator’s willingness and readiness to integrate technology effectively into
instructional practices (Angeli & Valanides, 2013; Joo et al., 2018). Teachers’ self-efficacy and
their favorable experiences with technology can directly link their intentions to use technology in
the classroom. However, having only technology knowledge does not ensure its effective use
(Guggemos & Seufert, 2021). It is far easier to be distracted by the shiny new tool, site, or
program than to develop deep reflective practices that connect one’s content and approach to
34
available or future applications or technologies. Teachers who develop TPACK have more
confidence in their ability to select and use technology in their instructional practices
appropriately (Maeng et al., 2013). Therefore, experienced teachers with the confidence and
positive experiences with TPACK can influence instructional practices for 21st-century learning
environments (Tondeur et al., 2019).
Self-Efficacy
Self-efficacy is the belief in oneself to succeed in tasks and skill performance (Bandura,
1995). According to Bandura (1986, 1997a), educators must have sufficient self-efficacy and
human agency to administer control in choosing actions that will affect their lives and positively
affect performing a skill. In other words, for educators to consider integrating technology into
instructional practices and eliminate second-order barriers to integrating technology, they need to
believe they can perform the task successfully (Harris, 2016). These barriers include teachers’
willingness to change, beliefs about computers, and attitudes towards technology (Teo et al.,
2017). Teachers with solid self-efficacy will be motivated to set higher goals and spend the
needed effort to achieve those goals (Bandura, 1997a). Self-efficacy influences instructional
practice choices and a teacher’s belief in changing student learning outcomes (Poulou et al.,
2019).
Bandura (1986, 1995) labeled four sources of self-efficacy, but the two most potent are
mastery performance experiences and vicarious learning. Mastery experiences are the most
influential source of self-efficacy and evolve as teachers reflect on their performance (Bandura,
1995). The sequence to building self-efficacy is completing a task, evaluating the task results,
and making adjustments to reach competency. Self-efficacy increases as teachers gain knowledge
and believe they have overcome obstacles rather than simply completing the task (Bandura,
35
1997a). Self-efficacy can be lowered if there is a perception of failure. Teachers who have high
self-efficacy in their instructional practices use this to create mastery experiences for their
students (Bandura, 1995). In contrast, researchers have cited low self-efficacy as a first-order,
internal barrier because it can affect teachers’ instructional technology practices (Birisci & Kul,
2019; Hsu, 2016).
Vicarious learning is the second most influential source of building self-efficacy and
helps inform educators about what they can do. Teachers can observe the actions of others and
seek information by watching others model. Self-efficacy is positively influenced if the teacher
perceives similarities with the model teachers and deems them masters in their field (Bandura,
1995). This empowers the teacher to attempt new learning. Instructional and technology coaches
use online instructional videos and classes to model vicarious learning that demonstrates new
technology tools and integration. Vicarious learning is compelling if it helps teachers avoid the
negative consequences of failure (Schunk, 2020). Effective models help the teacher-learner build
knowledge and skills to strategically manage new demands on their instructional practice
(Bandura, 1995). Vicarious learning is most successful when a teacher is partnered with an
educator with similar pedagogical styles (Barton & Dexter, 2020). Teachers who are seen as
knowledgeable about technology integration work with other educators to eliminate barriers that
may prevent classroom technology usage. Teachers accomplish this by modeling and providing
1:1 vicarious learning experiences. Teachers who positively influence student learning with
successful technology integration are encouraged to break the status quo on teacher-centered
instructional practices and integrate technology into constructivist pedagogy practices (Durff &
Carter, 2019).
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Teacher Self-Efficacy
Studies and literature have cited that teacher self-efficacy (TSE) is a strong predictor of
teachers’ beliefs about teaching (Poulou et al., 2019; Suprayogi et al., 2017) and intentions to use
technology in the classroom (Banas & York, 2014; Jeung, 2014; Valtonen et al., 2015; V oogt et
al., 2013). These beliefs affect teachers’ choices to integrate technology into instructional
practices. Bandura (1986) defined self-efficacy as the confidence in one’s ability to perform a
task. Building on Bandura’s work, teacher self-efficacy is associated with a teacher’s belief that
they positively impact student learning, performance, and outcomes (Poulou et al., 2019). For
example, suppose a teacher believes that scaffolding strategies will positively affect student
learning. They will use this teaching strategy if they believe in their ability to effectively use it
(Zee & Koomen, 2016). Therefore, teacher self-efficacy can influence an educator’s motivation
and instructional delivery practices. It is a strong predictor of a teacher’s choice to use new
instructional delivery strategies and positively affects student learning (Poulou et al., 2019; Zee
& Koomen, 2016). According to a study by Klassen and Chiu (2011), TSE for instructional
teaching strategies positively predicted an in-service educator’s commitment to the teaching
profession. Barouch Gilbert et al. (2014) and Klassen et al. (2013) found similar results with
teachers across multiple countries and different levels of commitment related to teaching. As a
result, in-service teachers with higher self-efficacy are more committed to student-centered,
constructivist pedagogy that enhances students’ opportunities to engage and be interested in
learning (Zee & Koomen, 2016).
Participation in professional development opportunities is an example of mastery and
vicarious learning (Perera et al., 2019). These experiences can positively affect a teacher’s self-
efficacy beliefs (Yoo, 2016). In a study of 148 in-service teachers, educators stated that their self-
37
efficacy increased as they gained knowledge by participating in professional development. These
mastery experiences include participation in an online class, engaging in discussions on scholarly
articles, working in a professional learning community or with a coach, and timely applying their
new knowledge in the classroom (Yoo, 2016). Working with a mentor, a coach, or a professional
learning community to create learning experiences positively impacts a teacher’s self-efficacy
beliefs. It benefits both the mentor and mentee (Carney et al., 2016).
Similarly, Cho and Shim (2013) found evidence linking teacher self-efficacy and mastery
learning experiences and pedagogical approaches. In yet another example, Saudelli (2016)
discusses a 10-year veteran whose self-efficacy increased through both vicarious and mastery
experiences when using an iPad within the class context. For a year, the educator attended a
professional development session run by an expert Apple© representative, read technology
blogs, and experimented with using iPads in the classroom. The study noted that the teacher’s
self-efficacy beliefs evolved during this time from being skeptical about the pedagogical values
of using iPads to developing real-world connections across disciplines for her students. At first,
students used the devices for simple reading tasks, and evolved into personalized and
collaborative student-centered learning activities with applications such as iMovie
TM
, Clips, and
Book Creator.
Researchers have argued that providing more successful mastery experiences and
vicarious learning directly increases teacher self-efficacy (Kimmons et al., 2015; Yoo, 2016).
Teachers with high levels of self-efficacy create meaningful learning experiences in classroom
instruction. Led by expert teacher-leaders, professional learning communities provide mentoring
relationships, peer support, and shared experiences using technology in instructional practices.
PLCs are designed for teachers to collaborate on common goals for developing curriculum and
38
identifying best pedagogy practices. This learning can occur naturally, implemented immediately,
and educators can evaluate and self-reflect on their experiences. Actively reflecting and receiving
feedback is necessary for meaningful changes in instructional practices (Luttenberg et al., 2017),
and teachers use this as evidence to inform future instructional practices (Farrell & Jacobs,
2016). By participating in PLCs, members have opportunities to build technology skills,
integrate technology with content, and increase self-efficacy (Paulus et al., 2020). Teachers with
high TSE and content knowledge often collaborate with a PLC to implement data-driven
instructional decisions (Zee & Koomen, 2016). These findings are consistent with Bandura’s
(1997) beliefs that mastery experiences and vicarious learning can positively affect teacher self-
efficacy if designed to enhance teachers’ knowledge (Yoo, 2016). Teacher self-efficacy is a
decisive factor that influences teacher behavior and performance in the classroom (Gokcek et al.,
2013; Joo et al., 2018), and technology knowledge could be a good predictor of a teacher’s use of
technology (Scherer et al., 2019; V oogt et al., 2013).
Teacher Self-Efficacy and TPACK
Teacher self-efficacy indicates a teacher’s intentions, choices, and motivation to use new
instructional strategies (Peker & Erol, 2018). Many researchers have also found that TSE is a
variable that influences teachers’ behaviors and instructional strategies in the classroom (Morris,
2019; Perera et al., 2019; Poulou et al., 2019; Zee & Koomen, 2016). Technology integration
self-efficacy is the level of confidence that teachers have in their ability to use technology in
instructional practices in a meaningful way (Hur et al., 2016). The definition of technology self-
efficacy is broad and not attached to a single task. Instead, it is connected to different tasks in the
present and future uses of technologies. Previous technology experience is directly correlated
with technology integration self-efficacy (Birisci & Kuui, 2019; Lemon & Garvis, 2016).
39
Teachers’ beliefs about using technology in instructional practices are linked to increased
TPACK knowledge. Equally important are teacher self-efficacy beliefs that influence teachers’
intention to use technology in the classroom. Numerous researchers have cited teacher beliefs as
an internal barrier to technology integration because it has been shown to affect instructional
technology practices (Birisci & Kul, 2019; Hsu, 2016). Feeling confident with technology and
technology integration is also essential and achievable with mastery experiences and engagement
with technologies. Choosing to use the computer, internet, mobile devices intentionally, and
various applications are vital to achieving high levels of technological self-efficacy (Kiili et al.,
2016). A study about TSE and the 1:1 laptop program showed that high school teachers who
demonstrated high TSE levels are more likely to utilize technology in instructional practices
(Morrison, 2019).
TPACK is a framework that provides a structured format for teachers to understand how
technology is integrated into instructional practices and provides how this integration process
takes place (DeSantis, 2016; Kimmons & Hall, 2018; Koehler et al., 2013). In a study of seven
school or school districts, Harris and Hofer (2017) identified five different themes that emerged
from the use of the TPACK framework: a connector between instructional coaches and teachers,
grass-roots initiative to intentionally use TPACK within existing coaching and PLC structures, a
check and balance system to collaboratively work to reconstruct lessons for TPACK, planning
within PLCs to use technology as an instructional tool, and scaffolding approach to selecting
tools to build technology knowledge (Harris & Hofer, 2017). In addition, the TPACK framework
is flexible and recognizes that a one-size-fits-all approach to technology integration does not
appreciate a teacher’s technology strengths or learning needs.
40
While each of the participants approached technology integration differently, each was
careful to balance the importance of technology, pedagogy, and content in the professional
development experiences for teachers. TPACK knowledge, competency, and understanding lead
teachers to integrate technology into instructional practices (Lee & Tsai, 2010). Many forms of
professional development help teachers see the benefits of technology integration and positively
influence a teacher’s confidence to integrate technology (Hur et al., 2016). Taking classes, in
person or online, attending professional development workshops, or working 1:1 with a teacher
expert or coach positively influences teachers’ attitudes and beliefs towards technology use in the
classroom (Hur et al., 2016). These learning opportunities positively influence instructional
practices, TSE, and intentional technology use (Joo et al., 2018). TSE beliefs influence teachers’
transformational use of technology, from using technology to deliver content to constructivist
practices that emphasize a student-centered learning environment and approach to learning
(Birisci & Kul, 2019; Han et al., 2017).
The study by Perera et al. (2019) suggests that teachers can have different levels of self-
efficacy in multiple knowledge domains. This would mean that teachers could have high self-
efficacy in content and pedagogical knowledge but could lack self-efficacy in the technological
domain (Perera et al., 2019). While confidence may be increased in more than one domain, this
study suggests that a lack of confidence in one domain area would likely decrease exploring new
instructional strategies that would benefit student learning (Perera et al., 2019; Zee & Koomen,
2016). To make learning meaningful, teachers need to know all three TPACK domain areas and
recognize that each domain knowledge does not act independently from the others. The use of
technology needs to be active, intentional, and motivating for students by designing lessons that
offer voice, choice, and action to construct new knowledge based on the understanding and
41
sense-making of their experiences. This type of meaningful learning is the foundation of the
constructivist teaching approach. (George & Sanders, 2017).
Research has shown that in-service teachers’ use of technology in instructional practices
is affected by a teacher’s technology self-efficacy and beliefs that technology will positively
impact student learning (George et al., 2018, López-Vargas et al., 2017; Poulou et al., 2019; Zee
& Koomen, 2016). In-service teachers vary in their technology strengths and TPACK, suggesting
a need for ongoing technology support to provide mastery experiences and vicarious learning.
These experiences are provided through professional development, 1:1 training, and working
with other experienced teachers. Different instructional practices can positively affect teacher
self-efficacy, as found in the study on providing learner-centered instructional practices (Choi et
al., 2019). For TPACK to be used and implemented, using the framework must ensure that equal
representation is given to each domain (Harris & Hofer, 2017). While internal barriers still exist,
teacher self-efficacy improves when teachers successfully overcome these barriers to complete
tasks. The challenge for most schools is to provide practical TPACK learning experiences to
positively affect technology self-efficacy.
Conceptual Framework
Integrating technology into instructional practices has many layers that need to be
examined: Influencing factors, TPACK, and self-efficacy. Equal access to digital materials and
resources is not enough to ensure equitable opportunities to acquire knowledge and skills so that
the needs of all students are met. As shown in Figure 2, effectively teaching with technology
begins with understanding how the three knowledge domains of TPACK, technology, pedagogy,
and content, provide a framework to design and deliver content-specific, purpose-driven
instruction using student-centered strategies. Developing strategies to improve teacher self-
42
efficacy and confidence and provide positive mastery educational experiences are strong
predictors of teachers embracing technology integration. Moving towards a constructivist
teaching approach will lead to authentic and meaningful uses of technology to support students
in building knowledge together.
Figure 2
Conceptual Framework
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This quantitative research study explores relationships between independent variables of
TPACK, teacher self-efficacy, and teacher-specific demographic information (see Figure 2). The
dependent variable of technology integration unearths information that explains why teachers use
technology in their instructional practices. In the context of Hillier International High School,
teachers and students work in a well-established 1:1 technology program, and the institution has
a strategic plan with specific language that supports teachers’ use of technology in the classroom.
The technology support systems emphasize personal and small group professional development
to design lessons that will engage students in meaningful learning opportunities that support
21st-century learning. The survey instrument will collect data from participants about their
experiences with TPACK knowledge and teacher self-efficacy to give a unique opportunity to
explore these constructs through the lens of the participants.
Social learning theory and constructivism are part of the theoretical framework for this
study to explore teachers’ perceptions about their technological pedagogical knowledge and
influences on technology integration. Albert Bandura (1997b) suggested that humans learn to
think and behave by interacting with the social environment. This is done by observing others’
model skills, techniques, strategies, rules, beliefs, and attitudes and having opportunities to
repeat these interactions in different environments. As a result, people can acquire knowledge
and learn to act accordingly based on the modeled behaviors. Humans can also learn about the
consequences of the modeled behaviors and weigh their usefulness related to their own beliefs
about expected outcomes (Schunk, 2020). The four components of Bandura’s social learning
theory are attentional processes, retention processes, motor reproduction processes, and
motivational processes (Bandura, 1977b).
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When educators acquire new knowledge on integrating technology into instructional
practices, they are more likely to pay attention to behavior modeled by someone considered
attractive, knowledgeable, or interesting (Bandura, 1977b). Furthermore, if there is a chance to
perform the task in their classroom, more attention is devoted to modeling (attentional
processes). Therefore, teachers must receive immediate feedback and opportunities to practice
the modeled behavior to retain the behavior (retentional process). These practice opportunities
allow teachers to decide whether or not they will continue with the behavior and determine the
level at which they plan to do so. Positive outcomes and responses are more likely to influence
and motivate teachers to continue with the behavior (motivational process). Teachers, knowingly
or unknowingly, base their performance decisions on their level of self-efficacy. Teachers who
feel comfortable and confident are more likely to continue with the modeled behavior if they find
the behavior rewarding and value the outcomes (Bandura, 1977b).
Many researchers have identified internal and external barriers that prevent teachers from
using digital devices and technologies in the classroom (Durff & Carter, 2019, Ertmer, 1999;
Hsu, 2016; Hur et al., 2016; Sang et al., 2011). These barriers are extrinsic and intrinsic (Huda et
al., 2018; Kim et al., 2013). Over the last 20 years, diminishing the extrinsic barriers such as
access to laptops and high-quality internet has made great strides. However, eliminating the
intrinsic barriers has been a much more arduous task to complete as educators have differing
pedagogical beliefs, attitudes, and levels of self-efficacy regarding technology use in the
classroom. Furthermore, these barriers may also be influenced by the subject context knowledge,
learned pedagogical practices, and cultural contexts. Thus, it is a complex system of challenges
to ensure technology usage in instructional practices.
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Self-efficacy is the belief and confidence in oneself to succeed in task performance
(Bandura, 1995). Educators with high self-efficacy are more likely to be comfortable with
change, see barriers as challenges rather than obstacles, and pursue personal growth and
development (Eun, 2019). Self-efficacy is critical to promote teacher agency and positive beliefs
about technology integration (Schunk, 2020). The higher a teacher’s self-efficacy is with a task,
the more likely they are motivated to complete it. High self-efficacy also indicates a willingness
to persist when internal or external barriers are present. This study will focus on in-service
teachers’ self-efficacy with integrating technology into instructional practices based on teachers’
self-reported skills and knowledge with TPACK (technology pedagogy and context) and how
that may affect their self-efficacy with technology integration. If Bandura’s social learning theory
holds, educators who have opportunities for vicarious learning with technology and practice
these tasks continuously will have higher self-efficacy with technology integration.
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Chapter Three: Methodology
This study aims to identify the factors that pertain to teachers’ use of technology in
instructional practices. Specifically, this research looked at different variables that included
teachers’ self-reported self-efficacy (Bandura, 1997b) and technology pedagogical content
knowledge (TPACK) to utilize technology in instructional practices effectively (Koehler et al.,
2013). Many researchers (Scherer et al., 2017; Schmid et al., 2020; Scott & Nimon, 2020;
Valtonen et al., 2017; Willermark, 2018) have cited that self-assessment of technology
competence is a common methodology used for TPACK assessment. It is also noted that self-
efficacy data revealed from self-assessment instruments is a good indicator of teachers’ use of
technology (Scherer et al., 2017; Voogt et al., 2013). This chapter provides a detailed description
of the methodology applied to this study. It outlines the setting, sample and population, survey
instrument, research questions, data collection methods, the method of analysis of the data, and
ethical concerns.
This study examines the factors that prevent teachers from using technologies to enhance
instruction in the classroom. The study focuses on the following questions to understand the
relationships between the independent variables of teachers’ years of experience, participation in
technology professional development, TPACK knowledge, and technology self-efficacy, with
that of the dependent variable, level of technology integration:
1. Is there a relationship between high school teachers’ attributes (years of experience
and participation in professional development) and their level of technology
integration?
2. Is there a relationship between high school teachers’ technological pedagogical
content knowledge (TPACK) and their level of technology integration?
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3. Is there a relationship between high school teachers’ technology self-efficacy and
their level of technology integration?
A non-experimental descriptive study seeks to understand an in-service teacher’s level of
use and confidence to integrate technology into pedagogical practices. This quantitative research
design will seek to examine the relationships between variables. These variables can be
measured using a research instrument to produce numerical data, which will be analyzed through
various statistical methods and procedures (Salkind, 2017). Graphical displays will visually
represent the data and support the written explanations (Jebb et al., 2017). A survey is ideal for
efficiently capturing large amounts of self-reported information, such as participants’ attributes,
behaviors, and abilities (Robinson & Leonard, 2019).
Sample and Population
The setting for this study is a private, international school that serves an Early Learning
Center (3 years old) through 12th grade. Hillier International Secondary School (HISS,
pseudonym) prides itself on being the world’s leader in international education. There are 4,000
students and 650 adults represented by administrators, educators, and instructional assistants.
The population represents 56 nationalities, with most holding passports from North America and
the United States. HISS ranks in the high 90th percentiles for standardized testing in AP, SAT,
and MAP scores. Ninety-nine percent of the graduating students seek post-high school education
and are accepted at universities worldwide.
The international secondary in-service teachers included 225 middle and high school
educators on a full-time contract for the 2021–2022 school year. This site provided access to the
sample that will represent the population and help to ensure the study has a high degree of
generalizability. The faculty are foreign hired teachers on government-issued work passes or
48
permanent resident cards. The teachers are mainly from the United States and include expatriates
from Canada, Australia, India, New Zealand, France, Mexico, Peru, and Spain. All teachers must
possess a bachelor’s degree from an accredited university; however, 74% of the faculty also hold
either a master’s or doctorate. In addition, educators must have a valid teaching license to be
employed. The initial employment contract is 2 years, with each additional year renewed
annually. The average teacher tenure at this international school is 7.3 years, 2 years above the
current international average (Search Associates, 2019).
The unit of analysis for this study is a convenience sample of individual secondary school
teachers in this private international school that utilizes an American curriculum. This site allows
for the convenience of collecting and analyzing data and is relevant to the primary purpose of
this study (Lochmiller & Lester, 2017). The convenience sample was used to determine if
relationships existed between the independent variables (years of teaching experience,
participation in professional development, TPACK knowledge, and technology self-efficacy) and
the dependent variable, level of technology usage. The results may have substantial implications
for educators in the elementary division and other international schools that operate under the
same guidelines as WASC and an American curriculum (Salkind, 2017).
Instrumentation
The pre-established instruments, administered electronically via email, asked the in-
service secondary teacher to self-report and self-reflect on their current instructional practice to
integrate technology. The anonymous, online instruments include demographic questions
(Appendix A), Concerns-Based Adoption Model (CBAM) Levels of Use of an Innovation
(Appendix B), TPACK Questionnaire (Appendix C), and Technology Integration Self-Efficacy
scale (TISES; Appendix H). The authors of the CBAM (Appendix B), TPACK Questionnaire
49
(Appendix C), and TISES (Appendix D) granted permission to use each instrument in this
study. The combined instruments took participants an average of 13 minutes to complete. Using
descriptive analysis to organize and identify the unique characteristics and constructs of the data
sets was ideal for this correlation study to determine if relationships exist between these
variables. Additionally, a Spearman rank correlation and Kruskal-Wallis test were used to
determine if relationships exist between variables, identify the degree of this relationship
(Creswell, 2013; Lochmiller & Lester, 2017; Salkind, 2017), and answer the research questions.
Attribute Demographic Questions
The demographic questions (Appendix A) asked participants to identify years of teaching
experience and how often they participated in technology-oriented professional development
training. The participants were directed to select one answer from the response choices for each
statement. No other identifying information was collected, and this data is not sufficient to
identify the individuals who provided the data.
Concerns-Based Adoption Model (CBAM) Levels of Use of an Innovation
The first survey instrument used is the Concerns-Based Adoption Model (CBAM) Levels
of Use of an Innovation (Appendix B). The authors grant permission to use this instrument for
non-profit scholarly and research activities (Griffin & Christensen, 1999). The researchers
appreciate acknowledgments in the references, usage notification, and published results using
their instruments (Appendix D). This survey is a quick self-assessment that indicates the level of
technology integration along a technology use continuum. The participant chooses the option
that best matches their level of technology integration. There are eight levels in which the
participant may only select one. The levels are non-use (0), orientation (1), preparation (2),
mechanical use (3), routine (4a), refinement (4b), integration (5), and renewal (6). This
50
instrument is a single-item survey per level that cannot measure internal consistency reliability
(Salkind, 2017).
TPACK Questionnaire
The second instrument is the Technological Pedagogical Content Knowledge (TPACK)
Questionnaire (Appendix C). This original questionnaire contained 57 items that measured pre-
service teachers’ knowledge in the seven TPACK domains (Schmidt et al., 2009). This
questionnaire was modified from its original state to eliminate subject-specific language that
narrowed the focus to only math and science teachers (Jang & Tsai, 2012). Jang and Tsai (2012)
conducted their study with secondary in-service math and science educators in Taiwan. This
instrument aligns well with the current population of secondary school educators at Hillier
International Secondary School and allows data to be collected from all content areas.
For this study, permission was obtained from both Jang & Tsai (2012) and Schmidt et al.
(2009); however, Jang and Tsai’s version of the survey instrument was used for this study
(Appendix C). The questionnaire contains 35 items that use a Likert style scale to measure self-
reported Technological Pedagogical Content Knowledge (TPACK). There are five items for each
domain (TK, CK, PK, TCK, PCK, TPK, and TPCK). The researchers (Jang & Tsai, 2012)
produced reliability data for four of the subscales on their questionnaire that were content
knowledge (CK) which has a Cronbach’s α = .862, pedagogical content knowledge (PCK) with α
= .913, technology knowledge (TK) with α = .892 and TPACK with a Cronbach’s α = .960. A
Cronbach’s α greater than 0.80 is a good indicator of reliability (Salkind, 2017).
Response options on the TPACK questionnaire ranged from 1 = strongly disagree to 4 =
strongly agree as it relates to the participant’s knowledge of each TPACK domain. A neutral
point, neither agree nor disagree, was not a response option. The survey guided respondents to
51
express their feelings and commit to a positive or negative answer choice (Robinson & Leonard,
2019).
A few items were revised for this study, and the demographic questions were eliminated
from the original survey in favor of the demographic items stated earlier. For example, the
question “I can use interactive whiteboards (technology) to promote learning and inquiry of
lessons” was revised to “I use interactive technology (such as iPads, smartphones, or applications
such as Pear Deck, back channels, or polls) to promote learning and inquiry of lessons.” The
reason for revising this term was to allow participants to answer this item based on the
technological tools widely available in the teachers’ classrooms.
Technology Integration Self-Efficacy Scale (TISES)
The third survey instrument, the Technology Integration Self-Efficacy scale (TISES)
(Appendix D), was used as a pre-and post-survey to examine the impact of vicarious learning
experiences on pre-service teachers’ level of self-efficacy to integrate technology into
instructional practices (Wang et al., 2004). It was hypothesized that vicarious learning
experiences that modeled successful technology integration would increase self-efficacy levels
for technology integration versus those who did not have access to vicarious experiences (Wang
et al., 2004). The survey uses a four-point Likert scale to measure a participant’s self-reported
self-efficacy beliefs for technology integration. The TISES questionnaire has 21 items, in which
the participant was asked to rate their level of agreement with the statement. Response items
ranged from 1 = strongly disagree to 4 = strongly agree as it relates to the participant’s
confidence level regarding technology use. A neutral point, neither agree nor disagree, was not a
response option to remain consistent with answer choices from survey to survey. The survey
guided respondents to express their feelings and commit to a positive or negative answer choice
52
(Robinson & Leonard, 2019). The instrument was measured for both content and construct
validity in a previous study. It is highly reliable and valid for measuring self-efficacy for
technology integration (Wang et al., 2004). Using the Cronbach alpha coefficient, the pre-survey
was α = .94, and the post-survey was α = .96, evidence of the instrument’s reliability (Wang et
al., 2004).
Data Collection
Data collection for this survey was via an online survey. Hillier International Secondary
School’s leadership team requires approval from the University of Southern California
Institutional Review Board (Appendix H), and a written request was sent to divisional leadership
for permission to collect data (Appendix I). Upon approval, 225 participants representing
teachers in the secondary school received a survey link via an email invitation from the
divisional principal to participate in the study. The email contained information about the study,
its purpose of understanding in-service teachers’ perceptions on integrating technology into
classroom instructional practices, methods used to ensure confidentiality, and guidelines to
adhere to USC’s research policies for data protection. The letter also informed participants that
the survey was anonymous and of their right to opt-out of any question or the entire survey at
any time. The demographic information collected was insufficient to obtain the identities of
individuals who provided data. Participants were given a 3-week window in October 2021 to
complete the online survey that included a weekly reminder via the principal’s weekly faculty
email to complete the survey. Surveys are a cost-effective way to collect participants’
perceptions, personal experiences, points of view, and the data collected is easily converted and
analyzed (Lochmiller & Lester, 2017).
53
Data Analysis
Qualtrics software was used to construct and collect the survey data (“Qualtrics,” 2021),
and IBM Statistical Package for Social Sciences (SPSS) was used to analyze the data (“SPSS
Statistics Software,” 2021). Once the data was collected, it was exported from Qualtrics and
imported to the SPSS software for the initial analysis. The SPSS Statistics Software prepared the
data sets for descriptive and analysis tests (“SPSS Statistics Software,” 2021). All incomplete
responses from the survey were removed via the listwise method within the SPSS software.
The three research questions for this study sought to determine the following
relationships: (a) the relationship between teachers’ level of education and participation in
professional development and level of technology integration, (b) the relationship between
teachers’ knowledge of TPACK and level of technology integration, and (c) the relationship
between teachers’ level of self-efficacy and level of technology integration. As a starting point to
examine the research questions, it is assumed that there is no relationship between these
independent variables (level of education, participation in professional development, TPACK,
and self-efficacy) and the dependent variable of technology integration.
Spearman rank correlation and Kruskal-Wallis analysis determined the relationships
between the independent variables (years of teaching experience, frequency of participating in
professional development, and TPACK) with the dependent variable of technology integration. It
is noted that the dependent variable of technology integration is ordinal with eight levels and the
independent variables are ordinal or scales. The years of experience independent variable is
categorical and represents seven categories of years taught. A Kruskal-Wallis analysis was used
to determine the relationship between the independent variable of technology self-efficacy and
levels of technology use.
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Researcher’s Positionality
Technology has profoundly impacted my life and choices for the last 25 years. I have built
digital capital by gaining knowledge, experience, skills, and improved access to education that
directly improved my digital competence. Unfortunately, witnessing disadvantaged groups
become further marginalized due to a lack of access to digital materials is a reality. We can all
construct knowledge by critically analyzing and questioning what is happening globally, but not
having digital access makes learning construction more difficult. We are empowered to
challenge and build new knowledge with digital access and meaningful use. Believing everyone
can learn and deserves equitable opportunities to build digital capital and competence is what I
bring to this study.
Every experience that I have had has allowed me to look through many different lenses,
which has shaped my positionality. It is a given that my positionality shapes my epistemology. I
identify as a white female educator and know that privileges afforded me come with
responsibility. I can freely cross borders with dual passports and live a comfortable life as a
credentialed, non-disabled scholar in the lucrative ever-changing technology field. I am not
always viewed as an equal contributor to technology as a woman. Being told that I cannot do
something has made me work harder to learn more to make positive contributions. Through
experiences, a person gains knowledge. As Takacs (2002) has indicated, “understanding how
one’s experiences and identities have shaped what we know about the world” (p. 31) illustrates
that the ability to gather knowledge is all around us every day.
The biases that I bring to this research are real challenges for some teachers. As a
technology teacher, the curriculum I taught evolved, and this curriculum needed to update each
year. The curriculum design meant constant change with multiple possibilities and realities to
55
each question and project. While textbooks were available, most would be out-of-date within a
few months of purchase. Therefore, access to real-time information via the internet was cost-
effective, practical, and beneficial. With a constructivist worldview, using technology produces
many viable solutions to problems, and there are means and methods to provide meaningful
learning opportunities for students with technology. However, I need to be conscious and aware
that other learners are not as comfortable as I am with change. The real challenge will be
constructing new knowledge to build self-efficacy through learning experiences to become
lifelong learners and informed consumers. When teachers, like students, feel safe and valued,
they can learn. When teachers have access to professional development, collegial support, and
digital access to materials and tools, positive attitudes will inform technology instructional
practices. Together we can become experts in supporting our community, and in doing so, we
develop respect and move to celebrate our differences to continue creating new knowledge
together.
Summary
This quantitative research aimed to evaluate teachers’ level of self-efficacy and
confidence to integrate technology into international teachers’ instructional practices. Using the
three combined survey instruments, this study examined the components of teachers’ technology
self-efficacy and TPACK knowledge related to integrating technology into instructional
practices.
This chapter discussed the details of the research methods used and the design for the
quantitative study, described the study’s purpose, research questions, target population,
instruments for data collection, and data analysis. This study used a convenience sampling of
full-time secondary teachers during the 2021–2022 school year at the private international
56
school. Consent for the anonymous research study was obtained through a letter addressed to the
school’s administration and teacher participants (Appendix J). The descriptive data and statistics
were computed and analyzed to understand the research questions.
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Chapter Four: Results
This study intended to investigate relationships between the independent variables of
years of teaching experience, participation in professional development, TPACK (technological
pedagogical content knowledge), and technology self-efficacy, with the dependent variable of
the level of technology integration among secondary in-service teachers at an international
school. I am interested in examining the statistical significance of how these variables correlate
to technology integration. For example, researchers have identified teacher self-efficacy as a
factor strongly correlated to a teachers’ choice and motivation to use new instructional strategies
(Morris, 2019; Peker & Erol, 2018; Perera et al., 2019; Poulou et al., 2019: & Zee & Koomen,
2016). Similarly, Lefebvre et al. (2017) found the pillars of TPACK to be strongly correlated
with influencing teachers’ pedagogical decisions about technology integration. Likewise,
teachers’ technology experience correlates with technology integration self-efficacy (Birisci &
Kuui, 2019; Lemon & Garvis, 2016). Based on the responses received from the combined
TPACK, TISES, and the CBAM-LoU, descriptive statistics were used, and nonparametric
bivariate analysis was run (Spearman and Kruskal-Wallis) to determine if there were significant
relationships between each of the independent variables and the level of technology integration.
Demographic Data
Approval to conduct the research study was granted by the Internal Review Board at the
University of Southern California in October 2021 (Appendix H). Permission was given from the
principals of the secondary schools to invite educators to participate in the online survey. The
online survey link was distributed in the weekly email principals sent out each Sunday. The
combined survey of 59 items took less than 13 minutes to complete and included two
58
demographic questions, CBAM-LoU technology integration levels, the TPACK questionnaire,
and the TSES. The authors of the instruments granted permission for their use (Appendix E–G).
Data collection began on November 1, 2021, and ended on November 19,
2021. The
sample included 7–12 grade teachers at Hillier International Secondary School (pseudonym),
located in Southeast Asia. The principals allowed the survey to be listed in the teachers’ weekly
brief for three weeks, which served as a reminder for participation. Forty–three respondents, out
of the 225 recipients of the weekly brief, completed the survey. This yielded a response rate of
19%. Participants that did not complete the full questionnaire were removed from the dataset
using listwise within the SPSS software (“SPSS Statistics Software,” 2021). The small sample
size made it difficult to obtain normally distributed data; as such, the approaches for data
analyses were adjusted as needed. As a result of the sample size, generalizing these results to a
larger population poses challenges; however, exploring respondents’ insights remains valuable.
A descriptive analysis was used to examine teachers’ attributes (years of teaching
experience and frequency of professional technology development) and to describe the variation
in the dependent variable, levels of technology use. The survey asked participants to select one
of six category options to indicate the number of teaching years. The seven categories were: 0 to
5 years, 6 to 10 years, 11 to 15 years, 16 to 20 years, 21 to 25 years, 26 to 30 years, and 31 or
more years (Table 1). Each category was coded in numerical order from one (0 to 5 years)
through seven (31 or more years.) Most participants (n = 12; 27.9%) had 21–25 years of teaching
experience. The sample consisted of zero people with 0–5 years of experience, seven people with
6–10 years of experience, seven with 11–15 years of experience, nine with 16–20 years of
experience, twelve people with 21–25 years of experience, and six people with 26–30 years of
experience. Two participants reported more than 31 years of teaching experience.
59
Table 1
Years of Teaching Experience
Years n Percent
6–10 years 7 16.3
11–15 years 7 16.3
16–20 years 9 20.9
21–25 years 12 27.9
26–30 years 6 14.0
31 or more years 2 4.7
Total 43 100.0
Likewise, participants were asked to select one of six category options to indicate the
frequency of attendance in technology-oriented professional development over the course of 1
school year. The six categories were: none in the last year, annually, twice per year, four times
per year, six times per year, and monthly (Table 2). Each category was coded numerically from
one (none) through six (monthly). Those that self-reported attending a technology-oriented
professional development training annually represented 39.5% of the sample (n = 17). The
remaining results included five participants who reported attending no training (11.6%), eleven
participants who reported attending two trainings (25.6%), three participants who reported
attending four trainings (7.0%), four participants who reported attending six trainings (9.3%),
and four participants who reported attending monthly trainings (7.0%).
60
Table 2
Frequency of Professional Development
Frequency n Percent
Monthly 3 7.0
6 times per year 4 9.3
4 times per year 3 7.0
Twice per year 11 25.6
Annually 17 39.5
None in the last year 5 11.6
Total 43 100.0
Levels of technology use, the dependent variable for this study, were measured across
eight categories and across six levels including level zero and two-level fours (4a and 4b, defined
below) using the CBAM-LoU assessment (Appendix B). Each category was coded in numerical
order from one (Level 0) through eight (Level 6). Nearly all participants (n = 42; 98.0%) ranked
themselves in the top four levels of technology use, indicating a high comfort level with using
technology to improve teaching and learning for students (Table 3). The most frequent level of
technology use was the sixth level of 4b: Refinement, which indicates educators want to work
with others to design various uses of technology tools to enhance learning experiences for
students, (n = 18, 42%). This is followed by Level 5: Integration; a combination of one’s own
effort with related activities of other teachers to achieve impact in the classroom (n = 10; 23.3%).
Level 4a: Routine; comfortable using technology but puts forth minimal effort to improve (n = 9;
21%). No participants reported at Level 0, Level 1, or Level 2.
61
Table 3
Levels of Technology Use
Level n Percent
Level 0: Nonuse 0 0
Level 1: Orientation 0 0
Level 2: Preparation 0 0
Level 3: Mechanical use 1 2.3
Level 4a: Routine use 9 21.0
Level 4b: Refinement 18 42.0
Level 5: Integration 10 23.3
Level 6: Renewal 5 12.0
Note. n = 43.
Data Analysis
This study investigated relationships between four independent variables: years of
teaching experience, participation in technology professional development, technology self-
efficacy, and TPACK (technological pedagogical content knowledge), and a dependent variable,
the level of technology integration. Each of the research questions sought to find potential
relationships between the independent variables (experience, professional development, TPACK,
and self-efficacy) and the dependent variable of technology integration. Given the small sample
size and non-normal distributions, analyses were adjusted accordingly.
62
Research Question 1
Research Question 1: Is there a relationship between high school teachers’ attributes
(years of experience and participation in technology professional development) and their level of
technology integration?
For this research question, participants completed two demographic questions. For the
first demographic question, participants chose one of seven categories about years of teaching
experience: 0–5 years, 6–10 years, 11–15 years, 16–20 years, 21–25 years, 26–30 years, and 31
or more years. The scores were coded in numerical order and ranged from one (0–5 years) to
seven (31 years or more). Similarly, participants chose one of six categories for participation in
professional development: monthly, six times per year, four times per year, annually, or none in
the last year. The scores were coded in numerical order and ranged from one (none in the last
year) to six (monthly).
A Spearman correlation coefficient, a nonparametric test, examined the relationships
between years of teaching experience, frequency of participation in technology professional
development, and levels of technology use in classroom instructional practices. The results of the
analysis showed different relationships between years of teaching experience (M = 4.21, SD =
1.44) and level of technology use in classroom instruction (M = 6.16, SD = 1.022) and frequency
of participation in technology professional development (M = 2.84, SD = 1.40) and levels of
technology use in classroom instruction (M = 6.16, SD = 1.022) (Tables 4 and 5). Between years
of teaching experience and levels of technology use (Table 6), there is a negative relationship
that is not statistically significant (rs = -0.167, n = 43, p = .142). However, the frequency of
participation in technology professional development and levels of technology use (rs = 0.419, n
= 43, p = .003) was a positive relationship that was statistically significant (Table 6). Within this
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sample, the results suggest that the level of technology use in classroom instructional practices is
not influenced by the teachers’ years of experience. The frequency of attendance in technology
professional development was positively correlated and statically significant with years of
teaching experience.
Table 4
Years of Teaching Experience Compared to Levels of Technology Use
Years of teaching experience Mean levels of technology use
6–10 years 6.00
11–15 years 6.43
16–20 years 6.44
21–25 years 6.25
26–30 years 5.83
31 or more years 5.00
Total 6.16
Note. n = 43.
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Table 5
Professional Development Training and Level of Technology Use
Frequency of technology PD Mean level of technology use
Monthly 7.67
6 times per year 6.75
4 times per year 6.33
Twice per year 6.27
Annually 5.71
None in the last year 6.00
Total 6.16
Note. n = 43.
Table 6
Spearman Rank-Order Correlations Between Frequency of Professional Development, Years of
Teaching Experience and Level of Technology Use
Years of
experience
Participation in
PD
Level of
technology use
Years of experience
Participation in PD
0.294*
Levels of technology use
-0.167 0.419**
Note. **. Correlation is significant at the 0.01 level (1-tailed);
*. Correlation is significant at the 0.05 level (1 tailed).
n = 43.
65
Research Question 2
Research Question 2: Is there a relationship between high school teachers’ technological
pedagogical content knowledge (TPACK) and their level of technology integration?
The TPACK questionnaire contained 35 items that examined each participant’s
knowledge in the seven domains as scored on a Likert scale from 1–4 ranging from strongly
disagree (1) to strongly agree (4). The TPACK framework is a visual representation of how
knowledge in pedagogy, content, and technology is essential for teachers to move toward
student-centered constructivist learning environments (George & Sanders, 2017). Each of the
knowledge domains, technology knowledge (TK), pedagogy knowledge (PK), content
knowledge (CK), pedagogy content knowledge (PCK), technology pedagogy knowledge (TPK),
technology content knowledge (TCK), and technology pedagogy content knowledge (TPACK)
are represented by five questions each from the questionnaire and represents a separate score.
The items on this survey were altered slightly from the previous authors’ study (Jang & Tsai,
2012). The descriptive statistics for mean and standard deviation for each of the seven
knowledge domains are shown in Tables 7–13. A high mean score represents a higher level of
knowledge in that TPACK domain.
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Table 7
Descriptive Statistics for Technology Knowledge (TK)
Statement Mean
(scale is 1–4)
SD
I know how to solve many of my own technology
problems. 2.07 0.961
I learn to use new technologies easily. 2.02 0.950
I keep up with important new educational
technologies. 2.16 0.898
I routinely design lessons in which students learn using
technology. 2.30 0.914
I know about a lot of different technologies. 2.19 0.824
Note. n = 43.
67
Table 8
Descriptive Statistics for Pedagogical Knowledge (PK)
Statement Mean
(scale is 1–4)
SD
I use appropriate instructional tools (models, examples,
images, etc.) to explain concepts within the subject
that I teach.
1.74 1.026
I can adjust my teaching approaches for students with
different learning needs.
1.86 0.966
In teaching, I create an atmosphere for appropriate
interactions between teachers and students.
1.81 1.097
I adjust my teaching based on students’ level of
comprehension.
1.93 0.936
I use different teaching approaches when teaching
different content in my subject area.
1.86 0.941
Note. n = 43.
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Table 9
Descriptive Statistics for Content Knowledge (CK)
Statement Mean
(scale is 1–4)
SD
I have sufficient content knowledge of the subject that I
teach.
1.72 1.054
I can clearly explain the content of the subject that I teach. 1.70 1.103
I am aware of common misconceptions that students have
in the subject that I teach.
1.81 1.075
I am aware of the prerequisite knowledge students need to
be successful in the subject that I teach.
1.81 1.052
I use different ways of assessing students’ level of
understanding of the subject that I teach.
1.98 1.047
Note. n = 43.
Table 10
Descriptive Statistics for Technology Content Knowledge (TCK)
Statement Mean
(scale is 1–4)
SD
I use technology to enhance students’ understanding
and learning of the content.
1.98 0.859
I use technology to explain concepts in the subject that I
teach that are difficult for students to understand.
2.00 0.873
I use technology to promote teaching activities for a
specific course unit.
2.10 0.932
I can choose appropriate technology that enhances my
teaching for a specific course unit.
2.12 0.931
I help students use technology to collect or organize
information.
2.14 0.941
Note. n = 43.
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Table 11
Descriptive Statistics for Technology Pedagogy Knowledge (TPK)
Statement Mean
(scale is 1–4)
SD
I use technology to create teaching activities for student
interactions.
2.09 0.811
I use technology to explain the content of the subject
matter.
2.00 0.816
I use technology to enhance my teaching effectiveness.
2.00 0.900
I use technology to get students motivated in learning and
help them learn diligently.
2.26 0.819
I use technology to enrich my teaching materials and
content.
1.95 0.909
Note. n = 43.
Table 12
Descriptive Statistics for Pedagogical Content Knowledge (PCK)
Statement Mean
(scale is 1–4)
SD
My teaching approaches make students stay interested in
the content of the subject matter.
1.98 0.780
I use different teaching approaches such as group
discussions and collaboration to teach the contents.
1.71 0.929
I know how to choose effective teaching approaches to
guide students’ learning and thinking.
1.86 0.99
I use a variety of teaching approaches to transform subject
matter into comprehensive knowledge.
1.81 0.982
I create a classroom circumstance to promote students’
interest for learning.
1.86 0.804
Note. n = 43.
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Table 13
Descriptive Statistics for Technology Pedagogy Content Knowledge (TPACK)
Statement Mean
(scale is 1–4)
SD
I integrate content, technology, and teaching approaches to
teach subject units.
2.02 0.831
I use interactive technology (such as iPads, smartphones, or
applications such as Pear Deck, back channels, or polls) to
promote learning and inquiry of lessons.
2.26 0.875
I use technology to find out students’ understanding of
abstract concepts of the subject.
2.30 0.832
I use technology and teaching approaches in different course
units to help students comprehend easily.
2.21 0.888
Using technology can improve my teaching approaches to
promote students’ learning.
2.05
a
0.999
Note. n = 43;
a
n = 42.
The composite scores for each knowledge domain are represented in Table 14. The
participants rated themselves above midpoints in the four technology domains: TK (M = 2.15,
SD = 0.798), TCK (M = 2.07, SD = 0.818), TPK (M = 2.07, SD = 0.764) and TPACK (M = 2.17,
SD 0.771) and below the midpoints in the content and pedagogy domains. For CK, the mean
score (1.80) is the lowest, yet it has the highest SD score (1.020).
71
Table 14
Descriptive Statistics for TPACK Composite Scores
Statement Mean
(scale is 1–4)
SD
Technological knowledge (TK) 2.15 0.798
Content knowledge (CK) 1.80 1.020
Pedagogical knowledge (PK) 1.87 0.844
Technological content knowledge (TCK) 2.07 0.818
Pedagogical content knowledge (PCK) 1.87 0.844
Technological pedagogical knowledge (TPK) 2.07 0.764
Technological pedagogical content knowledge (TPACK) 2.17 0.771
Note. n = 43.
Next, a Spearman rank correlation coefficient examined the relationship between each of
the TPACK knowledge domains and levels of technology use in classroom instructional
practices (Table 15). There were negative correlations between all the TPACK knowledge
domains and levels of technology use: Technology knowledge, TK (rs = - 0.43, n = 43, p = .002);
content knowledge, CK (rs = -0.02, n =43, p =.439); pedagogy knowledge, PK (rs = -0.01, n = 43,
p = .474); technology content knowledge, TCK (rs = -0.35, n = 43, p =.011); pedagogy content
knowledge, PCK (rs = -0.01, n =43, p =.474); technology pedagogy knowledge, TPK (rs = -0.35,
n = 43, p =.011); technology pedagogy content knowledge, TPACK (rs = -0.30, n = 43, p = .024).
The results suggest that if a teacher reported a high level of knowledge, this resulted in a low
level of technology use. All the domains about technology were statistically significant: TK (p =
.002), TCK (p = .011), TPK (p = .011, and TPACK (p = .024). It was expected that those
72
teachers with more technology knowledge would report higher levels of technology use;
however, these results do not align with that expectation or the literature.
73
Table 15
Spearman Rank-Order Correlations Between Each TPACK Knowledge Domain and Levels of Technology Use
Technology
knowledge
(TK)
Content
knowledge
(CK)
Pedagogy
knowledge
(PK)
Technology
content
knowledge
(TCK)
Pedagogy
content
knowledge
(PCK)
Technology
pedagogy
knowledge
(TPK)
Technological
pedagogy content
knowledge
(TPACK)
Level of
Technology
use
-0.43** -0.02 -0.01 -0.35* -0.01 -0.35* -0.30*
Note. **. Correlation is significant at the 0.01 level (1-tailed);
*. Correlation is significant at the 0.05 level (1 tailed).
n = 43.
73
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Research Question 3
Research Question 3: Is there a relationship between high school in-service teachers’
technology self-efficacy and their level of technology integration?
For this research question, teachers completed the 21 items on the TISES questionnaire
on a 4-point Likert scale ranging from strongly disagree (1) to strongly agree (4) on their
confidence level with technology use. The mean scores for technology self-efficacy are shown in
Table 16. Most teachers reported they felt comfortable helping students when they have
difficulty with their technology devices (M = 2.35, SD = 0.824). Likewise, teachers were
confident they can effectively monitor students’ technology use for project development (M =
2.25, SD = 0.770). Finally, teachers feel comfortable selecting appropriate technology tools to
use in instructional practices as it relates to the curriculum standards (M = 2.14, SD = 0.887).
75
Table 16
Descriptive Statistics for Technology Self-Efficacy
Statement Mean
(scale is 1–4)
SD
I feel confident that I understand the technology
and its capabilities well enough to maximize
them in my classroom.
2.05 0.880
I feel confident that I have the skills necessary to
use technology for instruction.
2.03 0.928
I feel confident that I can successfully teach
relevant subject content with the appropriate use
of technology.
1.95 0.941
I feel confident in my ability to evaluate
applications for teaching and learning.
2.05 0.941
I feel confident that I can use correct technical
terminology when directing students’ computer
use.
2.08 0.829
I feel confident I can help students when they
have difficulty with their technology devices.
2.35 0.824
I feel confident I can effectively monitor students’
technology use for project development in my
classroom.
2.25 0.770
I feel confident that I can motivate my students to
participate in technology-based projects.
2.05 0.911
I feel confident I can mentor students in the
appropriate uses of technology.
2.30 0.845
I feel confident I can consistently use educational
technology in effective ways.
2.11 0.966
I feel confident I can provide individual feedback
to students during technology use.
2.05 0.815
I feel confident I can regularly incorporate
technology into my lessons, when appropriate
for student learning.
1.97 0.986
I feel confident about selecting the appropriate
technology for instruction based on curriculum
standards.
2.14 0.887
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Statement Mean
(scale is 1–4)
SD
I feel confident about assigning and assessing
technology-based projects.
2.08 1.025
I feel confident about keeping curricular goals and
technology uses in mind when selecting an ideal
way to assess student learning.
2.11 0.875
I feel confident about using technology resources
(spreadsheets, digital portfolios, etc.) to collect
and analyze data from students’ tests and
products to improve instructional practices.
2.05 1.026
I feel confident that I will be comfortable using
technology in my teaching.
1.92 1.010
I feel confident that I can be responsive to
students’ needs during technology use.
2.11 1.022
I feel confident that, as time goes by, my ability to
address my students’ technology needs will
continue to improve.
1.78 0.917
I feel confident that I can develop creative ways to
cope with system constraints (such as budget
cuts on technology facilities and equipment)
and continue to teach effectively with
technology.
1.92 0.795
I feel confident that I can carry out technology-
based projects even when I am opposed by
skeptical colleagues.
1.97 0.928
Note. n = 37.
Worth noting, there were six participants who did not complete the items that measured
technology self-efficacy, which was the last questionnaire in the survey. Most likely, these
participants did not have the time to complete these last questions or accidentally did not realize
that they were not finished yet. There were very few missing data (<5%) on the rest of the items,
with five participants missing one item and two participants missing two items. Listwise within
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SPSS deleted incomplete data when running analyses. The composite mean score for technology
self-efficacy is shown in Table 17 and represents the mean of the scale items that were
completed.
Table 17
Composite Score for Technology Self-Efficacy
M SD
Technology self-efficacy 2.07 0.797
Note. n = 37.
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Using the mean scores for technology self-efficacy and isolating the TPACK knowledge
domain for technology (TK, TCK, TPK, and TPACK), Table 18 shows a Spearman rank-order
analysis to determine the statistical significance between these variables. The variables were
derived from two self-reported categorical independent variables of technology self-efficacy
(mean categorical variable ranging from 0–84) and each of the technology knowledge domains
(mean categorial variable ranging from 0–25). The results indicate there was a statistical
significance between technology self-efficacy and technology knowledge (rs = 0.79, n = 37, p <
.001), technology content knowledge (rs = 0.95, n = 37, p < .001), technology pedagogy
knowledge (rs = 0.92, n = 37, p < .001), and technology pedagogy content knowledge (rs = 0.90,
n = 37, p < .001).
Table 18
Spearman Rank-Order Correlations Between Technology Knowledge Domains and Technology
Self-Efficacy
Technology
knowledge
(TK)
Technology
content
knowledge
(TCK)
Technology
pedagogy
knowledge
(TPK)
Technology
pedagogy
content
knowledge
(TPACK)
Technology self-efficacy
.79** .95** .92** .90**
Note. n = 37; **. Correlation is significant at the .01 level.
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To answer Research Question 3 and determine the effect of level of technology use on
technological self-efficacy, a Kruskal-Wallis H test was selected for this analysis due to the non-
normality of the data for both the dependent (levels of technology use) and the independent (self-
efficacy) variables. The Kruskal-Wallis H test is also referred to as a one-way ANOVA on mean
ranks and it is a nonparametric testing method.
The Kruskal-Wallis test evaluated six levels (across eight categories) of technology use
on technological self-efficacy. The independent variable was technology self-efficacy (summed
categorical variable ranging from 0–84). The categorical dependent variable was level of
technology use: (a) Level 0: None; (b) Level 1: Orientation; (c) Level 2: Preparation; (d) Level 3:
Mechanical Use; (e) Level 4a: Routine; (f) Level 4b: Refinement; (g) Level 5: Integration; and
(h) Level 6: Renewal (Appendix B). Each category was coded in numerical order from one
(Level 0) through eight (Level 6). A Kruskal-Wallis test showed there was no statistical
significance between levels of technology use (Level 3, Level 4a, Level 4b, Level 5, Level 6)
and technological self-efficacy, H(4) = 6.377, p = 0.173.
Summary
This study sought to find potential relationships between the dependent variable of level
of technology use with the independent variables of an in-service teacher’s years of teaching
experience, level of participation in professional development, TPACK knowledge, and
technology self-efficacy. Descriptive statistics, Spearman rank correlation, and Kruskal-Wallis
were used to explore the data further to answer the research questions. These results are not
aligned with current literature that discusses factors that influence the use of technology in
classroom instructional practices. First, the results suggest that the use of technology in the
classroom is not influenced by years of teaching experience or participation in professional
80
development. Next, the data analysis showed negative correlations between each of the TPACK
knowledge domains and levels of technology use in the classroom. Worth noting, each
technology domain (TK, TCK, TPK, and TPACK) showed negative statistical significance that
suggests increases in TPACK knowledge decreases the use of technology in the classroom and
vice versa. This implies that a teacher with more technical knowledge reports a lower level of
technology use in the classroom. Last, a Kruskal-Wallis analysis showed no statistical
significance between a teacher’s technology self-efficacy and their use of technology in the
classroom. However, there was a strong, statistically significant relationship when isolating the
technology domains (TK, TCK, TPK, and TPACK) with technology self-efficacy (p = < .001).
While the results are not aligned with the literature, the data does suggest that teachers are using
technology in instructional practices. Chapter Five will explore these results and discuss the
implications of these findings and recommendations for future research and practice.
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Chapter Five: Discussion
The purpose of this quantitative correlational research study was to investigate the
perceived insufficient use of technology in classroom instructional practices at a large
international secondary school in Southeast Asia. Educators, administrators, and students rely
heavily on technology in the education field. This relationship with technology will only deepen
as opportunities for innovation increase and create new challenges (Chicioreanu et al., 2019).
These rapid changes require educators to engage with technology in their classrooms and present
students with opportunities to have the technical skills and knowledge to prepare themselves to
function digitally post-graduation (Lombardi et al., 2017). Internal barriers such as self-efficacy,
technology knowledge, and pedagogical knowledge can disrupt technology integration into
teachers’ instructional practices. (Durff & Carter, 2019; Ertmer, 2015).
This quantitative correlation research study examined the relationships between years of
teaching experience, level of participation in professional development, TPACK (technology
pedagogy content knowledge), technology self-efficacy, and the influences on technology
integration. Many researchers have indicated that integrating technology into classroom
instruction supports student academic achievement (Durff & Carter, 2019; Hamilton, 2015;
Harrell & Bynum, 2018; Kimmons, 2016). However, research also shows that barriers to
technology integration still need to be investigated and addressed (Chicioreanu & Ianos, 2019;
Durff & Carter, 2019; Harrell & Bynum, 2018; Hur, 2016). The setting for the study is a well-
resourced international school, where educators can freely determine how to use and implement
technology into their instructional practices. However, according to researchers (Harrell &
Bynum, 2018; Zehra & Bilwani, 2016), access to digital equipment and resources does not
ensure that technology is integrated into instructional practices. Given this degree of access to
82
technology, the design of this study helped in understanding teachers’ self-reported perceptions
of technology use and to what extent teachers integrate technology into instructional practices.
This chapter will provide the findings from the three research questions, discuss the
limitations of the study, and then consider practices to improve technology integration and
identify options for further research. Ultimately, the results revealed insignificant relationships
between technology integration, teaching experience, professional development participation,
TPACK knowledge, and technology self-efficacy. The results indicated significant findings
between the technology knowledge domains of TPACK and self-efficacy. All participants
received the same instructions and opportunities to engage with the self-assessment instruments
via an online survey. Overall, the quantitative study created results that are not aligned with the
literature but provide an interesting context of technology use in a large private international
school.
Interpretation of Findings
The theoretical perspective from which this study was developed derived from the social
learning theory. This theory supported examining the relationships between self-efficacy and
technology integration and the relationship between TPACK and technology integration. The
technology self-efficacy findings reflected Bandura’s (1977) defined self-efficacy as a multi-
dimensional and context-specific construct. Self-efficacy is believing in one’s self to succeed in
tasks and skill performance (Bandura, 1995). Self-efficacy is also defined as having the ability to
navigate unpredictable situations (Bandura & Schunk, 1981). Developing new instructional
material can be daunting and a higher level of self-efficacy to make decisions on the use of
technology explains that teachers are willing to change and have positive attitudes toward
83
technology to benefit student learning (Teo et al., 2017). Teachers with high levels of self-
efficacy influence instructional practice choices with technology (Poulou et al., 2019).
Teacher Demographic Findings
Research Question 1 looked at the relationship between the dependent variable levels of
technology use and two independent variables that addressed teacher demographics (years of
experience and participation in technology professional development). The results of the study
indicated there was no statistically significant relationship between technology integration and
years of teaching experience (rs = -0.167, n =43, p = .142). The results did show a positive
relationship that was statistically significant between the frequency of participation in
professional development and levels of technology use (rs = 0.419, n = 43, p = .005). Those
teachers who identified having 16–20 years of teaching experience had the highest level of
technology use mean score (M = 6.44), followed closely by those with 11–15 years of experience
(M = 6.25). Teachers who participated in and gained knowledge from monthly technology
professional development had the highest mean score in the level of technology integration (M =
7.67), which represents the CBAM-LoU level five (integration) and six (renewal). These are the
highest levels of technology integration for this assessment which reveals that age is not a factor.
The social learning theory describes mastery and vicarious learning experiences as
having the most influence on self-efficacy (Bandura, 1995). Social constructivists have stated
that learning experiences between people (Vygotsky, 1978) and their learning environments
(Piaget, 1972) assist with developing knowledge. Educators have opportunities to construct
technology knowledge through professional development, as a member of the professional
learning communities, or by experimenting with various tools in their classroom. Adopting
constructivist pedagogy and using technology to promote critical thinking, communication,
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construction of, and presentations of ideas can extend to teachers’ instructional practices that
engage students in learning (Teo & Zhou, 2017). With these practices, the classroom shifts to
student-centered learning, and teachers are no longer the holder or source of the knowledge.
Instead, teachers become the facilitator to monitor students’ steps to explain their understanding
and apply it to real-life situations (Hamilton, 2015; Masduki et al., 2019; Morchid, 2020).
Researchers have found that previous experience with technologies is directly correlated
with technology integration self-efficacy (Birisci & Kuui, 2019; Lemon & Garvis, 2016). Given
this relationship between these types of learning experiences and self-efficacy, it was expected
that this study would find a statistically significant and positive relationship between years of
experience and technology integration or participation in professional development and
technology integration. In this study, a statistically significant relationship was found only in the
latter. Seventy-five percent of the respondents self-reported that they were engaging in
professional development about technology none, annually, or twice a year. It is assumed that
teachers are receiving mastery and vicarious learning experiences through their work in
professional learning communities, support from a technology department, and the daily practice
of integrating technology in their team approach to lesson planning.
Numerous researchers have studied and cited many internal barriers that have hindered
teachers from utilizing technology in their pedagogical practices (Durff & Carter, 2019; Ertmer,
1999; Hur et al., 2016; Hsu, 2016; Sang et al., 2011). Great strides have been made to reduce
these internal barriers over the last two decades, including opportunities for professional
development which may address the comfort level teachers experience with integrating
technology. Based on the results of this study, the more experience a teacher has the older they
are; the older teachers are, the more comfortable they become with technology integration. Teo
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and Zhou (2017) studied secondary teachers from South-East Asia and discovered that an
educator’s age did not influence a teacher’s use of technology in instructional practices. In
comparison, Tou et al. (2020) found that Singaporean teachers with more than 20 years of
experience had positive attitudes toward technology integration compared to teachers with fewer
years of experience.
TPACK Findings
Research Question 2 looked at the relationship between the variable TPACK and levels
of technology use. The study examined each of the seven knowledge domains and found an
inverse correlation suggesting that the variables move slightly in opposite directions. The
negative correlations are weak amongst the technology knowledge domains and are statistically
significant: Technology knowledge, TK (rs = -0.43, n = 43, p = .002); technology content
knowledge, TCK (rs = -0.35, n = 43, p =.011); technology pedagogy knowledge, (TPK) (rs = -
0.35, n = 43, p =.011); technology pedagogy content knowledge (TPACK) (rs = -0.30, n = 43, p
= .024). The negative correlation was unexpected, and it is not known why. This suggests that a
qualitative research study is needed to understand how TPACK knowledge influences
technology use in instructional practices.
The TPACK knowledge domains are linked to positive mastery experiences and a
teacher’s willingness to integrate technology into instructional practices (Angeli & Valanides,
2013; Joo et al., 2018). Yildiz Durak (2021) found that TPACK knowledge provided a
framework for a successful technology integration process for K–12 teachers. In contrast,
Raygan & Moradkhani (2020) found a weak significant relationship between TPACK and
technology integration (r = .612, p<.01) among Iranian English as a Foreign Language teachers.
In this study, there were no significant relationships between TPACK and levels of technology
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integration. However, each of the technology domains, TK (M = 2.15) TCK (M = 2.07), TPK (M
= 2.07), and TPACK (M = 2.17) showed higher mean scores than the other knowledge domains
for CK (M = 1.80), PK (M = 1.87), and PCK (M = 1.87). The research suggests technology
integration does impact student learning and that result was not found in this study. Educators
need to know all areas of TPACK and recognize that each does not operate independently from
the others (Perera et al., 2019; See & Koomen, 2016).
Teacher Self-Efficacy Findings
Research Question 3 looked at technology self-efficacy and levels of technology use in
classroom instructional practices. The composite scores for technology self-efficacy are above
but close to the midpoint (M = 2.07, SD = .80). The results of the study indicated that there was
no statistical significance between the higher levels of technology use (Level 3, 4a, 4b, 5, and 6)
and technology self-efficacy (H [4] = 6.377, p = 0.173). Overall, the results did not find a
significant relationship between technology self-efficacy and teacher technology use. However,
the technology self-efficacy results reflected that those items that supported students and their
learning had a higher mean score (M = 2.25, SD = 0.77).
Researchers have cited teacher self-efficacy as a strong indicator of using technology in
classroom instructional practices (Banas & York, 2014; Jeung, 2014; Li et al., 2019; Valtonen et
al., 2015; Voogt et al., 2013). For example, in a study with high school teachers, Li et al. (2019)
concluded that technology self-efficacy was directly related to the use of technology in the
classroom. In addition, in two other studies, it was found that higher levels of technology self-
efficacy positively influenced technology use in the classroom (Joo et al., 2018; Morrison, 2019).
On the other hand, Farjon et al. (2019) has argued that factors that influence technology
self-efficacy and the intent to use technology in the classroom may also be affected by the
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specific period of use and various levels of support from collaborative groups. The study of 398
pre-service teachers showed a medium correlation between technology self-efficacy and
technology integration (Farjon et al., 2019). Knezek and Christensen (2016) used an expanded
Will, Skill, and Tool Model of Technology Integration and the CBAM-LoU surveys to determine
a strong correlation between technology proficiency (skill) (r = .549, p<.0005) and pedagogy
knowledge (r = .585, p<.0005). Finally, Morales (2006) had different results for levels of
technology integration based on geographic locations. Teachers surveyed from Mexico cited
access to technology as a strong predictor of technology usage, while teachers in the United
States cited self-efficacy in skill development. The year 2006 marked the era in which U.S.
teachers had technology skill training while Mexico had few technology tools in the classroom
(Knezek & Christensen, 2016). This supports Farjon et al. (2019) arguments that various levels
of mastery and vicarious learning experiences, geographic locations, and different eras influence
technology integration. Self-efficacy, as defined by Bandura (1977) is multi-dimensional and is a
context-specific construct.
High levels of technology self-efficacy influence a teacher to overcome the obstacles that
may prevent technology integration. Teachers who doubt their ability to use technology will not
have an open mindset to overcome difficulties and obstacles versus teachers with high self-
efficacy (Bandura, 1989). Teachers who adopt a growth mindset will put forth the effort to learn
effective strategies to improve skills (Dweck et al., 1995). Upon learning the new skills and
improving technology self-efficacy, the same growth mindset allows teachers to take a risk
trying new technology and pedagogy approaches in classroom instruction. Suppose a teacher
believes that instructional strategies that use technology will positively affect student learning. In
that case, the teacher will incorporate that teaching strategy if they believe in their ability to
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effectively deliver the lesson (Zee & Koomen, 2016). The results of this study support teachers’
ability to mentor students in the appropriate uses of technology (M = 2.3, SD = .845), provide
feedback to students during technology use (M = 2.05, SD = .815), and select the appropriate
technology for instruction (M = 2.14, SD = .887). As teachers’ self-efficacy increases, the
teacher is motivated and committed to these strategies that center student learning and create
opportunities rooted in constructivist pedagogy approaches that give students opportunities to
engage with the instructional materials (Zee & Koomen, 2016).
TPACK and Self-Efficacy
Previous knowledge in the TPACK framework and higher levels of technology self-
efficacy influence a teacher’s intention to use technology in instructional practices (Birisci &
Kuui, 2019; Lemon & Garvis, 2016). The results of this study showed that there was a statistical
significance between each of these technology knowledge domains and technology self-efficacy:
technology knowledge (rs = 0.79, n = 37, p < .001), technology content knowledge (rs = 0.95, n =
37, p < .001), technology pedagogy knowledge (rs = 0.92, n = 37, p < .001), and technology
pedagogy content knowledge (rs = 0.90, n = 37, p < .001). The significant relationship between
technology integration and the TPACK knowledge domains of content and pedagogy indicates
that teachers who have higher levels of self-efficacy for instructional strategies have a higher
degree of technology integration into their instructional practices.
TPACK is a flexible framework that provides teachers with the structure needed to
understand how technology is integrated into instructional practices (DeSantis, 2016; Kimmons
& Hall, 2018; Koehler et al., 2013). Knowing all the domain areas is ideal. However, Perera et
al. (2019) suggest that it is possible to have different confidence and knowledge levels in each
TPACK domain. In their study with schools in the United States, Australia, and the United
89
Kingdom, Harris and Hofer (2017) have identified the TPACK construct as having significant
influences on instructional planning. The same study acknowledges that TPACK is also a
connector between teachers and instructional technology coaches and is a progressive, flexible
model that assists with selecting appropriate tools that enhance student learning. Teachers who
develop TPACK have more confidence to choose appropriate technologies for integration
(Maeng et al., 2013). Joo et al. (2018) found statistical significance (p<.05) in their study of pre-
service teachers in Korea that knowledge in TPACK improves technology self-efficacy and
recommended continued professional development for the improvement of TPACK levels. For
continuous improvement in implementing technology into instructional practices, teachers need
to believe they are self-efficacious (Zee & Koomen, 2016).
Limitations
This study has some limitations. Teachers who chose to participate in the study are more
than likely to have a positive attitude toward, and positive experiences with, the use of
technology than those choosing not to participate, given the topic of the study included factors
that affect instructional practices of integrating technology (Durff & Carter, 2019; Ertmer, 1999;
Hsu, 2016; Hur et al., 2016; Sang et al., 2011). The instruments used in this study, the TPACK
questionnaire, TISES, and CBAM-LoU, are self-assessment instruments. The scores on these
instruments measure a participant’s self-perception of their knowledge, self-efficacy, and levels
of technology use, which may not accurately reflect or assess the actual levels of these variables.
This also includes the raised concerns in case studies regarding the differences between an
individual’s self-reported perceptions versus enacted constructs of TPACK (Akapame et al.,
2019). It is also worthy to note the difficulty in determining the definition and meaning of
teacher instructional practice (Lefebvre et al., 2017). Instruments that use self-reported
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assessments allow teachers to define instructional practices that may or may not include
preparing the learning activities in and outside the classroom.
Delimitations
When looking at the results and making interpretations for the study, it is also essential to
identify delimitations that may influence the results. First, the results are limited to a single
international secondary school with a teacher population of 225 teachers. For this study, the
decision to extend the survey invitation to only secondary teachers was influenced by the
differences in available resources for primary and secondary divisions. The nonparametric data
analysis invites readers to treat the results with caution. The study should be replicated to see if a
new, larger data set produces the same relationships.
Next, the study link was distributed as the last line item via the principal’s weekly email
communication to ensure anonymity. This communication is sent on Sunday evenings when
most teachers are not checking emails or rushing to read the communication on Monday
mornings. It is also worth noting that most teachers were mentally and physically exhausted due
to school and country lockdowns that limited movement and travel due to the COVID-19
pandemic. The survey was distributed in November 2021 at a time when educators had not seen
family for nearly 2 years due to travel restrictions. Mental exhaustion may have contributed to
the low n = 43 sample size.
Recommendations for Practice
I began the research for this dissertation in 2020. So much has changed in the field of
technology in 2 years. As the COVID-19 pandemic swept through the world, educators grappled
with pedagogical and technological changes in their instructional practices. Overnight, a new
educational vocabulary included Zoom, Google Meets, and online assessments. As the world
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shifted to an online platform, the digital inequities in education were exposed. While inequities
in digital devices still exist in schools, this study addressed the inequity in the teachers’ level of
technology use. In an international school that is well equipped with technology devices and
digital tools, inequities are created when teachers choose to use or not use technology in their
instructional practices.
Students miss opportunities to learn technical knowledge and have experiences with new
technologies due to a teacher’s choice to not utilize technology in instructional practices (Mir &
Parrey, 2019). The study showed that teachers are confident in helping students with their
technology devices (M = 2.35, SD = 0.824), are confident in choosing appropriate technology
tools for instruction (M = 2.14, SD= 0.887), and can monitor project development using devices
(M = 2.25, SD = 0.77). This confidence may result from access to a full-time divisional
technology support team and co-teaching with a technology coach. This study also indicated a
need for ongoing support for technological pedagogical training. The results of the study say that
technology is being used and confirm the importance of pedagogy and years of experience in
relation to technology integration (rs = 0.294, n = 43, p = .05). We do not want to give up on
professional learning; thus, further investigations regarding the alignment of professional
development with teachers’ pedagogical and technological goals are indicated.
TPACK and Self-Efficacy
The research indicates that technology knowledge and technology self-efficacy can
positively influence the use of technology in instructional practices. However, the results from
this study are counter-intuitive to the current literature. Teaching experience, which is closely
related to a teacher’s age, can be eliminated as a factor for non-use of technology; however, the
internal barriers are still not identified. To improve technology usage in instructional practices,
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the factors causing this problem must first be identified. It is unknown if teachers know and use
TPACK or if TPACK is the right technology integration model for this international school.
Therefore, the first recommendation is to repeat the current study to further inquire about teacher
TPACK knowledge and usage of the framework for technology integration in instructional
practices. The repeated study can also include interviews and observations to have data
triangulation and improve the sample size to increase the chances of receiving normally
distributed data.
If the repeated study can determine that teachers lack TPACK knowledge, targeted and
practical professional development focused on improving teachers’ technological knowledge will
positively affect technology self-efficacy (Harris & Hofer, 2017) and enhance technology
integration. The self-efficacy results from this new study can be used to provide high-quality
targeted professional development opportunities that align with levels of self-efficacy (Perera &
McIlveen, 2017). The TPACK framework is flexible; therefore, teachers can improve their
technology knowledge and learn how it specifically enhances the content and delivery of
instructional materials. Teacher coaching or working within the collaborative professional
community provides the learning environment for active engagement to learn effective strategies
and tools for technology integration to students’ learning experiences. A menu of learning
opportunities that range from technology application support, engagement in a coaching cycle,
co-teaching or data collection, and reflection conversations provide time to think about learning
materials and how technology can enhance or showcase learning. Each of these methods
provides sustainable technology integration that is personalized, based on teacher interest, and
offers opportunities for conversations that are solution driven.
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Targeted professional development builds teachers’ technology knowledge and provides
technology experiences that improve teachers’ self-efficacy to use technology in the classroom,
lowers technology barriers, and increase levels of technology integration. In a 2020 study, the
researchers discovered that American in-service teachers who improved their knowledge of
TPACK adjusted their pedagogical approaches to using technology (Oda et al., 2020). Similarly,
American mathematics teachers gained new knowledge in pedagogy (PK), technology (TK),
pedagogy content (PCK), and technology content (TCK) through TPACK-based professional
development (Young et al., 2019).
4Shifts Protocol Framework
While the TPACK conceptual framework shows how content and pedagogy knowledge
intersect to influence technology integration, the framework is not an instructional guide that
explicitly teaches educators what changes need to be made to instructional practices to integrate
technology (McLeod & Graber, 2018). As an alternative, the school should follow and adopt the
4Shifts Protocol as a tool for teachers to deeply reflect and examine lesson content in four areas:
deeper thinking and learning, authentic work, student agency, and technology integration. Each
shift asks a series of questions that must be answered yes, no, or somewhat. When answering no
or somewhat, more attention can be devoted to that area of the lesson to address those gaps to
enhance the student learning experience (McLeod & Graber, 2018).
Technology integration is purposeful, intentional, and targeted for the sake of enhancing
pedagogical approaches and student learning. The 4Shifts Protocol forces educators to critically
think about the purpose of technology within the lesson. The 4Shifts Protocol puts teaching and
student learning first and intentionally structures conversations to think about aligning
instructional materials within the four areas of focus. This professional learning opportunity
94
allows teachers to collaborate with a coach and teams to grow a shared technology vision.
Focusing only on one area of the protocol, educators make shifts in their lessons over time to fill
in the gaps and in turn improve their TPACK knowledge (McLeod & Graber, 2018).
Constructivism
The literature has highlighted the need for ongoing professional development in shifting
from traditional to constructivist pedagogical methods. Those that made the changes to their
delivery practices during online digital learning shifted their instructional practices as quickly as
possible to maintain the delivery of high-quality instruction (OECD, 2020). Similarly,
professional development programs that focus on effective constructivist pedagogy rather than
technology ensure teachers understand effective teaching strategies that promote student
learning. Working with teacher coaches or PLCs, educators begin with the end in mind and
scaffold the learning steps that engage students to critically think and have real-world
experiences. Support teams and instructional technology coaches assist teachers with creating
learning resources that are housed on learning management systems that can be accessed anytime
anywhere. As teacher self-efficacy and technology knowledge increase, teachers transform their
instructional practices to provide student voice and choice in learning. Teachers become
facilitators of learning and help identify tools that will enhance their practices and can assist
students with identifying the best tools to demonstrate their learning.
Professional development that encourages conversations and critical examination to
identify areas within a lesson that can be enhanced with technology creates different interactions
between teachers and students and amongst the students (McLeod & Graber, 2018). These small
changes engage all class members to co-construct knowledge and lead to endless possibilities for
innovative ideas and projects that can be enhanced with the use of technology. These are strong
95
indicators that teachers who adapt to constructivist pedagogy teaching methods will likely use
technology in their instructional practices (Teo & Zhou, 2017).
Creating and supporting a school culture where learning is deprivatized, valued, and
celebrated encourages educators to experiment with technology. Teachers do want to use
technology in their instructional practices and if they knew what changes needed to be made in
their instructional practices, they would be more than likely to make those changes. Teachers
learn by doing and are willing to acquire technology knowledge (TK) and technology
pedagogical knowledge (TPK) through trial and error in their teaching experiences (Nelson et al.,
2019). However, teachers also indicated that they are not confident in incorporating technology
into their lessons to enhance student learning (M = 1.97, SD = 0.97) or in using technology to
enrich teaching materials and content (M = 1.95, SD = 0.90). Divisional leadership teams must
work with and support instructional technology coaches to foster a culture of technology learning
and experimenting with technology integration in teaching practices (Nelson et al., 2019) and
provide ongoing professional learning opportunities to acquire and improve technology
pedagogy knowledge (TPK). This requires schools to examine the values, beliefs, and visions for
the placement of technology and ongoing instructional support in the hands of coaches, teachers,
and students.
Future Research
The research indicates that technology knowledge and technology self-efficacy can
positively influence the use of technology in instructional practices. However, the results from
this study are counter-intuitive to the current literature. Teaching experience, which is closely
related to a teacher’s age, can be eliminated as a factor for the non-use of technology. However,
96
the internal barriers are still not identified. Therefore, the first recommendation is to repeat the
current study to garner a larger sample size to have a normal data distribution.
The results from this study allowed me time to critically reflect on my experiences as a
researcher and instructional technology coach. I continue seeking ways to increase teacher self-
efficacy, technology knowledge, and positively influence the use of technology in instructional
practices to improve student technology knowledge and learning. Keeping student learning at the
forefront, I would recommend future researchers consider the following recommendations that
are based on the findings and limitations of this study:
1. Conduct a quantitative or mixed-methods study to investigate students’ use of
technology in daily classroom instruction.
2. Conduct a mixed-methods study that includes students and teachers responding to
questions about the use of technology in the classroom.
3. Increase the sample size by including teachers from all grade levels, all subject areas,
and similar international schools to increase the variation and better transferability of
the findings to the larger population of international teachers.
4. Conduct a focus group study on TPACK knowledge and subject area taught to
examine the relationship between TPACK and the practical use of technology in the
classroom.
5. Conduct a focus group study on the 4Shifts Technology Protocol to critically examine
instructional materials in the four learning areas: deeper thinking and learning,
authentic work, student agency, and technology integration.
97
Conclusion
This research study was developed to consider and understand teachers’ levels of
technology use, technology knowledge, and self-efficacy to use technology in classroom
instructional practices. Furthermore, the study allowed a glimpse into potential barriers that
hinder the progress of teachers’ willingness to innovate and experiment with different
technologies to enhance student learning. From the research, it was clear that technology is being
used on a surface level to deliver lessons and instructional materials. However, the broad term of
technology is more than using technology tools. It’s the pedagogy that matters, not the
technology. Thoroughly embracing and integrating technology in classroom instructional
practices requires a positive attitude towards technology, opportunities to learn and gain new
knowledge through vicarious or professional development, and time to practice new skills. These
learning opportunities increase technology self-efficacy and improve the instructional delivery of
lessons that will enhance student learning.
Technology self-efficacy is an essential factor that predicts teacher use of technology.
Teachers’ instructional approach and openness towards technology also predict technology
integration that supports student-centered teaching. This study raises important implications for
the field of professional learning. Pedagogical readiness is as important as technological
readiness for teachers to integrate technology to serve more advanced teaching purposes. It will
be essential to focus on effective pedagogical practices alongside technology use skills and
training when providing professional development opportunities to teachers.
Research is already suggesting that we will only deepen our relationship with technology.
We will continue to expand our technical knowledge and create opportunities for innovation.
However, doing this will also create new challenges that need to be solved (Chicioreanu et al.,
98
2019). The global pandemic demonstrated that digital divides are not just related to a lack of
digital resources. In a well-resourced school, a lack of technological knowledge has the potential
to create learning gaps for students and teachers. Abrupt shifts to online learning platforms
forced teachers to engage and learn new technologies and adopt constructivist pedagogical
approaches to create meaningful learning experiences in an online environment. Utilizing Zoom
and breakout rooms, teachers learned how to design interactive lessons that intentionally targeted
lesson objectives constructively, were authentic, and provided opportunities for collaboration
amongst students and between teachers and students (George & Sanders, 2017). Strategic
planning and commitment from teachers and senior leadership teams to keep innovation and
technology at the forefront of discussions within learning communities will close the digital gaps
and ensure all students will have the skills they need for their future success.
99
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and Educational Development, 3(1), 1–29. https://doi.org/10.22555/joeed.v3i1.709
Zhang, S., Liu, Q. T., & Wang, Q. Y . (2017). A study of peer coaching in teachers’ online
professional learning communities. Universal Access in the Information Society, 16(2),
337–347.
119
Appendix A: Demographics
Question stem Responses
Years of teaching experience 0–5 years
6–10 years
11–15 years
16–20 years
21–25 years
26–30 years
31 or more years
How often do you participate in
technology-oriented professional
development or training?
None in the last year
Annually
Twice per year
4 times per year
6 times per year
Monthly
Note. N = 43. Participants received directions to select one answer. Most participants had 21–25
years of experience (n = 12, 27.9%). Most participants reported participating in technology-
oriented professional development training annually (n = 17, 39.5%).
120
Appendix B: Concerns-Based Adoption Model (CBAM) Levels of Use of an Innovation
Note. N = 43. This is a quick self-report measure that assesses the level of technology utilization
that describes levels of behavior for technology use. It is a single-item survey therefore internal
consistency reliability cannot be measured. Nearly all participants (n = 42; 98.0%) ranked
themselves in the top four levels of technology use, indicating a high comfort level with using
technology to improve teaching and learning for students. From the Institute for the Integration
121
of Technology into Teaching and Learning (2021). The Concerns-Based Adoption Model Levels
of Use (CBAM-LoU v1.1). The University of North Texas, Denton, TX.
https://iittl.unt.edu/content/concerns-based-adoption-model-levels-use-cbam-lou. Reprinted with
permission.
122
Appendix C: Technological Pedagogical Content Knowledge (TPACK) Questionnaire
Question stem
TK (technological knowledge)
I know how to solve many of my own technology problems.
I learn to use new technologies easily.
I keep up with important new educational technologies.
I routinely design lessons in which students learn using technology.
I know about a lot of different technologies
CK (content knowledge)
I have sufficient content knowledge of the subject that I teach.
I can clearly explain the content of the subject that I teach.
I am aware of common misconceptions that students’ have in the subject that I teach.
I am aware of the prerequisite knowledge students’ need to be successful in the subject that
I teach.
I use different ways of assessing students’ level of understanding of the subject that I teach.
PK (pedagogical knowledge)
I use appropriate instructional tools (models, examples, images, etc.) to explain concepts
within the subject that I teach.
I can adjust my teaching approaches for students with different learning needs.
In teaching, I create an atmosphere for appropriate interactions between teachers and
students.
I adjust my teaching based on students’ level of comprehension.
I use different teaching approaches when teaching different content in my subject area.
123
Question stem
TCK (technological content knowledge)
I use technology to enhance students’ understanding and learning of the content.
I use technology to explain concepts in the subject that I teach that are difficult for students
to understand.
I use technology to promote teaching activities for a specific course unit.
I can choose appropriate technology that enhances my teaching for a specific course unit.
I help students use technology to collect or organize information.
PCK (pedagogical content knowledge)
My teaching approaches make students stay interested in the content of the subject matter.
I use different teaching approaches such as group discussions and collaboration to teach the
contents.
I know how to choose effective teaching approaches to guide students’ learning and
thinking.
I use a variety of teaching approaches to transform subject matter into comprehensive
knowledge.
I create a classroom circumstance to promote students’ interest for learning.
TPK (technological pedagogical knowledge)
I use technology to create teaching activities for student interactions.
I use technology to explain the content of the subject matter.
I use technology to enhance my teaching effectiveness.
I use technology to get students motivated in learning and help them learn diligently.
I use technology to enrich my teaching materials and content.
124
Question stem
TPCK (technological pedagogical content knowledge)
I integrate contents, technologies, and teaching approaches to teach subject units.
I use interactive technology (such as iPads, smartphones, or applications such as Pear Deck,
back channels or polls) to promote learning and inquiry of lessons.
I use technology to find out students’ understanding of abstract concepts of the subject.
I use technology and teaching approaches in different course units to help students
comprehend easily.
Using technology can improve my teaching approaches to promote students’ learning.
Note. Technology is a broad concept that can mean a lot of different things. For this
questionnaire, technology is referring to digital technology/technologies we use such as
computers, laptops, desktops, iPads, smartphones, Apple TV, software programs, applications,
etc. Participants respond to each statement by selecting only one response: SD = Strongly
Disagree, D = Disagree, A = Agree, SA = Strongly Agree. From “Exploring the TPACK of
Taiwanese Elementary Mathematics and Science Teachers with Respect to Use of Interactive
Whiteboards,” by S.-J. Jang and M.-F. Tsai, 2012, Computers & Education, 59(2), 327–338.
Reprinted with permission.
125
Appendix D: Technology Integration Self-Efficacy Scale (TISES)
Question stem
I feel confident that I understand technology and its capabilities well enough to
maximize them in my classroom.
I feel confident that I have the skills necessary to use technology for instruction.
I feel confident that I can successfully teach relevant subject content with
appropriate use of technology.
I feel confident in my ability to evaluate applications for teaching and learning.
I feel confident that I can use correct technology terminology when directing
students’ computer use.
I feel confident I can help students when they have difficulty with their technology
devices.
I feel confident I can effectively monitor students’ technology use for project
development in my classroom.
I feel confident that I can motivate my students to participate in technologybased
projects.
I feel confident I can mentor students in appropriate uses of technology.
I feel confident I can consistently use educational technology in effective ways.
I feel confident I can provide individual feedback to students during technology use.
I feel confident I can regularly incorporate technology into my lessons, when
appropriate for student learning.
I feel confident about selecting appropriate technology for instruction based on
curriculum standards.
I feel confident about assigning and assessing technology-based projects.
I feel confident about keeping curricular goals and technology uses in mind when
selecting an ideal way to assess student learning.
I feel confident about using technology resources (spreadsheets, digital portfolios,
etc.) to collect and analyze data from students’ tests and products to improve
instructional practices.
I feel confident that I will be comfortable using technology in my teaching.
I feel confident that I can be responsive to students’ needs during technology use.
126
Question stem
I feel confident that, as time goes by, my ability to address my students’ technology
needs will continue to improve.
I feel confident that I can develop creative ways to cope with system constraints
(such as budget cuts on technology facilities and equipment) and continue to teach
effectively with technology.
I feel confident that I can carry out technology-based projects even when I am
opposed by skeptical colleagues.
Note. Teachers are instructed to indicate the strength of their agreement or disagreement on each
of the statements using the definition of technology integration as using technology devices to
support students as they construct their own knowledge through the completion of authentic
meaningful tasks. Participants were instructed to answer here statement from four answer
choices: SD = Strongly Disagree, D = Disagree, A = Agree, SA = Strongly Agree. From
“Increasing Pre-service Teachers’ Self-Efficacy Beliefs for Technology Integration by L. Wang,
P.A. Ertmer, and T.J. Newby, 2004, Journal of Research on Technology in Education, 36(3),
231–250. Reprinted with permission.
127
Appendix E: CBAM-LoU Survey Permission
Note. From “Concerns-Based Adoption Model (CBAM) Levels of Use of an Innovation
(CBAM-LoU)” by D. Griffin and R. Christensen, 1999. Institute for the Integration of
Technology into Teaching and Learning. Reprinted with permission.
128
Appendix F: TPACK Questionnaire Permission
129
130
131
Appendix G: TISES Survey Permission
132
Appendix H: Permission from The University of Southern California Institutional Review
Board
133
134
Appendix I: Permission to Conduct Study
135
136
Appendix J: Participant Invitation Email
Dear participant,
As a doctoral student at the University of Southern California (USC), I am conducting a study
for my dissertation to understand teachers’ technology self-efficacy and their levels of
confidence to integrate technology into instructional practices. As a participant, your responses
will be anonymous, and your name will not be associated with any research findings. Your
participation is entirely voluntary and does not entail any foreseeable risks. You may choose not
to participate or complete/submit the online survey at any time.
There is no compensation for participating. However, by participating in the study, you will be
able to (a) self-reflect on your instructional practices and (b) contribute to the scholarly research
as your input is extremely valuable for future professional development, serve as baseline data
for improvement to technology initiatives, and facilitate future coaching in instructional
technology. This survey takes approximately 15 minutes to complete. By clicking the survey link
below and submitting your survey, you consent to participate in this study.
The Internal Review Board (URB) at USC has approved this survey instrument and granted
permission for its use by all the applicable sections of the IRB policies. This approval has been
reported to the IRB board.
Thank you in advance for your consideration and participation. If you have any questions
regarding this study, please contact the principal researcher via email using the link listed below.
Sincerely,
Jennifer K. Norman
Doctoral Student
jknorman@usc.edu
Online Survey Link: https://usc.qualtrics.com/jfe/form/SV_6ro1jCxlnWeHFwG
Abstract (if available)
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Technology integration and self-efficacy of in-service secondary teachers in an international school
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Degree Conferral Date
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Publication Date
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