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Student engagement: a quantitative analysis on aspects that are predictive of engagement

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Student engagement: a quantitative analysis on aspects that are predictive of engagement

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Content Student Engagement: A Quantitative Analysis on Aspects that are Predictive of
Engagement
by
Kyle Joseph Coppes
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
December 2022

© Copyright by Kyle Joseph Coppes 2022
All Rights Reserved

The Committee for Kyle Joseph Coppes certifies the approval of this Dissertation

Committee Member Courtney Malloy
Committee Member Alison Muraszewski
Kimberly Hirabayashi, Committee Chair

Rossier School of Education
University of Southern California
2022

iv

Abstract
Research on student engagement shows dwindling levels of engagement as students progress
from elementary school through the high school. In the context of this research study, similar
trends existed in the school setting as shown through the Student Voice Survey. The purpose of
this study was to determine if any aspects were predictive of student engagement. The study
utilized a quantitative methods design for data gathering and analysis. A census of students was
taken across the secondary school, consisting of 592 respondents. The findings of the research
indicate that student-teacher relationships, a sense of school belonging, a sense of
accomplishment, confidence to take action are all predictive of student engagement. Implications
of this study indicate that schools could target initiatives and programmatic development to build
on these four aspects with the overall aim to improve student engagement levels.
Keywords: behavioral engagement, cognitive engagement, emotional engagement,
student engagement, teacher-student relationship, teacher care, teacher understanding.

v

Dedication
First and foremost, I want to thank my wife and children for supporting me through this entire
process. If it were not for my wife Dina, and her endless support and understanding of the time
commitment one needs to undertake doctoral work, this research project would have gone on
forever. To Ramzi and Sophia, my two lovely children, I promise to make up all the lost
Saturday mornings I spent in the office finishing up this dissertation.

vi

Acknowledgements
I want to thank Dr. Hirabayashi, Dr. Malloy, and Dr. Muraszewski, my dissertation
committee for all your support along this long and winding journey. Your guidance and wisdom
ensured that this dissertation is a worthy academic pursuit. I would also like to thank Dr. Quaglia
from the QISA Institute for releasing the raw data of the Student Voice Survey which constituted
the quantitative data and basis for this research project.

vii

Table of Contents
Abstract …………………………………………………………………………………………...iv
Dedication …………………………………………………………………………………………v
Acknowledgements……………………………………………………………………………….vi
List of Tables……………………………………………………………………………………... x
List of Figures…………………………………………………………………………………….xi
Dissertation Title…………………………………………………………………………………..1
Context and Background of the Problem…………………………………………………. 2
Purpose of the Project and Research Questions…………………………………………...2
Importance of the Study………………………………………………………………….. 3
Literature Review……………………………………………………………………….... 3
Student Engagement…………………………………………………………….... 4
Historical Context of Research on Student Engagement………………..... 4
Student Engagement Conceptualized…………………………………….. 6
Behavioral Engagement…………………………………………... 6
Emotional Engagement…………………………………………… 8
Cognitive Engagement………………………………………….... 9
Student Engagement and Motivation……………………………………. 10
Student Engagement and Achievement Outcomes……………………… 12
Student-Teacher Relationships………………………………………………….. 13
Teacher Care and Understanding and Student Engagement…………….. 14
Conceptual Framework………………………………………………………………….. 16
Methodology…………………………………………………………………………….. 19

viii

Research Setting………………………………………………………………… 19
The Researcher………………………………………………………………………….. 20
Data Sources…………………………………………………………………….. 20
Participants……………………………………………………………….21
Instrumentation………………………………………………………….. 21
Data Collection Procedures………………………………………………23
Data Analysis……………………………………………………………. 23
Validity and Reliability………………………………………………………….. 24
Findings…………………………………………………………………………………. 25
Research Question 1: Do the subscales on the Student Voice Survey differ by
gender or age?........................................................................................................ 27

Research Question 2: What are the correlations between the various subscales on
the Student Voice Survey?..................................................................................... 32

Research Question 3: To what degree, if at all, do the various subscales on the
Student Voice Survey predict student engagement?..............................................33

Summary………………………………………………………………………… 34
Recommendations………………………………………………………………………. 34
Discussion of Findings………………………………………………………….. 34
Recommendations for Practice…………………………………………………. 35
Recommendation 1: Teacher training on the impact of teacher care and
understanding and the creation of a teacher mentor program…………… 35

Recommendation 2: Create student goal-setting initiative and celebrate
individual successes ……………………………………………………...36

Recommendation 3: Use programmatic development to target student
belonging…………………………………………………………………37

Limitations and Delimitations……………………………………………………38
Recommendations for Future Research ………………………………………….38

ix

Conclusion ……………………………………………………………………………….39
References ……………………………………………………………………………………….40
Appendix A: Definitions …………………………………………………………………………45
Appendix B: The Researcher …………………………………………………………………….47
Appendix C: Ethics ………………………………………………………………………………48

x

List of Tables
Table 1: Cronbach’s alpha for Subscales 24
Table 2: Descriptive Statistics for Age 25
Table 3: Frequency and Percent for Age 25
Table 4: Frequency and Percent for Demographics 26
Table 5: Eight Subscales: Descriptive Statistics 26
Table 6: Descriptives for Gender by Dependent Variables 27
Table 7: Results Independent Samples t Test: Gender by Dependent Variables 28
Table 8: Descriptives Statistics: Age by Dependent Variables 30
Table 9: Results Independent Samples t Test: Age by Dependent Variables 30
Table 10: Bivariate Correlations for Eight Dependent Variables 32
Table 11: Results of Regression: Predictors of Engagement (Super Subscale) 33

xi

List of Figures
Figure 1: Adapted SEC Model 14
Figure 2: The Student Aspirations Framework 17

1

Student Engagement: A Quantitative Analysis on Aspects that are Predictive of
Engagement
Educators have been attempting to find the panacea for increasing student engagement
levels since the 1980’s with varying degrees of success (Reschly & Christenson, 2012). Pianta et
al. (2012) contend that the student-teacher relationship plays a central role in the complex,
multidimensional concept of student engagement. The broad, overarching aim of this study is to
investigate the nature of student engagement and its implications in developing school
improvement initiatives. One might argue that the ultimate goal of K-12 education is to prepare
students to be capable and ready to either engage in higher education or directly join the
workforce. As such, on a global scale, education is seen as the great equalizer. Access to a
quality education can open doors and impact overall lifetime earnings (Chapman et al., 2011).
And yet, a problem of practice in the field of education is those students who actively or
passively disengage from their educational experience. The extreme outcome of a disengaged
learner is complete withdrawal, ultimately ending in drop out (Chapman et al., 2011). The far
more common experience of the disengaged learner is underperformance (Wang & Eccles,
2011). Year after year of not reaching one’s full academic potential in a K-12 setting results in
missed opportunities at university and beyond (Chapman et al., 2011). As students progress
through schooling, research indicates that engagement levels slowly decline (Corso et al., 2013).
At the American International School (AIS), students are following a similar trend.

2

Context and Background of the Problem
AIS is a private, K-12 international school located in the Middle East.
1
The student
population consists of 1,050 students from over 55 countries who speak more than 35 mother
tongue languages. A strategic pillar of the school’s development plan for the 2018/19 and
2019/20 academic years was to increase student engagement levels across the secondary school.
Survey data from the Student Voice Survey administered at AIS in 2016 indicated low levels of
engagement, specifically emotional engagement, across the secondary school student population.
The survey revealed that only 48% of students feel that they are a valued member of the school
community. Additionally, administrator walkthrough data demonstrated low levels of student
behavioral engagement with an average of 35% of students engaged in off-task behaviors during
the course of 50 lesson walkthroughs in the fall quarter of the 2019/20 academic year. During the
same time period, the school’s Measures of Academic Progress (MAP) test results demonstrated
that only 56% of students are meeting expectations in the areas of math, reading, language usage
and science, demonstrating a lack of cognitive engagement across the student body.
Purpose of the Project and Research Questions
The specific purpose of this study is to investigate the relationship between the various
subscales on the Student Voice Survey as well as to determine of any of the subscales are
predictive of student engagement. In order to do so, this research study will examine the
following research questions through a quantitative analysis of the results from the Student
Voice survey:
1. Do the subscales on the Student Voice Survey differ by gender or age?

1
For the purposes of protecting anonymity, this research study will use the pseudonym of the American
International School (AIS) when discussing the specific organizational context in which the problem of practice
exists.

3

2. What are the correlations between the various subscales on the Student Voice Survey?
3. To what degree, if at all, do the various subscales on the Student Voice Survey predict
student engagement?
Importance of the Study
Research has shown that disengaged students underperform and have lower overall
academic outcomes (Finn, 1989; Chapman et al. 2011; Finn & Zimmer, 2012). Additionally, as
students progress through school from elementary to secondary, more and more students struggle
with engagement (Corso et al., 2013). The Quaglia Institute for Aspirations (2013) conducted a
survey of over 90,000 secondary students in more than 350 U.S. schools and discovered over
half of all students are chronically disengaged. Wang and Eccles (2011) found that declines in
overall school participation, negative affective affiliations with school, and a lack of self-
regulated learning all correlate with a decrease in overall academic achievement. The problem of
low student engagement, specifically in secondary education, is one of great importance as
research suggests that disengaged students consistently underperform when compared to their
engaged classmates (Klem & Connell, 2004: Wang & Holcombe, 2010; Zyngier, 2008).
Literature Review
This literature review addresses the problem of low student engagement and the impact
on educational outcomes. This literature review will be broken down into two large sections. The
first section is student engagement which is further delineated by sections on the historical
context of research on engagement, student engagement conceptualized, student engagement and
motivation, as well as student engagement and academic outcomes. The second section focuses
on student-teacher relationships and their connection with student engagement.

4

Student Engagement
Research on student engagement gained prominence in the late 1980’s and has stayed at
the forefront of research relating to student performance and graduation rates ever since
(Chapman et al., 2011). In order to provide a framework for a conversation regarding
engagement, this section will be delineated into a subsection on the historical context of research
on student engagement and another on how student engagement has been conceptualized since
the early 2000’s. From there, the conversation will shift to engagement and motivation and
ultimately to the connection between engagement and academic outcomes.
Historical Context of Research and Programmatic Implementation Regarding Student
Engagement
Educational researchers have been investigating the concept of engagement and its link to
student outcomes since the 1980’s (Reschly & Christenson, 2012). The interest lies in the
inherent desire to improve learning and ultimately student achievement outcomes. Work on
engagement has gained prominence in the macro levels of educational research and the realm of
state and national policy development, as well as the micro level of school improvement
planning (Fredricks et al., 2016). This is due in large part to the potential positive impact that
increased levels of student engagement have on various problems plaguing the educational
system, such as underachievement, high dropout rates, increased levels of student boredom as
students progress from elementary into secondary schools, as well as student alienation (Lei et
al., 2018). Mosher and McGowan (1985) were the first to conduct a review of the literature to
find only implicit references to the notion of student engagement rather than any direct
conceptualization and subsequent measurement of it in secondary school settings. They
concluded their study with a broad, yet multifaceted definition to include the “attitudes leading

5

to, and the behavior of, participation in” (p. 14) the school environment (Mosher & McGowan,
1985). The notion that student engagement is multidimensional only continued to exist in the
subsequent literature.
In his seminal work on the problem of school dropout, Finn (1989) established the
participation-identification model which focuses on the behavioral and emotional components of
a student’s overall involvement in schooling. Finn (1989) contends that identification refers to
the internal sense of belonging to and valuing the school. Participation, on the other hand, is an
external manifestation which can be seen as on-task behaviors in the classroom or involvement
in extracurricular school activities. Finn’s (1989) ultimate purpose was to establish intervention
strategies aimed at increased levels of student engagement which result in school completion.
This theoretical framework would serve as the foundation for Check & Connect, an evidence-
based intervention program created to promote school completion (Christenson & Reschly,
2010).
Check & Connect has been implemented in a variety of school settings, from urban to
suburban, and across all age groups from elementary to high school (Christenson & Reschly,
2010). Numerous studies have demonstrated the effectiveness of the program in not only
reducing elements of disengagement such as truancy, tardiness and suspensions, but also
improving behaviors and academics, leading to increased levels of school completion
(Christenson & Reschly, 2010). The program consists of three key elements: relationship-
building; systematic monitoring of attendance, academic performance, and behavior; and
following students and families (Christenson & Reschly, 2010). Check & Connect views student
engagement as a malleable state of being, one that is highly influenced by external factors such
as family and the overall school community (Christenson & Reschly, 2010).

6

Student Engagement Conceptualized
Reschly and Christenson (2012) contend that the increasing interest in student
engagement has stemmed from three distinct arenas. The first of which is situated in a response
to the growing concern around school dropout rates and the development of intervention
strategies aimed to curtail the problem (Reschly & Christenson, 2012). The second lies in the
broader movement of school reform research and the third comes from the literature on
motivation (Reschly & Christenson, 2012). These varying antecedents drive the research down
diverging paths and the only constant in the field of research on student engagement is that there
is no constant. At best, the research agrees in the multidimensional nature of student
engagement, but with nuanced differences in each study. Consequently, it is up to the researcher
to clearly establish a working definition of student engagement. As such, this study will rely
heavily on the first established multidimensional conceptualization of engagement comprising
behavioral, emotional, and cognitive components (Fredricks et al., 2004).
Behavioral Engagement
The notion of behavioral engagement has a surface level simplicity to it. Classroom
educators will often view engagement through the narrowed lens of time-on-task. However,
behavioral engagement can be further broken down into three distinct components (Fredricks et
al., 2004). The first sub-level definition of behavioral engagement refers to student conduct that
aligns with the general school rules and norms set out by the teacher (Fredricks et al., 2004). This
type of rule-following behavior would lead to students who arrive to class on time, speak when
called upon, and treat their peers with respect. Beyond rule following, the second sub-level
definition refers to the active involvement in learning activities and academic tasks (Fredricks et
al., 2004). This type of behavior is often seen as effort and/or persistence in completing complex

7

academic tasks (Birch & Ladd, 1997). Furthermore, offering probing questions which contribute
to the overall class discussion is a critical component of behavioral engagement (Fredricks et al.,
2004). The third sub-level definition of behavioral engagement refers to active participation in
extracurricular activities (Finn, 1989). This type of behavior can be seen when students get
involved in programs such as athletics, drama, music, and/or student government. As behavioral
engagement is by far the most observable of the multidimensional model of engagement, the
measurement strategies employed to collect data are plentiful.
Data collection methods for studying student engagement range from student self-reports
to teacher ratings and from observations to interviews (Fredricks & McColskey, 2012). The
benefit of assessing behavioral engagement lies with access to large data sets normally collected
by schools. These data can range from attendance records to homework completion rates as well
as records indicating noncompliance with school rules and regulations. In order to gain deeper
insights into behavioral engagement, researchers often pair these objective data points with the
subjective perception of students through the use of student self-reports (Fredricks &
McColskey, 2012). In order to assess persistence, Finn et al. (1995) asked teachers to determine
if a particular student “is persistent when confronted with difficult problems” and “approaches
new assignments with sincere effort.” Fredricks and McColskey (2012) conducted a meta-
analysis of 11 self-report survey instruments and found that of the many scales and subscales of
behavioral engagement, students largely reported on attention, attendance, time dedicated to
homework, preparedness, participation, concentration, effort, compliance, and risk-taking
behaviors.

8

Emotional Engagement
The study of student emotional engagement focuses on the affective reactions both in and
outside of the classroom (Fredricks et al., 2004). Finn’s (1989) identification portion of the
participation-identification model, or the overall sense of belonging to the school and the value
that comes from school-related success, lies firmly in the realm of emotional engagement. Yet,
Finn’s (1989) identification concept of school connectedness does not fully expound on the
entirety of recent conceptions of emotional engagement. The feeling of value alone has further
divisions. Eccles et al. (1983) have divided value into four component parts: interest, attainment
value, utility value, and cost. Although Eccles work explicitly deals with motivation rather than
engagement, it brings to light the interconnectedness of these theories and models. If engagement
is to be considered as an expression of involvement in school, then motivation might be viewed
as it’s antecedent.
Another aspect of emotional engagement is that of investment or high emotional
involvement in a particular task. Csikszentmihalyi (Nakamura & Csikszentmihalyi, 2014) refers
to this state of being as flow. An individual in a flow state is so incredibly caught up in the task
at hand that they lose track of time (Fredricks et al., 2004). Emotional engagement, and the
ability to measure it accurately, is a subjective matter. As such, most research studies have relied
on student self-reports to determine levels of emotional engagement (Fredricks et al., 2004).
In their analysis of 11 self-report survey instruments, Fredricks and McColskey (2012)
found a variety of approaches to measure emotional engagement. The ISQ survey asked students
to rate their agreement with statements like “school is one of my favorite places to be” (sense of
belonging) and “most of the things we learn in class are useless” (value in school-related
activities) in order to assess students’ level of identification with the school (Fredricks &

9

McColskey, 2012). On the other hand, the SEI asked students to rate their agreement with
statements like “adults at my school listen to the students” and “I have some friends at school” to
assess student relationships and their impact on emotional engagement (Fredricks & McColskey,
2012). Ulmanen et al. (2016) found a strong association between teacher-student relationships
and perceived peer-group dynamics, particularly in a secondary school setting. Emotional
engagement, particularly in the form of school connectedness measured through teacher-student
relationships as well as peer group relationships, has been shown to positively impact future
orientations (Crespo, et al., 2013).
Cognitive Engagement
Research on cognitive engagement has focused on four main areas, the first of which is a
forward focus on future aspirations which manifests itself in setting goals (Fredricks &
McColskey, 2012). The second component is the cognitive strategy utilized for deep learning of
academic materials while the third focuses on self-regulatory strategies such as planning and
actively seeking out information beyond what is provided by the teacher (Fredricks &
McColskey, 2012). Ben-Eliyahu et al. (2018) investigated the multidimensionality of
engagement and argue that the self-regulated component of cognitive engagement is task
dependent. At times, processes such as elaboration, organization may or may not be present
depending on the nature of the task. Alternatively, actively involving oneself in extra work that is
beyond the scope of the requirements of the class or school is a sign of high cognitive
engagement (Fredricks & McColskey, 2012). A preference for challenge and the ability to be
flexible while engaged in a problem-solving activity have also been used as measures of
cognitive engagement (Fredricks et al., 2004). Like behavioral engagement, most studies have

10

relied on student self-reports to assess levels of cognitive engagement (Fredricks & McColskey,
2012).
Fredricks and McColskey (2012) found numerous question types in the several self-
report surveys to measure cognitive engagement which they compared in their meta-analysis.
The ATM survey asked students questions regarding varying levels of self-regulation practices
as related to the study of math (Fredricks & McColskey, 2012). The SEI asked students the
extent to which they agreed with the statement “the tests in my classes do a good job of
measuring what I am able to do” to measure the degree to which students have an understanding
and appreciation for the relevance of schoolwork (Fredricks & McColskey, 2012) The School
Engagement Measure asks, “When I read a book, I ask myself questions to make sure I
understand what it is about?” (Ben-Eliyahu et al., 2018). Ultimately, these surveys rely on self-
reported notions of what it means to be cognitively engaged at school.
Student Engagement and Motivation
Discussions regarding motivation and engagement have been analyzed deeply for
decades and remain at the forefront of research. This is likely due to the belief that engaged
students have higher academic outcomes than their non-engaged classmates (Klem & Connell,
2004: Wang & Holcombe, 2010; Zyngier, 2008). These unengaged students are often also
labeled as unmotivated which leaves teachers conflating these two constructs. Educational
researchers however have drawn a clear distinction between motivation and engagement.
Engagement has been defined as a conceptual framework consisting of behavioral,
emotional, and cognitive engagement (Fredricks et al., 2004). In each case, engagement refers to
the presence of an action, feeling, or thought which are the outcome of some antecedent.

11

Motivation is that antecedent (Reeve, 2012). If engagement is an outward expression, it is
considered as the manifestation of motivation (Raftery, Grolnick & Flamm, 2012).
A leading conceptual framework in motivation studies is the Eccles expectancy-value
theory of motivation. Expectancy-value theory lives in the overall world of research on
motivation in an attempt to explain a person’s choice, persistence and performance for a given
task (Wigfield & Eccles, 2000). The model consists of a number of key motivational factors
including the value one ascribes to a given task, the task-specific expectancy of completion, and
the belief in one’s overall ability (Fan, 2011).
Research suggests that students’ perception of the instrumentality of class work as crucial
for attaining success in future achievement goals as a key motivating factor (Greene et al., 2004).
In their seminal work on expectancy-value theory, Eccles et al. (1983) describe instrumentality
as part of the larger utility and attainment value constructs. Fan (2011) contends that task value is
generally a good indicator of persistence or effort, two common components of overall
behavioral student engagement.
Wang and Eccles (2013) argue that cognitive engagement is a result of high levels of
expectancy of success on the part of students. Students have higher levels of expectancy based
on prior successes and therefore it is incumbent upon teachers to provide differentiated
achievement tasks for students within their zone of proximal development (Levykh, 2008). These
tasks will challenge students yet provide them with tasks still within their reach. Successful
completion of these tasks will build future positive expectancy, thus expanding their overall
cognitive engagement.

12

Student Engagement and Achievement Outcomes
The impact of positive behavioral, emotional, and cognitive engagement levels on the
process of learning has been researched extensively. Wang and Eccles (2011) analyzed data sets
from the Maryland Adolescent Development in Context Study (MADICS) and the Study of
Adolescents in Multiple Contexts (SAMC). They found that students who follow school rules
and generally avoid troublemaking behaviors, such as truancy, academic dishonesty, and
breaches to the school’s code of conduct, tend to achieve higher outcomes and aspire to further
education beyond that of secondary school. Beyond the basic compliance level of behavioral
engagement, studies on emotion have proved to highlight its importance in the field of student
engagement research. Wang & Eccles (2011) also found emotionally engaged students,
specifically students with a strong sense of belonging to their school, had higher grade point
averages and educational plans that extended beyond high school. Cognitive engagement
“involves psychological investment in learning and a mastery of academic material” (Corso et
al., 2013). Overall, it is a student’s desire to delve deeply into a topic, plan their studies and
monitor their success. Greene et al. (2004) demonstrate a positive relationship between high
levels of cognitive engagement and perceived instrumentality, thus impacting overall motivation
and strong academic outcomes.
Establishing practical applications of theory into practice to improve the engagement
dilemma in secondary education is critical for educational practitioners. Chapman et al. (2011)
found that the average freshman graduation rate for public schools across the United States for
the class of 2008/09 was 75.5% (p. 13). The Quaglia Institute for Student Aspirations (2014)
found that students who are engaged are sixteen times more likely to be academically motivated.

13

Increased levels of student engagement lead to improved academic success, consequently
improving the graduation rates of students across the globe (Chapman et al., 2011).
Student-Teacher Relationships
The role of the classroom teacher on student engagement cannot be overstated. Within
every classroom there exists a teacher, students and the content; the interactions of which has
been described as the “student engagement core (SEC) model” (Corso et al., 2013).
In the SEC model, the interaction between teacher and student is characterized as
relationship. Koca (2016) found that positive teacher-student relationships promote a secure
learning environment where students feel safe to take intellectual risks. Klem and Connell (2004)
analyzed longitudinal data sets utilizing the Research Assessment Package for Schools (RAPS)
as a benchmark assessment to gauge the impact of comprehensive school reform models. They
found that a strong teacher-student relationship, which is built through explicit displays on the
part of the teacher to show care for the students, has a positive impact on student outcomes. This
is accomplished through specific pedagogical practices such as promoting fairness, encouraging
a sense of well-being, and genuinely seeking out students’ interests. These practices effectively
target emotional engagement by establishing a deep sense of belonging to the learning
environment. The teachers’ next role is to motivate by establishing high levels of task value
amongst their students in relation to academic assignments.
In the SEC model, relevance is the interaction between the student and the content (Corso
et al., 2013). Corso et al. (2013) argues the more relevant the topic, the more likely a student is to
be engaged in the learning process. They have identified “three ways the content of a class may
be relevant to students: relevance to one’s current interests, relevance to one’s future goals, and
relevance to one’s identity or sense of self” (p. 56). The role of the classroom teacher is to

14

establish a connection between the students’ interests (intrinsic value), goals (utility value) or
identity (attainment value) and the content being delivered. Once the teacher fosters high levels
of task value, and students feel the level of support offered by the teacher, they tend to delve
more deeply, commit more readily, and show evidence of higher achievement (Perry et al.,
2010). The classroom teacher who can skillfully blend motivational and learning theory within a
framework on student engagement into their practice is a crucial step in establishing and
maintaining high levels of student engagement.
Teacher Care and Understanding and Student Engagement
At the crux of the student-teacher relationship lies the notions of teacher care and
understanding. Martin and Dowson (2009) describe it as relatedness. This can be observed in the
adapted SEC Model below whereby relationship is defined as teacher care and understanding.

Figure 1
The Adapted SEC Model

(adapted from Corso et al., 2013)
Care
&
Understanding

15

This is developed through a concerted effort on the part of teachers to actively listen to students’
attitudes and opinions related to decisions that impact their educational experience (Martin &
Dowson, 2009). It also includes getting to know students on a personal level, including their
interests outside of school and future aspirations (Martin & Dowson, 2009). Interestingly,
declared educator awareness of the conceptual importance of the teacher-student relationship and
its impact on engagement does not always translate into observed practice, specifically regarding
the time spent in the classroom getting to know students interests and personal context (Pedler et
al., 2020). Setting high, but achievable expectations and accepting each student’s individuality
and without showing favoritism are also ways to increase relatedness in the classroom (Martin &
Dowson, 2009).
Cooper and Miness (2014) define relatedness as a sense of belonging and the belief in
strong interpersonal connections across the school community. Relatedness has the “power to
communicate worth, respect, and care to students” (Cooper & Miness, 2014). The specific notion
of teacher care is defined as a deep concern for the well-being of a student (Cooper & Miness,
2014). Student perceptions of teacher care have been identified as a general sense of respect and
encouragement as well as individual help with academic work (Cooper & Miness, 2014).
Additionally, the more frequent the individual interaction, within and outside of the classroom,
between a teacher and the student has been identified as a key indicator of perceived care
(Cooper & Miness, 2014). Students identify the notion of fairness and equal treatment of
students in applying classroom rules and school policies as part of the larger concept of teacher
care (Cooper & Miness, 2014). Lastly, students feel a deep sense of care from their teachers
when their support them with personal issues (Cooper & Miness, 2014). The expression of care
from teachers often comes from two specific areas, both related to individual conversations. The

16

first is inquiring about their personal lives and the second is discussing academic progress
(Cooper & Miness, 2014). Cooper and Miness (2014) go further to draw a clear distinction
between care and understanding. While care is seen as concern for well-being, understanding
goes further to the level of knowing who the student is as a person (Cooper & Miness, 2014).
In summary, student engagement is a multi-faceted concept that has shifted over time. It
has strong research ties to the concept of motivation and has been shown to have an impact on
achievement outcomes in a school setting. The teacher-student relationship has also been shown
to be a key player in student engagement research.
Conceptual Framework
The overall conceptual framework utilized in this study is the Student Aspirations
Framework (Quaglia & Corso, 2014). It consists of student aspirations as the overarching result
of three guiding principles, which are self-worth, engagement, and purpose. Self-worth is defined
as a combination of student belonging, the concept of heroes, and a sense of accomplishment.
Engagement is comprised of the notions of fun and excitement, curiosity and creativity, and a
spirit of adventure. Purpose is a combination of leadership and responsibility and confidence to
take action. The methodological approach is a quantitative analysis of the Student Voice Survey,
an instrument developed around the Student Aspirations Framework consisting of 67 questions,
each feeding into one of the eight conditions of belonging, heroes, sense of accomplishment, fun
and excitement, curiosity and creativity, spirit of adventure, leadership and responsibility, and
confidence to take action, see figure 3 below (Quaglia & Corso, 2014).

17

Self-worth is a guiding principle comprised of a sense of student belonging, the notion of
heroes, and a sense of accomplishment. The condition of belonging harkens back to the
participation-identification model Finn (1989) established where he contends that identification
refers to the internal sense of belonging to and valuing the school. This notion of membership
and understanding the value one brings to the community is crucial to the condition of belonging
(Quaglia & Corso, 2014). The condition of heroes refers to students having an adult advocate on
campus who believes in them and cares for them. Klem and Connell (2004) refer to it as the
teacher-student relationship while Martin and Dowson (2009) describe it as relatedness. In all
accounts, the concept hinges on the connectedness between the teacher and the student. Lastly,
the condition of a sense of accomplishment refers to the recognition one receives from various
Figure 2
The Student Aspirations Framework

Goal

Guiding Principles

Conditions

Aspirations

Self-Worth

Belonging

Heroes

Sense of Accomplishment

Engagement

Fun & Excitement

Curiosity & Creativity

Spirit of Adventure

Purpose

Leadership &
Responsibility

Confidence to Take Action

(adapted from Quaglia & Corso, 2014)

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forms of success in school, including high levels of effort (Quaglia & Corso, 2014). Each of
these conditions come together to form the guiding principle of self-worth.
As a guiding principle of the Students Aspirations Framework, engagement is comprised
of the conditions of fun and excitement, curiosity and creativity, and a spirit of adventure. Fun
and excitement is characterized by active engagement in school activities (Quaglia & Corso,
2014). This level of active engagement is defined in the literature as behavioral engagement.
Fredricks et al. (2004) describe it as following school rules and deep involvement in learning
activities. Birch and Ladd (1997) refer to it as effort and the determination to engage in and
finish complex learning tasks. Finn (1989) also describes it as engaging in extracurricular
activities. Quaglia and Corso (2014) focus on the level of enjoyment while actively engaging in
such activities. The condition of curiosity and creativity is characterized by inquisitiveness and
eagerness to learn new concepts or master new skills (Quaglia & Corso, 2014). The literature
defines this as cognitive engagement. Fredricks & McColskey (2012) identified it as setting
goals, engaging in deep learning of academic materials, and using self-regulatory strategies.
Fredricks et al. (2004) highlight the importance of adopting challenges as well as the capacity to
be adaptable while engaged in complex problem-solving activities. Lastly, the condition of a
spirit of adventure is characterized by the excitement to try new things with maintaining a high
degree of positivity even in the face of adversity (Quaglia & Corso, 2014). This type of
engagement is defined in the literature as emotional engagement. Csikszentmihalyi (2014) refers
to this high level of emotional involvement in a particular task as being in a state of flow.
Fredricks et al. (2004) characterize someone in a flow state as being so emotionally involved in a
task that they lose track of time. Each of these three conditions form the overall guiding principle
of engagement.

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The guiding principle of purpose is comprised of the conditions of leadership and
responsibility and confidence to take action. Quaglia and Corso (2014) define leadership and
responsibility as the ability for students to share their ideas, engage in decision-making regarding
their academic journey, and the capacity to be accountable for their choices and behaviors.
Furthermore, confidence to take action involves students setting rigorous, yet attainable goals
and following through in the steps necessary to achieve the goals which they set out to achieve.
The condition of leadership and responsibility, paired with the condition of the confidence to
take action, comprise the guiding principle of purpose (Quaglia & Corso, 2014).
Methodology
The overall design of this research study will rely on a quantitative approach utilizing an
existing data set. The Student Voice Survey was administered at AIS in 2016 by the Quaglia
Institute for Student Voice and Aspirations, a research institute dedicated to promoting student
voice and building student engagement in schools across the U.S. and internationally through the
application of the Student Aspirations Framework. The survey report provided to AIS from the
Quaglia Institute relied on descriptive statistics and was the impetus for the current research,
namely the discovery that only 48% of students felt that they were a valued member of the
school community. The current research project expanded on this by engaging in secondary data
analysis in the form of inferential statistical analysis of the data set.
Research Setting
AIS is a private international school in the Middle East serving roughly 1,050 students
from over 40 different countries. The diversity in the student population is represented by more
than 25 mother-tongue languages spoken in the school corridors. AIS follows the American
Education Reaches Out (AERO) standards as well as the International Baccalaureate Diploma

20

Program. Students who graduate earn an American High School Diploma by default and an IB
Diploma if they have followed that curricular path through their last two years in high school.
AIS operates with roughly 130 educators from nearly 10 different countries. The participants of
this research are students who attended AIS in 2016 when the Student Voice Survey was
administered.
The Researcher
The researcher served as the assistant principal in the secondary school during the time of
the Student Voice Survey and went on to serve two academic years as principal in the years after
the survey was conducted. Although the researcher was in a position of power with regards to the
participants, there is little to no impact on the overall results of the survey. The Quaglia Institute
for Student Voice and Aspirations was brought in as educational consultants and informed
students ahead of the survey that the data will be used to guide school improvement planning
through unpacking the voices of the student body. A Student Voice team was created that
consisted of student representation across all grade levels and members of staff that were not in
executive leadership positions. As such, the researcher did not serve on the Student Voice
Committee, but rather heard from them regarding the recommendations they made after
receiving the survey results.
Data Sources
This research study has made use of a quantitative methods approach. An established
survey instrument, the Student Voice Survey, along with an existing data set was used to conduct
secondary data analysis. This section will further discuss the participants involved, the
instrumentation, the data collection procedures, and ultimately the data analysis.

21

Participants
The Student Voice Survey data set constitutes a census of AIS students. The total number
of respondents to the survey were 592 representing students in grades 6 through 12. More than
99% of the total student body were present on the scheduled day of the survey as well as the
make-up day. In regard to gender, 311 of the respondents were male while 283 were female.
Only 1% of the respondents indicated that they do not plan on attending university. The
respondents’ nation of origin varies widely with over 40 nationalities represented. Roughly 40%
of these come from Arabic speaking countries with Lebanon representing the single largest
nationality. India, Pakistan, and Korea represent three noteworthy countries of origin, each
representing nearly 10% of the student population. The remaining 30% is spread out across the
entire globe.
Instrumentation
The Student Voice Survey consists of 67 questions across 3 guiding principles 8
conditions that impact student aspirations (Quaglia, 2017). The guiding principles are: (1) self-
worth; (2) engagement and (3) purpose. Each guiding principle is comprised of combining
several of the 8 conditions. Self-worth is comprised of (1) belonging; (2) heroes; (3) and a sense
of accomplishment. Engagement is comprised of (4) fun and excitement; (5) curiosity and
creativity; (6) and a spirit of adventure. Purpose is comprised of (7) leadership and
responsibility; and (8) confidence to take action (Quaglia, 2017). For the purposes of this
research study, the guiding principle of engagement is the only super subscale used in further
statistical analysis. A standard Likert scale was used containing strongly agree, agree, undecided,
disagree, strongly disagree, as well as did not answer. AIS added five additional questions to the

22

survey regarding aspects specific to school life, with the end result of the survey totaling 72
questions.
The Student Voice Survey is a proprietary instrument from the QISA Institute and
therefore direct instrument questions will not be shared in this research study. However, for the
purposes of providing clarity, each subscale with be characterized in some detail. The condition
of belonging included eight questions on the survey instrument. It is characterized by a sense of
fitting in, as well as both, being proud to be and feeling valued as, a member of the school
community (Quaglia, 2017). The condition of heroes included nine questions on the survey
instrument. Heroes are those individuals at school who inspire a student to excel and engage in
positive school activities and is deeply rooted in notions of respect and care (Quaglia, 2017). A
sense of accomplishment also included nine questions on the survey instrument. It is comprised
of notions of encouragement, recognition of effort, importance of success, and resilience
(Quaglia, 2017). The condition of fun and excitement included seven questions on the survey
instrument. It is characterized by notions of enjoyment, excitement, and active participation in
learning (Quaglia, 2017). The condition of curiosity and creativity includes ten questions on the
survey instrument. It is characterized by notions of inspiration, future aspirations, problem
solving, and innovation (Quaglia, 2017). The condition of spirit of adventure includes seven
questions on the survey instrument. It is characterized by notions of facing challenges, pushing
oneself to improve, and tackling a task with fear of failure (Quaglia, 2017). The condition of
leadership and responsibility includes seven questions on the survey instrument. It is
characterized by notions of voice, goal orientation, decision-making, and a willingness on the
part of teachers to learn from students (Quaglia, 2017). Lastly, the condition of confidence to
take action includes ten questions on the survey instrument. It is characterized as a belief in

23

future success, the ability to make a difference, the importance of university pursuits, and belief
that hard work results in accomplishments (Quaglia, 2017).
Data Collection Procedures
The Student Voice Survey was administered in advisory lessons from October 16, 2016
through November, 6, 2016. Parents of the students involved were required to sign off on a
parent permission slip in order to participate in the survey. Any student who did not return a
signed permission slip was automatically removed from the survey process. Students were given
the entire advisory lesson of 50 minutes to complete the survey. As the advisory lesson took
place directly before lunch, students were given extra time to complete the survey if need be.
Students were read explicit instructions regarding the purpose of the survey by their advisory
teacher, including that individual responses were anonymous. The Quaglia Institute for Student
Voice and Aspirations generated a report of the survey results for AIS on October 16, 2017. The
Student Voice Committee, comprised of both students and teachers, was developed shortly after
unpack the results of the report and provide possible direction to the school leadership team to
further support the development of student voice.
Data Analysis
A variety of inferential statistical tests were conducted to answer each of the three
research questions set out in this study. A series of independent samples t tests were performed
to determine the significance of any gender across the subscales in the data set. A series of
independent samples t tests were also conducted to determine the significance of age across the
various subscales in the data set. A Pearson r Correlational Coefficient was performed to
examined multiple bivariate correlations among the eight dependent variables. Lastly, a multiple

24

regression was performed to determine which of the dependent variables was the best predictor
of engagement.
Validity and Reliability
Merriam and Tisdell (2016) argue that all researchers aim to generate knowledge from
their research that is valid and reliable. In a quantitative method study, one important aspect of
survey instrument reliability is establishing internal consistency reliability (Salkind, 2020). The
Student Voice Survey is a well-established survey and has been administered to 452,329 students
in grade 6-12 between the 2009-2018 academic years (Quaglia Institute for Student Aspirations,
2018). A Cronbach’s alpha test was conducted to determine the internal consistency and
reliability for the Student Voice Survey instrument. The overall data set reveals that seven out of
nine subscales meet the minimum acceptable reliability level of .70. The subscale of spirit of
adventure has a questionable reliability level of .558, however when it is computed as part of the
super subscale of engagement (which combined fun and excitement, curiosity and creativity, and
a spirit of adventure), the reliability score is a strong .865. Lastly, the subscale of leadership
narrowly missed the acceptable level of .70 and as such is not used in answering research
question 3 which attempts to determine if the remaining subscales (belonging, heroes, a sense of
accomplishment, and confidence to take action) predict the super subscale of engagement.
Table 1

Cronbach’s alpha for Subscales

Subscale Alpha
Belonging .703
Hero .810
Sense of Accomplishment .733
Fun & Excitement .840
Curiosity & Creativity .839

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Spirit of Adventure .558
Leadership .680
Confidence to Take Action .772
Engagement (super subscale) .865

Findings
The following is a set of findings based on each of the three research questions. As a
point of departure, Tables 2, 3, and 4 provide age and demographic information on the 592
respondents. The respondents range in from 10 years of age to 18 years of age representing
students in grades 6 through 12 at the American International School, as seen in Tables 2 and 3.
Table 4 provides demographic information regarding ethnicity, albeit from a particularly North
American perspective. As such, this research study did not make further use of the demographic
information collected in the survey instrument.
Table 2
Descriptive Statistics for Age

N Range Minimum Maximum Mean Std. Deviation
Age 592 8 10 18 13.83 2.011
Valid N (listwise) 592

Table 3
Frequency and Percent for Age

Age Frequency Percent
10 14 2.4
11 75 12.7
12 93 15.7
13 89 15.0
14 84 14.2
15 86 14.5
16 95 16.0

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17 45 7.6
18 11 1.9
Total 592 100.0

Table 4
Frequency and Percent for Demographics

Race and Ethnicity Frequency Percent
White 229 38.6
Black or African American 38 6.4
Hispanic, Latino 25 4.2
Asian 166 27.9
Native Hawaiian 1 .2
American Indian 6 1.0
Other Pacific Islander 2 .3
Other 261 43.9
Total
2
728 122.5

Table 5 provides basic descriptive statistics on the eight subscales as well as the super
subscale of engagement. Responses to instrument items were collected through a standard Likert
scale rating with the following breakdown: 5 = strongly agree, 4 = agree, 3 = undecided, 2 =1
disagree, and 1 = strongly disagree. The means of the various subscales range from the lowest
rating of 3.31 for fun and excitement, to the highest of 4.02 for confidence to take action as you
can see in Table 5 below.
Table 5
Eight Subscales: Descriptive Statistics
N Range Min Max Mean Std. Deviation
Belonging Total Mean 592 4 1 5 3.44 .631
Hero Total Mean 592 3 2 5 3.54 .659
Accomplishment Total Mean 592 3 2 5 3.71 .596

2
In this table, the percentages add up to more than 100% since respondents were instructed to select all that apply.

27

Fun Excitement Total Mean 592 4 1 5 3.31 .769
Curiosity & Creativity Total Mean 592 4 1 5 3.65 .669
Spirit of Adventure Total Mean 592 3 2 5 3.72 .536
Leadership and Responsibility Total Mean 592 4 2 5 3.36 .646
Confidence to Take Action Total Mean 592 3 2 5 4.02 .557
Engagement (Super Subscale) 592 3 2 5 3.56 .590
Valid N (listwise) 592

Research Question 1: Do the subscales on the Student Voice Survey differ by gender or
age?
An independent samples t test was performed to answer research question one that
examined whether there was a significant difference for gender by eight dependent variables (i.e.
Belonging, Hero, Accomplishment, Fun/Excitement, Curiosity & Creativity, Leadership and
Confidence to Take Action). For the purpose of this analysis, gender was a grouping variable and
was treated as dichotomous in nature. The eight dependent variables were treated as continuous
or grouping variables. Examination of Table 6 shows the basic descriptive statistics for gender
by the eight dependent variables. Following this the t test was employed. Results of the t test can
be found in Table 7. Further examination of Table 7 found gender to not be statistically
significant for any of the eight dependent variables.
Table 6
Descriptives for Gender by Dependent Variables
Dependent Variable Grouping Variable N M SD
Belonging Male 311 3.47 .664
Female 283 3.41 .592
Hero Male 311 3.51 .692
Female 283 3.58 .618
Accomplishment Male 311 3.67 .622
Female 283 3.75 .563

28

Fun Excitement Male 311 3.30 .789
Female 283 3.33 .744
Curiosity & Creativity Male 311 3.65 .691
Female 283 3.65 .645
Spirit of Adventure Male 311 3.70 .523
Female 283 3.74 .547
Leadership and Responsibility Male 311 3.36 .651
Female 283 3.36 .643
Confidence to Take Action Male 311 4.03 .550
Female 283 4.01 .566

Table 7
Results Independent Samples t Test: Gender by Dependent Variables

Variable Variances F Sig t df Sig.
Belonging Equal variances not
assumed
3.322 .069 1.013 590 .312
Hero Equal variances
assumed

1.018 589.725 .309
Equal variances not
assumed
1.570 .211 -1.318 590 .188
Sense of
Accomplishment
Equal variances
assumed

-1.325 589.801 .186
Equal variances not
assumed
3.528 .061 -1.715 590 .087
Fun and Excitement Equal variances
assumed

-1.723 589.981 .085
Equal variances not
assumed
.352 .553 -.536 590 .592
Curiosity and
Creativity
Equal variances
assumed

-.537 589.188 .591
Equal variances not
assumed
.655 .419 .009 590 .993

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Spirit of Adventure Equal variances
assumed

.009 589.656 .993
Equal variances not
assumed
.341 .559 -.913 590 .362
Leadership Equal variances
assumed

-.911 578.888 .363
Equal variances not
assumed
.761 .383 -.074 590 .941
Confidence to Take
Action
Equal variances
assumed

-.074 586.323 .941
Equal variances not
assumed
.320 .572 .242 590 .809
.242 581.491 .809
*p < .05

A series of independent samples t tests were performed to answer the second aspect of
research question one that examined whether there was a significant difference for participants’
age by eight dependent variables (i.e. belonging, hero, accomplishment, fun and excitement,
curiosity and creativity, spirit of adventure, leadership and confidence to take action). For the
purposes of this analysis age was a grouping variable with two levels: < 14 yrs. of age and 14 or
more year of age). A histogram was performed in order to determine the mean for age and it was
determined after inspection of the histogram to use age 14 as the point to dichotomize the
variable in order to properly assess the statistical significance difference in age of the
respondents. The eight dependent variables were treated as continuous of grouping variables.
Examination of Table 8 shows the basic descriptive statistics for age by the eight dependent
variables. Following this the t tests were employed. Results of the t tests can be found in Table 9.
For the assumption of homogeneity curiosity and creativity, spirit of adventure, and leadership
and responsibility all violated the assumption and therefore equal variances were not assumed

30

when examining Table 9 for the results. All other dependent variables met the assumption.
Despite the three variables not meeting the assumption all dependent variables were statistically
significant (p < .05). In all cases those students who were less than 14 years of age had higher
means on all eight dependent variables than those who were 14 or more years of age.
Table 8
Descriptive Statistics: Age by Dependent Variables

Variable Age N M SD
Belonging 14 or more yrs. 321 3.29 .600
Less than 14 yrs. 271 3.62 .621
Hero 14 or more yrs. 321 3.43 .613
Less than 14 yrs. 271 3.68 .684
Accomplishment 14 or more yrs. 321 3.56 .548
Less than 14 yrs. 271 3.89 .602
Fun Excitement 14 or more yrs. 321 3.17 .694
Less than 14 yrs. 271 3.48 .818
Curiosity & Creativity 14 or more yrs. 321 3.46 .633
Less than 14 yrs. 271 3.88 .641
Spirit of Adventure 14 or more yrs. 321 3.62 .477
Less than 14 yrs. 271 3.83 .576
Leadership and Responsibility 14 or more yrs. 321 3.24 .596
Less than 14 yrs. 271 3.51 .674
Confidence to Take Action 14 or more yrs. 321 3.90 .538
Less than 14 yrs. 271 4.16 .549

Table 9
Results Independent Samples t Test: Age by Dependent Variables

Variable Variances F Sig t df Sig.
Belonging Equal variances not
assumed
.371 .543 -6.483 590 .000
Hero Equal variances
assumed

-6.464 566.285 .000

31

Equal variances not
assumed
2.896 .089 -4.824 590 .000
Accomplishment Equal variances
assumed

-4.780 547.941 .000
Equal variances not
assumed
3.075 .080 -6.996 590 .000
Fun Excitement
Total Mean
Equal variances
assumed

-6.940 551.637 .000
Equal variances not
assumed
9.563 .002 -5.050 590 .000
Curiosity &
Creativity
Equal variances
assumed

-4.981 531.904 .000
Equal variances not
assumed
.089 .766 -7.973 590 .000
Spirit Equal variances
assumed

-7.964 570.910 .000
Equal variances not
assumed
7.288 .007 -5.027 590 .000
Leadership Equal variances
assumed

-4.949 524.965 .000
Equal variances not
assumed
4.836 .028 -5.070 590 .000
Confidence Equal variances
assumed

-5.018 544.037 .000
Equal variances not
assumed
.715 .398 -5.741 590 .000
-5.732 569.740 .000
**p < .01

32

Research Question 2: What are the correlations between the various subscales on the
Student Voice Survey?
In order to address the abovementioned research question, a Pearson r Correlational
Coefficient was performed to examined multiple bivariate correlations among the eight
dependent variables. All correlations were found to be significant (p =.000). Correlations among
variables ranged from r = .552 (fun by confidence) to r = .774 (fun by curiosity) (see Table 10).
Table 10
Bivariate Correlations for Eight Dependent Variables

Variable 1 2 3 4 5 6 7 8
1. Belonging 1.000**
2. Hero .743** 1.000
3. Accomplish .686** .720** 1.000
4. Fun .705** .766** .691** 1.000
5. Curiosity .700** .733** .733** .774** 1.000
6. Spirit .588** .608** .694** .660** .652** 1.000
7. Leader .687** .639** .651** .621** .662** .614** 1.000
8. Confidence .590** .560** .630** .552** .644** .608** .643** 1.000
N = 592
** p = .000

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Research Question 3: To what degree, if at all, do the various subscales on the Student
Voice Survey predict student engagement?
Next a multiple regression was performed to determine which of the dependent variables
was the best predictor of engagement. Engagement was operationalized as a super subscale based
on the conceptual framework which combined fun and excitement, curiosity and creativity, and a
spirit of adventure. For the purpose of this analysis, four of the remaining five subscales were
treated as predictor variables and were loaded into the model (i.e. belonging, heroes,
accomplishment, and confidence) and treated as continuous variables. The fifth variable, a spirit
of adventure, had a Cronbach’s alpha of .558 and was therefore not used as a predictor variable
due to a limited internal reliability rating. The outcome variable, engagement, was also treated as
a continuous or interval data. Examination of the model summary table found the adjusted R
2
to
be .764 or explaining 76.4% of the variance to be explained by the model. Based on this further
examination of the coefficients table was warranted. All the above variables were all found to be
significant predictors of engagement (see Table 11). Examination of the Standardized Beta
weights revealed that of those variables that were significant predictors hero contributed most to
the model (.339), followed by accomplishment (.307), belonging (.183), and confidence (.176).
Examination of the unstandardized beta found that for every point a student increased in hero the
participant increased on engagement by .303 points.
Table 11
Results of Regression: Predictors for Engagement (Super Subscale)
Variable Unstand. B Coefficients
Std. Beta
t Sig.
Model
1
(Constant) .016 .090

.182 .855
Hero .303 .030 .339 10.209 .000*
Accomplishment .304 .032 .307 9.534 .000*

34

Belonging .171 .030 .183 5.652 .000*
Confidence .186 .028 .176 6.544 .000*
* p < .05
a. Dependent Variable: Engagement (Super Subscale)
Summary
Although the research findings did not demonstrate a significant difference by gender,
age was a significant distinguishing factor across all 8 conditions with students below age 14
having statistically significant higher average scores. All 8 conditions were shown to be
positively correlated to one another. Lastly, each of the four dependent variables of heroes, sense
of accomplishment, confidence to take action, and belonging were predictive of overall student
engagement.
Recommendations
Discussion of Findings
Presented in this section are proposed recommendations for establishing initiatives and/or
programs with the ultimate purpose of improving student engagement levels. The results of this
study shown no statistical significance across gender for each of the eight categories from the
Student Voice Survey. However, students below the age 14 had higher means on each dependent
variable when compared to students aged 14 or more years of age. Additionally, all eight of the
categories from the Student Voice Survey were shown to be significantly positively correlated.
Lastly, the categories of hero, sense of accomplishment, confidence to take action, and a sense of
belonging were all predictive of the engagement. Each recommendation targets one or more of
the predictive conditions from the Student Aspirations Framework. Fredricks et al. (2004)
seminal work on conceptualizing a multidimensional framework of student engagement
underpins the multifaceted approach to target the predictors of student engagement.

35

Recommendations for Practice
Recommendation 1: Teacher training on the impact of teacher care and understanding and
the creation of a teacher mentor program.
With the condition of heroes being the single variable most predictive of student
engagement, there is potential for increasing student engagement through targeted professional
development on to improve student-teacher relationships. Such an initiative should begin with
unpacking the research for teachers to gain better insight into how their actions and behaviors
impact student engagement. Martin and Dowson (2009) contend that active listening is essential
to understand students educational experience and that personal knowledge of students’ lives
outside of school builds a sense of relatedness. Cooper and Miness (2014) highlight the
importance of respect and praise when working one on one with students in their academic work.
Once teachers better understand the actions which have an impact of students’ perception of
teacher care and understanding, they will be better equipped to alter their behaviors with
intentionality. Subsequently, the creation of a mentorship program could have significant impact
on a student’s sense of heroes by ensuring that each student have an adult advocate on campus
whom they feel they can rely on for support, whether it be socially, academically, or
emotionally. Klem and Connell (2004) found that strong teacher-student relationships,
particularly when teachers genuinely seek out the interests of students, had a positive impact on
student outcomes. The safety provided by a strong teacher-student relationship, built through a
robust mentorship program, provides space for student to engage in intellectual risks (Koca,
2016). A mentorship program would require structures and procedures, such as time in the
schedule for meeting as well as discussion protocols to support teacher interaction with their
mentees, to be in place in order for it to be successfully implemented.

36

Recommendation 2: Create student goal-setting initiative and celebrate individual successes
With the conditions of confidence to take action and a sense of accomplishment both
having a significant predictive impact on student engagement, there is potential to drive student
engagement through a student goal-setting initiative and in finding ways to celebrate individual
successes. Fredricks and McColskey (2012) highlight the importance of future aspirations and
goal setting as key components of cognitive engagement. In order to ensure the widest possible
impact on the overall student body in a given school, this goal-setting initiative would need to be
rolled out strategically with clear guidelines and specific time allocated to its implementation. If
a school engages in some form of regular interval standardized testing, students could set goals
and targets based on these test results. At AIS, the school engages in MAP testing three times
throughout the academic year. The MAP, or the Measures of Academic Progress, test looks at a
student’s current achievement level in math, language, and reading and monitors growth over
time. It also provides the school and subsequently the students with a projected degree of growth
from one test session to the next. MAP goal-setting, along with students establishing clear
individualized intervention or study strategies, could positively impact a students confidence to
take action. In addition to setting longer term goals facilitated through MAP progress tracking,
students could engage in regular short-term goal-setting whereby teachers assist in ensuring their
relevance to the longer-term goal and celebrating small achievement wins along the way (Corso
et al., 2013). By implementing targeted study strategies to achieve specific academic goals,
students may have a higher degree of task value when engaging in study activities (Fan, 2011).
Perry et al. (2010) also argue that by establishing relevance and ultimately task value, students
often commit themselves more deeply to academic pursuits. This, in conjunction with a
systematized celebration of MAP goal achievement could positively impact students’ sense of

37

accomplishment. Celebrations of past successes increase a student’s expectancy of future
successes (Wang & Eccles, 2013; Levykh, 2008) and ultimately their level of cognitive
engagement.
Recommendation 3: Use programmatic development to target student belonging
The condition of belonging is predictive of student engagement and should therefore be a
focus of programmatic development in schools. One such way to target belonging is through a
robust student advisory program. Through this robust program, a school could develop ways to
encourage further involvement in the school community beyond the advisory program itself.
Finn’s (1989) seminal work developing the participation-identification model regarding school
connectedness highlights the importance of positive school affiliation. As part of the advisory
program, advisors could ask students to write a journal entry to reflect on when they felt most
connected to the school community. A deep sense of school connectedness has been shown to
positively impact overall future orientations and aspirations (Crespo, et al., 2013). Subsequent to
student reflections, advisors could encourage students to engage in a number of similar tasks
each month and continue to reflect in their journals regarding the impact of their involvement in
activities outside of the classroom. This is one simple example of how an advisory program
could be geared towards focusing on the multiple ways a student can find their unique
community within the structure of the overall school community. Cooper and Miness (2014)
found that frequent interactions between teachers and students outside of the normal classroom
environment increased students’ overall perception of care and ultimately school connectedness.
Fredricks and McColskey (2012) found that school connectedness and the notion of belonging
was a key indicator of overall student emotional engagement.

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Limitations and Delimitations
In any research study there exists both limitations and delimitations. First and foremost,
this data set pertains to one individual school in an international setting and therefore the
findings have limited ability to generalize to a larger population. Another limitation of this
research is relying on the truthfulness of the respondents. The survey was part of a larger student
voice initiative at AIS which was comprised of a student led steering committee, a faculty
member who served as their sponsor, and a member from the Quaglia Institute who acted as their
coach. An advisory lesson was dedicated to discussing the importance of an accurate portrayal of
the opinions of the student body at AIS and that real change was possible if both the students and
the school had accurate data from which to plan and carry out improvement initiatives. A major
delimitation of the research is the choice to focus on quantitative methods over a mixed methods
study.
Recommendations for Future Research
Recommendations for future research are to engage in longitudinal studies that follow
schools that have engaged in initiatives that focus on student-teacher relationships, or student
goal-setting with celebrations of individual successes, or programmatic development to target
school belonging. Both qualitative and quantitative studies to measure the impact of such
programs over time and their impact on not only student engagement, but overall academic
outcomes could be very beneficial to the world of education as a whole. A future researcher who
might continue to use the Student Voice Survey as the survey instrument could consider a mixed
methods approach to delve deeper into the role of heroes, belonging, a sense of accomplishment
and confidence to take action, and how each of these aspects impact an individual’s level of
engagement.

39

Conclusion
This research study is just one of many within the massive investment in educational
research on the importance of student engagement. The overall importance of research on student
engagement is profound as it has a large impact on overall academic outcomes and ultimately on
an individuals’ lifetime earning potential. Determining impactful ways to systematically target
student engagement is crucial for the success of individual students on the micro level as well as
the entire system of education on the macro level.

40

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Appendix A: Definitions
This section provides the key terms and their definitions used in this study.
Behavioral engagement
Behavioral engagement is typically viewed as a general adherence to the rules and
regulations established by the classroom teacher (Fredricks et al., 2004). Behavioral engagement
also includes on-task behaviors and has often been described as either effort or concentration.
Overall, behavioral engagement concerns actual behaviors displayed by the student and whether
they are positively contributing to the learning experience (Fredricks et al., 2004).
Cognitive engagement
Cognitive engagement refers to a student’s ability to meaningfully engage in
metacognitive practices and the extent to which one can self-regulate (Wang & Eccles, 2011).
Cognitive engagement also refers to the level of investment a student puts into the overall
learning process (Corso et al., 2013). Overall, it is a student’s desire to delve deeply into a topic,
plan their studies and monitor their success.
Emotional engagement
Corso et al. (2013) contend that emotional engagement is basically a general sense of
student belonging. In a more nuanced sense, emotional engagement involves not only the extent
to which a student is connected with a given content area, but also the level of confidence a
student has in her academic ability (Corso et al., 2013).
Student engagement
Fredricks et al. (2004) conducted a metanalysis of the literature on student engagement
and conceptualized a three-part framework that comprises behavioral, emotional, and cognitive
student engagement.

46

Teacher-student relationship
The teacher-student relationship is operationalized by the level of care displayed by the
teacher as well as the degree to which the teacher understands the student (Cooper & Miness,
2014).
Teacher care
Teacher care is a general concern for student well-being, both academically and social-
emotionally (Cooper & Miness, 2014).
Teacher understanding
Teacher understanding goes beyond teacher care to the level of knowing who the student
is as a person (Cooper & Miness, 2014).

47

Appendix B: The Researcher
The researcher served as the assistant principal in the secondary school during the time of
the Student Voice Survey and went on to serve two academic years as principal in the years after
the survey was conducted. Although the researcher was in a position of power with regards to the
participants, there is little to no impact on the overall results of the survey. The Quaglia Institute
for Student Voice and Aspirations was brought in as educational consultants and informed
students ahead of the survey that the data will be used to guide school improvement planning
through unpacking the voices of the student body. A Student Voice team was created that
consisted of student representation across all grade levels and members of staff that were not in
executive leadership positions. As such, the researcher did not serve on the Student Voice
Committee, but rather heard from them regarding the recommendations they made after
receiving the survey results.

48

Appendix C: Ethics
This research study will operate under the rigorous IRB process at the University of
Southern California to ensure that the data that was collected in 2016 obtained informed consent,
protected respondent anonymity, and operated from a prospective to do no harm. Both parents
and students were informed that the intent of the survey was to measure the students’ sense of
self-worth, engagement, and purpose. Parents signed off that this data may be used by either the
Quaglia Institute or by AIS in the future to promote positive learning environments at AIS and
beyond. In the permission form, students and parents were given the opportunity to decline
participation. Any student who did not submit a permission form was automatically left out of
the survey. The survey was administered anonymously, and no identifying information was
gathered at any point in the survey. Both the Quaglia Institute and AIS have provided expressed
written permission to the researcher to conduct inferential statistical analysis for the purposes of
undertaking the current research.

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Asset Metadata

Creator Coppes, Kyle Joseph (author)

Core Title Student engagement: a quantitative analysis on aspects that are predictive of engagement

School Rossier School of Education

Degree Doctor of Education

Degree Program Organizational Change and Leadership (On Line)

Degree Conferral Date 2022-12

Publication Date 09/08/2022

Defense Date 09/01/2022

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

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