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What are the relationships among program delivery, classroom experience, content knowledge, and demographics on pre-service teachers' self-efficacy?

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What are the relationships among program delivery, classroom experience, content knowledge, and demographics on pre-service teachers' self-efficacy?

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WHAT ARE THE RELATIONSHIPS AMONG PROGRAM DELIVERY,
CLASSROOM EXPERIENCE, CONTENT KNOWLEDGE, AND DEMOGRAPHICS
ON PRE-SERVICE TEACHERS’ SELF-EFFICACY?

By

Aaron Keao Tano

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

December 2012

Copyright 2012 Aaron Keao Tano

ii
Dedication
This work is dedicated first and foremost to my father, Darrel Gene Tano and my
most talented and gifted mother, Colleen Alberta Laukiamalu Hew Tano. It is her
example that has led me to strive for the best and reach for the highest. It is her guidance
that has paved the way for me to reach my goals. As self-efficacy is the ability to
persevere in the face of obstacles, it is their light that guides me to succeed despite my
challenges. Finally, it is her love for people that has helped me to be a better teacher.
Most importantly, may this work always be a symbol to my 5 special nephews
(Brenden, Kaleb, Aiden, Dallen, and Kala`iakea) the importance of education. I dedicate
this study as a prequel to their studies, so that they will one day be much better, smarter,
wiser, kinder, truthful, and happier than me J
I also thank my siblings: my big brother Ben, my little sis Amy-Gene Kiyoko, and
my little brother Brett! Picked from the same vine, they are my challengers, supporters,
and the ones that know me best! Also to my loudest cheerleader Dane Rosselli, with
whom I have the privilege of sharing my life.
Finally, I dedicate this work to the memory of my grandmothers Olga Leiola
Naomi Alo Hew, and Beatrice Yoshika Kono Tano, and to my grandfathers Albert
Pa`awa`a Keao Hew and Benito Barlaan Guilermo Tano. It is their love that gives me
strength, and their blood and sacrifice that has given me the opportunity to reach for the
stars!

iii
Acknowledgements
To my chairperson Dr. Kim Hirabayashi; my dissertation committee members Dr.
Melora Sundt and Dr. Gisele Ragusa; and to my fellow Ed.D. classmates and friends,
may you forever feel my heartfelt gratitude for your guidance, support, friendship,
patience, and leadership during these many years of my studies. Without you this study
would not be possible.

iv
Table of Contents

Dedication ..................................................................................................................ii

Acknowledgements ....................................................................................................iii

Abstract ......................................................................................................................vi

Chapter One: Introduction .........................................................................................1
Background of the Problem ...........................................................................2
Statement of the Problem ...............................................................................9
Purpose of the Study ......................................................................................10
Research Questions ........................................................................................11
Significance of the Study ...............................................................................12
Methodology ..................................................................................................14
Assumptions ...................................................................................................14
Definition of Terms ........................................................................................15
Organization of the Study ..............................................................................16

Chapter Two: Review of the Literature .....................................................................17
Theoretical Framework ..................................................................................18
Influences of Self-Efficacy ............................................................................19
Influences on Self-Efficacy ............................................................................25
Development of Self-Efficacy in Pre-Service Teachers ................................29
Role of Online Delivery on Teacher Self-Efficacy ........................................32
Needed Research on the Effectiveness of Online Educational Programs ......37
Conclusion .....................................................................................................39

Chapter Three: Research Methodology .....................................................................41
Research Questions ........................................................................................41
Research Design .............................................................................................43
Independent and Dependent Variables ..........................................................44
Population and Sample ..................................................................................45
Instrumentation ..............................................................................................45
Data Collection ..............................................................................................49
Data Analysis .................................................................................................50

Chapter Four: Results ................................................................................................53
Intercorrelations .............................................................................................53
Teaching Experience by Delivery Method ....................................................57
Research Question 1 ......................................................................................58
Research Question 2 ......................................................................................60
Research Question 3 ......................................................................................62
Research Question 4 ......................................................................................66

v
Research Question 5 ......................................................................................74
Additional Power Analysis ............................................................................81
Summary ........................................................................................................82

Chapter Five: Discussion ...........................................................................................84
Findings .........................................................................................................84
Implications ....................................................................................................92
Social Significance of the Study ....................................................................94
Limitations .....................................................................................................95
Delimitations ..................................................................................................96
Recommendations ..........................................................................................97
Conclusion .....................................................................................................98

References ..................................................................................................................100

Appendix A: Survey ..................................................................................................107

Appendix B: Information Sheet .................................................................................109

Appendix C: Permissions ...........................................................................................110

vi
Abstract
This study examines the relationship between self-efficacy development with
program delivery, and prior experience. The student demographic categories of age,
ethnicity, gender, content area, and first generation status was also examined against level
of self-efficacy. Sixty six students from the online and on-campus cohorts of the Masters
of Arts in Teaching program at the University of Southern California were questioned
using a 24 point Likert type self efficacy survey for pre-service teachers. Overall self-
efficacy was broken down into three subscales: classroom management, innovative
teaching practice, and student engagement). Results showed no significant difference in
overall self-efficacy or the subscales between the online and on-campus cohorts, or prior
experience. Further, the demographics of age, ethnicity, gender, and content area did not
account for any variance in self-efficacy development. However, it was found that first
generation college status of participants did have a significant difference in self-efficacy
development. Students who were first in their families to attend college had a higher level
of self-efficacy than those whose parents already attended college.

1
Chapter One: Introduction
In a meeting of top researchers at the Association of Pacific Rim Universities
(APRU) World Institute workshop, William Tierney (2007) noted, “The cartography of
what we once meant by a campus is lessening both by institution and by country.” Today,
teacher education is no longer constrained by location and standard mapping. While
distance learning has been popular for several decades, globalization and cyberspace have
now widened the possibilities of higher education and teacher education in particular.
However, even as online instruction provides flexibility for the distance learner, those
programs also can produce specific challenges (DeTure, 2004).
Researchers continue to ask if learning outcomes from online delivery programs
are comparable to face-to-face instruction in terms of teacher self-efficacy, content
knowledge and classroom experiences. Even though it is clear from prior research that
teacher self-efficacy is a multidimensional construct (Hoy & Hoy, Moran, Tschannen,
1998; Skaalvik, Skaalvik, & Sidsel, 2007), it is less obvious how program delivery, prior
classroom experiences and content knowledge interplay with program delivery and self-
efficacy, especially as they ultimately relate to student achievement and success.
Noted authors, Li and Irby (2008) have lamented the lack of definitive studies
regarding the effectiveness of online instruction to optimize cognitive, affective, and
experiential dimensions of teacher effectiveness. These researchers call for further study
to compare online programs with traditional programs because of discrepancies due to
differences in school characteristics and standards. Their study found issues regarding the
quality of information presented through online courses.

2
Cognitively, concerns about information accuracy, lack of complexity, and depth
of information presented through the Internet pose unique challenges and a possibility of
potential flaws (Pan & Singh, 2004). Like the difference between black and white photos
versus color, or looking at snapshots versus movies or standardized test scores to
portfolios, so can online learning assignments lack depth and a better picture of what
students know and are able to do. Other issues involve the absence of face-to-face
interaction, the translation of material to electronic and web-based environments, and
students unfamiliarity with technology (Coyner &McCann, 2004; Reeves & Brown,
2002) Further, the cost effectiveness of online education has expanded so rapidly there
has not been sufficient time to review every aspect of quality (Barbour & Reeves, 2009)
and the perceptions of online learning as it affects self-efficacy.
At the same time, the need for highly-qualified teachers is becoming increasingly
critical in American schools because of federal mandates. Administrators and teachers are
in a run to meet the demands of the No Child Left Behind Act, which requires all students
to be proficient in Mathematics and English Language by the year 2014. Colleges like the
University of Southern California (USC) are deploying new teacher education programs
utilizing new technology and distance learning in their quest to garner and develop better
and more effective teachers for the 21
st
century classroom.
Background of the Problem
Growth of online learning. With the growth in technology in the past two
decades, online and E-learning have become increasingly popular. The Alfred P. Sloan
foundation conducted the 2010 Sloan Survey of Online Learning Report presented by

3
Allen & Seaman (2010). The Sloan consortium revealed that online enrollment rose by
over one million students in the last year, showing the largest ever year-to-year increase.
The accessibility of the Internet has created worldwide opportunities for learning and
exposure to information and experiences that were previously unavailable to the broader
student populations. Universities and K-12 institutions have found online education to be
beneficial in providing increased access for more students (Irby & Li, 2008; Karber,
2003). The Sloan Report (Allen & Seaman, 2010) also revealed that online enrollments
for the past eight years have grown substantially faster than overall higher education
enrollments. This expansion is due not only to advancements in technology and the
inability of universities and schools to increase physical facilities, but also to the
economic decline in the United States and around the world (Irby & Li, 2008; Karber,
2003). The Sloan report suggested that bad economic times are good for higher education
because the decreased availability of good jobs encourages people to seek education or
improve their chances for advancement by advancing their education.
In addition, technology and web-based delivery are cost efficient, allowing non-
traditional students (older, married, working, etc.) to go back to school (Barbour &
Reeves, 2008; Irby & Li, 2008). Online learning meets the needs of these niches of
perspective student populations who need to gain an education on their own time. Coyner
and McCann (2004) reported that the most important aspect of online learning is
accessibility. Students who would otherwise have no opportunity to attend a chosen
university can now gain an education even if they live far away from a physical campus.

4
In terms of technology, the flourishing of software programs and delivery modes
beyond Blackboard and WEBCT, such as Brain Honey, Live Text, Elluminate, SKYPE,
Screen-o-matic, VoiceThread, and Instructure, shows that multiple user-friendly
programs are becoming increasingly available from which colleges and professors can
choose to use to facilitate communication between teacher and student. As web-based
instruction continues to expand, understanding how to moderate learning and create
situations in which students are building in content knowledge and efficacy in a virtual
world are acutely needed.
Content knowledge. At the core of preparing individuals for teaching is content
and foundational knowledge of specific domains in which the candidate hopes to be
called a professional. The teacher candidate needs to develop the capacity to act on that
knowledge and make teaching decisions based on that knowledge. Researchers Ball,
Thames, & Phelps (2008) developed a practice-based theory of content knowledge that
divides it into three subcategories (1) knowledge of content and its relationship to
students, (2) knowledge of content and its relationship to teaching, and (3) and pure
content knowledge or specialized content knowledge unique to teaching. Thus we see,
according to Ball and colleagues, that content knowledge represents what is currently
shared in the field, subject to change over time as experience and new understandings are
acquired. In order for teaching and learning to be powerful, content knowledge needs to
be significant, deep, and meaningful. Conceptual understanding of students requires not
just breadth but depth i.e. knowledge of content and relationship to students, knowledge
of content and its application to teaching, and pure content as a basis of expertise.

5
Concerns over the depth and quality of information via web instruction (Li &
Irby, 2008) have driven the purpose of this study. Superficial knowledge of teachers fall
short of the demands of the 21
st
century classroom. Indeed, if content knowledge is
lacking in the teacher candidate, self-efficacy will also weaken, as they perceive their
own lack of competency (Bandura, 1977).
As part of the certification process required by most states and professional
licensing organizations, certification tests are taken by individuals entering the teaching
profession. These tests measure teacher candidate’s basic knowledge in reading, math,
writing, and respective secondary content fields. As teacher candidates complete their
education and classroom practicum, more subject-specific content knowledge tests are
required. Most states require these tests as a criterion for professional licensing decisions.
Even as teacher candidates pass certification (content knowledge) tests, it is unclear how
this knowledge affects teacher self-efficacy.
Teacher self-efficacy. In 1977, Albert Bandura forwarded the powerful theory
that self-efficacy is the major mediator for behavior choices and behavior changes. It
began an era of research that has linked efficacy to several behavioral issues that include
depression (Davis & Yates, 1982), smoking (Dorfia, Schmitz, & Doerflor, 1990) phobias
(Bandura, 1983), and addiction (Marlatt, Baer, & Quigley, 1995). Educationally,
Bandura’s study on self-efficacy was groundbreaking as the study suggested self-efficacy
is related to motivation (Pintrich & Schunk, 1996), self-regulated learning (Zimmerman,
1995), and the effort and persistence exerted when facing challenges and distress

6
(Pajares, 1997). These are the critical intangibles that can mean success or failure in
meeting learning goals.
Bandura (1986) posited that “perceived self-efficacy results from diverse sources
of information conveyed vicariously and through social evaluation, as well as through
direct experience” (p. 411). Bandura (1986, 1997) argued that efficacy develops from
four sources (1) information derived from actual or vicarious experiences (2) direct
observation or visualization of what others perform (3) information from verbal
persuasion or others’ positive feedback and (4) information gained from physiological
experiences such as anxiety or trembling before a task. In addition, these four things must
be processed and analyzed by oneself through self-referent thought (Bandura, 1986,
1997). These are called mastery experiences and are considered the most powerful
influence on efficacy as they provide direct feedback regarding capabilities (Tschannen-
Moran, Hoy & Hoy, 1998). However, attribution and self-analysis concerning outcomes
may impact the interpretation of those experiences (Tschannen-Moran, Hoy & Hoy,
1998). For example, task value, social opinions, or one’s emotional state can strengthen
or weaken self-efficacy beliefs regardless of outcomes (Tschannen-Moran, Hoy & Hoy,
1998). Therefore not all success leads to increased efficacy.
In short, teacher efficacy is often cited as a key to improving the quality of
learning and has been found to relate significantly to many positive outcomes, including
student achievement (Smylie, 1990; Ebmeier, 2003). Self-efficacy is the underlying
theme in current views of motivation (Pintrich & Schunk, 1996) because of its predictive
power and application for almost any behavioral task (Henson, 2001). Interest in

7
examining the interplay among online program delivery, classroom experiences and
content knowledge upon the development of pre-service teacher self-efficacy is justified
because of the powerful influence teacher efficacy has on classroom practice and
subsequent student achievement (Ebmeier, 2003; Pintrich & Schunk, 1996, Henson,
2001).
Building upon Albert Bandura’s (1977, 1997) foundational study relating self-
efficacy to student achievement, several researchers (Schunk, Pajares, Wigfield, Eccles,
Guskey, 1997, 1998; Smylie, 1988; Ashton & Webb, 1986) point to the impact of
teacher self-efficacy beliefs to learning outcomes. Specifically, Smylie (1988) found that
self-efficacy was the leading factor in changing teacher practices that lead to student
achievement. Studies by Guskey (1997, 1998) found that teachers’ self-efficacy had
powerful effects on their own ability to create mastery learning environments as well as
on their own ability to initiate innovative instructional practices, thus improving student
learning. This is because efficacy has a powerful influence in creating changes in teacher
practice that can bring about these positive outcomes (Smylie, 1988). As teachers feel
more confident about their abilities, they will have higher expectations and manage their
classrooms in a way that will help students learn (Cruz & Arias, 2007; Emmer &
Hickman, 1991; Tschannen-Moran et al. 1998; Woolfolk & Hoy, 1990). For these
reasons, many universities have increased resources to better prepare these future
teachers through technology, and distance learning, in hopes of developing positive
teacher self-efficacy in their pre-service teacher candidates (Barbour & Reeves, 2008).

8
Classroom experience. Finally, evidence suggests a causal link of prior
classroom experiences to teacher self-efficacy. Several studies (Darling-Hammond,
Chung, & Frelow, 2002; Prieto, Altmaier, 2008), indicated that previous teaching
experience explained a significant amount of variance in self-efficacy. Results from
another study conducted with over 3000 beginning teachers by Darling-Hammond (2002)
revealed that teachers with more classroom experience from their teacher education
programs felt markedly better prepared across most dimensions of teaching than those
with little prior classroom experience. The extent to which teachers felt well-prepared
when they entered teaching was significantly correlated with their sense of teacher
efficacy. While this study was conducted with beginning teachers, it begs the question of
whether the same relationship holds true with classroom experience prior to their teacher
education programs.
Bandura (1986) argued that one source of efficacy development is based on
mastery experiences (classroom experiences) or vicarious experiences, in which a teacher
has learned by observing the performances and skills of others, can identify with the
performer, and can assess their own capabilities. Teacher efficacy is self-referent and
tempered after teacher candidates examine their own classroom experiences. Teacher
candidates analyze the experience and their own skills before they make a final estimate
of their own efficacy (Tschannen-Moran, et al, 1998).
This study is based on theories of self-efficacy that define it as a major social
cognitive factor in teachers’ ability to affect student motivation and achievement. A
careful analysis of the link among online program delivery, content knowledge and

9
classroom experiences to self-efficacy is important if a more complete picture of student
achievement is to be obtained.
The University of Southern California (USC) is one of the first Tier 1 schools to
provide an accredited online education program for pre-service teacher candidates.
According to US News and World Report (2011), The University of Southern California
is ranked 14
th
overall as a Tier 1 college in the National Universities Ranking, and 5
th
in
the Nation for its Education Programs (US News and World Report, 2009). USC’s
Rossier School of Education offers various graduate degrees in education, one of which is
the Masters of Arts in Teaching program or MAT. As of Fall 2009, the MAT program
was offered both on campus and as an online degree program. The online MAT program
at the Rossier School of Education is the first teacher education program offered at USC
providing more opportunities for training new teachers virtually. Although curriculum
and operations of the program are based on time -tested theoretical research and well-
developed technology, the new online program has little or no collected data on the self-
efficacy of pre-service teachers.
Statement of the Problem
The problem of this study was to find out whether the online MAT program at the
Rossier School of Education delivers a program that develops or advances the self-
efficacy of its teacher candidates. Research shows that teachers with teacher self-efficacy
have higher ability to manage classrooms, use innovative teaching practices, have higher
expectations of their students, and persist at teaching challenges; resulting in higher
student achievement (Guskey, 1997, 1998; Smilie, 1988). However, there is insufficient

10
evidence regarding the influence of teacher education program delivery, content
knowledge, classroom experience, and teacher self-efficacy.
Finally, another issue specific to the University of Southern California’s MAT
program, was trying to understand characteristics of pre-service teachers in the MAT
program. More specifically, a collection of data regarding the relationship between prior
teaching experience and prior content knowledge of pre-service teachers, and the
influence they have on self-efficacy to help direct the teacher education program and
better meet the needs of students.
Purpose of the Study
The purpose of this study was to investigate the relationship between self-efficacy
of pre-service teachers, and delivery method of the teacher education program. Does type
of delivery predict self-efficacy of pre-service teacher candidates? There is limited
research that focuses specifically on the role of program delivery and self-efficacy
development of pre-service teacher candidates.
Teacher education programs at USC are offered both online and on-campus. The
goal of this study was to discover the relationship that both of these programs have with
self-efficacy in preparing these future educators for the classroom.
Finally, another aim of the study was to better understand the extent to which
prior experience and content knowledge can influence the development of self-efficacy in
pre-service teachers in the MAT program at the University of Southern California. These
experiences may influence students’ perception and perspective on teaching and thus
affect classroom learning outcomes.

11
Research Questions
The following research questions were addressed to meet the purpose of this study. They
are as follows:
1. a. What is the self-efficacy of pre-service teacher candidates in the MAT @
USC program?
b. What is the self-efficacy of pre-service teacher candidates for each of the
following subscales: innovative strategies, classroom management, and
student engagement?
2. Does program delivery predict self-efficacy of pre-service teacher candidates
in the MAT @ USC program?
3. Does prior experience and content knowledge predict self-efficacy of pre-
service teacher candidates?
Upon initial completion of data analysis, it was found that the number of
respondents in the online cohort of the MAT @ USC program was insufficient to
conclude with significant findings. As such, additional questions were added to this study
to further explore the relationships that exist between teacher self-efficacy and MAT @
USC pre-service teacher candidate characteristics. For the purpose of this study, we will
allow data results for the previous initial three research questions to be included in the
study, and add the data and findings to the following additional questions.
4. Does teacher self-efficacy of pre-service teacher candidates differ by gender,
content area, or first generation college status?

12
5. Does teacher self-efficacy of pre-service teacher candidates differ by age, or
ethnicity?
Significance of the Study
This study has shed light on whether online program delivery at USC affects pre-
service teacher self-efficacy. Currently, there is little to show if self-efficacy is affected
by program delivery and the issue was finding results that may reveal if the type of
delivery regarding the teacher education program at USC can predict the self-efficacy of
pre-service teachers or if online delivery affects self-efficacy in the same way as
traditional face-to-face programs.
The implication of this research will help to determine the degree of focus for
student characteristics for success, specifically, self-efficacy, and how they are influenced
by delivery methods. As previously stated, many studies have been conducted that
investigate the relationship between self-efficacy and student achievement. However,
very little research has been done that considers the influence delivery methods have on
self-efficacy. This study adds to the few new studies (DeTure, 2004; Miller & Rainier,
2003) on self-efficacy with online delivery methods.
Research findings from this study has contributed to an array of interested
stakeholders in education. The University of Southern California’s Rossier School of
Education has had the most beneficial impact. First, USC will be able to use this data as
information regarding the difference in delivery for evaluative purposes of this newly
formed online program. This data has revealed differences, between their online and on-
campus programs. Second, with this information, changes and adjustments can be made

13
to curriculum, organization, technology, and other aspects of the program to improve its
outcomes and meet its goals. Also, the study can promote emphasis and attention to
program components that need improvement. Lastly, as program improvements are
made, results can be used as a major attraction to perspective students, schools, and
school administrators. Increased popularity will produce revenue for the school and add
prestige to the program.
With this information, decision makers can gain a better understanding of
appropriate profiles of aspiring pre-service teacher candidates, and provide targeted
support and program changes to support student learning for the MAT online and on-
campus programs at the University of Southern California.
The current and future students of the MAT program can also greatly benefit from
this study. As part of student coursework, pre-service teachers can learn the benefits and
impact that self-efficacy can have on their teaching outcomes. Further, as the MAT
program improves, future students will benefit as partakers of state-of-art education.
Although findings are not be generalizable across universities, it can be a starting
point to help universities understand and be aware of the relationship between online
teacher education programs and self-efficacy. The online MAT program can serve as an
example on how to structure, or modify future distance education programs.
Communities and schools can benefit from having better prepared educators who can
affect learning outcomes of their students positively.

14
Methodology
To fulfill the purpose of this study, quantitative methods was be used. A survey
with a Likert type scale to measure self-efficacy was be given to evaluate the self-
efficacy of pre-service teachers enrolled in the on-campus and online Masters of Arts in
Teaching program. A t-test of independent samples was be used to compare the means
between the two groups. A 1-way ANOVA and regression model will also be employed
to answer the 3 research questions.
Included in the survey were questions regarding student characteristics;
specifically a student’s prior experience in educational fields, and which program they
are participating in. It was planned for the level of content knowledge they have in their
area of concentration be determined through the CSET scores from student records.
However, this meant, steps had to be taken to obtain permission to retrieve this
information from the State of California; this was not possible. Students were also asked
for permission to use personal information by obtaining their student ID numbers.
Correlational analysis was be used to determine whether a relationship exits between
student characteristics, self-efficacy, and program delivery.
Assumptions
It was assumed that all participants contributed honest answers to the data
collection methods. Another assumption was that students will give honest answers
regardless of previous engagement with other surveys. A final assumption was that the
answers we attained during data collection would reflect the general population of all
students.

15
Definition of Terms
Self-efficacy refers to a person’s confidence in their ability to complete a specific
task or reach a given goal (Bandura, 1977). For the purpose of this study we will be
looking self-efficacy of teachers as it relates to their belief system in the role of teachers.
This includes outcome expectancies and efficacy expectancies that inform actions that
teachers can take to have an effect on student learning. Specifically we will measure
personal teacher self-efficacy; a teachers’ perception of their own ability to influence
student learning (Smylie, 1988). This type of efficacy has been the primary predictor of
teacher behavior (Ashton and Webb, 1986).
Online education refers to the use of technology and Internet-based delivery of
education and learning to students. Synonymous terms that are used in research are E-
learning, distance learning, distance education, and virtual schools.
Content knowledge is the level of knowledge that pre-service teachers have in
their content area. This includes undergraduate courses in the content area, undergraduate
majors, and test scores on the California Subject Examination for Teachers (CSET)
scores.
Educational or teaching experience means the working experience that pre-
service teachers have in the education and working with children. This will include
personal, professional, and educational experience where the candidates have worked
with children as tutors, teachers, or mentors. This will be measured by the levels of
involvement students have had in the past with the classroom.

16
Organization of the Study
Chapter 1 of the study has presented the introduction, the background of the
problem, the statement of the problem, the purpose of the study, the questions to be
answered, the research hypotheses, the significance of the study, a brief description of the
methodology, the assumptions, and the definitions of terms.
Chapter 2 is a review of relevant literature as it pertains to the problem and
background of the problem. This is followed by Chapter 3; the methodology used in the
study, including the research design; population and sampling procedure; and the
instruments and their selection and development, together with information on validity
and reliability. A description of the procedures for data collection and the plan for data
analysis was also be included in Chapter 3.
Chapter 4 reportedthe results of the study. Chapter 5 will finalize the study with a
discussion of the results and implications for practice and research. Each of these sections
concludes with a rationale, including strengths and limitations of the design elements.

17
Chapter Two: Review of the Literature
The current educational landscape has changed remarkably to include multiple
pathways to a college degree. While distance learning has widened possibilities, there are
many concerns regarding its effectiveness to optimize cognitive, affective, and
experiential dimensions of teacher effectiveness, motivation, and efficacy. Considerable
research has focused on motivation science along with cognitive science that influences a
variety of different student and teacher outcomes (Chapman & Tunmer, 2003; Pintrich,
2003; Schunk, 1999; Zimmerman, et al., 1992). Some of those outcomes can be seen in
teacher persistence, classroom management, student achievement, and the use of
innovative practices. For the purposes of this study, we will look at how content
knowledge, educational experience, and program delivery can be related to the
development of self-efficacy.
According to research, we now know that there are clear relations among self-
efficacy and choice of activities, goals, effort and persistence, learning, and achievement
(Bandura, 1977; Ormrod, 2008; Wigfield & Eccles, 1992). Subsequently, there are three
main goals of educational researchers. The first is to comprehend the factors that
influence self-efficacy such as previous successes and failures, messages received from
others, success or failures of others (especially those similar to us), and success and
failures of an entire group. Second to grasp how those understandings and interests
interact with program delivery. Finally, discern how institutions and specifically, teacher
education programs can appropriate and build upon these understandings and interests to

18
ensure engagement and success of pre-service teacher candidates (Baker, Afflerbach, &
Reinking, 1996).
Special attention in this study was to measure the outcomes of self-efficacy in
pre-service teachers in teacher education. Factors that influence or foster high self-
efficacy have serious implications for teacher education programs, not just to improve
success rates in teacher education, but to also enhance delivery methods that prove
conducive for pre-service teachers. Specifically, this study looked at how prior
experience in teaching and content knowledge, can influence the development of self-
efficacy in pre-service teachers during their teacher education program; both online and
on-campus.
To address these, the literature review was introduced through a framework and
then divided into five sections. The first section broadly addresses the influence of self-
efficacy on achievement. This will be followed by a discussion of the factors that can
influence the development of self-efficacy. The next section will reveal research that
shows the influences of self-efficacy on pre-service teacher candidates. Following this
will be a discussion on research regarding program delivery. The last section will include
areas of online program delivery that need further research. Although each area is
explained separately, these factors are best understood as a whole supporting each other.
Theoretical Framework
Self-efficacy refers to a person’s confidence in his or her ability to complete a
task or reach a goal without necessarily having an actual experience with performing the
task previously (Bandura, 1977, 1986, 1995). According to Bandura, past experiences,

19
successes, vicarious learning, verbal persuasion, group successes, and affective states all
contribute to self-efficacy. Research in this field has shown that self-efficacy can
influence achievement and performance (Bandura, 1977; Ormrod, 2008; Wigfield &
Eccles, 1992), and that specific self-efficacy measures that match the task are better
predictors of success than general self-efficacy measures (Joo, Bong & Choi, 2000).
Teacher self-efficacy beliefs begin with pre-service teacher training programs.
Research by Kazelas, Reeves-Kazelsids, and Kersh (1991), found that teaching self-
efficacy beliefs affect teacher performance, student achievement, and the attitudes and
perceptions that teachers have on their future teaching performance. Because of this, we
looked at teacher education as the precursor and foreground where personal teaching self-
efficacy is developed.
Influences of Self-Efficacy
Since Albert Bandura’s (1977) groundbreaking research on self-efficacy as a
unifying theory of behavioral change, researchers have studied self-efficacy in almost
every discipline. As previously discussed, self-efficacy is the belief that one is capable of
executing certain behaviors or reaching certain goals (Bandura, 1977; Wigfield & Eccles,
1992; Ormrod, 2008). Self-efficacy is a social cognitive factor that may increase a
teacher’s effectiveness in producing student learning. Bandura (1986, 1997) forwarded
four sources of efficacy building information: mastery experiences, vicarious
experiences, social persuasion, and physiological or emotional arousal.

20
This section will review specific research that shows how self-efficacy is related
to pre-service teacher outcomes; specifically persistence, student achievement, classroom
management styles, and use of innovative practices.
Teacher self-efficacy and student achievement. Years of research have shown
increasing support for teacher and school influences on student achievement. Multilevel
modeling methods along with large databases have consistently been used to show that as
teachers develop self-efficacy in classroom experiences, they can positively influence
student achievement (Muijs & Reynolds, 2000). In 2000, researchers Muijs and Reynolds
presented findings that classroom level variance was twice as high as school level
variance in student achievement. This means that teachers have more influence on
student learning in the classroom, than school influences outside of the classroom. This is
because teachers are the principal agents or instrument interacting with students therefore
directly affecting these outcomes and learning (Muijs & Reynolds, 2000).
Several studies (Anderson, Greene, & Loewen, 1988; Ashton & Webb, 1986;
Gibson & Dembo, 1985; Ross, 1992) highlighted positive relationships between teachers’
self-efficacy and the achievement of their students. Gibson and Dembo’s (1985) two-
factor analysis of self-efficacy has been used as a measure by numerous researchers to
test this relationship. Additional studies (Ross, 1992; Anderson, Greene, & Loewen,
1988; Armor, et al., 1976), found that student achievement was higher in classrooms of
teachers with higher self-efficacy. This was due to mastery experiences (in the
classroom) being considered the most powerful influence on efficacy as they provide
direct feedback regarding capabilities (Tschannen-Moran, Hoy & Hoy, 1998). Although

21
an older study, there may be merit to mention in the study of Armor et al. (1976), the
effectiveness of the reading program in LAUSD was found to have higher gains in
classroom with teachers who felt more efficacious.
These studies indicate that as teachers develop self-efficacy, their positive belief
about the role of a teacher increases and leads them to act in ways that increase the
achievement of their students. They feel more efficacious about the difference they can
make in students’ learning through their effort as a teacher. Thus, they will put in more
effort and make classroom decisions that help students make gains in their learning, even
in the face of obstacles.
Self-efficacy and teacher attitudes. Self-efficacy can affect teacher attitudes. In
an effort to examine teacher perception and teacher attitude toward implementing new
instructional practices, Guskey (1998, 1997) found that teacher beliefs and self-efficacy
were significantly related to teacher attitudes toward implementing mastery learning in
the classroom and innovative instructional strategies. The use of innovative practices in
the classroom is an important indicator of the level of efficacy that a teacher possesses.
Brouwers and Tomic (2000) found that a decrease in the effectiveness of instruction time
lead to feelings of de-personalization and eventual teacher burnout. Because Guskey’s
research (1998,1997) found that self-efficacy is related to activities that lead to teacher
effectiveness, the lack of self-efficacy can lead to what Brouwers and Tomic’s (2000)
describe as a decrease in effective instructional time which resulted in de-personalization
and teacher burnout.

22
Another study by Smylie (1988) measured individual change in instruction and
innovation with personal teaching efficacy. Of the different variables tested, such as class
size, setting, student achievement levels, and certainty of practice, personal teaching
efficacy was found to have the largest significance on change in teacher practices through
change in teacher attitude. As teacher’s attitudes change through the development of self-
efficacy, they make changes in their classrooms that will help create mastery learning
experiences for their students (Smylie, 1988). Examples of these changes can include the
ability to and improve classroom management, adapt and use effective strategies and
create a variety of activities to engage individual students’ interests and needs.
Self-efficacy informs us about the belief system teacher’s hold in their ability to
produce student outcomes (Moseley, Rienke, & Bookout, 2002). This difference in
attitude helps teachers see the connection between effort and results. Thus, more effort
means a change in classroom instruction and practices. Moseley, Rienke, & Bookout,
(2002) inform educational leaders of the cyclical importance of attitude in changing
teachers’ behaviors that ultimately affect student learning positively which, in turn,
increase teacher self-efficacy.
Self-efficacy and persistence. Bandura’s (1977) pioneering work revealed that
self-efficacy is positively related to perseverance and can be sustained regardless of
obstacles or adverse experiences. Interest in this area inspired researchers Multon,
Brown, and Lent (1991). Their meta-analysis revealed a significant relationship between
self-efficacy and persistence. The authors found that across various types of student
samples, study characteristics, measures, and designs, self-efficacy accounted for 14% of

23
the variance in academic persistence of participants. Interestingly, their analysis revealed
this relationship to vary by achievement status. Students in the study who were low
achieving had a stronger relationship between efficacy and performance than moderate-
achieving students and in turn high-achieving students. This finding suggested that in
lower performing students, self-efficacy made a bigger difference on their achievement
gains than average performing students. In short, Multon, Brown, and Lent’s (1991)
findings support Bandura’s (1977, 1982, 1986) work. As self-efficacy increases these
pre-service teachers will persist academically. This can lead to better outcomes both as
pre-service teachers and future teachers.
In a study byWoolfolk and Hoy (1990), the authors revealed that pre-service and
inservice teachers who had lower degrees of personal efficacy felt that they had no
control over the organization of the school environment and parental influence. Personal
efficacy refers to a teachers belief in their personal ability to complete a task, as opposed
to their belief that teachers have the ability to be successful in a task. To the teachers with
lower personal efficacy, external home backgrounds were fixed and made them feel
powerless to overcome socioeconomic status; thus limiting their chances to change
student academic achievement. Their narrow viewpoints resulted in a more constrictive
management policy and inadequate differentiated instructional methods. Conversely,
Woolfok and Hoy (1990) showed that pre-service teachers who had higher levels of
efficacy had a more humanistic view and dealt more personally with students. They
tended to have higher expectations for their at-risk students not just in their classroom but
for the whole school and wider professional learning community.

24
Still other studies have added to the body of work that show teachers with higher
levels of efficacy tended to choose activities that promoted positive learning experiences
for their students (Dembo & Gibson, 1984; Emmer & Hickman, 1991). Those activities
included giving students praise, modifying instruction to student needs, motivating
students to put in more effort, and providing additional help on difficult tasks. These
studies underscore the fact that teachers with high self efficacy put more effort into their
teaching and are more persistent in helping students learn. Teachers who felt lower levels
of efficacy had lower expectations for their students. Subsequently, those teachers
focused more on behavior rules, using external rewards, and applying punishment for
undesired behavior. This classroom management style has been found to be more
prevalent among teachers who have lower levels of self-efficacy (Dembo & Gibson,
1984; Emmer & Hickman, 1991).
In short, research on teachers and students reveal the significant influence that
self-efficacy can have on academic outcomes and student motivation. One of these
outcomes is persistence. Self-efficacy increases persistence (Bandura, 1977; Ormrod,
2008; Wigfield & Eccles, 1992). Academic achievement is also found to be influenced by
an increase in self-efficacy. As teachers become more efficacious in their ability to
control the classroom environment, they will make different decisions about instruction,
which will help to increase student learning (Emmer and Hickman. 1991). All of these
outcomes are influenced by self-efficacy and can help to enhance teaching. In the
following section, I will discuss the role of previous experiences and cognitive
knowledge on self-efficacy.

25
Influence on Self-Efficacy
Influence of experience on self-efficacy. According to Bandura (1997), several
factors may influence self-efficacy. Among them are prior experiences (also called
mastery experiences) in challenging tasks, vicarious experiences, and previous cognitive
knowledge. Bandura (1997) also described prior experiences that build self-efficacy,
mastery experiences or simply, successful experiences. Bandura (1977) describes mastery
experiences as authentic success at completing tasks, and that through authentic
successful experiences; people receive evidence upon which they base their belief in their
source of efficacy. This can add power to a person’s motivation.
A case study done by Milner (2002) found that the successful completion of
several years of teaching was the most significant factor in developing teacher self-
efficacy. In his case study, it was this increase in efficacy that prevented a teacher from
quitting the profession during critical years of crisis (Milner, 2002). Although this case
study only included one participant, its findings helped in informing direction for other
similar studies. One such study done by Hoy and Spero (2005) tested four measures of
efficacy and revealed mastery experience as being one of the most influential sources of
efficacy during student teaching and the induction years. This much stronger and
empirical longitudinal study followed pre-service teachers from entry into an educational
program through student teaching until the end of the induction year. The design of this
study was based on Bandura’s theory of self-efficacy, which suggests that the early years
of teaching are the most impressionable and thus critical for long-term development of
teaching efficacy. Multiple quantitative assessments were used and found a significant

26
increase in self-efficacy from the beginning of the education program to the end of
student teaching. However, it was also found that self-efficacy decreased through the
induction year. It is important to also note that the change during induction year
correlated with level of support given (Hoy & Spero, 2005). These studies by Hoy &
Spero (2005) support Bandura’s theory that mastery experiences are significant sources
of self-efficacy in pre-service candidates in teacher education programs.
Another significant source of self-efficacy is vicarious experiences (Bandura,
1995). With the introduction of the Internet and web-based courses, vicarious experiences
may be a primary factor of self-efficacy. Vicarious experience is defined as a technique
in which students gain the internal imagery needed to succeed in a task by observing
experienced from others providing that context; thus understanding vicariously (Bandura,
1995). Posanski (2002) conducted a study of science tutors who used role playing to
guide science student teachers. In the course, student teachers assumed the role of young
science students. The study found an increase of science teaching efficacy in student
teachers.
Tschannen-Moran and Hoy (2005) researched the role that mastery experiences
have on novice and experienced teachers. They hypothesized that because novice
teachers do not have many mastery experiences, factors such as vicarious experiences,
must play stronger roles in the development of self-efficacy. In their findings, their
hypothesis was supported. For novice teachers, vicarious experiences accounted for 49%
of the variance in the teacher self-efficacy scale; along with verbal persuasion, and
emotional arousal. For experienced teachers, these factors only accounted for 19%. This

27
means that these contextual factors play a stronger role for novice teachers than expert
teachers.
In sum, prior experience has an important role in the development of self-efficacy
of pre-service teachers and beginning teachers. These experiences whether mastery or
vicarious that occur in the early years of teaching or during student teaching can
influence the developing belief systems of early teachers. Bandura (1995) states that
these are critical developing years for teachers to develop long-term efficacy which can
help to carry them through critical points in teaching difficulties which result in longer
teaching careers.
Influence of prior knowledge on self-efficacy. Knowledge is another source of
self-efficacy for teachers. Palmer (2006) conducted a study that measured various sources
of self-efficacy for primary pre-service teachers: enactive mastery experiences, vicarious
experiences, verbal persuasion, physiological/affective states, cognitive content mastery,
and cognitive pedagogical mastery. Palmer (2006) found that cognitive pedagogical
mastery was the main source of efficacy in a primary science methods course. After
collecting data on changes in self-efficacy of pre-service science teachers, Palmer (2006)
concluded that teachers first need the necessary pedagogical and content knowledge in
order to make judgments about how they might be able to organize and carry out
classroom decision making in ambiguous and unpredictable situations. Often, this can be
stressful for teachers. However, Palmers (2006) conclusions inform us on how an
increase in content knowledge will increase self-efficacy, which is necessary to help pre-
service teachers become efficacious in the classroom.

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A similar study conducted by Settlage (2000) was designed to understand the
relationship between science content knowledge and pre-service science teachers’
attitudes and teaching self-efficacy. Pre-service teachers’ efficacy was measured via pre
and post test STEBI (Science Teacher Efficacy Belief Instrument) efficacy scales during
elementary education courses. Settlage (2000) found significant correlations between
understandings of the course material with post-test levels of efficacy. These findings
suggest that instruction during coursework increased the knowledge base for pre-service
teachers, which contributed to an increase in self-efficacy.
Looking at the relationship among subject knowledge, student achievement and
self-efficacy, Muijs and Reynolds (2002) also found that subject knowledge was the
strongest predictor of teacher efficacy and that teacher efficacy and subject knowledge
directly impacted teacher behaviors and student achievement. In a related study by
medical doctors published in The American Journal of Preventative Medicine (2002),
results of a yearlong medical study (Carson, Gillham, Kirk, Reddy, and Battles, 2002)
revealed a significant increase in self-efficacy at monthly examinations of students who
participated in a medical education program that helped to develop nutrition knowledge.
An experimental and control group were charted throughout the study. The self-efficacy
scores of the experimental group significantly increased and were two times that of the
control group whose findings were not significant. The authors credit this raise in self-
efficacy to the increase in knowledge gained. Doctors in the experimental group were
also more likely to apply that knowledge in patient care. Although not pre-service

29
teachers, this study is important in showing the connection between cognitive knowledge
and self-efficacy in college students.
In summary, mastery experiences, vicarious experiences, positive feedback and
support along with cognitive knowledge all play a part towards influencing self-efficacy
for pre-service teacher candidates. The following section will tie these findings to the
development of self-efficacy in pre-service teachers.
Development of Self-efficacy in Pre-Service Teachers
Developing self-efficacy in pre-service teachers is essential in preparing them to
teach effectively (Enochs & Riggs, 1990). This section will discuss the different factors
in the teacher preparation experience of students that have an influence on the
development of self-efficacy.
The student teaching experience is usually toward the end of pre-service teacher
education programs and can serve as a strong indicator of self-efficacy. A study of novice
teachers by Moseley, Keinke, and Bookout (2002), revealed interesting pre and post
results after seven weeks of student teaching. Moseley and his colleagues (2002) found
that student teaching efficacy was high before the program and remained unchanged
during the teaching process. However, post-test results at the end of the seven weeks,
showed teaching self-efficacy significantly dropped. The authors’ evaluation highlighted
a significant negative relationship between self-efficacy and teaching experience. The
authors suggested that this could be due to program and teacher characteristics, lack of
reinforcement, or the fact that this classroom experience was the first and potentially only
teaching experience of pre-service teacher candidates. Further, such an evaluation is

30
incremental throughout the seven weeks, and thus student teachers were more thoughtful
about their experience and reevaluated their ability and knowledge about teaching
methodologies toward the end.
Supporting this trend, Lin and Gorrell (2001) studied the difference in efficacy
beliefs of beginning pre-service teachers and ending pre-service teachers. The
participants came from four-year teacher education institutions. Finishing pre-service
teachers had two more years of professional training than beginning pre-service teachers.
Findings showed that pre-service teachers at the beginning level and pre-service teachers
at the ending level of their education were significantly different in their self-efficacy
beliefs. Beginning level pre-service teachers had a higher self-efficacy when teaching
difficult students, and in adjusting to students’ ability levels. They were also more
confident in their ability to provide culturally relevant and appropriate learning
experiences. However, at the same time, these beginning pre-service teachers had lower
efficacy in their ability to make a difference in a student’s actual learning. In other words,
they were confident that they could apply teaching skills in the classroom, but had low
self-efficacy in those things actually causing student outcomes. Some of the difference
was attributed to beginning pre-service teachers having less educational experiences with
subsequent lower levels of self-efficacy. On the other hand, finishing pre-service teachers
were found to have higher confidence in their ability to affect student learning. Finishing
pre-service teachers also felt more confident that students can learn regardless of family
background or other socioeconomic factors, while beginning teachers had a stronger
belief that student learning is limited and related to family background. Ending pre-

31
service teachers believed that their efforts would result in more effective pedagogical
skills that were not limited by family support.
A longitudinal study conducted by Woolfolk and Hoy (2000) argued that pre-
service teachers’ level of efficacy increases from the beginning of their program to the
end of their program. However, results from after their first year of teaching showed that
their levels of efficacy lowered. They also concluded that the increase during the teacher
education program was due to the support provided to them as students. When this
support is taken away, their expectancies of efficacy decreased. Bandura (1997) stated
that the first year of teaching is the critical stage in establishing long lasting efficacy.
Veenman (1984) has titled this time in a teacher’s career as the “reality shock” where
teachers come to understand the complexities of teaching.
Teacher education programs often provide some sort of mentorship for pre-
service teachers. The extent of involvement and the role of these mentor teachers vary
depending on the structure of the program. Further, the state of California has initiated a
Beginning Teachers Support and Assessment (BTSA) program that monitors new
teachers’ progress toward attaining a cleared credential. This program provides an
individual mentor to each new teacher in order to provide support as teachers, confidant,
role model, developer of talent, and sponser (Gehrke & Kay, 1984). Other research shows
that mentors provide encouragement, counseling, and friendship to teachers(Anderson &
Shannon). This kind of mentorship helps to build confidence in preservice teachers, and
create a perception of confidence and adequacy in various areas of teaching, which lead
to higher levels of self-efficacy (Walker, 1992).

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In sum, experience of pre-service teachers can influence self-efficacy. Research
supports that self-efficacy rises from beginning to the end of teacher preparation
programs, but may decrease after one year of teaching experience, partly due to a
realization of the complexities of teaching. The next section will review research that will
help us understand the role of learners’ self-efficacy in distance education technologies
that they might succeed more readily and thus address the retention problem in distance
education (DeTure, 2004; Diaz, 2000).
Role of Online Delivery on Teacher Self-Efficacy
The acceleration of technological advances worldwide has provided expansion
and diversification of opportunities, formats, learning experiences, and degrees (Tierney,
2007; Pont, 2004). A report in 2004, showed that over 54,000 online courses were offered
by universities in the United States with more than 1.6 million student enrolled (Singh &
Pan, 2004). Another survey conducted by the United States Education Department shows
enrollment as 2.9 million in 2001 (Lyons, 2004). More specifically, Internet accessibility
has created unprecedented opportunities in teacher education for non-traditional students
(Karber, 2003; Li & Irby,). As the popularity of new learning formats grow, so does the
attention of researchers who want to investigate implications of online learning in
education. This section will begin with a brief description of the basic types of distance
learning programs followed by a discussion of the interplay between program delivery
and student self-efficacy.
There are many types of online or distance education programs. Clark (2000)
described virtual schools and Blended Learning Environments. Moore (1993) proposed

33
two classifications of online education programs: distance and autonomy. Distance is
determined by measuring the ability of the program to support two-way communication
such as dialogue and student interaction as well as structure, or the ability to respond to
student needs such as support and feedback. Autonomy on the other hand is described as
student control over his or her learning through planning, execution, and evaluation of
their own work. Moore (1989) also categorized distance education program interaction
into three types: learner-content, learner-instructor, and learner-learner. This is the
amount of interaction that occurs in a distance program between (1) the learner and the
content, (2) the lerner and insructor, and (3) the learner with other learners. Hillman,
Willis, and Gunawardena (1994) added a fourth category, learner-interface, as distance
education requires the student to interface with more and more technologies. Making
these distinctions is important for future analyses. For example, follow-up studies
(Garrison, 1990, Hackman & Walker, 1990; Saba & Shearer, 1994) showed students who
perceive higher levels of interaction with professors and other students tended to have
more positive attitudes and higher achievement (Navarro & Shoemaker, 2000).
The MAT @ USC program utilizes technology that provides opportunities for
weekly face-to-face interaction between pre-service teachers and professors. Deture
(2004) found that cognitive style scores and specific online technologies self-efficacy
were poor predictors of student success in online distance education courses. Deture’s
(2004) study raises the awareness that just because students have higher confidence with
technologies does not necessarily mean they will produce higher grades.

34
There have been many studies conducted to measure the effectiveness of these
different online programs. One meta-Analysis conducted by Sitzmann, Kraiger, Stweart,
and Wisher (2006) compared the effectiveness of online education, otherwise known as
web-based instruction (WBI) and online education including aspects of personal
interaction, known as blended learning environments (WBI-S), with traditional classroom
instruction (CI). Their analysis included 96 research reports between 1996 and February
2005, 71 effect sizes and 10,910 participants. In their final conclusions, the researchers
found WBI to be 6% more effective than CI in teaching declarative knowledge but not
for teaching procedural knowledge. Interestingly, they found that WBI-S, which included
multiple delivery media with benefits of personal interaction, optimized the instructional
advantages of WBI and CI resulting in better outcomes (Sitzmann, Kraiger, Stewart, &
Wisher, 2006).
Using the Online Learning Value and Self-Efficacy Scale (OLVSES), Anthony
Artino and Betsy McCoach (2008) theorized that self-efficacy and self-regulation are
important factors in online learning. The authors examined a quantitative self-report that
measured task value and self-efficacy in online learning environments. Six variables were
correlated with self-efficacy using this measure; boredom, frustration, elaboration,
metacognitive self-regulation, task value, and self-efficacy. Findings from their study
reveal that self-efficacy is significantly related to these six variables. Students’ negative
achievement emotions such as boredom and frustration were negatively related to self-
efficacy, and use of cognitive and metacognitive learning strategies were positively
related to self-efficacy. Self-efficacy beliefs were also found to be positively related to

35
students’ use of self-regulated learning strategies in online academic settings. The study
revealed the extent to which students feel they can learn effectively using online
coursework was significant. This investigation is important because it supports previous
research that posits self-regulation and self-efficacy as predictors of motivation and
student success (Artino & McCoach, 2008; Bandura, 1977).
Another study conducted by So and Brush (2006) looked at student perceptions in
a blended learning environment (i.e. using computer mediated communications). They
found that in either distance or traditional learning environments, collaborative learning
and social presence were significant predictors of student satisfaction. With new
technology advances such as SKYPE, Voicethread, YouTube, etc., the ability for student-
to-teacher, and student-to-student interaction has become increasingly feasible in distance
education. This kind of collaborative learning can be experienced through computer-
mediated communication (CMC) in distance learning, or face-to-face communication in
traditional settings. Findings from So and Brush (2006) revealed that students with higher
perceptions of collaborative learning have greater satisfaction with their distance
coursework and traditional learning settings, thus raising their level of efficacy.
David Hansen (2008) showed that online learning can increase student
satisfaction and self-efficacy. He found that online learning environments produced more
learning as measured by grades, student satisfaction, and performance. Students cited less
barriers to communication, quicker feedback, more accessibility to curriculum, and more
control over their own learning. These factors contribute to building content knowledge

36
and providing mastery and vicarious experiences, which influence the development of
self-efficacy.
One issue fundamental to building self-efficacy is providing competence
promoting feedback. Interestingly, a study by Kitsantas and Chow (2007) 474 students
enrolled in distance and traditional classes found that students preferred electronic means
of seeking help, and they found it more effective because of its ability to provide instant
feedback; as opposed to appointments, and waiting for professors. The same study
revealed that student achievement was significantly correlated with academic self-
efficacy and perceived threat to seek help. The authors found that students enrolled in
courses with an online computer component reported (a) higher instances of help seeking
behavior, particularly from instructors; and (b) felt less threatened to seek help than
students in traditional learning environments. Further, the study revealed that student
achievement was significantly correlated with formal help seeking, academic self-
efficacy, and perceived threat to seek help. Lastly, Kitsantas and Chow (2007) reported
that students preferred electronic means to seek help and that they found electronic means
more effective.
In summary, a new body of research has converged to find that delivery of
educational programs influence self-efficacy and student satisfaction. Artino and
McCoach (2008) validated the OLVSES scale that measures self-efficacy beliefs in
online learning to student boredom and frustration. With the influx of universities rushing
to provide internet-based courses for distance education, there are many concerns
regarding a high quality education. The concluding section will discuss further research

37
needs in the area of online education and self-efficacy; specifically the self-efficacy of
teachers and online teacher preparation programs.
Needed Research on the Effectiveness of Online Educational Programs
Although there are expansive amounts of interesting research on online
educational programs, there is still a lack of research in the specific area of teacher
education and self-efficacy. Barbera (2004) states that there is still a lot of research that is
needed to prove high quality education through virtual environments can meet the
promises that they have to provide equal learning environments and achievement.
Taking into account the purpose of this study, there is limited to no research done
measuring teaching self-efficacy of online education versus face-to-face or traditional
education. Most of the research is in effectiveness of knowledge acquisition or student
achievement rather than measuring self-efficacy of teachers.
The study previously mentioned by So and Brush (2006) which measured student
perceptions in a blended learning environment would be the perfect example of a study
that could have included teacher and student self-efficacy as a factor in their analysis of
online and traditional learning environments. However, they state in their findings that
further research is needed to find other factors that can influence distance students’
satisfaction, frustration, and anxiety. Also, much of the research surrounding self-efficacy
and online education defines self-efficacy as the students’ ability to use technology rather
than the effective use of technology to build teaching efficacy that leads to student
achievement. This is a critical key in predicting student outcome (Bandura, 1977).

38
An article which is currently in press written by Clark, Yates, Early, and Moulton
(in press) claim that media technology does not influence student learning or achievement
at all. Rather, it is only the vehicle that delivers information, but the information itself is
what motivates and creates the student learning. They claim that in studies that show
benefits from certain media mistakenly insert different instructional methods and
information content in one media, but not in the comparison media. The authors claim
media does not make the difference or cause learning, and warn about the assumption
that delivery through media technology are an active ingredient in learning and
motivation.
A review of the literature by Barbour and Reeves (2009) identified some of the
existing major research needs. One of the most important is the need for researchers to
evaluate more in-depth the factors that affect student success. These include student
characteristics, processing skills, and motivation. This will help better understand the
experiences of students participating in online learning. Researchers such as Roblyer and
Marxhal (2002-2003) have begun this type of study by developing a reliable instrument
(ESPRI) that can predict student success based on such factors, however even they claim,
that this is only preliminary. Rice (2006) suggested researchers to continue and expand
on developing a predictive instrument that can help identify successful learner attributes.
Another concern regarding the effectiveness of online education is the integrity
and accuracy of web commercialization. Singh and Pan (2004) posit that there are flaws
in the quality of information provided on the Internet and that commercialization of
Internet programs create the possibility of biased results. Their review also reveals that

39
there has been little done to compare the effect of student attendance in online programs
with traditional programs.
Effective research is never ending in the need to evaluate the benefits of new
media. Technology is continually changing in better and new ways. Software programs,
and Internet accessibility are creating an online environment where students can have
more realistic communication that mimic’s and sometimes enhances face-to-face
experiences. It is essential that researchers continue to keep up with these advances and
provide academic fields the most up-to-date findings that affect how these technologies
help us learn.
In summary, more research is needed to address the quality and integrity of online
programs in producing the same outcomes as traditional settings. More specifically, the
research needs to compare the differences in self-efficacy in online versus on-campus
programs. Consideration must also be given to media technology as the vehicle that is
separate from the content that is being presented. Taken together, they add to the body of
literature to help us better understand student success.
Conclusion
The consequences of dramatically increasing access to teacher education through
online delivery options demand that educators grasp understandings of self-efficacy and
how they interact with program delivery, and the success of pre-service teacher
candidates. To most researchers, the evidence is clear that there are relationships among
self-efficacy and choice of activities, goals, effort and persistence, learning, and
achievement (Bandura, 1977; Ormrod, 2008; Wigfield & Eccles, 1992). Research in self-

40
efficacy explains that previous experiences, both successes and failures, feedback from
others, vicarious experiences, and cognitive knowledge relate to persistence and success.
Teachers with high self-efficacy are more willing to experiment with new strategies, set
higher goals, and put more effort into their teaching and are more persistent at helping
students learn (Ormrod, 2008). Bandura (1997) explains that it is useful to view self-
efficacy as a fundamental construct by which individuals’ needs and desires are activated
and thus, directs their behaviors and goals. Factors that influence or foster high self-
efficacy have serious implications for teacher education programs, not just to improve
success rates in teacher education, but to also enhance delivery modalities that prove
conducive for students.

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Chapter Three: Research Methodology
Colleges like the University of Southern California are deploying new teacher
education programs that help to develop better teachers for the classroom by increasing
teacher self-efficacy. The Master of Arts in Teaching program at USC (MAT @ USC) is
one such program. Starting in the Fall of 2009, students across the Nation were able to
complete this degree via online education. This study looked at both the online and
traditional versions of the MAT @ USC program in conjunction with its relationship to
self-efficacy development in pre-service teacher candidates.
There were three goals of this study. The first goal was to reveal the relationship
between self-efficacy and delivery method of the MAT teacher education program at the
University of Southern California. The second goal was to see if there is a relationship
between the sociocultural factors of prior knowledge and prior experience, with self-
efficacy of pre-service teachers. Third, additional addendum questions were added to
explore the relationship between self-efficacy of all students in the MAT @ USC
program with student demographics. This chapter includes the research questions, the
hypotheses, and a description of the research methodology. The latter includes the
sampling procedure and population, instrumentation, and procedures for data collection
and analysis.
Research Questions
Three original research questions were posited to meet the purposes of this study.
Due to a small sample size, they have been slightly edited to include subscales of self-

42
efficacy, and eliminate delivery as a focal point for each question. Instead, delivery
method is in question 2 for informational purposes. The following research questions are:
1. a. What is the self-efficacy of pre-service teacher candidates in the MAT @
USC program?
b. What is the self-efficacy of pre-service teacher candidates for each of the
following subscales: innovative strategies, classroom management, and
student engagement?
2. Does program delivery predict self-efficacy of pre-service teacher candidates
in the MAT @ USC program?
3. Does prior experience and content knowledge predict self-efficacy of pre-
service teacher candidates?
Research Questions Addendum. Upon initial completion of data analysis, it was
found that the number of respondents in the online cohort of the MAT @ USC program
was insufficient to conclude with significant findings. As such, additional questions were
added to this study to further explore the relationships that exist between teacher self-
efficacy and MAT @ USC pre-service teacher candidate characteristics. For the purpose
of this study, we will allow data results for the initial three research questions to be
included in the study, and add the data and findings to the following additional questions:
4. Does teacher self-efficacy of pre-service teacher candidates differ by gender,
content area, or first generation college status?
5. Does teacher self-efficacy of pre-service teacher candidates differ by age, or
ethnicity?

43
The overarching issue of these research questions is that of self-efficacy. Because
self-efficacy can be applied in numerous different constructs and tasks, it is important to
clarify what type of self-efficacy was addressed in this study. The study looked at self-
efficacy in relation to pre-service teachers’ beliefs of classroom practices. In other
words, how efficacious they feel about their ability to become good teachers.
Research Design
This study explored the relationship that exists among self-efficacy, program
delivery, prior experience, and student demographics. The aim was to probe these
relationships in a cohort of MAT @ USC program using quantitative research methods.
We used a descriptive study, (non-experimental) design,not seek to find causality, but
rather to investigate correlations between factors through quantifying these relationships.
This study will include a t-test comparison of means, a regression model, and an ANOVA
test that will map out the relationships among variables.
The cohort of both online and on campus students in the MAT @ USC program
was surveyed for this study. The survey was administered toward the end of the program
of study and was given to the MAT students by the researchers via on-campus classes
and through Internet-based technology. Permission was sought beforehand from both the
directors of the MAT program, as well as the specific instructors for each section of
students surveyed. An information sheet was given to all students. Students were asked to
sign an informed consent sheet giving researchers permission to collect the necessary
data.

44
Independent and Dependent Variables
The independent variables in this research design were:
• Online delivery method of the MAT @ USC Program
• On campus delivery method of the MAT @ USC Program
• Prior knowledge of pre-service teacher candidates as measured by CSET and
PRAXIS scores
• Prior educational experience of pre-service teacher candidates as measured on a
self designated scale from uninvolved, to involved, to engaged.
• Student male/female gender identification
• Age of pre-service teacher candidates
• Identified ethnicity of pre-service teacher candidates
• First generation college graduate status of pre-service teacher candidates
• Content area namely single subject and multiple subject area disciplines
The one main dependent variable for this study was teacher self-efficacy. Self-
efficacy is then further broken down into three subcategories that were used to analyze
additional secondary dependent variables. The three subcategories were:
• Self-efficacy in classroom management,
• Self-efficacy in the use of instructional strategies, and
• Self-efficacy in the ability to engage students.

45
Population and Sample
The population for this study consisted of two cohorts of post-Baccalaureate, pre-
service teacher candidates in the MAT @ USC program. The first cohort of students was
enrolled in the online program and consisted of 142 students. The second cohort of
students was enrolled in the on-campus program. There were 92 students in this cohort. .
The data analysis for each of the research questions was done separately for the
two cohorts and then grouped together for an overall analysis. A total of 77 responses
were collected from students enrolled in the online and on-campus USC @ MAT
program. There were 11 deletions made due to lack of response, and missing information.
An additional three respondents were deleted due to inaccurate identification numbers.
This information was put into Qualtrics with a total of 66 responses available for self-
efficacy data analysis, and 63 responses available for demographic data analysis. The
following tests were used for each question:
Instrumentation
Dependent variable.
Self-efficacy. Teacher candidate self-efficacy was determined by the test called
the Teacher’s Sense of Efficacy Scale, which was developed by researchers Anita
Woolfolk Hoy and Megan Tschannen-Moran (2001), also referred to as The Ohio State
Teacher Efficacy Scale (OSTES).
The Teacher’s Sense of Efficacy Scale was used to measure three moderately
correlated subscales: efficacy in student engagement, efficacy in instructional strategies,
and efficacy in classroom management. Originally a 52-item scale, through testing and

46
development was rounded down to two versions: a 24-item scale, and a 12-item scale.
The purpose in choosing this scale over other options was because this scale was
developed specifically for use with pre-service teacher candidates, furthermore the 24-
item scale contributed to greater reliability on the three subscales. Permission to use this
scale was granted by the creator, Anita Wolfolk Hoy Ph.D. (Appendix D).
Dr. Anita Wolfolk Hoy examined the construct validity of the Teacher’s Sense of
Efficacy Scale by assessing the correlations with other teacher efficacy scales; including
Kerlinger (1986), Hoy and Woolfolk (1993), Gibson and Dembo (1985), and the two
original self-efficacy Rand items. The researchers found positive correlations, especially
for the personal teaching efficacy factor. The total scale and each of the subscales were
found to be highly reliable. Reliability was found for the total scale and each of the three
factors using Cronbach’s alpha reported as follows: Teaching Self-Efficacy Scale .97,
Student Engagement .87, Instructional Practices .91, Classroom Management .90. The
full Teaching Self-Efficacy Scale that we used for this study is attached as Appendix B.
This includes the TSES and the additional questions regarding the independent variables
of content knowledge and prior experience.
Independent variables.
Delivery. The first question in the survey asked which of the two types of
program they are currently enrolled in. Students answered whether they were in the
online or on-campus cohort. The surveys were then separated by cohort and analyzed
independently and then compared to each other.

47
Prior Knowledge. It is important to annotate here that this study was not able to
incorporate prior knowledge as a variable for data analysis. This was because the State of
California did not release the needed test scores to either the students, or USC. This
information was presented to us after data collection and post dissertation proposal.
However, prior knowledge is still an important variable to the overall purpose of the
study and thus the original plans are included and were as follows:
To measure prior knowledge of pre-service teacher candidates, we asked for their
scores on the California Subject Examination for Teachers (CSET). The CSET is scored
on a scale of 100-300. The minimum passing score on this exam is 220. We assumed
that all current students in the MAT @ USC program had passed this exam. For each
subject area, there are three to four subtests that students are required to take. Each test is
5 hours long. Students will report their scores for each subtest. Student scores will then
be separated in an ordinal scale using the following guidelines: (1) score of 281-300, (2)
score of 261-280, (3) score of 240-260, (4) score of 220-240. A 220 is the minimum
passing score for the CSET.
It is important to note that not all students in the program are required to take the
CSET for their subject matter. Students who majored in their subject area as
undergraduates from a recognized accredited university by the State of California’s
Department of Education are exempt from taking the CSET.
Prior Experience. To measure prior educational experience, students were given
a list of what is considered educational experience. They were subsequently asked what
their experience was, which was then categorized into three levels. The first level was

48
engaged teaching experience; specifically full responsibility in the classroom, either as a
teacher or a substitute. The second level was involved teaching experience. This
experience includes responsibilities as a tutor, teaching assistant, or aid. Finally, the last
level was uninvolved teaching experience; meaning observations of classrooms or
working with a classroom environment indirectly. The number reported was accumulated
and represented numerically to meet the needs of the quantitative methodology in this
study.
Demographic Information. To include demographic information in analysis for
this study, researchers sought permission from participants by including identification
information at the beginning of the survey. Students were also asked to sign an
information sheet, asking permission to use their ID numbers, for the purpose of gaining
information from each of their student files. The office at MAT provided the following
demographic information; Age, Ethnicity, Gender, Content Area, and 1’st generation
college status.
Scale Creations. Scale authors, Woolfolk-Hoy and Tschannen-Moran (2001)
previously ran primary analyses, examining students’ responses to the entire 24-item
scale, as the authors have previously noted that the factor structure of the scale may be
less clear when pre-service teachers are examined (Wolfolk-Hoy, Tschannen-Moran,
2001). In order to create an overall self-efficacy score, respondents’ answers to the full
24-item scale were averaged together. Examination of Cronbach’s alpha revealed an
exceptionally high value for alpha (∝ = .97), however, this may be attributable, in part, to
the fact that alpha reflects the number of items in the scale, as well as the items internal

49
consistency. Considering the 24-items included in the scale, it may thus be unsurprising
to find a high alpha value. Given that single-item deletions failed to substantively
improve the scale, and that the scale values found in this study (M = 7.2, SD = 1.1, ∝ =
.97) closely resemble those reported in previous research (M = 7.1, SD = 1.1, ∝ = .94;
Tschannen-Moran & Woolfolk, 2001), it was decided to retain the full 24-items for the
primary analyses. Similarly, the three subscales each showed high levels of internal
consistency: Student Engagement .92, Instructional Practices .91, and Classroom
Management 94.
Data Collection
The data collection for this study took place during class hours, for those students
in the on-campus courses, and via the Internet for students in the online program.
Permission to use this time for data collection was sought from the director of the MAT
@ USC program as well as the professors whose classes were utilized.
During data collection, the researchers passed out the survey to all students. They
were given time to complete the survey and submit surveys to researchers, who then
input the data into Qualtrics. Volunteers from the MAT office were employed to collect
demographic information for each participant. All this information was used for data
analysis in SPSS. Students in the online cohort submitted the surveys via the Internet.
The surveys that were administered to the students were on a volunteer basis. Completion
of the survey did not take more than 10 minutes.

50
Data Analysis
Research Question 1a – What is the self-efficacy of pre-service teacher
candidates in the MAT @ USC teacher education program?
Research Question 1b – What is the self-efficacy of pre-service teacher
candidates in the MAT @ USC teacher education program for each of the
subscales: classroom management, instructional strategies, and student
engagement? SPSS statistics data analysis program was used to run a one-sample
statistics test to find the means of overall self-efficacy. In addition, the means of the three
subcategories of classroom management, instructional strategies, and student engagement
were also programmed into the test. This test revealed the overall mean self-efficacy
scores for all respondents from the MAT @ USC program.
Research Question 2 – Does program delivery predict the self-efficacy of pre-
service teachers? To answer this question, a regression model was run to compare the
self-efficacy of both programs. Additional power analysis was run to find any statistical
difference between program type and overall self-efficacy. SPSS was used to examine the
mean difference between delivery method and overall self-efficacy, including the
subcategories. A series of independent samples t-test was used to examine these
relationships.
Research Question 3 – Does prior experience and content knowledge predict
self-efficacy of pre-service teacher candidates? To answer this question, a series of
regression models was constructed to test the predictive value of prior teaching
experience on self-efficacy development. The first regression model tested the MAT @

51
USC cohort as a whole. All pre-service teacher candidates were combined and measured
against Prior experience. This was the independent variable, and self-efficacy was the
dependent variable. The second regression model measured the predictive value between
the two delivery methods in the MAT @ USC program. The subscales of classroom
management, instructional strategies, and student engagement were also included in the
regression against prior teching experience.
In addition, a 1-way ANOVA was run to compare the mean scores of self-efficacy
to each level of prior teaching experience. The purpose of running this second test was to
examine if there existed any significant difference between the levels of prior teaching
experience other than the predictive value.
Research Question 4 – Does teacher self-efficacy of pre-service teacher
candidates differ by gender, content area, or first generation college status? The data
for this research question was collected from student files and input into SPSS statistics
program for analysis. A t-test of independent samples was conducted to explore the mean
efficacy-scores of each demographic category against each other. First, researchers ran
gender as two groups, 1 represented male participants, and 2 represented female
participants. The means of each group was calculated and represented in the data
findings. Second, content was split into two areas, 1 represented students seeking a
multiple subject credential, and 2 represented students seeking a single subject credential.
Finally, first generation college status was split into “yes” and “no” groupings.
Research Question 5 – Does teacher self-efficacy of pre-service teacher
candidates differ by age, and ethnicity. Similar to research question 4, data for this

52
research question was collected from student files at the MAT @ USC program office.
All information was imported into the SPSS statistical program for analysis. Researchers
ran a linear regression model to explore the relationship between age and the means of
overall self-efficacy scores, as well as the three subcategories of classroom management,
instructional strategies, and student engagement. In addition, an ANOVA test of means
was conducted to explore the relationship between ethnicity and overall self-efficacy,
including the three subcategories; classroom management, instructional strategies, and
student engagement.

53
Chapter Four: Results
This chapter presents the data analysis corresponding to the research questions.
Each question required different statistical tests and the resulting findings were presented
to answer each question separately.
Intercorrelations
Data Cleaning. During the data collection phase of this study, 77 responses were
collected from students enrolled in the online and on-campus USC @ MAT program.
These responses were recorded and input into Qualtrics. Of these, 8 were removed due to
lack of responses, 1 was removed because the student did not consent to participate, and
2 were removed because the subjects declined to provide a campus ID # or answer the
survey items. As a result of these 11 deletions, a total of 66 subjects was retained for
analysis of the self-efficacy scores. In addition, 2 more responses were removed due to
incorrect ID information during the demographics analysis phase of this study leaving a
total of 64 usable responses for research question 4 and 5.
Correlation Matrix. The following are the correlations between the variables
tested for this study. Looking at the values in Table 1, we can see that teaching
experience is not highly correlated to self-efficacy. As expected though, the results show
that overall self-efficacy is very much correlated to the three subscales of student
engagement, instructional practice, and classroom management. Also the three subscales
are highly correlated to each other, though slightly less than we observed with the overall
self-efficacy.

54
Table 1: Correlational Matrix
1 2 3 4 5
1. Teaching Experience - .15 .17 .06 .18
2. Overall Self-Efficacy - .94* .94* .95*
3. Student Engagement Self-Efficacy - .83* .83*
4. Instructional Practice Self-Efficacy - .85*
5. Class Management Self-Efficacy -
* p < .05
Frequencies. The following are the frequencies for each of the variables. The first
table shows the total number of valid participants for each of the demographic area. As
shown, there were 63 valid entries and no missing data. The following tables 2 through
table 7 show the frequency break down of each demographic areas. The first column
reveals the number of participants for each category within the demographic. The second
column is the percentage of each category within the whole group.
Table 2: Content area frequencies
Content Area Frequency Percent Valid Percent Cumulative
Percent
Multiple Subject 28 44.4 44.4 44.4
Single Subject 35 55.6 55.6 100.0
Total 63 100.0 100.0

55
Table 3: First generation college status frequencies
First Generation Frequency Percent Valid Percent Cumulative Percent
Yes 21 33.3 33.3 33.3
No 42 66.7 66.7 100.0
Total 63 100.0 100.0

Table 4: Gender status frequencies
Gender Frequency Percent Valid Percent Cumulative Percent
Male 17 27.0 27.0 27.0
Female 46 73.0 73.0 100.0
Total 63 100.0 100.0

Table 5: Teaching experience frequencies
Frequency Percent Valid Percent Cumulative Percent
Full 12 19.0 19.0 19.0
Assistant 27 42.9 42.9 61.9
Observer 13 20.6 20.6 82.5
None 11 17.5 17.5 100.0
Total 63 100.0 100.0

56
Table 6: Age status frequencies
Age Frequency Percent Valid Percent Cumulative Percent
24 8 12.7 12.7 12.7
25 12 19.0 19.0 31.7
26 14 22.2 22.2 54.0
27 6 9.5 9.5 63.5
28 8 12.7 12.7 76.2
29 3 4.8 4.8 81.0
30 2 3.2 3.2 84.1
31 4 6.3 6.3 90.5
33 1 1.6 1.6 92.1
34 1 1.6 1.6 93.7
35 1 1.6 1.6 95.2
43 1 1.6 1.6 96.8
52 1 1.6 1.6 98.4
60 1 1.6 1.6 100.0
Total 63 100.0 100.0

57
Table 7: Ethnicity status frequencies
Ethnicity Frequency Percent Valid Percent Cumulative Percent
Asian 9 14.3 14.3 14.3
Black/African American 3 4.8 4.8 19.0
Hispanic 8 12.7 12.7 31.7
Multi Cultural 10 15.9 15.9 47.6
Native American 1 1.6 1.6 49.2
Unreported 4 6.3 6.3 55.6
White 28 44.4 44.4 100.0
Total 63 100.0 100.0

Teaching Experience by Delivery Method
In order to test whether teaching experience was associated with program delivery
method, a chi-square test of independence was conducted. The test failed to reveal any
significant relationship between course format and level of teaching experience (x
2
(3)
=
2.67, p = .45).
The following table shows these results. As indicated in Table 8, the percentage
of students who claimed the various levels of teaching experience is similar in both
cohorts. None of the percentages shows a significant difference between cohorts.

58
Table 8: Tabulation of Teaching Experience by Program Type
Delivery Method
Teaching Experience Online On-Campus
Full responsibility in the classroom 4 (26.7%) 9 (17.6%)
Responsibility as a tutor, teaching assistant, or aid 4 (26.7%) 23 (45.1%)
Observation of indirect contact 3 (20.0%) 12 (23.5%)
None 4 (26.7%) 7 (13.7%)

Research Question 1 – a. What is the self-efficacy of pre-service teacher candidates
in the MAT @ USC program? b. What is the self-efficacy of pre-service teacher
candidates for each of the subscales; innovative strategies, classroom management,
and student engagement?
In order to determine the self-efficacy of pre-service teacher candidates, a one-
sample t-test was conducted to calculate the overall mean scores of participants. As seen
in Table 9, the overall analysis showed a mean score of 7.04 for overall self-efficacy,
7.23 for classroom management, a mean of 7.33 for instructional strategies, and 7.16 for
student engagement. The total participants as previously mentioned was 63 and being a
one-sample test, there is no test of significance.
Table 8 is a display of the level of self-efficacy of teacher candidates from both
cohorts. A Lickert scale was used to measure self-efficacy with answer possibilities
ranging from1 to 9. Findings revealed that the average score of self-efficacy and its three
subscales was 7. This score is in the upper half of the possible answers and shows a

59
strong positive outcome for all teacher candidates. This is important as we are seeking to
reveal self-efficacy without actually comparing it to any other variable.
Table 9: One-Sample Statistics test of self-efficacy and subscales
N Mean Std. Deviation Std. Error Mean
Overall SE 63 7.04 1.02 .12
Classroom Management 63 7.22 1.20 .15
Instructional Strategies 63 7.33 1.05 .13
Student Engagement 63 7.15 1.14 .14

Table 10 shows the 95% confidence interval for the lower and upper mean scores
for overall self-efficacy and it’s subscales. This means that for 95% of the respondents,
the lowest mean score was a 6.79 and the highest mean score was 7.30. The other 5% of
respondents’ scores lie outside of the confidence interval, or two and three standard
deviations away from the mean. Each of the subscales, lower and upper scores, were as
follows: classroom management was 6.92 and 7.53, instructional strategies were 7.07and
7.60, and student engagement was 6.87 and 7.45.

60
Table 10: One Sample Test of means
Test Value = 0
95% Confidence Interval
t df Sig.
(2-tailed)
Mean
Difference
Lower Upper
Overall SE 54.40 62 .000 7.04 6.78 7.30
Classroom Management 47.67 62 .000 7.22 6.92 7.52
Instructional Strategies 54.95 62 .000 7.33 7.06 7.60
Student Engagement 49.47 62 .000 7.15 6.86 7.44

Research Question 2 – Does program delivery predict self-efficacy of pre-service
teacher candidates in the MAT @ USC program?
In order to determine whether subjects’ overall self-efficacy scores varied
between the online and on-campus class sections, an independent samples t-test was
conducted. The analysis revealed no statistically significant difference in self-efficacy
scores of students enrolled in the online or on-campus class sections (see Table 10).
Given the relatively small sample size obtained for this study, a post hoc power
analysis was run to determine the required sample size to find statistical significance
given the relatively small observed effect size of 0.37. Using an alpha value of 0.05,
Power of 0.95, and changing the current ratio of online to face-to-face students to a 1:1
ratio, it was determined that a total sample size of 320 (160 online students and 160 face-
to-face students) would have been required to show a statistically significant difference in
overall self efficacy scores.

61
Given these figures, the present data suggests that self-efficacy does not differ
between the online and face-to-face classes in either a statistically or practically
significant manner.
Examining the three subscales of self-efficacy and program delivery. In
addition to the primary analysis examining overall teaching self-efficacy, a series of
independent samples t-tests were conducted to test for differences in subjects’ self
efficacy in student engagement, instructional practice, and class management between the
online and on-campus class sections. See Table 11.
Given these figures, the present data suggests that the three subscales examined,
student engagement, instructional practice, and classroom management, do not differ
between the online and on-campus programs in either a statistically or practically
significant manner.

62
Table 11: Summary of Independent Samples t-test Comparisons of Self Efficacy Based
on Class Format (N = 63)

Variable
Mean
Online
Mean
On-campus
Test
Statistic

df

sig
Overall Self Efficacy 7.57 7.15 1.35 64 -.18

Subscales
Student
Engagement
7.40 (1.30) 7.11 (1.09) 0.88 64 .38
Instructional
Practice
7.73 (1.06) 7.20 (1.01) 1.74 64 .09
Class
Management
7.58 (1.51) 7.14 (1.07) 1.03 18.32 .22

Research Question 3. Does prior experience and content knowledge predict self-
efficacy of pre-service teacher candidates?
To answer this question, the study looked at all variables and subscales and
compared them in multiple tests. First, a regression model (see table 12) was run
comparing the self-efficacy of all participants. This was done to test the predictive value
of each level of teaching experience. We also ran a secondary regression to test if the
predictive value is different between program delivery. Again, it is important to note that
program delivery analysis is included only for observational value, and not for statistical
significance. Finally, an ANOVA test of means was conducted to reveal any differences
between the levels of teaching experience with self-efficacy and its subscales of
classroom management, instructional practice, and student engagement.

63
The results of the regression model can be seen in Table 12. As displayed, the R
Square of the regression model for overall self-efficacy is .008 or 0% of the variance. In
addition, the R Square for classroom management is .027 or 3% of the variance,
instructional strategies is .002 or 0% of the variance, and student engagement is .021 or
2% of the variance. This means that teaching experience of pre-service teacher candidates
had no predictive value for self-efficacy or its subscales. The amount of teaching
experience with which students enter the MAT @ USC program did not impact how
efficacious they felt about becoming successful teachers upon completing the program.
Table 12: Summary of regression modeling of self-efficacy and teaching experience
R
R
Square
Adjusted
R Square
Std. Error
of the
Estimate
Change Statistics
R Square
Change
F
Change df1 df2
Sig. F
Change
Overall Self-
efficacy
.091 .008 -.008 1.03 .008 .509 1 61 .478
Classroom
Management
.164 .027 .011 1.19 .027 1.681 1 61 .200
Instructional
Strategies
.049 .002 -.014 1.06 .002 .145 1 61 .704
Student
Engagement
.145 .021 .005 1.14 .021 1.316 1 61 .256

64
In order to determine whether program type (online versus on-campus) predicts
teachers’ reported levels of overall teaching self-efficacy after controlling for their
experience teaching, a hierarchical linear regression model was examined (see table 13).
As teaching experience was measured as an ordinal variable, it was recoded and force
entered into the model, in the first block, as a series of dummy-coded variables. Program
type was then force entered into the model in a second block.
As shown in Table 13, the level of students’ teaching experiences did not predict
their reported overall teaching self-efficacy (F
(3,62)
= 0.63, p = .60). When program type
(online versus on-campus) was added in the second block, the resulting model did not
predict any additional variance in participants’ overall self-efficacy scores (F
(4,61)
= 0.91,
p = .46 The results are consistent in that neither prior teaching experiences nor program
delivery mode affected teacher candidate self efficacy.
Table 13: Summary of Hierarchical Linear Regression Modeling of Teaching Experience
and Program Type on Overall Teaching Self-Efficacy
Regression Model and Predictors Β SE Β β R
2
sig
Block 1 .03 .60
Full 9.97 10.47 .16 .95
Teaching Experience
a
Assistant 3.41 9.15 .07 .37
Observer -2.85

Block 2 .06 .46
Full 10.53 10.42 .17 .32
Teaching Experience
a
Assistant 5.57 9.24 .11 .55
Observer -1.21 10.17 -.02 .91
Program
b
-10.01 7.62 -.17 .19
a
Reference Category: No teaching experience
b
Reference Category: Online cohort

65
The ANOVA test was also used to determine if there was a statistical significance
based on the null hypothesis. In addition, it tests the differences between the levels of
teaching experience against the variable of self-efficacy. In this study, the null
hypothesis would state that there is no difference between teaching experience and self-
efficacy. Our result of .60 means we accept the null hypothesis., The level of claimed
teaching experience from the 66 participants did not affect their self-efficacy regardless
of program delivery.
Table 14: Summary of 1-way ANOVA Comparisons of Self Efficacy Based on
Experience Teaching (N = 65)

Variable
Test
Statistic

df

sig
Overall Self Efficacy .63 3, 62 .60

Subscales
Student Engagement .65 3, 62 .59
Instructional Practice .50 3, 62 .68
Class Management 1.28 3, 62 .29

These tests revealed no statistically significant differences in the self-efficacy
scores of students by teaching experience. Given these figures, the present data suggests
that the three subscales examined, student engagement, instructional practice, and class
management, do not differ significantly across the four levels of teaching experience
examined in the current study. Also, upon re-examination of the regression model in table

66
13, we can see that there was no predictive value of self-efficacy through prior teaching
experience. The data showed no significance between these two variables.
Research Question 4 – Does teacher self-efficacy of pre-service teacher candidates
differ by gender, content area, or first generation college status?
To answer this question demographic information was first collected from student
files using identification numbers. Permission was given by the participants, and special
care was taken by researchers to protect their identities. A series of independent samples
t-test was conducted for each demographic. Also included in the data results are Levene’s
Test for Equality of Variances. For both tests, data was run using equal variances
assumed, and equal variances’ not assumed.
The first set of tables show the results of the t-test for gender versus self-efficacy
and the subcategories of self-efficacy. Table 15 reveals the mean efficacy scores for both
male and female respondents. Interestingly, in all categories, male efficacy scores were
lower than female scores, with a standard error of between .14 and .34. However, further
analysis of Table 15 shows that there was no significant difference between male and
female self-efficacy scores, including the overall and all subscales of self-efficacy. This
finding remained true for both the t-test of means and Levene’s test of equal variances.
This means that although males had lower self-efficacy scores than females, these
scores were not meaningful in revealing a significant difference between the two groups.
It is also important to note that there are more than twice as many female respondents
than male respondents. If the number of participants were more similar in both groups,

67
there would be a greater likelihood of finding results that revealed a significant
difference.
Table 15: Independent samples t-test of means Group Statistics (1-male; 2-female)
Gender N Mean Std. Deviation Std. Error Mean
Overall SE
1 17 6.76 1.14 .27
2 46 7.14 .97 .14
Classroom Management
1 17 6.84 1.42 .34
2 46 7.36 1.09 .16
Instructional Strategies
1 17 7.19 1.00 .24
2 46 7.38 1.08 .15
Student Engagement
1 17 6.76 1.27 .30
2 46 7.30 1.07 .15

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Table 16: Independent Samples t-test of means and Levene’s Test for Equality of
Variences for gender and self-efficacy
Levene's Test for
Equality of Variances
t-test for Equality of Means
F Sig. T Df Sig. (2-tailed)
Overall SE
Equal variances
assumed
1.533 .220 -1.318 61 .192
Equal variances not
assumed

-1.223 25.08 .233
Classroom
Management
Equal variances
assumed
2.178 .145 -1.543 61 .128
Equal variances not
assumed

-1.366 23.32 .185
Instructional
Strategies
Equal variances
assumed
.144 .706 -.645 61 .522
Equal variances not
assumed

-.667 30.60 .510
Student
Engagement
Equal variances
assumed
.924 .340 -1.671 61 .100
Equal variances not
assumed

-1.544 24.91 .135

The following set of tables 17 and 18, reveal the findings from the independent
samples t-test for content area. Content area was split into two groups. The first group
was respondents seeking a multiple subject credential, and the second group was

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respondents seeking a single subject credential. As shown in Table 17 the means of both
groups were similar, for both overall self-efficacy and the subscales of classroom
management, instructional strategies, and student engagement. Both groups in this
category had a similar number of participants.
Looking at Table 18, Levene’s Test for Equal Variances was employed to assess
the equality of variances in both samples. In this test, overall self-efficacy scores
revealed a significant difference between single subject and multiple subject participants.
Self-efficacy in student engagement and instructional strategies revealed scores that
approached significance. However, for the purpose of this study, we confirmed with an
independent samples t-test of means that neither overall self-efficacy nor its subscales
revealed any significant difference between the two groups of content area.
This means that although Levene’s test showed overall self-efficacy between the
groups to have a meaningful difference, we must accept the null hypothesis which states
that there is no difference in self-efficacy between students who are seeking a single
subject credential and students who are seeking a multiple subject credential. Although
the number of participants in each group was somewhat similar, the data does not
conclude that these groups differ in self-efficacy scores.

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Table 17: Descriptive statistic for content area (1-multiple subject, 2-single subject)
Content N Mean Std. Deviation Std. Error Mean
Overall SE
1 28 7.03 1.23 .23
2 35 7.05 .84 .14
Classroom Management
1 28 7.16 1.36 .25
2 35 7.27 1.07 .18
Instructional Strategies
1 28 7.33 1.24 .23
2 35 7.33 .90 .15
Student Engagement
1 28 7.17 1.34 .25
2 35 7.13 .98 .16

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Table 18: Independent samples t-test for content area (1-multiple subject, 2-single
subject)
Levene's Test for Equality
of Variances
t-test for Equality of Means
F Sig. t df Sig. (2-tailed)
Overall SE
Equal variances
assumed
4.038 .049 -.065 61 .948
Equal variances not
assumed

-.063 45.814 .950
Classroom
Management
Equal variances
assumed
1.211 .276 -.331 61 .742
Equal variances not
assumed

-.323 50.566 .748
Instructional
Strategies
Equal variances
assumed
3.610 .062 .010 61 .992
Equal variances not
assumed

.010 47.971 .992
Student
Engagement
Equal variances
assumed
3.823 .055 .134 61 .894
Equal variances not
assumed

.129 48.227 .898

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The following two tables 19 and 20 are results of the independent samples t-test
of means comparing self-efficacy and the subscales of self-efficacy with participants first
generation college attendance status. A “1” response would indicate the participant is the
first in his or her family to receive a college degree. A “2” response would indicate that
the participant has parents who also attended college and received a degree. As shown in
Table 19, the means self-efficacy scores for first generation students were higher than 2
nd

generation college students in all categories of self-efficacy; with a standard error mean
of between .15 and .24. Also noted in Table #a is that there are twice as many students
who had parent attend college than those who did not attend college.
Looking at Table 20, it is clear that there is a significant difference between self-
efficacy for the two groups in overall self-efficacy, classroom management, and student
engagement. Self-efficacy in instructional strategies was the only category that did not
show a significant finding between the two groups of first generation college status. This
means that we will accept the hypothesis that pre-service teacher candidates in the MAT
@ USC program who are the first in their family to attend college have higher self-
efficacy than those who have parents with a college degree.
This is a meaningful finding for the purpose of this study because the difference is
a particularly strong one and suggests that there is a higher confidence factor in students
who are the first in their family to attend college. This confidence also expands into their
ability to manage classrooms and create student engagement. The only factor that was not

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found to be significant was instructional strategies. As can be seen in Table 20, the
overall mean score for instructional strategies was still higher in that group than those
whose parents attended college.
Table 19: Descriptive statistics for first generation status (1-first generation, 2- non-first
generation)
First
Gen
N Mean Std. Deviation Std. Error Mean
Overall SE
1 21 7.43 .96 .21
2 42 6.84 1.00 .15
Classroom Management
1 21 7.69 1.10 .24
2 42 6.99 1.19 .18
Instructional Strategies
1 21 7.64 1.12 .24
2 42 7.17 1.00 .15
Student Engagement
1 21 7.56 1.10 .24
2 42 6.95 1.12 .17

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Table 20: Independent samples t-test for first generation status (1-first generation, 2- non-
first generation)
Levene's Test for Equality
of Variances
t-test for Equality of Means
F Sig. t df Sig. (2-tailed)
Overall SE
Equal variances
assumed
.018 .895 2.221 61 .030
Equal variances not
assumed

2.252 41.608 .030
Classroom
Management
Equal variances
assumed
.000 .992 2.266 61 .027
Equal variances not
assumed

2.325 42.982 .025
Instructional
Strategies
Equal variances
assumed
.137 .713 1.697 61 .095
Equal variances not
assumed

1.633 36.317 .111
Student
Engagement
Equal variances
assumed
.011 .917 2.049 61 .045
Equal variances not
assumed

2.063 40.853 .046

Research Question 5 – Does teacher self-efficacy of pre-service teacher candidates
differ by age or ethnicity?
Age. To determine whether the age of participants makes any difference in self-
efficacy a regression model was used to analyze data. Since age is an ordinal value,
researchers tried to seek an R Squared value that would warrant a linear relationship.
However, as seen in Table 21, there is no significant finding to show that age reflects a

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significant variation in self-efficacy or its subscales. According to the data in Table 21,
zero percent of the variance in self-efficacy is caused by age. To further test the
relationship between age and self-efficacy, a one way ANOVA was run to test for
significance. As seen in Table 22, the significance value is higher than p>0.05, thus
revealing no meaningful relationship.
This means that in both tests, the difference in self-efficacy, or its subscales
within the different ages of participants, did not approach significance. Students across all
age groups had similar self-efficacy scores. The ANOVA showed the mean scores
between all age groups were the same.
Table 21: Regression Model summary for self-efficacy predictors: (Constant), Age
R R
Square
Adj. R
Square
Std. Error Change Statistics
R Square
Change
F
Change
df1 df2 Sig. F
Change
Overall Self-
efficacy
.108 .012 -.004 1.02 .012 .726 1 61 .397
Classroom
Management
.145 .021 .005 1.20 .021 1.313 1 61 .256
Instructional
Strategies
.088 .008 -.009 1.06 .008 .472 1 61 .495
Student
Engagement
.058 .003 -.013 1.15 .003 .206 1 61 .651

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Table 22: One way ANOVA comparison of means for self-efficacy and Age.
Sum of Squares df Mean Square F Sig.
Overall SE
Between Groups .770 1 .770 .726 .397
Within Groups 64.698 61 1.061
Total 65.468 62
Classroom
Management
Between Groups 1.890 1 1.890 1.313 .256
Within Groups 87.855 61 1.440
Total 89.746 62
Instructional
Strategies
Between Groups .534 1 .534 .472 .495
Within Groups 69.029 61 1.132
Total 69.563 62
Student
Engagement
Between Groups .275 1 .275 .206 .651
Within Groups 81.474 61 1.336
Total 81.749 62

Ethnicity. In order to test the relationship between ethnicity and self-efficacy a
one way ANOVA was conducted. Ethnicity being a nominal value, an ANOVA test of
means would be appropriate to explore if there is any difference in self-efficacy between
each ethnic group for overall self-efficacy, classroom management, instructional
strategies, and student engagement. The following series of Tables 23-25 reveals that
there are no significant differences within, and between, ethnic groups for both overall
self-efficacy and its subscales. Table 25 continues with the descriptive statistics for each
ethnic group and the mean self-efficacy scores. As seen in that table 22 however, there

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were differences in self-efficacy scores within the groups although not statistically
significant.
This means that participants did not differ in overall self-efficacy, classroom
management, instructional strategies, or student engagement and ethnic grouping of pre-
service teacher candidates in the MAT @ USC program. In other words, ethnicity did not
play a significant role in the level of self-efficacy or its subgroups. One ethnic group did
not have a more positive self-efficacy than another ethnic group. Table 23 shows it was
evident that there were differences between the groups, though not statistically valuable.
Although there were no significant differences in self-efficacy among ethnic groups, the
differences among ethnic groups was marginally insignificant.
To further explore ethnicity, participants were force-coded into two groups: white
(1), and non-white (2). The results were then analyzed using an independent samples t-
test to compare the means of the two groups. The purpose in conducting this additional
test was to test significance using similar number of respondents. As seen in Table 25 the
results were the same as the ANOVA test of means. There was no significance in self-
efficacy between white respondents and non-white respondents. This means that both
groups had similar self-efficacy scores and that ethnicity did not account for any
difference in self-efficacy between the groups.

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Table 23: One-way ANOVA comparison of means for self-efficacy and Ethnicity.
Sum of Squares df Mean Square F Sig.
Overall SE
Between Groups 5.31 6 .88 .825 .555
Within Groups 60.15 56 1.07
Total 65.46 62
Classroom
Management
Between Groups 7.52 6 1.25 .854 .534
Within Groups 82.22 56 1.46
Total 89.74 62
Instructional
Strategies
Between Groups 4.13 6 .68 .589 .737
Within Groups 65.43 56 1.16
Total 69.56 62
Student
Engagement
Between Groups 9.02 6 1.50 1.158 .342
Within Groups 72.72 56 1.29
Total 81.74 62

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Table 24: Descriptive statistics of mean scores for self-efficacy and Ethnicity.
N Mean Std.
Deviation
Std. Error 95% Confidence Interval for Mean
Lower Bound Upper Bound
Overall SE
1 28 6.89 .95 .17 6.52 7.26
2 3 7.45 .63 .36 5.87 9.03
3 9 7.60 .73 .24 7.04 8.16
5 1 5.96 . . .
6 8 7.00 1.12 .39 6.06 7.93
7 10 7.06 1.51 .48 5.97 8.14
8 4 6.84 .60 .30 5.88 7.79
Total 63 7.04 1.02 .12 6.78 7.30
Classroom
Management
1 28 7.00 1.093 .20 6.57 7.42
2 3 7.66 .79 .45 5.69 9.63
3 9 7.88 .83 .27 7.24 8.53
5 1 6.37 . . . .
6 8 7.46 1.31 .46 6.36 8.56
7 10 7.03 1.83 .57 5.72 8.34
8 4 7.18 .52 .262 6.35 8.02
Total 63 7.22 1.20 .15 6.92 7.52
Instructional
Strategies
1 28 7.25 .92 .17 6.89 7.61
2 3 7.66 .90 .52 5.42 9.91
3 9 7.77 .97 .32 7.03 8.52
5 1 6.37 . .
6 8 7.12 1.32 .46 6.01 8.23
7 10 7.45 1.45 .46 6.40 8.49
8 4 7.00 .74 .37 5.81 8.18

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Table 24: (Continued)

Table 25: Independent samples t-test of means for white(1) and non-white(2) respondents
on self-efficacy.
Levene's Test for
Equality of Variances
t-test for Equality of Means
F Sig. t df Sig. (2-
tailed)
Overall SE
Equal variances assumed .702 .405 -1.034 61 .305
Equal variances not assumed -1.049 60.440 .298
Classroom
Management
Equal variances assumed .616 .435 -1.343 61 .184
Equal variances not assumed -1.366 60.643 .177

Total 63 7.33 1.05 .13 7.06 7.60
Student
Engagement
1 28 6.96 1.11 .21 6.53 7.40
2 3 7.66 .26 .15 7.02 8.31
3 9 7.81 .82 .27 7.18 8.45
5 1 5.500 . . . .
6 8 7.01 1.13 .40 6.06 7.96
7 10 7.30 1.58 .500 6.16 8.43
8 4 6.93 .83 .41 5.61 8.26
Total 63 7.15 1.14 .14 6.86 7.44

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Additional power analyses
Given the relatively small sample size obtained by the present study, a series of
post hoc power analyses were run to determine the observed power of the analysis and
the required sample size to find statistical significance given the observed parameters.
Examining overall self-efficacy. Given the relatively small observed effect size
of 0.17 and assuming an alpha value of 0.05, Power of 0.95, and a standard deviation of
25.34 (the standard deviation observed for overall self-efficacy), the analysis revealed
that a sample of 592 subjects would have been required to find statistical significance.
The observed power of the analysis ran was .18.
Examining student engagement self-efficacy. Given the relatively small
observed effect size of 0.17 and assuming an alpha value of 0.05, Power of 0.95, with a
standard deviation of 9.07 (the standard deviation observed for student engagement self-
efficacy), this analysis revealed that a sample of 576 subjects would have been required
to find statistical significance. The observed power of the analysis ran was .18.
Examining instructional practice self-efficacy. Given the relatively small
observed effect size of 0.15, and assuming an alpha value of 0.05, Power of 0.95, with a
standard deviation of 8.31 (the standard deviation observed for instructional practice self-
efficacy), this analysis revealed that a sample of 740 subjects would have been required
to find statistical significance. The observed power of the analysis ran was .15.
Examining classroom management self-efficacy. Given the relatively small
observed effect size of 0.24, and assuming an alpha value of 0.05, Power of 0.95, with a
standard deviation of 9.48 (the standard deviation observed for class management self-

82
efficacy), this analysis revealed that a sample of 304 subjects would have been required
to find statistical significance. The observed power of the analysis ran was .32.
Summary
This study investigated the relationship between self-efficacy development and
various demographics, as well as online versus on-campus program delivery. Further, the
study explored how the level of prior teaching experience affected self-efficacy
development between the two delivery methods. The overall findings of this study
revealed that the variables tested had no statistical relationship or predictive value.
However, it found that first generation college status did reveal a significant finding. This
means that pre-service teacher candidates who were the first in their families to attend
college felt more efficacious toward becoming teachers, providing classroom
management, instructional strategies, and engaging students.
As expected, the overall self-efficacy levels of participants in the online and on-
campus programs were similar. Further, the subscales of self-efficacy did not differ
between programs. However, contrary to expectations, the level of prior teaching
experience did not predict overall self-efficacy, or self-efficacy for the three subscales:
instructional practice, classroom management, and student engagement.
Additionally the data revealed that self-efficacy scores were similar between the
different demographics tested. For pre-service teacher candidates in the MAT @ USC
program, age, ethnicity, gender, or content area revealed no significant difference. The

83
only demographic with a significant score was first generation status. However, as
expected, there were observed differences in mean scores between demographics, but
they were not found to have significance.

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Chapter Five: Discussion
Albert Bandura’s (1977, 1986) early works on self-efficacy were developed from
his postulation that psychological changes can be achieved and mediated by cognitive
events which are induced and altered through effective mastery performance. He
forwarded the theoretical framework of self-efficacy with the idea that a person’s
expectation of success can determine how much effort they will expend, and how long
that effort will be sustained in the face of obstacles. Albert Bandura paved the way for
future decades of self-efficacy research spanning multiple disciplines.
This study examined the difference in self-efficacy development in pre-service
teachers participating in the MAT @ USC teacher preparation Master’s program. The
study explored demographic variables as well as the variable of prior experience and
program delivery in relation to self-efficacy development and three subscales of self-
efficacy; classroom management, student engagement, and instructional strategies.
Findings
Overall self-efficacy. One purpose of this study was to explore the overall self-
efficacy of pre-service teacher candidates in the MAT @ USC program. These students
were at the final stages of their teacher education program and have completed course
work and their student teaching practicum. The study also explored the subscales of
teaching self-efficacy, which were (1) a teacher’s ability to create classroom
management, (2) use instructional strategies, and (3) engage students. These three
subscales were measured, along with overall teacher self-efficacy, through a Likert type
scale and analyzed using SPSS statistical analysis software.

85
According to our analysis, the reported mean of self-efficacy and each of its
subscales for pre-service teacher candidates in the MAT @ USC program, was around
77% or and average of 7.0 out of 9.0 points. In other words, although students did not
record a perfect score, they did however remain in the upper 25% range. With an average
self-efficacy score of 77%, our analysis revealed that students in the MAT @ USC
program have an above average sense of efficacy.
Self-efficacy in student engagement, instructional strategies, and classroom
management. The self-efficacy scale used in this study included a subcategory, which
measured pre-service teachers self-efficacy in their ability to use innovative instructional
strategies. Results showed a slightly higher mean efficacy score for instructional
strategies than the overall efficacy mean. Although not statistically significant, the
slightly higher score may be seen as further support for the MAT program’s ability to
provide teacher candidates with higher efficacy in instructional strategies. Scientific
research findings previously discussed revealed a common thread between self-efficacy
and instructional strategies. Specifically, Guskey (1998, 1997) found that teacher beliefs
or self-efficacy were significantly related to their decision to implement innovative
practices in the classroom. Brouwers and Tomic (2000) added that these innovative
practices are an important indicator of a teacher’s level of efficacy. Through
understanding the benefits these other studies have set forth, our results may be seen as a
positive implication for the MAT @ USC program.
Further, similar results were reported for the subcategory of classroom
management and student engagement. Both subscales revealed a higher level of self-

86
efficacy than reported for overall self-efficacy. Students in the program come out with
more confidence in their ability to achieve positive academic outcomes through
management and engagement. Gibson and Dembo (1984) and Emmer and Hickman
(1991) both found connections between a teacher’s choice in classroom management
style and levels of self-efficacy. Teachers with lower efficacy levels tended to
concentrate more on behavior rules and external rewards rather than putting more effort
into teaching. As self-efficacy increases, so does a teachers ability to achieve positive
academic outcomes through persistence and higher motivation.
In sum, similar to our first finding, data results showed that students felt equally
confident in their ability to engage students in the classroom, create effective
instructional strategies, and manage students. It is important to remember that it is not the
actual ability of the participants to engage students, use effective instruction, or manage
students. Rather it is their levels of confidence, or self-efficacy in their ability to problem-
solve and face challenges with a belief that they are capable of executing these tasks once
they are in the classroom. Finding the level of self-efficacy in all three subcategories is a
key benefit of this study for USC because administrators of the program can better
understand how well pre-service teachers feel prepared upon leaving the program. It is a
valuable starting point in which decisions can be made for improvement.
Self-efficacy and First Generation status. In addition to the original goals of
this study, an addendum was added after the first run of the data to try and see if we could
add findings based on demographic information. A series of tests were used to compare
gender, content area, first generation college status, age, and ethnicity. Of all these

87
demographic variables, the only one that revealed significance was that of first generation
status. Interestingly, whether or not the pre-service teacher candidate was the first person
in his or her family to attend college made a difference in their self-efficacy score. It was
found that students who were in the first generation of college students in their families
had higher self-efficacy than those whose parents already attended college before them.
According to the actual self-efficacy mean scores, first generation students scored higher
than non-first generation students in overall self-efficacy as well as in all three subscales
of classroom management, instructional strategies, and student engagement. However,
significance was only found with overall self-efficacy, classroom management, and
student engagement. Interestingly, instructional strategies was the only category that
there was not a significant difference.
One reason why this finding is so interesting is because it was the only one of the
five demographics tested that revealed any significance. The other variables such as age,
ethnicity, content area, and gender did not come close to revealing any difference
between the groups. When examining these demographics, first generation status is the
only demographic that is more socially oriented rather than physically oriented. Meaning
the motivational constructs behind choice can take affect in first generation status pre-
service teachers. To expound, these students are the first in their families to go to college
meaning they are breaking the social limits of previous generations, experiencing college
without parents who can push them past a zone of proximal development, and may have
different reasons for the college choices they make.

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One possible explanation for the difference in self-efficacy for first generation
college students may be their level of confidence in their practical ability rather than
academic ability. This study revealed first generation candidates to have a difference in
self-efficacy related to their ability to manage classrooms, engage students, and overall
self-efficacy, but not in instructional practices; which is seen as more academically
charged and related to coursework. This suggest these students have more confidence in
the application of the practice of teaching.
In addition, students who go to college before parents attend with different
motivations and backgrounds than students whose parents were able to share their college
experience with their children. Researcher Mayes (2008) conducted a study that showed
first generation students are motivated by a different set of goals and a different set of
limitations. Some of these goals included finishings college faster with a more career
centered motivation. Also, Kohler, Munz, and Trares (2008) found that first generation
students view education with a higher importance factor and lower satisfaction factor.
Meaning, completing college and gaining an education was more important than going to
college for the “fun” aspect. It was more important for students to meet their goals of
attending college rather than meeting seeing college as a goal from a secondary source
like parents.
One study conducted revealed similar results. Researchers, Phinney and Haas
(2002) conducted a study with first generation college students and found that successful
and unsuccessful students did not differ within all demographics. Rather, self-efficacy
was the only factor found to be different in first generation college students. However,

89
contrary to our findings, Chan (1996) conducted a study that revealed first generation
students had significantly lower academic self-efficacy than students with parents who
attended college. Williams and Hellman (2004) recorded a study where first generation
students displayed lower levels of self-regulation and self-efficacy with learner choice.
Wang and Castaneda-Sound (2008) also found lower levels of academic self-efficacy
with first generation students. All these studies suggest there exists a negative
relationship between self-efficacy and first generation college status; which is contrary to
this study.
Self-efficacy and program delivery. One of the original purposes of this study
was to examine the relationships that existed between self-efficacy and program delivery.
Due to unexpected sampling and respondent issues, the results of these tests have been
found to be unvaluable. However, since program delivery was a focal point of the study,
researchers have decided to reveal the findings for observational value in this section of
the study. This is because of the many researchers whose studies have shown that there is
specific research needed to explore self-efficacy between delivery methods and teacher
education programs (Barbera, 2004; Barbour & Reeves, 2009: Rice, 2006; Singh & Pan,
2004). According to our research findings, there was no difference in the overall level of
self-efficacy for students in the on-campus and online cohort. We purport that students
completing coursework from both cohorts felt they were equally confident in their ability
to become successful classroom teachers. This finding can be seen as an optimistic result
for USC’s Rossier School of Education because it underscores the effectiveness of both
delivery modes the Rossier School of Education uses. In essence, had these findings been

90
valuable, we might be able to say that program delivery methods do not affect students’
self-efficacy differently nor do they affect self-efficacy negatively and that both programs
appear to equally provide learning experiences that equip pre-service teachers with
similar levels of self-efficacy.
Some previously research, however, shows that self-efficacy actually does have a
significant difference between delivery methods. Hanson (2008) showed that online
learning can actually increase satisfaction and self-efficacy. Kitsantas and Chow (2007)
as well as So and Brush (2006) revealed that students preferred online delivery with a
social presence over traditional delivery methods because they found it more effective in
seeking help. These studies suggest that our findings should have revealed a difference in
self-efficacy between the two delivery modes. That would have been nice!
Self-efficacy and teaching experience. Another purpose of this study was to
explore the relationship between previous teaching experience and self-efficacy. This
study found no significant difference in self-efficacy development based on previous
teaching experience. Further, data revealed that prior experience within program delivery
(online or face-to-face) did not significantly affect self-efficacy. These findings suggest
teaching experience to be less meaningful as an advantage in self-efficacy development.
These findings were unexpected due to opposite results found in many previous
studies on teacher experience and self-efficacy. Those studies indicated experience to
account for a more significant difference in self-efficacy development (Darling-
Hammond, Chung, & Frelow, 2002; Prieto, Altmaier, 2008). These studies also
suggested that the more prior experience one had in the classroom, the more confidence

91
one felt upon entering the classroom, which affected their teacher practices. Based on
this, it would be expected that the level of efficacy for students with more experience
should be higher or at least different than those with less or no experience.
Bandura (1977, 1986, 1995) suggested that major sources of self-efficacy
development are mastery and vicarious experiences. Bandura (1995) and Posanski (2002)
suggested that either direct experiences or vicarious experiences (or both) can be sources
of efficacy development. Milner (2002) conducted a study that revealed prior teaching
experience to be the most significant factor in developing self-efficacy. In addition, Hoy
and Spero (2005) conducted a longitudinal study following pre-service teacher candidates
through their student teaching and induction years. They found that the having mastery
experiences in teaching was the most influential source of efficacy development.
Tschanned-Moran and Hoy (2005) revealed that even vicarious experiences accounted
for significant increases in novice teachers’ self-efficacy.
In sum, final results of this completed study reveal the level of self-efficacy in
students from MAT @ USC program along with the level of self-efficacy in all three
subscales. Also, first generation college status’ of pre-service teachers is the only
demographic that revealed a significant difference in self-efficacy scores. When looking
further into the subscales of student engagement, and classroom management, similar
results were found. Finally, the amount of prior experience students came into the
program with did not affect self-efficacy differently or between the two cohorts. These
findings are positive outcomes for the MAT @ USC teacher education program because
it reveals information about their newly implemented program.

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Implications
MAT @ USC. The findings of this study are most meaningful for administrators
of the MAT @ USC program. This is the first time the Rossier School of Education is
providing an online Masters and teacher credentialing program. Because of this, there
have been many new changes implemented in course work, and requirements for the
program. Therefore, it is imperative that information regarding its effectiveness be
provided so that they can change and improve the program based on the results. As
reported, self-efficacy of students is at a 77%. This leaves room for administrators to find
ways to increase self-efficacy of future students in the MAT @ USC program.
Since self-efficacy of first generation candidates was found to be significantly
higher than students whose parents attended college, MAT @ USC can focus attention
toward both attracting first generation students into their program and structuring their
program that would promote more growth for that population. Emphasis in the
recruitment phase of the program can be given to areas, and populations where there are
more possibilities to find applicants who are highly qualified and first time college
attendees. This can be in urban areas, or certain socio-economically challenged locations.
MAT @ USC is dedicated to finding students from urban areas to promote educational
changes in these communities. One step toward meeting this goal can be to increase
attention toward students who would be the first in their families to attend college. As a
result, these pre-service teacher candidates can re-enter their communities with high
teaching self-efficacy essentially achieving higher student achievement.

93
Pre-service teacher candidates. For potential students, it is beneficial to know
the statistics behind the program they are applying to. With an understanding about the
connection between self-efficacy and future teacher effectiveness, students will want to
apply for colleges that can promote the highest sense of efficacy in their candidates.
Students attending the MAT @ USC program can be assured that they will be able to
develop a sense of teaching self-efficacy that will lead them to become better future
teachers. The findings of this study can be important information in the decision making
process, which can include fit, resources and services, and learning outcomes.
Researchers. There is limited research in the area of self-efficacy and first
generation status. One implication for researchers is that this opens the door for further
research to explore the possibility of finding these same results in other disciplines and
programs. In addition, researchers can explore the specific factors about first generation
students that aid in higher self-efficacy scores and find the factors that cause non-first
generation students to have lower self-efficacy scores. Also, it would be interesting for
researchers to see if there are other teacher education programs, or other discipline areas
where first generation students have higher self-efficacy than their counterparts.
Finally, researchers may continue to explore the self-efficacy differences within
the other demographic, prior teaching experience, and program delivery variables that
were tested. Many researchers are still calling for more research regarding online
education (Barbera, 2004; Barbour & Reeves, 2009). There is much to learn if online
learning can meet the promise of being able to produce the same quality, integrity, and
outcomes as traditional settings given that students, providers, and resources are not all in

94
one place. With our findings about self-efficacy in relation to other variables resulting in
no statistical significance, it opens the door for further research to continue.
Social Significance of the Study
One of the main significant points of this study was the fact that our results
revealed first generation students have higher self-efficacy scores than students with
parents who also attended college. This finding is positive yet contrary to many studies
that show first generation students to have significantly lower self-efficacy than their
counterparts. This gives positive hope for students who are experiencing college as the
first in their family. It also provides confidence to parents who have children that are the
first to attend college.
In some social circles, there is a negative stigma that comes with first generation
college status. Some people believe that first generation students come with less social
capital, educational background, and coping abilities. This stigma may have stemmed
from historical experience and a systematic structure unfamiliar to certain socio-
economic status. However, our research shows that correct and thoughtful
implementation of teacher education can produce positive results in teacher candidate
self-efficacy, and that it can be offered through highly respected universities. It follows a
right direction toward changing stereotype and stigma behind first generation students.
Finally, if we accept the hypothesis that first generation students have higher self-
efficacy scores, then we can move toward encouraging more first generation candidates
to become perspective students. With an effort at accepting into college more students
who are first time attendees, we may be able to create pre-service teacher candidates that

95
can better serve their future students. This effort can include societal and parental
pressure for children who will be the first in their families to go to college. In addition,
this effort can be expanded into other disciplines and schools of study. The idea behind
our statistical results is that it creates a new target population or focus group for potential
students.
Limitations
The foremost limitation to this study was the small number of participants and
useful responses from MAT students. The study included a total of 77 participants. Out
of that 63 responses were used for analyzing data. Because of this small number, we had
to implement additional statistical test and power analysis. According to the tests run, we
would have needed a minimum of 160 respondents from both cohorts to skip those
additional tests. Although that number is ideal, it would have been impossible for us to
have that many participants simply because there were not even that many students
enrolled in both programs.
Another limitation to this study was the fact that participants were only surveyed
once at the end of their program. This gave us helpful information regarding their level of
self-efficacy upon graduating from the program, but did not enable us to look at how and
when that self-efficacy was developed. It could be posited that some of these students
came into the program with the same self-efficacy that they left with. Others may have
had tremendous growth, while others may have had their self-efficacy lowered over their
experiences in the program.

96
One of the more significant missing pieces of this study was the inability for us to
measure content knowledge. Although permission to collect this data was received by all
participants, it was found that the State of California’s Department of Education does not
release CSET and CBEST scores to anyone , including universities and institutions,
school districts, and even testers. This restriction made it implausible for us to determine
the level of content knowledge of respondents. Content knowledge is still very much an
important variable in measuring differences in self-efficacy. As discussed earlier, having
a conceptual understanding of content in depth and breadth is a determining factor in self-
efficacy. This is because self-efficacy changes as individuals perceive their own lack of
competency. Therefore, it would be desirable to analyze data that measures the different
levels of content proficiency and how this affects levels of self-efficacy.
Delimitations
The scope of this study was limited by our research questions to the area of self-
efficacy and the subcategories of self-efficacy; specifically efficacy in classroom
management, instructional strategies, and student engagement. Other options for the
study that were excluded was looking at the actual student achievement of the children
these pre-service teacher candidates taught. This might have given this study a more
broad understanding between the level of self-efficacy and how effective each student
teacher actually was. Other possible options that were taken out of this study due to the
bounds of our research questions were longitudinal options, and other motivational
constructs. Finally, each of our three subcategories for self-efficacy could have been
explored to include the actual practice and success of each in relation to each student

97
teacher. However, this study only examined the self-efficacy or belief each student
teacher had in their ability produce classroom management, instructional strategies, and
student engagement; rather than actual production of such.
It is meant that this study accomplishes its task of revealing new information
regarding the direct relationship between self-efficacy, and delivery method of teacher
education. The main purpose for keeping within these bounds and not expanding to
include a broader scope was because other research studies have already been done to
account for those informational needs. This study covered a specific area of self-efficacy
with a population specific to the MAT program at the University of Southern California.
Recommendations
The first recommendation for a future study would be to replicate it with a larger
pool of participants that included cohorts from different graduation dates, and over time.
This would remedy many of the limitations encountered during the data analysis phase of
this study. With a higher number of participants, results would show a more reliable
statistically significant difference. This would hopefully produce results in both program
delivery and demographics that are statistically significant.
A second recommendation for research would be to select participants from
multiple cohorts of online students and multiple cohorts of on-campus students along
with demographic information to get a clearer understanding of how self-efficacy is being
developed between program delivery for the MAT program as a whole, and between
student characteristics, as opposed to a comparison of just one cohort of MAT @ USC

98
students. A greater cross-section of groups across the nation and overseas would provide
a wider picture.
Also, a longitudinal study following these students’ self-efficacy development
over time would give researchers data to analyze the growth or decay of self-efficacy
over time. It is hoped that these recommendations would mean that the Rossier School of
Education might have a clearer picture of how effective they are implementing the online
program in comparison to the already established on-campus program to help improve
student learning. It would also provide data to show if the MAT @ USC program
improves over time.
Finally, effort toward finding factors that have affected the difference in self-
efficacy scores between first generation and non-first generation pre-service teacher
candidates must be employed. First, it is important to figure out why other college
generation students scored lower in self-efficacy so that we can improve self efficacy in
more students. Second, if we figure out what positive factors of first generation students
helped to increase their self-efficacy, researchers could make an effort to expand and
exploit those factors in hopes of creating higher self-efficacy for all teacher candidates.
Conclusion
The purpose of this study was to investigate the relationship between self-efficacy
and characteristics of pre-service teachers in the MAT @ USC program. Our goal was
not about whether or not pre-service teachers have the ability to create a successful
classroom, rather it is about how well the programs can prepare them to do so by creating
the positive levels of self-efficacy. We looked at demographic information such as age,

99
gender, content area, ethnicity, and first generation status, as well as students’ previous
teaching experience, and the delivery method of the program. With this information, we
hoped to find conclusions that would better help educators understand and improve the
learning opportunities for these candidates. Further, this information would help key
stakeholders better understand the extent to which prior experience, program delivery,
and demographics influence self-efficacy development.
This study is just the beginning of research that is needed to enhance learning
opportunities for the possibility of many more students interested in becoming teachers or
in other disciplines as well. Additionally, it has revealed the importance of first
generation college students and their ability to develop in the program as highly
efficacious. This opens the door for further research and emphasis into what we can do to
inspire more potential college goers who come from families that have not yet entered the
higher education arena. The desire was that this work can help to shed more light and
improve the MAT @ USC program for all pre-service teacher candidates.

100
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Appendix A: Survey

108
Question 25 (Program Delivery): Which MAT @ USC program are you participating in?
(1) On-campus Cohort
(2) Online Cohort

Question 27 (Prior Experience): What is the highest level of your prior educational
experience? (Please select one in which you had a least a full year of experience)
(1) Engaged – Full responsibility in the classroom
(2) Involved – Responsibility as a tutor, teaching assistant, or aid
(3) Uninvolved – Observations of classrooms or working indirectly with classroom
student environments
(4) None

109
Appendix B: Information Sheet
University of Southern California
Rossier School of Education

INFORMATION/FACTS SHEET FOR NON-MEDICAL RESEARCH

What is the relationship between program delivery, classroom experience, and content knowledge on pre-
service teachers’ self-efficacy?

PURPOSE OF THE STUDY
The purpose of this study is to investigate the relationship between self-efficacy of pre-service teachers,
and delivery method of the teacher education program. Does type of delivery predict self-efficacy of pre-
service teacher candidates? There is limited research that focuses specifically on the role of program
delivery and self-efficacy development of pre-service teacher candidates. Your participation is voluntary.

PARTICIPANT INVOLVEMENT
If you agree to participate, you will be asked to complete three self-efficacy surveys. The surveys will be
conducted online or in the classroom, depending upon the cohort.

Your test scores will also be accessed with your written permission.

It is hoped that this study will help us better understand your experience as a student teacher in the MAT
program.

PAYMENT/COMPENSATION FOR PARTICIPATION
You will not be paid for your participation.

CONFIDENTIALITY
Information obtained from the surveys and academic records will be kept in a secure location, electronic
data will be maintained on a password-protected computer. The information collected will be coded for
anonymity and no identifying information will be included in the final analysis.

INFORMED CONSENT
Please complete the following questions by circling the appropriate answer.
1. I agree to participate in this study. (YES/NO)
2. I agree to have my CSET/PRAXIS scores collected for this study. (AGREE/DISAGREE)
3. If you circled AGREE, please provide your USC student ID number.

INVESTIGATOR CONTACT INFORMATION

Keao Tano
(323) 708-2233
atano@usc.edu

110
Appendix C: Permissions

College of Education Phone 614-292-3774
29 West Woodruff Avenue www.coe.ohio-state.edu/ahoy FAX 614-292-7900
Columbus, Ohio 43210-1177 Hoy.17@osu.edu

Anita Woolfolk Hoy, Ph.D. Professor
Psychological Studies in Education

Dear

You have my permission to use the Teachers’ Sense of Efficacy Scale in your research. A copy of both
the long and short forms of the instrument as well as scoring instructions can be found at:

http://www.coe.ohio-state.edu/ahoy/researchinstruments.htm

Best wishes in your work,

Anita Woolfolk Hoy, Ph.D.
Professor

Abstract (if available)

Abstract This study examines the relationship between self-efficacy development with program delivery, and prior experience. The student demographic categories of age, ethnicity, gender, content area, and first generation status was also examined against level of self-efficacy. Sixty six students from the online and on-campus cohorts of the Masters of Arts in Teaching program at the University of Southern California were questioned using a 24 point Likert type self efficacy survey for pre-service teachers. Overall self- efficacy was broken down into three subscales: classroom management, innovative teaching practice, and student engagement). Results showed no significant difference in overall self-efficacy or the subscales between the online and on-campus cohorts, or prior experience. Further, the demographics of age, ethnicity, gender, and content area did not account for any variance in self-efficacy development. However, it was found that first generation college status of participants did have a significant difference in self-efficacy development. Students who were first in their families to attend college had a higher level of self-efficacy than those whose parents already attended college.

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Asset Metadata

Creator Tano, Aaron Keao (author)

Core Title What are the relationships among program delivery, classroom experience, content knowledge, and demographics on pre-service teachers' self-efficacy?

School Rossier School of Education

Degree Doctor of Education

Degree Program Education

Publication Date 11/21/2012

Defense Date 04/04/2012

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

Tag classroom management,content knowledge,delivery method,Education,Ethnicity,innovative teaching practice,OAI-PMH Harvest,online education,pre-service teachers,program delivery,self-efficacy,self-efficacy development,student engagement,Teacher education,teaching experience,Technology

Language English

Contributor Electronically uploaded by the author (provenance)

Advisor Hirabayashi, Kimberly (committee chair), Ragusa, Gisele (committee member), Sundt, Melora A. (committee member)

Creator Email keao.tano@gmail.com,keaokun@yahoo.com

Permanent Link (DOI) https://doi.org/10.25549/usctheses-c3-112986

Unique identifier UC11290256

Identifier usctheses-c3-112986 (legacy record id)

Legacy Identifier etd-TanoAaronK-1322.pdf

Dmrecord 112986

Document Type Dissertation

Rights Tano, Aaron Keao

Type texts

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

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

Repository Name University of Southern California Digital Library

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