Perception and use of instructional technology: teacher candidates as adopters of innovation

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PERCEPTION AND USE OF INSTRUCTIONAL TECHNOLOGY:
TEACHER CANDIDATES AS ADOPTERS OF INNOVATION

by

Han Nee Chong

________________________________________________________________

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

May 2012

Copyright 2012 Han Nee Chong

ii
ACKNOWLEDGEMENTS
Much credit for the completion of this dissertation goes to my parents, Chen
Wah and Ah Mooi, who believed that I can be the first Dr. Chong in our family, and
whose undying love and support kept me going through long nights of research,
writing, and re-writing. I dedicate this paper to Wenling Anela, my daughter, who
has been my inspiration for success for the past three years. I miss her everyday…
her infectious smiles, warm hugs and butterfly kisses.
I also credit the completion of my doctorate degree, and my new full time
position as an Instructional Designer & Technology Specialist at Hawaii Pacific
University to the outstanding faculty at USC. Dr. Dominic Brewer, my dissertation
chair, is an amazing mentor and visionary advisor. His perspectives on innovations
in education provided a framework for all our studies in ‘Team Dom II’, also known
as ‘Team Innovation’. I also wish to thank Drs. Melora Sundt and Lawrence Picus,
my dissertation committee members, whose constructive feedback helped strengthen
my paper. Special thanks go out to Dr. Dennis Hocevar, USC’s statistic guru who
guided me through my data analysis with patience and dedication. You are a real life
saver!
Last but not least, this dissertation could not have been completed without the
love and support of five extraordinary individuals: Mitzie Higa, a fellow USC cohort
member with a heart of gold, who had generously shared her home with me for four
months as we worked through the last chapters of our dissertations; Yevy Kopeleva,
Ed.D. Program Advisor extraordinaire, who helped me navigate through the

iii
dissertation submission process with patience and dedication; Kim Wah Ong, my
best friend, who had cheered me on through hours of late night, long distance phone
calls; Nathan Garrett, my confidant and partner-in-crime, whose love was a source of
constant comfort; and last but not least, Dave Koltermann, my brilliant mentee
whose deep insights in life had spurred many interesting conversations. Thank you
all for being a part of this epic journey!
“We’re born alone, we live alone, we die alone. Only through our love and
friendship can we create the illusion for the moment that we’re not alone.” - Orson
Welles.

iv
TABLE OF CONTENTS
Acknowledgements ii
List of Tables v
Abstract vi
Chapter One: Introduction 1
Chapter Two: Literature Review 21
Figure 1. Guiding model for incorporating technology into 51
preservice education (Kay, 2006)
Chapter Three: Methodology 55
Chapter Four: Analysis 67
Chapter Five: Discussion, Conclusion and Recommendation 106
References 121
Appendices 132
Appendix A: Survey Instrument 132
Appendix B: Interview Questions 138

v
LIST OF TABLES
Table 1: Relationship Between Research Questions and Literature Review 53
Table 2: Relationship Between Research Questions and Survey/Interview 61
Instrumentations
Table 3: Demographic Data of Survey Participants 70
Table 4: Comparison of Demographic Data: Survey Participants versus 71
Total Graduate Enrollment at the Online MAT@USC Program
in Fall 2011
Table 5: Rotated Component Matrix: Attitude and Belief 74
Table 6: Frequencies: Statistics for ‘Attitude’ and ‘Belief’ 75
Table 7: Adjusted Means for Age, Gender, Teaching Experiences and 80
Location, Organized by Variables within the Dispositions about
Technology: Attitude and Belief
Table 8: Frequencies: Perceived Barriers Ranked by Means in Descending 84
Order
Table 9: Rotated Component Matrix: Resources, Knowledge, Motivation, 85
Rewards
Table 10: Frequencies: Statistics for ‘Resources’, ‘Knowledge’, ‘Motivation’ 86
and ‘Rewards’
Table 11: Adjusted Means for Age, Gender, Teaching Experiences and 92
Location, Organized by Variables/Perceived Barriers: Resources,
Knowledge, Motivation, and Rewards
Table 12: Frequencies: Attributes of Innovative Teacher Education 94
Program
Table 13: Frequencies: Teacher Candidates’ Sense of Preparedness 95
Table 14: Rotated Component Matrix: Attributes, Comfort, Sense of 96
Preparedness

vi
ABSTRACT
Education has been slow to catch up on the use of instructional technology.
Despite the fact that billions of dollars have been spent in purchasing, equipping and
supporting technology, increased access has not translated into significant
educational gain (McGrail, 2005; Selfe, 1999). One of the reasons for this is because
teachers are not prepared to use/integrate technology in their classrooms and if they
are, they are using them to do low-level tasks that are not student-centered
(Christensen, 2008; Rosen, 2010).
This research adds to the literature by providing insights into teacher
candidates’ perceptions on the use of instructional technology, factors as well as
barriers for using instructional technology, and whether experiences with innovative
technology in teacher preparation program help prepare new teacher candidates to
integrate technology into their classrooms. The focus of the study was on graduate
students who were training to be teachers in the MAT@USC program, which has
won numerous awards for its innovative curriculum, delivered 100% online through
the use of cutting edge technology. To study these factors, this study employed a
mixed method study, using both surveys and interviews.
Overall, it was found that teacher candidates in the MAT@USC program
have positive attitudes towards technology, are highly receptive to the use of
technology in education, and have high levels of personal comfort with technology
prior to entering the program. Participants were motivated to use technology in
classroom, yet they perceived lack of resources as a top organizational barrier to

vii
integration of instructional technology. Findings on teacher candidates’ preparedness
and likelihood to adopt technology learned in their teacher education program are
also consistent with Rogers’ (1995) studies on the diffusion of innovation, which
identified five major attributes which affect adoption: relative advantage,
complexity, compatibility, observability, and trialability. Finally, the findings also
revealed that while majority of the participants perceived technology used in the
MAT@USC program as innovative and highly collaborative, they also voiced
concerns over technological issues encountered when using the online platform.
The findings from this study will help teacher educators develop innovative
teacher education programs, by keeping in mind key attributes that will affect the
adoption of innovation. In addition, teacher educators should also consider the
following factors when designing or incorporating technology education into teacher
education: ease of access to technology and support, modeling and authentic
teaching activities, and collaboration between mentor and peers. The findings also
highlighted the digital divide between low SES and middle-class school districts. For
administrators and policy makers, this has two implications: one, annual funding on
technology needs to be distributed equitably; two, school leaders need to re-examine
their budgets and allocation of funds to ensure that urban schools have sufficient
access to technology and technical support. Ultimately, it is recommended that future
studies on the perceptions and use of instructional technology by teachers and
teacher candidates be expanded for eventual generalizability. Future research should
also include detailed data on other factors such as technology support, frequency of

viii
use, and instructional technology preferences, which were not the focus of the
investigation of this study, and were not collected in this study.

1
CHAPTER ONE
INTRODUCTION
Few of the innovations tried over the ensuing 25 years have resulted in large-
scale systemic change in education. Despite the revolutions wrought by
technology in medicine, engineering, communications, and many other fields,
the classrooms, textbooks, and lectures of today are little different than those
of our parents. Yet today’s students use computers, mobile telephones, and
other portable technical devices regularly for almost every form of
communication except learning (National Science Foundation, 2008, p. 12).

Educational leaders, administrators, researchers, scholars and public policy
makers generally agreed that there is a growing need to integrate computer
technology into all facets of learning in the United States (Handler, 1992). There is
also a general consensus that today’s teachers are expected to be well-trained not
only in the areas of pedagogical and content knowledge, but also in integrating
technological knowledge into instruction and delivery in order to impact student
learning outcomes (Mishra & Koehler, 2006). There are many reasons as to why
there is a growing and urgent need for teachers to be prepared to integrate
technology into classrooms and instruction.
First, despite the fact that today’s learners are tech-savvy and they learn
differently from the previous generations, classroom setting and instructional
delivery methods have not changed much over the years (Rosen, 2010). Coined as
the iGeneration by Rosen (2010), research indicated that the children and teens
currently in elementary schools, middle schools and high were born surrounded by
technology and that they grew up immersed in information and communication
technology – accessing information, entertainment, and communication constantly

2
on electronic media such as mobile phones, iPads, laptops and personal computers.
Furthermore, these children and teens are also reported to be multitaskers, social
networkers, electronic communicators and the first to embrace the latest technologies
offered in the market (Rosen, 2010). Therefore, teachers need to develop new
educational strategies by integrating technologies into classroom instruction and
delivery, in order to meet the learning styles and educational needs of these children
and teens (Ziegler, 2007).
Secondly, teachers as shapers of tomorrow’s minds need to prepare their
students for the role technology will play in their lives. In order to meet the complex,
evolving, global challenges of the 21
st
century, teachers need to prepare their
students to be able to think critically, solve problems, collaborate with others,
communicate, use various technologies, take initiatives, and bring diverse
perspectives into their learning environment (National Science Foundation, 2008).
To keep pace with scientific advances and to be successful in the global workplace,
today’s students need to be especially well trained in the areas of science,
technology, engineering, and mathematics (STEM). Moreover, research shows that
there is a shortage of U.S. labor to fill STEM jobs because the workforce is not well
prepared in these areas (George, Neale, Horne, & Malcom, 2001).
Thirdly, while technology cannot solve all of the educational challenges and
crises that we currently face, it has the potential to improve access to education,
promote public understanding, and strengthen learning in classrooms and beyond
(National Science Foundation, 2008). For example, Becker (2000) suggests that

3
computers serve as a “valuable and well-functioning instructional tool” (p. 29) in
schools and classrooms in which teachers: (a) have convenient access, (b) are
adequately prepared, (c) have some freedom in the curriculum, and (d) hold personal
beliefs aligned with a constructivist pedagogy. The perception that computer
technology has extensive pedagogical affordances and great potential for
transforming the teaching and learning environment when used effectively is also
shared by many education leaders (U.S. DOE, 2003). Recent legislation and policy
statements by the U.S. department of education indicated a firm commitment to
support the expansion and use of computers in K-12 classrooms (Ertmer, 2005).
Some examples included the adoption of standards for technology use by
administrators, teachers, and students (International Society for Technology in
Education, 2003); increased use of block scheduling at the high schools which allows
for longer class periods (American Federation of Teachers, 1999); and provisions
within the No Child Left Behind Act to ensure that teachers can integrate technology
into the curriculum for the purposes of improving student achievement (U.S. DOE,
2001).
Because the impact of computers and other technology on all aspects of our
lives will most likely continue to increase over time and billions of dollars have been
invested for the acquisition of computer technology, it is important to pose the
question of whether or not teachers are being prepared in their teacher education
programs to integrate computer technology into their teaching. This study explored
the perceptions of teacher candidates on the use of computer technology in

4
classrooms, innovation in their teacher education programs, and whether they
perceive the teacher education program that they went through prepared them to use
computer technology effectively in their own classrooms and instruction.

Background of the Problem
Although many initiatives have been undertaken to address the state of
education in the United States over the years, academic gains have been slow and the
state of public education has changed little since the U.S. Department of Education
report, A Nation at Risk, stirred the country to action over twenty-five years ago. In
President Bill Clinton’s 1996 State of the Union Address, Clinton called for modern
computers and learning devices to be made available to all students, classrooms be
connected to one another and to the real world, making educational software an
integral part of the curriculum, and having teachers ready to use and teach with
technology (http://clinton2.nara.gov/WH/New/other/sotu.html). A decade later,
schools in the United States are well equipped with computers, yet, classrooms look
largely the same as they did before the personal computer revolution, and the
teaching and learning processes are similar to what they were in the days before the
computers (Christensen, 2008).
Market Data Retrieval (MDR, 2002) reported that schools across the United
States currently have an average student-computer ratio of 4:1, with 98% of schools
and 77% of classrooms connected to the Internet. Recent demographic data from the
Integrated Studies of Educational Technology (ISET; U.S. Department of Education

5
[DOE], 2003) also revealed that 81% of teachers have either moderate or high levels
of access to instructional computers. However, despite increased access to
technology at schools, a survey by the National Center for Education Statistics
reported that only 20% of the current public school teachers feel comfortable using
technology in their teaching (Rosenthal, 1999). Although studies have shown that
technology use in classrooms has increased across the nation, in large part due to
increased access and skill as well as favorable policies for instructional technologies,
many teachers are still using computers for low-level tasks such as word processing
and searching information on the Internet (Barron, Kemker, Harmes, & Kalaydjian,
2003).
Despite the growing need for technology training, there is little evidence that
typical teacher education programs are permeated with opportunities to work with
technology (Handler, 1993). Formal technology preparation within teacher
education, such as dedicated courses in instructional technology, could be found in
some, but not all teacher education programs. Hence, while some teachers may have
taken either a required or elective course related to instructional technology during
their teacher education programs, others may not. Preparing teacher candidates to use
instructional technology has gained significant attention by national educational
associations, including the National Council for Accreditation of Teacher Education
(NCATE) and the American Association of Colleges for Teacher Education
(AACTE), and national technology organizations and international societies, such as

6
the National Science Foundation, and International Society for Technology in
Education (ISTE).

Statement of the Problem
As new technologies proliferate in society, so too does the urgency to
integrate computer technology into students’ educational experiences (Wiske, 2004).
Despite the fact that billions of dollars have been spent in purchasing, equipping, and
supporting the technology, the use of computer technology as instructional
technologies has not had a significant impact on teaching and learning in K-12
schools in the U.S. (Norris, Sullivan, Poirot, & Soloway, 2003). The biggest
concerns remain that while many classrooms in the United States have been
equipped with new technologies such as computers, the Internet, digital videos, and
other software programs, improved access has not translated into significant
educational gains (McGrail, 2005; Selfe, 1999).
There are many studies that explore the use of technology in education and its
impact on educational gains (Neuman, 1990; Reiser, 2001; Labbo, 2005; McGrail,
2005). Consequently, there are also many theories about why increased access to
technology has not resulted in proportionate educational gains; one of the reasons is
that teachers are not prepared to use these technology in their classroom and if they
are, they are using them to do low-level tasks that are not student-centered
(Christensen, 2008; Rosen, 2010). In order to dramatically change the way teachers

7
teach and the way technology is being used in education, Christensen (2008)
suggests that the current education system needs a ‘disruptive innovation’.

Need for Innovation in Education
In President Barack Obama’s 2011 State of the Union Address, the 44
th

President of the United States addressed the need for innovation in terms of
education and other sectors. According to Obama, innovation in research, education
and infrastructure would be key to keeping the United States competitive with
countries like China and India (http://www.whitehouse.gov/the-press-
office/2011/01/25/remarks-president-state-union-address). Innovation is widely
perceived as a source of competitive advantage for efficiency, and even for survival,
especially under the conditions of increased global competition, rapid technological
development, volatile market conditions and continuous customer demand for
quality services (Ekvall & Arvonen, 1994; Howell & Higgins, 1990; Tushman &
O’Reilly, 2002; Damanpour & Schneider, 2006). In both the academic and private
sector, innovation and rapid development of technology have provided opportunities
for organizations to create new products, transform their production processes, and
conduct businesses in new ways (Borins, 2002).
According to Christensen (2008), most schools employ the use of computer
technology in classrooms as a sustaining innovation – one that fits the processes,
values and economic models of the existing organization. In other words, computer
technologies are used to aid existing ways of teaching and learning, which

8
Christensen argued, will only marginally improve the way teachers already teach.
Furthermore, the attempt to implement computer technology in this manner will not
allow schools to migrate to a student-centric classroom, which will allow students to
learn in ways that correspond with how their brains are wired to learn (Christensen,
2008). In order for computer technology to transform teaching and learning, they
need to be integrated in the classroom with the intention of disrupting and
fundamentally altering current instructional environment, so that teaching and
learning occur differently than before the technology was introduced (Neuman,
1990).

Teachers as Adopters of Innovation
Although the importance of training for teachers is emphasized, teachers are
not passive recipients of innovations (Greenhalgh et al., 2004). When presented with
choices on whether to use and integrate instructional technology in their own
classrooms, teachers may or may not adopt the innovation. Four main elements that
may affect the patterns of teachers’ adoption of technology include: the innovation,
communication channels, time and the social system (Rogers, 1995). Teachers’
adoption patterns are also influenced by teachers’ knowledge and personal use of
computers, availability (or lack of) technical support and training, as well as support
by their peers (Jacobsen, 1998). The adoption process of innovation involves
complex interaction between the adopting institution, the user (teacher) system, and
the resource system (Hall, 1974). The presence of technical support and training

9
would be examples of resource system for teachers. In order for teachers to advance
to higher levels of technological use, their concerns during the preadoption stage and
early use need to be answered, most likely by the resource system at the institution
(Hall, 1974).

Innovative Teacher Education Programs
Teacher education programs play an integral role in equipping teacher
candidates with the skills, knowledge, motivation and support needed. Considering
that teacher candidates graduating from teacher education programs will be teaching
in classrooms and impacting student learning outcomes for potentially the next 30
years, it is critical to ask if today’s teacher education programs are preparing new
teachers to incorporate the power of technology into their classrooms and instruction
(Handler, 1992).
The National Council for Accreditation of Teacher Education (NCATE) has
also emphasized the important role of teacher education programs in the preparation
of teacher candidates to integrate technology in their classrooms. In preparing
teachers to embrace the use of instructional technology in education, teacher
education institutions employ a continuum of strategies and curriculum, aimed at
preparing teacher candidates to practice instructional technology in classroom
settings (IRTC, 1998). In a detailed analysis of 68 studies examining the use of
technology in preservice education, Kay (2006) reported these strategies to include:
integrating technology in all courses, using multimedia, focusing on education

10
faculty, delivering a single technology course, modeling how to use technology,
collaboration among preservice teachers, mentor teachers, and faculty, practicing
technology in the field, offering mini-workshops, improving access to software,
hardware, and/or support, and focusing on mentor teachers. Kay (2006) concluded
that in order for teacher education strategies to have impact on teachers, the
following conditions must first be met: (1) access to software, hardware, and support
both during the teacher training program and in field placement, (2) regardless of
whether the strategy is single-course, workshop, integration, multi-media, or a
combination, every effort must be made to model and construct authentic teaching
activities, (3) collaboration among preservice teachers and mentor teachers is
important, without which, it seems unlikely that gains in attitude and ability will
translate to meaningful use of technology.
In four case studies of exemplary colleges of education, as identified by the
Office of Technology Assessment (OTA, U.S. Congress, 1995), Strudler & Wetzel
(1999) reported that these colleges used a combined strategy for introducing
technology to new teachers, which included stand-alone technology courses,
integration of technology in subject areas, and assimilation of technology in student
field experiences. National educational associations also suggested that instructional
technology integrated throughout the teacher education program was more effective
than a one-course educational technology approach (NCATE, 2001). While some
teacher education institutions required instructional technology coursework to be
embedded as part of their programs, many still did not (NCATE, 2001).

11
Purpose of the Study
The purpose of this study was threefold: (a) To explore teacher candidates’
attitude towards technology and perceived learning benefits afforded by technology;
(b) To explore factors perceived by teacher candidates as barriers to the adoption of
technology in teaching; (c) To explore whether certain attributes of an online teacher
education program affect teacher candidates’ sense of preparedness to adopt of
technology in teaching.
Since technology has extensive potential in the transformation of the learning
environment when integrated effectively, it is important to understand how to use
technology innovatively in order to transform teaching and create new opportunities
for learning (Angeli & Valanides, 2009). One way to prepare teachers to keep up
with the acquisition of new technological knowledge is to boost teachers’ knowledge
and skills as well as teachers’ self-efficacy through innovative teacher education
programs. In order for change to occur in the classroom, we need to examine factors
impacting teacher candidates’ decision to integrate instructional technology in their
classrooms (enablers as well as barriers to integration), attributes of technology
which affect teachers’ adoption of technology, and strategies used in teacher
education program to help prepare teacher candidates to use and integrate
technology.

12
Research Questions
The following research questions guided this study:
1. How do teacher candidates perceive the use of computer technology in
classrooms, and to what extent do their dispositions about technology
relate to their age, gender, teaching experience and location (in California
versus out of state)?
2. What factors are perceived by teacher candidates as barriers to the
adoption of technology in teaching (lack of knowledge, motivation,
resources, and rewards), and to what extent do they relate to teachers’
age, gender, teaching experience and location?
3. What attributes of an online teacher education program are perceived by
teacher candidates as innovative, and to what extent do these attributes
relate to their sense of preparedness to adopt technology upon graduation
from the program?

Significance of the Study
This study will provide insights into teacher candidates’ perceptions on the
use of instructional technology, factors as well as barriers for using instructional
technology, and whether experiences with innovative technology in their teacher
preparation program help teacher candidates feel prepared to integrate technology
into their classrooms. This study is particularly important in helping teacher
educators identify factors that affect teacher candidates’ perception of “feeling

13
prepared” to use technology, and present opportunities for teacher educators to
improve the program and student learning outcomes. Exploring attributes of an
online teacher education program which affect teacher candidates’ adoption of
innovation may help teacher education institutions identify areas for improvement
within online teacher education programs, and to expand the program to reach more
teachers around the nation. Findings about what works in an innovative teacher
education program can also serve as benchmarks for other institutions to follow the
best practices.
Innovation in teaching and learning with computer technology is most likely
to occur when we attempt to look beyond traditional notions of teaching and to
experiment with new forms of representation that are possible in multimedia,
interactive, socially constructed, networked spaces (Dobson, 2006, 2007). Along
these lines, Neuman (1990) suggests that computer technology is best integrated with
the intention to disrupt pre-conceived notions about classroom practice. According to
Neuman, this requires a process whereby technology integration disrupts existing
classroom practice in a way that fundamentally alters the instructional environment
so that teaching and learning occur differently than before the technology was
appropriated (p. 110). Identifying strategies used in teacher education programs
which teacher candidates perceive as useful in helping them learn present an
opportunity to inform the field as to how to prepare teachers to use technology more
effectively in classroom.

14
This study will focus on teacher candidates who are graduate students at a
single teacher education program, the MAT@USC program, which has won
numerous awards for its innovative curriculum, delivered 100% online through the
use of cutting edge technology (Roshell, 2010). The sample, population and program
will be discussed in detail in the methodology section.

Limitations, Delimitations
The following limitations and delimitations apply to the study:
1. Data will be collected from one teacher preparation program. Surveys
will be administered only to students of the MAT@USC online teacher
education program. Students at other teacher education programs will not
be included in the data analysis.
2. Findings may not be applicable or generalizable to other instructional
populations including students at other teacher preparation programs.
3. The study investigates only self-reported and perceived use of
instructional technology practices, overall attitude toward the use of
instructional technology in teacher preparation, attitudes toward the use
of instructional technology by teachers, and influential and inhibiting
factors as identified by the survey instrument. Detailed data on
technology support, frequency of use, and instructional technology
preferences are not the focus of this investigation.

15
4. The study was limited by the number of participants surveyed and the
amount of time allowed for the study.

Definition of Terms
For this study, the following is a definition of terms:
Access – This refers to the access that teachers have to software, hardware,
and support. For example, access to personal laptops and software, access to
computers in the classroom and in the field, and technological support. Without key
access elements to computers at the university or in the K-12 schools, it is difficult to
use the technology in an effective manner. It should be noted that although providing
software, hardware, and support is critical, increased access does not automatically
mean that technology will be used in a meaningful and effective manner.
Adoption of innovation – Individuals adopt different innovations and then
spread them at different rates to other individuals; some innovations are adopted
quickly, some never adopted, while others are adopted but subsequently abandoned
(Greenhalgh et al., 2004).
Barriers to the use of technology – Variables designated as negative
contributors to the utilization of educational technology in the development and
delivery of instruction (Beggs, 2000).
Computer-assisted instruction (CAI) – A common application of technology
focusing on drill and practice, it is also an effective use of technology that addresses

16
retention and remediation of information and promotes cognitive skill development
(Moursund & Bielefeldt, 1999).
Collaboration – A collaboration strategy involves establishing partnerships
among universities, colleges, and public schools to create technology-rich learning
experiences. This approach involves developing communities of practice, knowledge
repositories, expertise directories, peer and mentor assistance, and best practice
examples (Carroll et al., 2003).
Combination of strategies – Combination of strategies in teacher education
involves using two or more approaches to incorporating technology. For example,
modeling/integration, single-course/integration, and integration/community
strategies are combinations regularly observed in faculties of education (e.g., Collier
et al, 2004; Compton & Harwood, 2003).
Computer technology – For the purpose of this study, the term ‘computer
technology’ encompasses both the use of technology as instructional technology as
well as delivery technology.
Concerns Based Adoption Model (CBAM) – CBAM is a widely applied
theory and methodology for studying the process of implementing educational
change by teachers and by persons acting in change-facilitating roles. CBAM views
adoption as a developmental process involving complex interaction between an
adopting institution, a user system, and a resource system (Hall, 1974).

17
Delivery technology – Technology used in course instruction to provide
efficient and timely access to those methods and environments and influence the cost
and access of instruction and information (Clark, 1994).
Diffusion of innovation – The process by which an innovation is
communicated through certain channels over time among the members of a social
system (Rogers, 1995). The four main elements are the innovation, communication
channels, time, and the social system.
Distance learning – Instruction from a remote site, using telecourse,
computer, Internet, cable television, interactive television, or electronic
correspondence (Beggs, 2000).
Education faculty – Professors who teach in teacher education programs in
the school of education.
Innovation – Innovation is the implementation of an internally generated or
borrowed idea- whether pertaining to a product, device, system, process, policy,
program or service- that was new to the organization at the time of adoption
(Greenhalgh et al., 2005). For the purpose of this study, innovation refers to the use
of computer technology for instructional and delivery purposes in classrooms, and
diffusion is the extent to which all teachers have adopted this innovation.
Instructional technology – Instructional technology is the theory and practice
of design, development, utilization, management, and evaluation of processes and
resources to make learning more efficient (Association for Educational
Communications and Technology, AECT). Instructional technology attempts to

18
specify the need for and type of instructional methods required for the essential
psychological support of student learning (Clark, 1994).
Integrated strategy – An integrated strategy weaves the use of technology in
all preservice education courses instead of a single course that teaches basic
computer skills.
Mentor teachers – This is a collaborative approach whereby the preservice
teacher is guided by the mentor teacher in terms of pedagogy and "real world"
experience. The mentor teacher, in turn, is supported by the preservice teacher with
respect to the latest technology and software. This strategy, although used sparingly,
appears to have considerable potential for promoting effective use of technology in
the classroom, even though empirical evidence is limited (Kay, 2006).
Modeling – The modeling approach involves demonstrating how technology
can be used in the classroom and is often combined with an integrated strategy.
However, the emphasis with modeling is to provide preservice candidates with
concrete examples of how technology can be used in the classroom. The
ISTE/NCATE standards (2003) support the use of modeling as an effective approach
to teaching technology in preservice education.
Preservice teacher candidates – Individuals admitted to, or enrolled in,
programs for the intial or advanced preparation of teachers (NCATE, 2004b).
Single course – A stand-alone course devoted to teach a wide range of basic
computer skills to all students with the goal of providing a good overview of the use
of technology in teaching (McRobbie et al., 2000) and developing a strong

19
foundation of technology skills (Strudler et al., 2003). Disadvantages observed in
using this strategy include learning technology skills in isolation (Gunter, 2001) and
limited extension of skills in the field (Pope et al., 2002).
Teacher education program – A higher education program of study, typically
beginning at the sophomore level, delivered by an institution of higher education,
intended to graduate students with a bachelors degree and concurrently receiving an
initial state license to practice teaching at the Pre Kindergarten through 12
th
grade
levels (ISTE, 2002).
Technology integration – The incorporation of electronic media into
curriculum with the intent of supplementing instruction to accommodate various
learning styles (ISTE, 2002).
Technology literacy – Operational knowledge of technology use in society;
basic vocabulary and operation of computer/technology-based systems; and use of
the computer as a vehicle for problem solving (ISTE, 2002).

Organization of the Study
This dissertation explored the perceptions that teacher candidates have of
instructional technology as an innovation, identified influencing factors as well as
barriers for using instructional technology, and explored whether attributes of an
innovative online teacher education program could affect teacher candidates’
adoption of technology in teaching. Next, an overview of the background of the
problem and statement of the problem were discussed. This was followed by the

20
purpose of the study, the research questions, and significance of the study. A brief
description of the limitations, delimitations, and the definition of terms were also
provided at the end of the chapter.
Chapter 2 is a review of the literature that is relevant to this study. The
introduction provided a historical context of the use of educational technology in the
K-12 school system in the U.S. The chapter specifically addresses computer
technology as innovation in education, teachers as adopters of innovation, teacher
education for both new and experienced teachers, and strategies for integrating
technology in teacher education program.
Chapter 3 provides the methodology that was used in this study, which
includes the research design, the population and sampling measures, a discussion on
the instrument selection and development process, a review of the validity and
reliability aspects of the methods and the data collection and data analysis
procedures.

21
CHAPTER TWO
LITERATURE REVIEW
This chapter provides a review of the literature addressing the use of
computer technology as an innovation in classrooms, teachers as adopters of
innovation, innovative online teacher education programs as a diffusion of
innovation and the probable link between these factors. The following literature
review is divided into five sections to broadly explore the problem of teachers being
underprepared to integrate computer technology in classrooms: 1) history of the use
of computer technology in classrooms, 2) attributes of computer technology which
affect adoption rates, 3) adoption patterns of teachers who integrate computer
technology in classrooms, 4) factors which are perceived barriers to the adoption of
technology in classroom, and 5) effective strategies for integrating technology in
teacher education programs.
Current teacher educators are being challenged to find opportunities for their
teachers to develop both competence in, and confidence for, integrating technology
into their curricula (Ertmer et al., 2003). In this chapter, the work of scholars who
have studied the use of computer technology as innovation in classrooms, factors
affecting teachers’ decisions to adopt technology, and the role of teacher education
programs in facilitating the diffusion of innovation will be discussed. By
understanding the complex relationships between these different strands of
interdisciplinary literature, we can gain a better appreciation for how and why

22
teachers use technology in classroom instructions that could lead to improved student
learning outcomes.

History of the Use of Computer Technology in Classrooms
Clark (1994) suggested that the use of technology or media in classrooms is
largely divided into two categories: instructional technologies and delivery
technologies. Both categories of technologies make important but different
contributions to education. Instructional technology attempts to specify the need for
and type of instructional methods required for the essential psychological support of
student learning (Clark, 1994). Delivery technology, on the other hand, provides
efficient and timely access to those methods and environments and influence the cost
and access of instruction and information (Clark, 1994). For the purpose of this
study, the term ‘computer technology’ encompasses both the use of technology as
instructional technology as well as delivery technology.
Computers were first used in education and training in the 1950s; researchers
at IBM developed and designed one of the first computer-assisted instruction (CAI)
programs to be used in the public schools (Reiser, 2001). During the 1960s and early
1970s, CAI systems such as PLATO and TICCIT were developed and applied at
both public schools and university settings (Saettler, 1990). Despite all the efforts,
Pagliaro (1983) reported that CAI did not have much impact on student learning. In
the 1980s, the next technological innovation to catch the attention of educators was
the microcomputers that had become available to the general public (Reiser, 2001).

23
The microcomputers were relatively affordable, compact in size, and could perform
many of the functions that were previously done on bigger computers. By early
1983, it was estimated that computer technology was being used for instructional
purposes in more than 40% of elementary schools and more than 75% of secondary
schools in United States (Center for Social Organization of Schools, 1983).
In 1995, schools in the United States reported an average ratio of one
computer for every nine students (Reiser, 2001). However, a substantial number of
teachers reported little or no use of the computers for instructional purposes (Reiser,
2001). Furthermore, even when teachers reported using computers for instructional
purposes, they were generally used for low-level technology uses. For example, in
elementary schools, teachers reported that computers were mainly being used for
drill and practice, and in secondary schools, they were used primarily for teaching
computer-related skills such as word processing (Anderson & Ronnkvist, 1999;
Becker, 1998). Despite the uncertainty surrounding teachers’ use of technology for
instructional purposes, the amount of technology available in schools in the United
States continues to increase. Results from a national survey revealed that by 1998,
there was one computer for every six students and the percentage of schools that had
Internet access also increased from 50% in 1995 to 90% in 1998 (Reiser, 2001).
Today, many of the classrooms in the K-12 school settings in the United States are
equipped with technology such as flatscreen television, laptops for teachers, SMART
boards, ELMO, iPads and high speed Internet access.

24
Anderson and Ronnkvist (1999) noted that one persistent trend continues
throughout the history of computers as instructional technology: an increase number
of computers in schools does not automatically equal an increased use of computers
for instructional purposes. Survey results conducted by Michigan Virtual University
as part of a program to give every Michigan teacher a laptop computer indicated that
while most teachers reported knowing how to use the computers and the Internet to
search for information and send e-mails, only a small percentage of the teachers
(sometimes ten percent) knew how to use high-tech tools such as spreadsheets,
presentation software, or digital imaging to enhance their lessons (Newman, 2002).
In general, low-level technology uses tend to be associated with teacher-centered
practices while high-level uses tend to be associated with student-centered, or
constructivist practices (Becker, 1994; Becker & Riel, 1999).
Results from Integrated Studies of Educational Technology [ISET] (U.S.
DOE, 2003) showed that the computer-related activities in which teachers most often
engaged their students are generally low-level technology uses, which included
asking students to express themselves in writing on computers, doing research using
the Internet, using computers as a free-time or reward activity, and doing practice
drills. The trend that an increasing number of media in schools does not
automatically equals an increased use of technology for instructional purposes
suggests, in part, that it is not enough to buy and equip schools with computer
technologies.

25
There are many reasons why computer technology is not adopted by teachers
in classroom instructions. According to Greenhalgh et al. (2004), individuals adopt
different innovations and then spread them at different rates to other individuals.
Furthermore, some innovations are adopted quickly, some never adopted, while
others are adopted but subsequently abandoned (Greenhalgh et al., 2004). The next
section of literature review examines some attributes of innovation which affect
adoption rates, as perceived by potential users.

Attributes of Computer Technology which Affect Adoption Rates
The perceived attributes of an innovation are important parts of the
explanation of the rate of adoption of an innovation. Innovation characteristics
research describes the relationship between the attributes or characteristics of an
innovation and the adoption and implementation of that innovation (Rogers, 1995;
Tornatsky & Klein, 1982). For the purpose of this study, innovation refers to the use
of computer technology for instructional and delivery purposes in classrooms. This
section of the literature explored how perceived attributes of computer technology
influence its rate of adoption by individuals. In order to achieve this, the diffusion of
innovation literature was reviewed, focusing on a set of common attributes that could
be responsible for the largest rate of adoption. Specifically, this section focuses on
studies that have been done on how potential users’ perceptions of innovations
influence their adoption.

26
In determining what attributes to examine in this study, the works of
Tornatsky and Klein (1982), Davis (1989), and Rogers (1995) are reviewed. In a
review of 75 articles concerned with innovation characteristics and their relationship
to innovation adoption and implementation, Tornatsky and Klein (1982) suggested
that the following attributes had the most consistent significant relationships to
innovation adoption: relative advantage (innovations that offer better performances
or cost effectiveness), compatibility (innovations that are compatible with the values,
norms and needs of the user), and complexity (difficulty to adopt). Tornatsky and
Klein (1982) found that compatibility and relative advantage were both positively
related to adoption while complexity was negatively related to adoption.
In 1989, Davis developed another model of diffusion of innovation called the
Technology Acceptance Model (TAM), which included two constructs: perceived
usefulness and perceived ease of use. According to Davis (1989), perceived
usefulness refers to the degree to which individuals believe that using a particular
system would enhance their job performance, whereas, perceived ease of use refers
to the degree to which individuals believe that using a particular system would be
free from physical and mental efforts.
In 1995, Rogers conducted an extensive study encompassing thousands of
innovations studies, and from these studies, Rogers identified five antecedents
affecting the rate of adoption by individuals: relative advantage, complexity,
compatibility, observability, and trialability. Rogers (1995) argues that up to 87
percent of the variance in rate of adoption is explained by these five antecedents.

27
Two of the antecedents identified by Rogers (1995), relative advantage and
perceived complexity, are similar to the two constructs identified by Davis (1989),
perceived usefulness and ease of use. Both Rogers (1995) and Davis (1989)
concluded that perceived usefulness and ease of use are important factors in
determining acceptance and use of innovation.
Rogers’ (1995) studies on the diffusion of innovations is one of the most
cited reviews of perceived innovation attributes literature. The five antecedents of
innovations are believed to be most applicable for this study, as a variety of diffusion
studies had shown that they consistently influence adoption. The following sections
will discuss each of the five constructs as pertaining to the adoption of computer
technology by teachers in schools.

Relative Advantage
Innovations that offer performance effectiveness or cost-effectiveness are
more likely to be adopted and implemented than those that do not (Greenhalgh et al.,
2004). In essence, if potential users see no relative advantage in the innovation, they
generally will not consider it further (Rogers, 1995). Hence, in order for computer
technology to be adopted by teachers in classrooms, teachers need to perceive
computers as possessing relative advantage to traditional methods of instructions.
Hence, teachers’ perceptions of the usefulness and advantages of computer
technology for instructional purposes is an important attribute to measure for this
study.

28
If the innovation is relevant to the performance of the intended user’s work
and if it improves task performance, it will be adopted more easily (Yetton, Sharma,
& Southon, 1999). Interventions to enhance task relevance improve the chances of
successful adoption. If the innovation is feasible, workable, and easy to use, it will be
adopted more easily (Yetton, Sharma, & Southon, 1999). Interventions to improve
the feasibility and workability of innovations for key staff members and teams
improve the chances of successful adoption (Greenhalgh et al., 2004). When asked to
elaborate on the incentives for using technology, the highest rated incentives have to
do with providing enriched learning opportunities for students and the personal
gratification teachers get from learning new computer knowledge and skills
(Jacobsen, 1998).
Nevertheless, relative advantage alone does not guarantee widespread
adoption (Grimshaw et al, 2004). The negotiation among potential adopters, in which
their meaning is discussed, contested, and reframed, can increase or decrease the
innovation's perceived relative advantage (Ferlie et al., 2001). Becker (1994)
reported the importance of a social network of computer-using teachers for
sustaining the work of exemplary computer-using teachers. In another study,
Marcinkiewicz and Regstad (1996) found that the only significant predictor of
teachers' computer use was “subjective norms,” which is defined as expectations for
computer use by influential others in teachers’ lives; e.g., principals, colleagues,
students, and the profession.

29
In other words, change in teachers’ perceptions regarding the value of
computers was more likely to occur when teachers were socialized by their peers to
think differently about technology use (Ertmer, 2005). These studies suggest the
need to provide sufficient time for teachers to interact with and help each other, as
they explore new technologies, as well as new pedagogies.

Compatibility
Innovations that are compatible with the intended adopters’ values, norms
and perceived needs are more readily adopted (Ferlie et al., 2001; Rogers, 1995).
According to Becker and Riel (1999), teachers’ values, norms and beliefs are
continually shaped by their ongoing experiences as teachers, by the values and
opinions expressed by their peers, and by the expectations of influential others, all of
which are transmitted through formal and informal norms, rules, and procedures.
Hence, compatibility with organizational or professional norms, values, and ways of
working is an additional determinant of successful assimilation (Ferlie et al., 2001).
These studies point to the influence of the school environment on how
teachers' perceptions about technology use might be developed and implemented. A
study conducted by Windschitl and Sahl (2002) of three teachers learning how to use
technology in the school’s laptop program found that the ways in which the teachers
learned to integrate technology were strongly influenced by their interrelated belief
systems about learners in schools, about what the institution considered as 'good
teaching', and about the role of technology in students’ lives.

30
Zhao, Pugh, Sheldon, and Byers (2002) conducted another study to
empirically address the broad question of why teachers do not necessarily innovate
when given computers; they collected data from all 118 teachers or teacher teams
who were selected to receive a state technology innovation grant. From data
collected at three levels: 1) all grant recipients (surveys), 2) a subset of 32 (surveys
and interviews), and 3) a subset of 10 (surveys, interviews, and observations), Zhao
et al. (2002) reported similar findings in their study: An innovation is less likely to
be adopted if it deviates too much from the existing values, pedagogical beliefs, and
practices of the teachers and administrators in the school.

Complexity
Innovations that are perceived by key players as simple to use are more easily
adopted (Rogers, 1995). Perceived complexity can be reduced by practical
experience and demonstration (Plsek, 2003). If the innovation can be broken down
into more manageable parts and adopted incrementally, it will be more easily
adopted (Plsek, 2003; Rogers, 1995). If an innovation in an organizational setting has
few response barriers that must be overcome, it will be assimilated more easily
(Rogers, 1995). Hence, interventions to reduce the number and extent of such
response barriers will potentially improve the chances of successful adoption
(Greenhalgh et al., 2004).
Rogers (1995) argued that the perceived complexity of innovation also
depends on which five adopter categories along the continuum of innovativeness that

31
the adopters belong to: innovators, early adopters, early majority, late majority, and
laggards. In the context of adoption of technology by teachers in classrooms,
Geoghegan (1994) contrast early adopters (teachers generally self-sufficient and
interested in technology itself) who are more willing to take risks and experiment
with technology, with early majority teachers. Geoghegan (1994) reported that early
majority teachers are more concerned with the teaching and learning problems being
addressed than the technology used to address them, and hence, these teachers view
ease of use as critical. Early majority teachers want proven applications with a low
risk of failure. Furthermore, Greenhalgh (1995) suggested that what is perceived as
easy to use for an early adopter may be perceived as complex and difficult by a
laggard.
Although Rogers’ (1995) five adopter categories were widely cited in studies
of innovation, Greenhalgh et al. (2004) cautioned that the adopter categories could
have been misapplied in some instances to explain the nature of adoption, as the
adoption process is a complex process. Furthermore, there is little empirical support
for the adopter categories, which tend to stereotype and fail to acknowledge the
adopter as an actor who interacts purposefully and creatively with a complex
innovation (Greenhalgh et al., 2004).

Trialability
Innovations with which the intended users can experiment on a limited basis
are adopted and assimilated more easily (Plsek, 2003; Rogers, 1995). Findings

32
indicated that teachers tend to develop a level of personal expertise with a particular
computer technology before attempting to integrate it into their teaching, hence
being able to try out the technology themselves is a factor affecting teachers’ choice
to integrate it into their classroom instructions (Jacobsen, 1998). To some extent, all
teachers experience barriers when they attempt to integrate technology in their
teaching (Jacobsen, 1998).
The most common explanation for non-adoption was the perceived lack of
time to learn how to use computer technology as pedagogical tools as well as
learning new methods for teaching (Jacobsen, 1998). By providing trialability space
for teachers to learn how to use the innovation, teachers are encouraged to
experiment with technology so that they are comfortable adopting it in classrooms
(Plsek, 2003; Rogers, 1995). The triablility space could be provided by innovative
teacher education programs that encourage teachers to learn to use technology and
become comfortable with it, prior to actually teaching in a classroom setting.

Observability
If the benefits of an innovation are visible to intended adopters, it will be
adopted more easily (Denis et al., 2002). Some of the resistance to adopt computer
technology for instruction may be due to teachers’ beliefs about teaching, learning,
and technology (Ertmer, 2005). While some teachers may think of technology as an
innovative tool to facilitate student learning, others may think of it as not having any
impact on student learning. Clark (1994) argued that media or technology have “no

33
learning benefits” on student learning outcomes. In his earlier research, Clark (1983)
claimed, in part, that media are “mere vehicles that deliver instruction but do not
influence student achievement any more than the truck that delivers our groceries
causes changes in our nutrition” (1983, p. 445). Clark (1983) concluded, from meta-
analyses and review of other studies of media's influence on learning, that consistent
evidence is found for the generalization that there are no learning benefits to be
gained from employing any specific medium to deliver instruction.
However, Clark’s views on technology did not go unchallenged. Kozma
(1994) argued that in order for technology to have an impact on learning, the
relationship between media and learning needs to be forged first, taking into account
the interactive capability presented by media. Furthermore, technology has evolved
so much since Clark’s studies in 1983 and even in 1994. Technology today presents
higher levels of interactive capabilities as well as ease of use. Kozma (1994) argued
that if technology was conceptualized as “mere vehicles,” the potential relationship
between technology and learning will most likely not be understood nor forged.
Rather, to understand the contribution that media make to learning, technology
should be considered not in terms of their surface features, but in terms of their
cognitively relevant capabilities or attributes. Initiatives to make more visible the
benefits of an innovation increase the likelihood of their assimilation (Greenhalgh et
al., 2004).
Other factors identified by Greenhalgh et al. (2004) as being necessary to
explain the adoption and assimilation of complex innovations in organizations

34
include: fuzzy boundaries, risk, task issues, knowledge required to use it, and
augmentation/support. The notion of fuzzy boundaries refers to the distinctions
between “hard core” (elements of the innovation itself) and a “soft periphery” (the
organizational structures and systems required for the full implementation of the
innovation); the adaptiveness of the “soft periphery” is a key attribute of the
innovation and an important feature of system readiness (Denis et al., 2000). In other
words, organizations with adaptive organizational structures and systems are more
ready for innovation and change than systems that are rigid.
Greenhalgh et al. (2005) concluded that it is the interaction among the
innovation, the intended adopter(s), and a particular context that determines the
adoption rate. This conclusion is supported by Dearing and And (1994) who stated
that the tendency to conceptualize innovations as having attributes when judging
something new undermines the importance of human perception in the diffusion of
innovations. For example, what is perceived as easy for one person to use may be
perceived as exceedingly difficult for another. Hence, the decision to adopt an
innovation is based on individual perceptions of the innovation’s worth relative to
other ways of accomplishing the same goal (Dearing & And, 1994). The next section
of the literature reviews adoption patterns of technology by teachers.

35
Adoption Patterns of Teachers Who Integrate Computer Technology in
Classrooms
Teachers are adopters of innovation who ultimately decide whether to adopt
technology for their classroom instruction or not. If educators are to achieve
fundamental changes in classroom teaching practices, we need to examine teachers
themselves and the beliefs they hold about teaching, learning, and technology. As
Marcinkiewicz (1994) noted, “Full integration of computers into the educational
system is a distant goal unless there is reconciliation between teachers and
computers. To understand how to achieve integration, we need to study teachers and
what makes them use computers” (p. 234).
Why is the integration of technology for teaching appealing to some teachers
and not to others? According to Greenhalgh et al. (2004), people are not passive
recipients of innovations. Rather, they seek innovations, experiment with them,
evaluate them, find (or fail to find) meaning in them, develop feelings (positive or
negative) about them, challenge them, worry about them, complain about them,
“work around” them, gain experience with them, modify them to fit particular tasks,
and try to improve or redesign them – often through dialogue with other users.
Rogers (1995) defined an innovation as an idea, practice or object that is
perceived as new by the individual, and diffusion as the process by which an
innovation makes its way through a social system. For our purposes, the innovation
is computer technology for teaching and learning in classrooms, and diffusion is the
extent to which all teachers have adopted this innovation. Because individuals in a

36
social system do not adopt an innovation at the same time, innovativeness is the
degree to which an individual is relatively earlier in adopting new ideas than other
members of a system.
The process of adoptions for innovation in schools may be best explained
using the Concerns Based Adoption Model. The Concerns Based Adoption Model
(CBAM) is a widely applied theory and methodology for studying the process of
implementing educational change by teachers and by persons acting in change-
facilitating roles. CBAM views adoption as a developmental process involving
complex interaction between an adopting institution, a user system, and a resource
system (Hall, 1974). The resource system is usually a formal organization whose
expert knowledge of the innovation is available to the user system. For example,
teacher education programs, trainers of professional development programs, and
technical support could act as resource system for teachers. Hall (1974) posits that
the user system's advancement to higher levels of use and concern is a developmental
process. Hence, the intervention strategies of the resource system are aimed at
answering the user's concerns, arousing higher concerns, and thereby advancing the
level of use of the innovation (Hall, 1974).
CBAM provided three components: concerns in preadoption stage, concerns
during early use, and concerns in established users. During the preadoption stage,
important prerequisites for adoption are that the intended adopters are aware of the
innovation, have sufficient information about what it does and how to use it, and are
clear about how innovation would affect them personally (Hall & Hord, 1987).

37
During the early use stage, successful adoption is more likely if the intended
adopters have continuing access to information about what the innovation does and
to sufficient training and support on fitting the innovation to daily work (Hall &
Hord, 1987). Finally, for established users, successful adoption is more likely if
adequate feedback is provided to the intended adopters about the consequences of
adoption and if the intended adopters have sufficient opportunity, autonomy, and
support to adapt and refine the innovation to improve its fitness for purpose (Hall &
Hord, 1987; Rogers, 1995).
Research on the adoption process of innovation also suggested that potential
adopters who are motivated and able to use a particular innovation are more likely to
adopt it (Ferlie et al., 2001; Yetton, Sharma & Southon, 1999). In the context of this
study, it means that teachers who are motivated and able in terms of values, goals,
and skills, are more likely to adopt computer technology in classroom than their
counterparts who are not. In the next sections of the literature review, factors which
are perceived by teachers as enablers and barriers to the integration of technology in
classrooms will be discussed.

Factors Perceived as Barriers to the Adoption of Instructional Technology
Factors that are perceived as barriers are those that hinder or discourage the
use and integration of innovation. The following were cited as top reasons that
hinder successful implementation of computers at schools: lack of time, teaching
philosophy of school leaders and administrators about technology, technological skill

38
of faculty of school of education, fear of technological issues, lack of clear
understanding about how to integrate technology into teaching, and limited access to
technology (Kay, 2006). For this section of the literature review, these factors will be
broadly grouped into three categories as per the gap analysis model by Clark and
Estes (2008): teachers’ knowledge, teachers’ motivation, and
organizational/structural barriers.

Teachers’ Knowledge
The growing increase in teachers’ technical skills is insufficient to guarantee
the effective use of technology in the classroom (Carvin, 1999; Marcinkiewicz,
1994). In order to translate skills into practice, teachers need specific ideas about
how to use these skills to achieve meaningful learning outcomes under normal
classroom conditions. Traditionally, inservice technology training programs have
been software- rather than curriculum-based (Gilmore, 1995). Thus, teachers
completed technology courses still not knowing how to create or implement small or
whole-group activities that incorporated meaningful uses of technology (Moersch,
1995).
Unfortunately, this also has been true for most teacher education technology
courses (Moursund & Bielefeldt, 1999; Yildirim, 2000). As Dexter, Anderson, and
Becker (1999) explained, “For teachers to implement any new instructional strategy,
they must acquire new knowledge about it and then weave this together with the
demands of the curriculum, classroom management, and existing instructional skills”

39
(p. 223). Teachers need information about how, as well as why, to use technology in
meaningful ways. Lack of knowledge regarding either element can significantly
decrease the potential impact that these powerful resources might have on student
learning.
Angeli and Valanides (2009) suggested that teacher educators need to
explicitly teach how the unique features or capabilities of a tool for educational
technology can be used to transform specific content domain for specific learners,
and that teachers need to be explicitly taught about the interactions among
technology, pedagogy, content, and learners. The failure to adequately prepare
teachers to teach with technology can be attributed to various factors. For example,
the emphasis of educational technology courses on the acquisition of technical skills
is one major contributing factor.
As Becker and Riel (1999) explained, although computing skills are
important, skills-based courses are not enough for preparing teachers to teach with
technology, because they are usually taught in isolation from a subject-specific
context. Kenny (2002) stated that the lack of a subject-specific focus in many
technology preparation programs remains an issue, but even in those cases where
subject applications are discussed, matters of how technology interacts with the
content and content-specific pedagogy are not sufficiently explored. As a
consequence, the programs fail to adequately prepare teachers in the direction of
establishing pedagogical connections between the affordances of technology and the
teaching of a particular content domain.

40
Technology is often seen as a universally applicable skill; hence, the standard
approach in teacher training suggests that teachers simply need to be trained on how
to use technology (Mishra & Koehler, 2006). Consequently, standard techniques of
equipping teachers with knowledge on how to use technology often consist of
standalone technological courses as part of teachers’ certification program (Mishra &
Koehler, 2006). The assumption underlying this approach is a view of technology as
being a universally applicable skill, and that knowing a technology automatically
leads to good teaching with technology (Mishra & Koeher, 2006). Most scholars
agree that these methods of technology training for teachers will not produce deep
understanding that will help teachers become intelligent users of technology for
pedagogy (Brand, 1997; Mishra & Koehler, 2006). Moursund and Bielefeldt (1999)
found that traditional teacher preparation programs that teach technology in separate
computer literacy classes which focused on simple applications such as e-mail and
word processing, did not help new teachers fully understand the potential impact of
technology on learning. Instead, the Milken Exchange on Teacher Technology posits
that new teachers will attain technology proficiency only if technology is integrated
into all course work (Moursund & Bielefeldt, 1999).
As pre service teachers prepare to enter their own classrooms to teach, it is
equally important that they observe technology being used for instruction and see
their own professors modeling what they, as classroom teachers, will be expected to
do in the future (Clark, 1994). Hence, teacher education programs should model the
process of integrating computers into teaching if it were to prepare teachers to do the

41
same in their classrooms. Although the majority of teacher preparation programs
now require that students take three or more credit hours of technology instruction,
survey data suggested that most teacher education faculty still do not feel that
technology use is being effectively modeled for future teachers (Schrum, 1999).
In a study conducted to review the effectiveness of a three-year Preparing
Tomorrow's Teachers to Use Technology (PT3) grant funded by the U.S. Department
of Education, researchers reported that in order for teacher educators to model
appropriate examples to future teachers, they needed to see examples of how
technologies could be applied to their specific disciplines (Brzycki & Dudt, 2005).
As recently as 2002, researchers were still reporting on computer anxiety, a powerful
deterrent in the early stages of technology adoption (Christiansen & Knezek, 2002).
Even when anxiety is reduced, there is still a need to integrate technology into
teaching itself. Three years into the innovation process, Adams (2002) found that
25% of teacher educators surveyed were still at the earliest stages of technology
adoption, suggesting that the innovation takes well over three years. Based on
interviews of 60 faculty at three universities, Brzycki and Dudt (2005) reported that
although faculty were making progress, many of them in the teacher education
programs were still at an early stage of technology usage after three years of the
grant. A content analysis revealed that, of 261 citations of technology use, more than
a third involved fairly simple technologies using the Internet, presentation software,
and e-mail (Brzycki & Dudt, 2005). This implies that knowledge gaps may exist at

42
both pre service teacher and teacher educator levels because innovation takes time to
mature.

Teachers’ Motivation
Ertmer (2003) suggested that unless teachers believe that they are capable of
implementing them in the classroom, even the best ideas about technology use will
remain unused. In particular, teachers' beliefs about their ability to use computers in
instruction may be key, given the role self-efficacy is proposed to play in
determining behavior. Self-efficacy refers to personal beliefs about one's capability
to learn or perform actions at designated levels (Bandura, 1997). According to
Bandura, self-efficacy is based, not solely on the level of skill possessed by an
individual, but on judgments about what can be done with current skills. That is, self-
efficacy comprises beliefs about what one is capable of doing, not about whether one
knows what to do. As such, self-efficacy is thought to mediate the relationship
between skill and action. Therefore, without knowledge or skill, performance isn't
possible; yet without self-efficacy, performance may not be attempted. According to
Bandura, “beliefs of personal efficacy constitute the key factor of human agency” (p.
3). Thus, teachers who have high levels of efficacy for teaching with technology are
more likely to participate more eagerly, expend more effort, and persist longer on
technology-related tasks than teachers who have low levels of efficacy.
Darling-Hammond, Chung and Frelow (2002) found in their research that
teachers who are well prepared in teacher education programs demonstrated higher

43
sense of efficacy and confidence about their ability to achieve teaching goals. This
view is supported by Bandura (1986) who posits that the task of creating learning
environments conducive to development of cognitive skills rests heavily on the
talents and self-efficacy of teachers; teachers who have a high sense of efficacy
about their teaching capabilities can motivate their students and enhance their
cognitive development. Teachers operate collectively within an interactive social
system rather than as isolates. Darling-Hammond, Chung and Frelow (2002) state,
“Teachers’ sense of efficacy is related to behaviors that affect student learning, such
as teachers’ willingness to try new instructional techniques, teachers’ affect toward
students, and their persistence in trying to solve learning problems” (p. 296).
Despite the increased availability and support for classroom computer use,
relatively few teachers have fully integrated computers into their teaching (Becker,
2000; Marcinkiewicz, 1994). There is substantial evidence to suggest that teachers’
beliefs in their capacity to work effectively with technology, that is, their computer
self-efficacy, may be a significant factor in determining patterns of classroom
computer use (Albion, 1999; Oliver & Shapiro, 1993). For example, Honey and
Moeller (1990) reported that when computer anxiety was not a factor preventing
technology integration, the 20 elementary and secondary school teachers they
interviewed were able to successfully integrate technology within a constructivist,
student-centered approach. Results from previous studies on teachers' self-efficacy
beliefs provide sufficient reason to undertake further investigations in this area and

44
to consider approaches to teacher education and professional development that might
be effective in increasing teachers’ self-efficacy for teaching with technology.
The literature has established independent effects of both vicarious learning
experiences and goal setting on learners’ judgments of self-efficacy, yet little work
has been done to examine how these strategies might be combined to create even
more accurate and more robust judgments of efficacy. In 1992, Gist and Mitchell
identified three general strategies for enhancing self-efficacy beliefs. Of these three,
two related to vicarious learning and goal setting, respectively: providing
opportunities to observe experts’ practice and providing opportunities to address a
specific goal while resolving a particular teaching issue. Gist and Mitchell concluded
that these strategies contributed to building teachers’ confidence for achieving
effective teaching.
According to Neck and Manz (1992), when people rehearse a task mentally,
they can see themselves performing it and hence, are exposed to the positive effect of
modeling (i.e., learn through vicarious experiences). Furthermore, the intense
cognitive processing that occurs during mental practice can heighten awareness of
how to attain specific goals and hence increase goal commitment and task
performance. Based on these premises, it was hypothesized that vicarious learning
experiences and goal setting could be combined to achieve a significant effect on
learners’ self-efficacy beliefs and task performance.
Ertmer and Wang (2003) conducted a pilot study to explore how vicarious
learning experiences and goal setting influence preservice teachers’ self-efficacy for

45
integrating technology into the classroom. Twenty undergraduate students who were
enrolled in an introductory educational technology course at a large Mid-western
university participated and were assigned into four conditions (3 experimental and 1
control). Results showed significant treatment effects of vicarious experiences and
goal setting on the participants’ judgments of self-efficacy for technology
integration. A significant interaction effect was not observed, possibly due to small
sample sizes.
From a teacher educator’s perspective, the use of vicarious learning
experiences and the incorporation of learning goals can positively impact teachers’
self-efficacy beliefs for technology integration. Furthermore, this type of modeling
and goal setting may help preservice teachers develop a vision for what technology
integration looks like in real classrooms as well as strategies for implementing those
visions in their own classrooms. Thus, as future teachers develop clearer visions and
more powerful strategies for achieving them, meaningful technology use can come
closer to being the norm, rather than the exception, in K-12 classrooms.

Organizational/Structural Barriers
Organizational barriers that may affect teachers’ adoption of technology
include: school leadership, school scheduling, and school planning. Research has
shown that school leadership can hinder the integration of technology by teachers
(Fox & Henri, 2005). In a survey conducted with teachers in Hong Kong, a majority
of the teachers felt that their principals did not understand technology and how

46
technology can be used to shift pedagogy from more teacher-centered to learner-
centered activities. Consequently, the impact of technology on the teachers' practices
in the classroom was restricted. A rigid school schedule can also be a barrier
affecting the integration of technology. In a survey of more than 4,000 teachers in
over 1,100 schools in the United States, Becker (2000) found that most secondary
students have a continuous block of less than one hour's duration to do work in any
one class. Such a time limit constrains the variety of learning modalities that teachers
can design. Consequently, fewer teachers plan computer activities on a regular basis.
Finally, the lack of school planning with regard to technology use also hinders the
integration of technology in classroom. For example, a case study on a school in the
United Kingdom that made minimal use of technology revealed that one of the
reasons why administrators had decided to enter a technology integration project was
because the project was seen as a way of getting free Internet access for a year
(Lawson & Comber, 1999). The decision to adopt technology was not planned
properly and once the technology once was installed, the administrators left the
information technology department to its own devices during the project.
Consequently, the use of technology did not extend beyond that department.
In summary, teachers' reported uses of technology-related teaching practices
was influenced by their knowledge on how to use computer technology, self-efficacy
for teaching with computers, organizational barriers such as leadership, school
scheduling and planning, and the likelihood of those factors occurring in their

47
schools. The next section of the literature presents effective strategies for integrating
technology into teacher education programs.

Effective Strategies for Integrating Technology into Teacher Education
Programs
In a study that examined data from a 1998 survey of nearly 3000 beginning
teachers in New York City regarding their views of their preparation for teaching,
their beliefs and practice, and their plans to remain in teaching, Darling-Hammond,
Chung and Frelow (2002) found that teachers who were prepared in teacher
education programs felt significantly better prepared across most dimensions of
teaching than those who entered teaching through alternative programs or without
preparation. Their findings also showed that certified teachers perceived themselves
to be better prepared than non-certified teachers on every factor except preparation to
use technology; in fact, neither group felt well prepared to use technology (Darling-
Hammond, Chung & Frelow, 2002).
According to Darling-Hammond, Chung and Frelow (2002), teacher
education programs seem to be a logical place to start to help preservice teachers
become better prepared across most dimensions of teaching. A national survey of
U.S. schools, colleges, and departments of education conducted by the Miliken
Exchange and ISTE to determine how new teachers are being prepared to use
information technology in their work found that although faculty information
technology skills are generally comparable to the information technology skills of

48
the students they teach, most faculty do not model use of those information
technology skills in their own instructions (Moursund & Bielefeldt, 1999). Survey
findings also revealed that integration factor (actual use of information technology
during college training) was the best predictor of basic technology proficiency, and
that, in order to increase the technology proficiency of new teachers in K-12
classrooms, teacher educators need to increase the level of technology integration in
their own academic programs (Moursund & Bielefeldt, 1999).
A study by Handler (1993) examined the self-perceptions of teacher
education graduates, after their first year in the classroom. They were asked to
evaluate their preparation to use technology in an instructional setting as it was
provided by their preservice programs. A total of 133 education graduates responded
to a survey that had been designed to collect their perceptions of the purpose of
intentional preservice computer experiences, the value of these experiences to their
professional preparation, and the ways in which those teaching are currently using
computers in their classrooms (Handler, 1993). Based on the survey, the respondents
were classified into one of two groups: 1) teachers completing their first year in the
classroom who felt their program resulted in their feeling prepared to use computers
in their teaching, and 2) those who did not perceive themselves as being prepared.
Within the total group of respondents to the survey (n=122), 18.8% indicated feeling
prepared by their preservice program to use computers for instruction. Eleven of the
total group of respondents were not in teaching positions and may not have felt able
to respond to this question.

49
In the data analysis, Handler (1993) reported that age was not a significant
factor in discriminating between prepared and unprepared respondents. However,
several factors did emerge as significant factors that contribute to a feeling of
preparedness among the small group identified as feeling prepared to use computers
in their teaching: 1) the value of a separate course on the introduction to computers
in education, 2) the degree to which computers were used during the methods blocks,
3) observation of and use of computers during the student teaching field experience,
and 4) to some degree, these factors were influenced by personal comfort with the
technology prior to entering the program or taking the introductory course. Those
teachers who were included in the “Feeling Prepared” group were also those who
had most frequently seen the computer used during their methods classes. This
finding indicates the importance of and need for faculty modeling technology use in
methods classes so that students will be more likely to use this tool in their own
teaching (Handler, 1993). The importance of modeling was also supported by
Schunk (2000). Schunk (2000) suggested that models can provide observers with
information about how to enact meaningful technology use, as well as increase
observers' confidence for generating the same behaviors. Furthermore, providing
access to multiple models increases both the amount of information available about
how to accomplish the performance and the probability that observers will perceive
themselves as similar to at least one of the models, thus increasing their confidence
for also performing successfully (Schunk, 2000).

50
According to a review of 68 refereed journal articles that focused on
introducing technology to preservice teachers, Kay (2006) found that at least ten
strategies were used to teach technology to preservice teachers; these strategies
include integrating technology in all courses (44% of studies); using multimedia
(37%); focusing on education faculty (31%); delivering a single technology course
(29%); modeling how to use technology (27%); collaboration among preservice
teachers, mentor teachers, and faculty (25%); practicing technology in the field
(19%); offering mini-workshops (18%); improving access to software, hardware,
and/or support (14%); and focusing on mentor teachers (13%). Kay (2006)
concluded that in order for teacher education strategies to have impact on teachers,
certain conditions must first be met.
Kay’s (2006) guiding model for incorporating technology into preservice
education is represented by Figure 1. First, good access to software, hardware, and
support is necessary in the university classroom and in the field placement. If
teachers do not have adequate access in either area, it is unlikely that the other
strategies will work. Second, regardless of whether the strategy is single-course,
workshop, integration, multimedia-based, or a combination, it is important that every
effort be made to model and construct authentic teaching activities. Modeling,
especially, is regarded as a powerful method for increasing teachers' ideas about and
self-efficacy for technology integration (Schrum, 1999). Although a number of
leading organizations have strongly endorsed an integrated approach (e.g., Moursund
& Bielefeltdt, 1999, or ISTE/NCATE, 2003), the empirical evidence supporting one

51
strategy over another is lacking at this point. Third, collaboration among preservice
teachers, faculty, and mentor teachers is ideal; however, partnerships between
preservice and mentor teachers may work just as well. Without collaboration
involving the mentor teacher, it seems unlikely that gains in attitude and ability will
translate to meaningful use of technology.

Figure 1. Guiding model for incorporating technology into preservice education
(Kay, 2006)

52
Conclusions
In this chapter, we provided a review of the literature for this study, which
included the following sections: 1) history of the use of computer technology in
classrooms, 2) attributes of computer technology which affect adoption rates, 3)
adoption patterns of teachers who integrate computer technology in classrooms, 4)
factors which are perceived barriers to the adoption of technology in classroom, and
5) effective strategies for integrating technology in teacher education programs.
The existing research provides guidance on diffusion of innovation, use of
instructional technology in education, and strategies used in teacher education to
prepare teachers to use technology; however, few studies addressed whether teacher
candidates’ exposure to use of technology in innovative teacher education programs
influence their decision to adopt instructional technology in their own teaching.
Since much of the decision on whether to adopt technology or not in classroom rely
on teachers, if researchers are truly interested in understanding the reasons for
adoption/non adoption of the innovation, a good place to start would be to study the
attributes of innovative teacher education program that could influence teacher
candidates’ sense of preparedness to adopt instructional technology.
Table 1 presents a summary of the research questions for this study, and the
literature review sections related to each research question.

53

Table 1
Relationship Between Research Questions and Literature Review
Research Questions (RQs) Concepts/Variables identified in Literature Review
RQ1: How do teacher
candidates perceive the use of
computer technology in
classrooms, and to what extent
do their dispositions about
technology relate to their age,
gender, teaching experience and
location (in California versus
out of state)?
Attitude Towards Technology:
1) The highest rated incentives for using instructional
technologies were related to providing enriched learning
opportunities for students and personal gratification
teachers get from learning new computer knowledge and
skills (Jacobsen, 1998).
2) Teachers’ beliefs about teaching, learning and technology
may create resistance to adopt technology for instruction
(Ertmer, 2005). While some teachers may think of
technology as an innovative tool to facilitate student
learning, others may think of it as not having any impact on
student learning.
Perceived Learning Benefits:
1) Technology has “no learning benefits” on student learning
outcomes (Clark, 1994).
2) Technology may improve learning, given its interactive
capabilities (Kozma, 1994).
RQ2: What factors are
perceived by teacher candidates
as barriers to the adoption of
technology in teaching (lack of
knowledge, motivation,
resources, and rewards), and to
what extent do they relate to
teachers’ age, gender, teaching
experience and location?
An innovation is less likely to be adopted if it deviates too much
from the existing values, pedagogical beliefs, and practices of
the teachers and administrators at school (Zhao et al., 2002).
Enablers of integration:
1) Teachers sense of feeling “prepared” (Handler, 1993)
2) Good resource system (technical support, professional
development, leadership, etc.)
Barriers to integration:
1) Lack of time
2) Lack of technological skills
3) Fear of technological issues
4) Limited access to technology
5) Limited financial support/funding

54

Table 1, continued
Research Questions (RQs) Concepts/Variables identified in Literature Review
RQ3: What attributes of an
online teacher education
program are perceived by
teacher candidates as innovative,
and to what extent do these
attributes relate to their sense of
preparedness to adopt
technology upon graduation
from the program?
Attributes of innovation/technology (Rogers, 1995) which
affects adoption:
1) Relative advantage
2) Complexity
3) Compatibility
4) Observability
5) Trialability
Guiding model for incorporating technology into preservice
education (Kay, 2006):
1) Access
2) Modeling and authentic teaching activities
3) Collaboration (mentor teacher and peer support)
Factors contributing to a feeling of “preparedness” among
new teachers to use and integrate technology (Handler,
1993):
1) Value of separate course on introduction to computers in
education.
2) The degree to which computers were used during the
methods block.
3) Observation of and use of computers during student
teaching field experience.
4) Personal comfort with technology prior to entering the
program.

55
CHAPTER THREE
METHODOLOGY
This chapter will identify the location and setting for the research, identify
the research design, describe the development and implementation of
instrumentation used to collect data, identify data collection procedures used in the
study, and identify statistical treatments and procedures used to analyze collected
data.
The purpose of this study was to explore teachers candidates’ attitude
towards technology and perceived learning benefits afforded by technology, factors
perceived by teacher candidates as barriers to the adoption of technology in teaching,
and whether certain attributes of an online teacher education program affect teacher
candidates’ sense of preparedness to adopt of technology in teaching. Specific
research questions are:
1. How do teacher candidates perceive the use of computer technology in
classrooms, and to what extent do their dispositions about technology
relate to their age, gender, teaching experience and location (in California
versus out of state)?
2. What factors are perceived by teacher candidates as barriers to the
adoption of technology in teaching (lack of knowledge, motivation,
resources, and rewards), and to what extent do they relate to teachers’
age, gender, teaching experience and location?

56
3. What attributes of an online teacher education program are perceived by
teacher candidates as innovative, and to what extent do these attributes
relate to their sense of preparedness to adopt technology upon graduation
from the program?
The study was a mixed method study, using surveys and interviews. A cross-
sectional study was conducted using a one-time survey questionnaire, which was
sent to all students of the MAT@USC program. A follow-up interview invitation
was also sent out to a smaller sample, with students randomly selected from the
MAT@USC database. Participation was completely voluntary in both the survey and
interview and participants could stop at any time.

Sample and Population
This study focused on graduate students at the Rossier School of Education,
University of Southern California (USC) who were training to be teachers at the
MAT@USC teacher education program. USC is one of the leading private research
universities in the United States, located in Los Angeles, California. The
MAT@USC program is an “award winning” online teacher education program,
which has won numerous awards for its innovative curriculum, delivered 100%
online through the use of cutting edge technology (Roshell, 2010). Although some
students prefer a campus-based experience, many of today’s college students, who
are adult, working, part-time students, may need a more flexible model (Brewer &
Tierney, 2010).

57
To resolve the issue of space and to cater to nontraditional students who are
interested in pursuing a MAT degree to become teachers, USC Rossier School of
Education, through a partnership with a for-profit company 2Tor Inc., launched an
online Master of Arts in Teaching (MAT@USC) in 2009. Under this partnership, the
marketing, student recruitment, and technology support are provided by 2Tor, while
admissions, curriculum design, and instructional delivery are provided by USC.
The MAT@USC program was recently awarded the American Association of
Colleges for Teacher Education’s Best Practices Award for the Innovative Use of
Technology, which recognizes an innovative use of educational technology in a
school, college or department of education (Roshell, 2010). The MAT@USC
program is unique in that it is the first online degree of its kind to be offered at a
major research university. Since the launch of the program in June 2009, enrollment
at the program has grown rapidly across the nation from 144 students in the first
cohort approximately 400 students in May 2010 (Roshell, 2010). The online program
blends the sophistication of new technology with traditional hands-on, in-classroom
training for every student. Some of the advanced technology offered by the program
includes real-time webcam discussions, which allows students to have face-to-face
interaction with their professors and classmates. Instruction is provided by faculty
via video, PowerPoint and even animation, which students can easily access anytime
of the day. Students can also connect with their professors and classmates through
custom-designed social-networking tools that look and function like Facebook. In an
interview, Karen Gallagher, dean of the Rossier School of Education said that she

58
hopes that the MAT@USC program will produce tech-savvy graduates who know
how to use technology effectively and will use it to reinforce learning in their own
teaching (Roshell, 2010).

Instrumentation
Surveys
The surveys used are designed to capture both quantitative and qualitative
data (Appendix A). The recipients were identified via USC’s student database based
on their student status, and their e-mail addresses will be pulled directly from the
database so that the survey could be e-mailed to them. Invitations to participate in the
surveys were sent to all students in the MAT@USC student database and distributed
using Survey Monkey, an online survey software and questionnaire tool. After the
initial survey was sent, three e-mails reminding participants to respond were sent,
beginning after approximately one week.
Items in the survey gathered information about participants’ demographic
information (age, gender, teaching experiences, number of courses taken at the
MAT@USC program, and where they plan to teach upon graduation), attitude and
beliefs towards pedagogy and technology, perceived learning benefits from use of
computer technology in classroom, perceived barriers to integrating technology for
teaching and learning, attributes of the MAT@USC program perceived by
respondents as innovative, and factors perceived to be contributing to respondents’
sense of “preparedness” to adopt instructional technology. The online surveys were

59
conducted at the beginning of the Fall 2011 semester, in order to maximize the
response rate.
Instrumentation used in this study (Appendix A) was adapted from items in
Teaching and Learning with Technology In Higher Education survey instrument
created by Jacobsen (1998), items from Rogers’ (1995) attributes of innovation that
contributes to adoption, and items from Kay’s (2006) guiding model for
incorporating technology into preservice education. Questions were adapted to
determine respondents’ self-reported knowledge, comfort level with technology prior
to entering the program, factors influencing their use of technology, and perceived
barriers to the use of technology in the classroom. Additionally, respondents were
asked to reflect on the whether they perceived the MAT@USC program as an
innovative teacher education program, attributes of the program that they perceived
as enablers of adoption, and if they would continue to adopt new technology in their
own teaching upon graduation, in this survey instrument. At the end of the survey,
participants were also invited to comment on any item in the questionnaire that they
would like to elaborate on their responses or positions in an open ended question.

Interviews
Following the survey, a smaller sample from the population were randomly
drawn and sent e-mail invitations to participate in a phone interview. Participation
was completely voluntary and phone interviews were conducted using Skype and
audio recorded with participants’ permission. Participants who declined to be audio

60
recorded may still participate in the interview. A list of the interview questions is
included in Appendix B.
The identities of all participants will remain confidential at all times during
and after the study. All collected data will be destroyed after the study is finalized.
To the extent possible, personally identifiable information will not be revealed in the
data analysis or conclusions. Demographic information collected in this study
include: age, gender, years of teaching experiences, and number of courses taken in
the MAT@USC program to date. No identifiable information such as names, student
ID, or social security numbers will be collected in either the survey or interview.
Table 2 provides an overview of how items in the survey and interview
instrumentations attempt to answer the research questions for this study:

61
Table 2
Relationship Between Research Questions and Survey/Interview Instrumentations
Research Questions (RQs)
Concepts/Variables identified in Literature
Review Survey/Interview Items
RQ1: How do teacher
candidates perceive the use of
computer technology in
classrooms, and to what extent
do their dispositions about
technology relate to their age,
gender, teaching experience
and location (in California
versus out of state)?
Attitude Towards Technology:
1) The highest rated incentives for using
instructional technologies were related
to providing enriched learning
opportunities for students and personal
gratification teachers get from learning
new computer knowledge and skills
(Jacobsen, 1998).
2) Teachers’ beliefs about teaching,
learning and technology may create
resistance to adopt technology for
instruction (Ertmer, 2005). While
some teachers may think of
technology as an innovative tool to
facilitate student learning, others may
think of it as not having any impact on
student learning.
Perceived Learning Benefits:
1) Technology has “no learning benefits”
on student learning outcomes (Clark,
1994).
2) Technology may improve learning,
given its interactive capabilities
(Kozma, 1994).
Survey Questions:
Perceptions of Computer
Use in Classroom: Questions
6 – 17.
Interview Questions:
Innovation: Questions 1 – 6.
RQ2: What factors are
perceived by teacher
candidates as barriers to the
adoption of technology in
teaching (lack of knowledge,
motivation, resources, and
rewards), and to what extent
do they relate to teachers’ age,
gender, teaching experience
and location?
An innovation is less likely to be adopted if
it deviates too much from the existing
values, pedagogical beliefs, and practices of
the teachers and administrators at school
(Zhao et al., 2002).
Enablers of integration:
1) Teachers sense of feeling “prepared”
(Handler, 1993)
2) Good resource system (technical
support, professional development,
leadership, etc.)
Barriers to integration:
1) Lack of time
2) Lack of technological skills
3) Fear of technological issues
4) Limited access to technology
5) Limited financial support/funding
Survey Questions:
Barriers to Integrating
Technology for Teaching
and Learning: Questions 18
– 37
Interview Questions:
Student Knowledge:
Questions 1 – 4, 6
Innovation: Questions 7 – 13

62

Table 2, continued
Research Questions (RQs)
Concepts/Variables identified in Literature
Review Survey/Interview Items
RQ3: What attributes of an
online teacher education
program are perceived by
teacher candidates as
innovative, and to what extent
do these attributes relate to
their sense of preparedness to
adopt technology upon
graduation from the program?
Attributes of innovation/technology
(Rogers, 1995) which affects adoption:
1) Relative advantage
2) Complexity
3) Compatibility
4) Observability
5) Trialability
Guiding model for incorporating
technology into preservice education
(Kay, 2006):
1) Access
2) Modeling and authentic teaching
activities
3) Collaboration (mentor teacher and peer
support)
Factors contributing to a feeling of
“preparedness” among new teachers to
use and integrate technology (Handler,
1993):
1) Value of separate course on
introduction to computers in education.
2) The degree to which computers were
used during the methods block.
3) Observation of and use of computers
during student teaching field
experience.
4) Personal comfort with technology prior
to entering the program.
Survey Questions:
Attributes of Innovative
Teacher Education Program:
Questions 38 – 47
Factors Contributing to
Teachers’ Sense of
“Preparedness”: Questions
48 – 52
Interview Questions:
Student Knowledge:
Questions 5, 7, 8.

63
Data Analysis
The three research questions below guided the analysis of the data:
1. How do teacher candidates perceive the use of computer technology in
classrooms, and to what extent do their dispositions about technology
relate to their age, gender, teaching experience and location (in California
versus out of state)?
2. What factors are perceived by teacher candidates as barriers to the
adoption of technology in teaching (lack of knowledge, motivation,
resources, and rewards), and to what extent do they relate to teachers’
age, gender, teaching experience and location?
3. What attributes of an online teacher education program are perceived by
teacher candidates as innovative, and to what extent do these attributes
relate to their sense of preparedness to adopt technology upon graduation
from the program?
A four-point Likert scale was used to collect responses regarding perceptions
of computer use in classroom, barriers to integrating technology for teaching and
learning, attributes of innovative teacher education program, and factors contributing
to teachers' sense of preparedness. The qualitative aspect of the data presented an
opportunity for teacher candidates to share their own specific situations beyond the
information that the survey data requested.
The survey’s quantitative and qualitative data collected from the teacher
candidates was analyzed by the researcher and organized by research questions.

64
Research Question 1 was analyzed using a 3 (age) by 2 (gender) by 2 (experience) by
3 (location) factorial ANOVA. Using SPSS 17 as the statistical analysis tool,
analyses were conducted to correlate teacher candidates’ dispositions about
technology (attitude towards technology and perceived learning benefits afforded by
technology) with their age, gender, teaching experience and location (in California
versus out of state).
For Research Question 2, frequency analysis was performed on the survey
items (questions 18 – 37) which measured teacher candidates’ perceptions of barriers
to integrating technology for teaching and learning. These barriers are then ranked by
means in descending order. Factor analysis was also performed on survey items 18-
37 to identify correlations between these barriers and to see which items are most
closely correlated. The items that are closely correlated are organized into groups
known as factors for perceived barriers. Research Question 2 was also analyzed
using a 3 (age) by 2 (gender) by 2 (experience) by 3 (location) factorial ANOVA.
The factor analysis analyzed to what extent factors perceived as barriers to the
adoption of technology in teaching (lack of knowledge, motivation, resources, and
rewards) relate to respondents’ age, gender, teaching experience and location.
For Research Questions 3, the survey items were organized in two broad
categories: what teacher candidates perceived as attributes of innovative teacher
education program, and how prepared teacher candidates feel about using
instructional technology. The survey items were then analyzed using factorial
analysis, which runs all possible correlations between the items in the surveys related

65
to Research Question 3 (questions 38-52) and group items which are most closely
correlated together. The SPSS program was used to select variables, merge files, and
create composites. Correlations, standard deviations, and frequency distributions was
outputted from SPSS and used for the data analysis.

Limitations
This study is limited by the data and analytical tools used in the analysis:
quality and quantity of data collected and reported, and the limitations of instruments
affect the strength of the validity of the study. Data collected were sometimes limited
because data sources were incomplete. The instrumentations only collected self-
reported data about perceived use of instructional technology practices, overall
attitude toward the use of instructional technology in teacher preparation, attitudes
toward the use of instructional technology by teacher education candidates, and
influencing factors and barriers to integrating technology as identified by the survey
instruments. Detailed data on other factors such as technology support, frequency of
use, and instructional technology preferences were not the focus of the investigation
and were not collected.

Ethical Considerations
The researcher obtained permission from the Institutional Review Board from
the University of Southern California to conduct the qualitative and quantitative
research. Participations by graduate students of USC were completely voluntary. To

66
the extent possible, personally identifiable information was not revealed in the data
analysis or conclusions. Furthermore, participants in the survey were informed that
the information they gave for this study would be used only for this study.

67
CHAPTER FOUR
ANALYSIS
In this chapter, survey data and interview data are reported and analyzed,
framed by research questions presented in Chapters One and Three. First, descriptive
findings will be presented to give a context for the results. Secondly, an overview of
what analysis was performed with the results will be discussed. Third, the findings
are organized by research questions presented in Chapters One and Three.

Description of Data
This study was a mixed method study, and used case study methodology to
collect data at the online MAT@USC teacher education program. Quantitative and
qualitative data were collected using online surveys and interviews. First, in
September 2011, all teacher candidates who were enrolled in the online MAT@USC
program (current students) in fall 2011 were e-mailed a survey. The survey consisted
of 53 attitudinal questions about dispositions towards technology, factors perceived
as barriers to the adoption of instructional technology, attributes on an online teacher
education program perceived as innovative, and teacher candidates’ sense of
preparedness to adopt technology upon graduation from the program.
Out of the 1,216 surveys sent, 166 were completed and returned to the
researcher (13.65% response rate). Out of the 166 responses that were completed and
returned to the researcher, 55 responses came from the September 2011 cohort (first
semester, just started), 45 responses came from May 2011 cohort, 13 responses came

68
from February 2011 cohort, 11 responses came from January 2011 cohort, 12
responses came from November 2010 cohort and 30 responses came from September
2010 (near graduation) cohort. This response rate is considerably low, especially in
light of three email reminders. Kittleson (1997) asserted that “one can expect
between a 25 and 30% response rate from an e-mail survey when no follow-up takes
place. Follow-up reminders will approximately double the response rate for e-mail
surveys” (p. 196). However, a higher number of reminder notices do not necessarily
increase response rates because of “individuals reaching a saturation point in reading
their e-mail messages, or they may have been resistant to being reminded more than
once about the survey – a common trait among individuals who receive too many
reminders” (Kittleson, 1997, p. 196). Factors such as length of survey, saturation of
emails, and lack of personalized contact could be factors that contributed to the
lower than expected response rate (Cook, Heath, & Thompson, 2000). Timing of the
distribution could also be a factor. The survey was first sent out at the start of the
Fall 2011 semester to capture all the online MAT@USC student at one time;
however, students may be too overwhelmed at the beginning of a semester to be
motivated to do an online survey.
Although the response rate was low, Cook, Heath, and Thompson (2000)
argued that the representativeness of the samples is more important than the response
rate in survey research. Cook, Heath, and Thompson (2000) cited the example of
election polls, where representativeness of samples, even a small sample of the
population can be more representative than a sample of 50% of the population. This

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study is a case study specific to the online MAT@USC program and results were not
used to generalize to the larger population. The study did not include any on campus
students in the Master of Arts in Teaching program, who meet face-to-face for
classes.
Table 3 presents the demographic data of survey participants in the online
MAT@USC program. Table 4 presents a comparison of demographic data from the
survey, which reveals that respondents to the surveys had similar characteristics and
are representative of the total enrolled population at the online MAT@USC program.
Further, the sample sizes for most questions are sufficient to be confident that the
reported means and frequencies reflect more than random variations.
Second, the researcher also interviewed five teacher candidates who were
graduate students at the MAT@USC program: four female and one male. Two of the
interviewees started their program in September 2010 and they were in their final
semester and graduating soon in Fall 2011. The other three were in the middle of
their course; one started in November 2010, one in January 2011, and another in
February 2011. Out of the five interviewees, four of them were from California while
one was from out of state.

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Table 3
Demographic Data of Survey Participants
Survey Percent
Age
<30 47.0%
30 – 40 30.1%
>40 22.9%
Gender
Female 74.1%
Male 25.9%
Teaching Experiences
Yes 66.1%
No 33.9%
Location
California 51.2%
Out of state 48.8%
Number of Courses Completed at MAT@USC
0 33.1%
1 – 6 48.8%
7 – 12 18.1%

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Table 4
Comparison of Demographic Data: Survey Participants versus Total Graduate
Enrollment at the Online MAT@USC Program in Fall 2011
Survey Percent Total Percentage
Gender
Female 74.1% 67.8%
Male 25.9% 32.2%
Location
California 51.2% 49.9%
Out of state 48.8% 50.1%
Number of Courses Completed at MAT@USC
0 33.1% 35.1%
1 – 6 48.8% 45.5%
7 – 12 18.1% 19.4%

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What Analysis Was Performed
First, the responses to attitudinal questions 6 to 52, which were scored as
Strongly Disagree, Disagree, Neutral, Agree, and Strongly Agree, were changed into
numeric scores of 1 to 5, respectively. A factor analysis was then performed on the
data sets for Research Questions 1, 2, and 3. The purpose of factor analysis is to
discover simple patterns in the pattern of relationships among the variables
(Darlington, 2004). In particular, Darlington (2004) explained that factor analysis
seeks to discover if the observed variables can be explained largely or entirely in
terms of a much smaller number of variables called factors. For each of the research
questions in this study, a number of factors were identified. A typical factor analysis
suggests answers to four major questions:
1. How many different factors are needed to explain the pattern of
relationships among these variables?
2. What is the nature of those factors?
3. How well do the hypothesized factors explain the observed data?
4. How much purely random or unique variance does each observed
variable include?
Furthermore, a reliability analysis was conducted for each of the factors, to
ensure that the survey was a reliable instrument. Cronbach’s alpha of more than 0.7
is considered reliable. Findings are supplemented by survey question 53, which is an
open-ended question for comments. Interview data with five of the respondents are
also included in the findings, organized by research questions.

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Findings Organized by Research Questions
Research Question 1: How do teacher candidates perceive the use of computer
technology in classrooms, and to what extent do their dispositions about
technology relate to their age, gender, teaching experience and location (in
California versus out of state)?
A factor analysis was performed on the responses to Questions 6 to 12 in the
survey, which measure teacher candidates’ perceptions of computer use in
classroom. For Research Question 1, two factors related to teacher candidates’
dispositions about technology were identified: their attitude towards technology
(attitude) and belief about learning benefits afforded by technology (belief).
Factor loadings with scores > .50 are included in the factor component (either
‘Attitude’ or ‘Belief’) while the ones lower and/or appear on both components are
excluded. Since Cronbach’s alpha for ‘Attitude’ was 0.724 and ‘Belief’ was 0.733,
the test appeared reliable. The descriptive statistics below provide summaries about
the sample and the measures of the two factors. The mean for teacher candidates’
attitude towards technology ‘Attitude’ is 4.01, and belief about learning benefits
afforded by technology ‘Belief’ is 4.20 on a scale of 1 to 5; a higher score denotes a
more favorite attitude or belief. This shows that in general, participants in the survey
has a positive attitude towards technology and believe that technology affords
learning benefits.

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Table 5
Rotated Component Matrix
a
: Attitude and Belief
Attitudinal Questions Attitude Belief
Students are enthusiastic about subjects which they use computers (Q.7) .710
Computers enable me to make a subject more interesting (Q.8) .690
Computers provide more opportunities for gifted students (Q.15) .608
Technology tools enable me to better diagnose learning problems (Q.9) .606
I get personal gratification from learning new computer knowledge (Q.10) .574
I enjoy figuring out how to use computers effectively (Q.14) .515
Computers provide a means for expanding what has been taught (Q.11) .514 .416
By integrating technology, I help student acquire computer education (Q.13) .742
Technology tools enable students to help each other and cooperate (Q.16) .667
Computer tools enable me to communicate & interact more with students (Q.12) .665
Computers are a tool that helps students with learning tasks (Q.6) .646
Computers appeal to a variety of learning styles (Q.17) .344 .592
Extraction Method: Principal Component Analysis.
Rotation Method: Varimax with Kaiser Normalization.
a. Rotation converged in 3 iterations.

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Table 6
Frequencies: Statistics for ‘Attitude’ and ‘Belief’
Attitude Belief
N (valid) 160 160
N (missing) 6 6
Mean 4.0110 4.2084
Std. Error of Mean .04144 .04266
Median 4.0000 4.2000
Mode 4.00 4.20
Std. Deviation .52421 .53957
Variance .275 .291
Range 2.50 2.20
Minimum 2.50 2.80
Maximum 5.00 5.00
Sum 641.77 673.35

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Finding 1: Participants in this study have positive attitudes towards
technology.
The participants in this study reported having positive attitudes towards
technology; they are highly receptive to the use of technology in education and have
high levels of personal comfort with technology prior to entering the program
(79.4%). The mean, median and mode for the variable ‘Attitude’ is 4.00, which is
‘Strongly Agree’. A teacher candidate admitted:
I didn’t have a class dedicated to computers in the MAT@USC, which was
fine because I’m a very advanced user of technology. I teach biology which
is a highly visual subject. Many concepts and processes are quite abstract
without some animation or video to illustrate. My students are accustomed to
seeing videos that I provide voice-overs for and enhance my lessons. Using
media and technology helps bridge language gaps and a picture is worth a
thousand words.

Based on a survey that examined self-perceptions of teacher education graduates
after their first year in the classroom, Handler (1993) reported that several factors
contributed to a feeling of preparedness to use technology among teachers; one of
these factors being teachers’ personal comfort with the technology prior to entering
the program or taking an introductory course.
The participants reported getting personal gratification from learning new
computer knowledge and skills (92.5%). The highest rated incentives for using
instructional technologies were related to providing enriched learning opportunities
for students and personal gratification teachers get from learning new computer
knowledge and skills (Jacobsen, 1998). Out of the 166 participants, 83.1% said that
they enjoy figuring out how to use technology for different teaching situations, and

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that the use of technology is compatible with their own values, norms and teaching
philosophy. In the interview, one teacher candidate said:
I enjoy the opportunity I have to use technology as much as I do in the
MAT@USC program. Since I have started teaching third grade, I include
technology whenever I can. I allow the children to video record each other’s
presentations. I also allow them to do mini-research projects on the computer.
While I love using books during lessons, children are always excited to
experience something new.

Another respondent described how he is currently using technology in class:
I currently teach Earth Science, Calculus and Physics. I see frequent use of
computers in Earth Science. Less in Calculus and a little more in Physics. For
the two former classes, I would use computers for graphical illustrations and
data.

Finding 2: Participants in this study believed that computers provide
learning benefits.
A majority of the respondents (92.6%) believed that technology is a tool that
will help students with learning tasks, such as writing, analyzing data, or solving
problems. In other words, they see the value of technology and believe that
technology offers learning benefits and improve student learning, given its
interactive capabilities. They also believe that computer knowledge is something that
students will need for future careers (93.8%). Participants in this study agreed that
computers provide the following learning benefits: providing a means of expanding
and applying what has been taught (88.1%), makes a subject more interesting
(77.5%), improve communication and interaction with students (72.5%), encourage
students to collaborate on projects (78.9%), and provides an environment that

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appeals to a variety of learning styles (76.3%). The mean, median and mode for the
variable ‘Belief’ is 4.20, which is ‘Strongly Agree’.
A teacher candidate mentioned that computer literacy is increasingly more
important for today’s students. She said, “Technology is not only a great resource but
also an increasingly necessary topic to teach our students. Without computer literacy,
they will be barred from many good jobs and careers, not to mention academic
success in high school and college.” Another respondent said:
Having taught in a professional setting, outside of the standard academic
arena, I have found the use of computers to be invaluable. I have found the
same true within the K-12 setting. I personally believe that utilizing
technology within learning, gives the student the opportunity to see how to
integrate the use of technology to best fit their own learning. In a technology
centric society, this is a crucial skill.

Technology was described as the future of education by another respondent:
Technology is the future of education. It opens the door to the whole world
for students. Literally and figuratively. There are so many resources available
through the Internet, and a variety of people and cultures that can be
interacted with. Technology is an effective tool for learning, in that today’s
generations are more comfortable and engaged by it, and programs like Excel
and Word are great tools. But there’s still a lot of unpacking of opportunities
for collaboration and creativity among teachers.

According to Ertmer (2005), teachers’ perceptions regarding the value of technology
was most likely to occur when teachers were socialized by their peers. This finding
suggested the need to provide sufficient time for teachers to interact with and help
each other as they as they explore new technologies and pedagogies.
Research Question 1 was also analyzed using a 3 (age) by 2 (gender) by 2
(experience) by 3 (location) factorial ANOVA to analyze to what extent do the

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respondents’ dispositions about technology (attitude towards technology and belief
about learning benefits afforded by technology) relate to their age, gender, teaching
experience and location (in California versus out of state). The effect of each factor
in the factorial ANOVA was adjusted for the three other factors and only adjusted
means are presented in Table 7. For example, when measuring the effect of ‘age’ as a
factor, the factorial ANOVA was adjusted for the three other factors, which were
‘gender’, ‘teaching experiences’, and ‘location’.
Table 7 shows the adjusted means for age, gender, teaching experiences and
location, organized by variables within the dispositions about technology: attitude
and belief. Significant (p < .05) age difference was found on the attitude variable. In
this study, more positive attitudes about technology are found as age increases. This
finding was interesting because it contradicted Handler’s (1993) study in which age
was reported as not a significant factor in discriminating between respondents who
believe they were prepared versus those who were not. In an interview with a
respondent who was 53 years old, she said:
I am somewhat comfortable with technology, especially with basic skills.
However, I can really see how much easier assignments are for my younger
counterparts. I would really like to adopt technology into my own teaching if
I knew how to set up a lot of this stuff myself, because I think this is going to
be the norm someday. I want to keep up with my students and also help them
learn how to use new technology.

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Table 7
Adjusted Means for Age, Gender, Teaching Experiences and Location, Organized by
Variables within the Dispositions about Technology: Attitude and Belief
Age
< 30 30-40 > 40 F-ratio (df) obs. prob.
Attitude 3.94 4.13 4.23 4.511 (2, 152) 0.012
Belief 4.17 4.32 4.21 1.110 (2, 152) 0.332
Gender
Female Male F-ratio (df) obs. prob.
Attitude 4.04 4.16 1.742 (1, 152) 0.189
Belief 4.24 4.23 0.021 (1, 152) 0.884
Teaching Experiences
Yes No F-ratio (df) obs. prob.
Attitude 4.04 4.16 2.109 (1, 152) 0.148
Belief 4.16 4.31 2.383 (1, 152) 0.125
Location
CA Other Unknown F-ratio (df) obs. prob.
Attitude 4.24 3.97 4.09 3.606 (2, 152) 0.029
Belief 4.27 4.19 4.25 0.317 (2, 152) 0.729
The F-ratio is a ratio of the average observed variability between the 3 means to the average
variability explained by chance. The observed probability (obs. prob.) is the probability that the
difference, as indicated by the size of the F-ratio, occurred by chance. If the probability is less than
.05, it is statistically significant.

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Throughout Table 7, which presents the adjusted means for age, gender,
teaching experiences and location, organized by variables within the dispositions
about technology, groups with different subscripts were found to be different using
the Fisher LSD post hoc test. Both female and male respondents, as well as those
with or without teaching experiences, reported favorable attitudes towards
technology and believe that technology afforded learning benefits. Significant (p <
.05) location difference was found on the attitude variable. For attitude, more
positive attitudes about technology were reported by respondents who plan to teach
in the state of California versus those who plan to teach out of state. For this study,
location may have influenced the answers given by respondents due to funding and
access to technology based on school districts.
During the interview, one of the respondents said:
My response to many of your questions would change depending on the
school used as reference. Many schools foster technology understanding and
skills where others do not – this may be related to funding for a particular
school or number of parent volunteers.

Another respondent made a similar comment, “A lot of these questions
depend on the individual school people teach at. Personally, the school I work for is
very lacking in technology, which may have affected some of my responses.” The
state technology programs, which provide funds and leadership for the use of
technology in schools in California, may have influenced some of the respondents’
attitude towards the use of instructional technology. The California State Board of
Education’s (SBE’s) Education Technology Planning encourage districts to focus on

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using technology to improve student achievement and to develop the components of
the technology plan, including curriculum; professional development; infrastructure,
hardware, technical support and software
(http://www.cde.ca.gov/ls/et/rd/edtechguide.asp).

Research Question 2: What factors are perceived by teacher candidates as
barriers to the adoption of technology in teaching (lack of knowledge,
motivation, resources, and rewards), and to what extent do they relate to
teachers’ age, gender, teaching experience and location?
For Research Question 2, frequency analysis was performed on the survey
items (questions 18 – 37) which measured teacher candidates’ perceptions of barriers
to integrating technology for teaching and learning. These barriers are then ranked by
means in descending order and presented in Table 8. The highest barrier reported is
survey item 22: “There are too few computers for the number of students”, with a
mean of 4.27 on a scale of 1 (strongly disagree, not a barrier) to 5 (strongly agree, a
major barrier). The least likely barrier to integration of technology reported by
respondent is survey item 36: “Computers do not fit the course or curriculum that I
teach”, with a mean of 2.02 (disagree).
Factor analysis was also performed on survey items 18-37 to identify
correlations between these barriers and to see which items are most closely
correlated. The items that are closely correlated are organized into groups known as
factors. Four factors related to perceived barriers were identified: lack of knowledge

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(knowledge), lack of motivation (motivation), lack of resources (resources), and lack
of rewards (rewards). Breakdown of the corresponding question items are shown in
Table 9. Factor loadings with scores > .50 are included in the factor component
(‘Resources’, ‘Knowledge’, ‘Motivation’, or ‘Rewards’) while the ones lower and/or
appear on both components are excluded. Cronbach’s alpha for ‘Resources’ was
0.778 and was 0.694 for ‘Knowledge’; the test appeared reliable for those two
factors. Cronbach’s alpha for ‘Motivation’ was 0.575 and was 0.585 for ‘Rewards’.
One of the reason why the reliability statistics were low for ‘Motivation’ and
‘Rewards’ could be because there are too few items for both the factors. However,
the Cronbach’s alpha could have been more precise. A higher Cronbach’s alpha of at
least 0.7 would have indicated that the two factors, ‘Motivation’ and ‘Reward’, were
more reliable measures.
The descriptive statistics shown in Table 10 provide summaries about the
sample and the measures of the four categories of perceived barriers to integration of
technology in the classroom. The mean for ‘resources’ as a barrier is 3.76,
‘knowledge’ as a barrier is 3.14, ‘motivation’ as a barrier is 2.55, and ‘rewards’ as a
barrier is 3.41. On a scale of 1 to 5, a higher score denotes that the factor is a major
barrier. This shows that in general, participants in the survey view ‘resources’ as the
most important barrier while ‘motivation’ was not perceived as a barrier for
integration and use of technology in teaching.

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Table 8
Frequencies: Perceived Barriers Ranked by Means in Descending Order
Perceived Barriers to Integrating Technology N Min Max Mean
Std.
Deviation
Too few computers for number of students (Q.22) 144 1.00 5.00 4.27 .864
Problems scheduling computer time/resources (Q.19) 144 1.00 5.00 4.09 .895
Inadequate financial support for development (Q.29) 143 2.00 5.00 3.92 .880
Financial support for integration inadequate (Q.27) 142 1.00 5.00 3.83 .929
Scarcity of printers and other peripherals (Q.24) 143 1.00 5.00 3.70 1.105
Reward structure does not recognize teachers (Q.21) 145 1.00 5.00 3.69 .827
Teachers lack time to develop instruction (Q.18) 145 1.00 5.00 3.57 1.025
Not enough support for supervising student (Q.28) 145 1.00 5.00 3.49 .928
Too few training opportunities for teachers (Q.34) 143 1.00 5.00 3.48 1.047
Too few computers for individual teacher (Q.23) 144 1.00 5.00 3.39 1.183
Hardware is unstable and breaks down (Q.20) 144 1.00 5.00 3.20 .995
Not enough time for computer related instruction (Q.25) 144 1.00 5.00 3.15 1.174
No recognition for using computers for teaching (Q.37) 144 1.00 5.00 3.11 .978
Limited research shows improvements in learning (Q.26) 144 1.00 5.00 3.11 .779
Computer manuals inadequate and unhelpful (Q.33) 144 1.00 5.00 2.82 .948
Software is not adaptable to instructional need (Q.32) 145 1.00 5.00 2.64 .954
Unsure how to integrate computers into instruction (Q.31) 145 1.00 5.00 2.55 1.129
Not interested in using computers for instructions (Q.30) 145 1.00 5.00 2.53 .979
Less control over classroom instruction (Q.35) 145 1.00 5.00 2.48 .921
Computers do not fit the course I teach (Q.36) 144 1.00 5.00 2.02 .872
Valid N (listwise) 132
1 = Strongly disagree, not a barrier 5 = Strongly agree, a major barrier

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Table 9
Rotated Component Matrix
a
: Resources, Knowledge, Motivation, Rewards
Perceived Barriers to Integrating Technology Resources Knowledge Motivation Rewards
Too few computers for individual teacher (Q.23) .819
Scarcity of printers and other peripherals (Q.24) .727
Too few computers for number of students (Q.22) .705
Inadequate financial support for development (Q.29) .665 .306
Financial support for integration inadequate (Q.27) .555 .341
Not enough support for supervising student (Q.28) .462 .419
Hardware is unstable and breaks down (Q.20) .676
Teachers lack time to develop instruction (Q.18) .644
Computer manuals inadequate and unhelpful (Q.33) .632
Software not adaptable to instructional need (Q.32) .629 .312
Problems scheduling computer time (Q.19) .320 .550
Unsure how to integrate computers (Q.31) .499 .435
Too few training opportunities for teachers (Q.34) .302 .364
Less control over classroom instruction (Q.35) .751
Computers do not fit the course I teach (Q.36) .751
Not interested in using computers (Q.30) .494 .313
Not enough time for computer instruction (Q.25) .374 .396 .468
No recognition for using computers to teach (Q.37) .793
Reward structure does not recognize teachers (Q.21) .710
Limited research shows learning benefits (Q.26) .334 .336
Extraction Method: Principal Component Analysis.
Rotation Method: Varimax with Kaiser Normalization.
a. Rotation converged in 6 iterations.

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Table 10
Frequencies: Statistics for ‘Resources’, ‘Knowledge’, ‘Motivation’ and ‘Rewards’
Resources Knowledge Motivation Rewards
N (valid) 143 145 145 145
N (missing) 23 21 21 21
Mean 3.7674 3.1476 2.5500 3.4138
Std. Error of Mean .05711 .05225 .05462 .06387
Median 3.6667 3.1667 2.5000 3.5000
Mode 3.67 3.00 2.25 3.00
Std. Deviation .68299 .62914 .65774 .76907
Variance .466 .396 .433 .591
Range 3.33 3.67 3.50 3.50
Minimum 1.67 1.00 1.00 1.50
Maximum 5.00 4.67 4.50 5.00
Sum 538.73 456.40 369.75 495.00

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Finding 1: Lack of resources was perceived as top barriers to integration
of technology.
The top five highest perceived barriers fall under the category of resources:
too few computers for the number of students (survey item 22), problems scheduling
enough computer time and/or resources for different teachers’ classes (survey item
19), inadequate financial support for the development of instructional uses of
computers (survey item 29), inadequate financial support for computer integration
(survey item 27) and scarcity of printers and/or other peripherals (survey item 24).
During the interview, when asked what are some barriers that they think may hinder
them from integrating technology into teaching, a respondent answered:
Money. I’m teaching in a school that does not have money for anything. I
bring my own computer to use in the classroom. The students don’t have
access to computers and are being limited due to the lack of money and
access. They’re not acquiring skills or useful function with non-Facebook
related computer or media.

Another respondent answered:
The use of technology in the classroom is great as long as there is sufficient
time and access for all of the students in the class. When these problems are
faced, integrating technology becomes such an extreme challenge that
teachers often end up eliminating the use at all. It is not beneficial to have 30-
35 students using five computers in a 45 minute time span.

This is consistent with Kay’s (2006) view that good access to software, hardware and
support is necessary to integration. Without adequate access, it is unlikely that other
strategies will work.
Respondents also perceived lack of funding as a direct cause for lack of
access to technology. One teacher candidate said:

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I’m currently teaching at a high school and the school has only one computer
lab which is usually booked and inaccessible by students. That’s a huge
barrier for me and the students. Lack of funding is likely the cause, but it is
denying students access to online resources.

These findings are consistent with the literature review in Chapter Two;
organizational barriers that may affect teachers’ adoption of technology include
school leadership, school scheduling, school planning and funding (Fox & Henri,
2005). Lack of school planning with regard to technology, limited access, and rigid
school schedule constrains the variety of learning modalities that teachers can design
(Becker, 2000).

Finding 2: Barriers to integration of technology depends on school
districts, especially teachers entering low SES districts.
Many of the respondents said that access to resources often depended on the
school districts. As a respondent said:
In my school district, many of the students’ families do not own computers.
Often times, going to the computer lab is a chore because students do not
have the basic computer skills to follow along with the teacher’s lesson. So
while teachers may want to integrate computers into their curriculum to better
prepare their students for the future, many back away because of the time
crunch. Hence, many teachers do not integrate technology into their
curriculum because of the necessity to teach students how to work a
computer. I think this is something to consider in your dissertation especially
for pre-service teachers who are entering low SES districts.

Another respondent agreed:
A lot of how much integration of technology depends on what a district has
to offer. Most of the districts I have been exposed to do not have the money
to invest in technology. So I may want to use technology but cannot because
it is not available.

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Use of technology was also perceived to be very different for students in
suburban districts compared to low SES districts. A respondent explained during the
interview:
Two classes in my last semester discussed the importance of technology in
classrooms like mine (“at risk” in a neighborhood characterized by violence,
poverty and tenuous immigration status). The lessons were lovely and
thought-provoking but they seemed to be geared toward more
suburban/wealthy classrooms. The use of technology is very different in
wealthier communities. They talked about using iPads, nooks, computers,
video cameras, “about half my students use notebooks in class”. My students,
for the most part, do not have computers at home and 85% (estimated) do not
have internet aside from their smart phones which are used strictly for
socializing. I was a little sad to hear how large the technology gap is and how
much my students are missing out by not having technology or access.

Support offered by school districts is also a factor. As one respondent put it:
While technology has advanced, there are few advances in the support and
budgets within the school districts that have the technology. In the three
districts near my residence, grants for computers and software rarely include
funding for teacher or tech team personnel and training. Therefore,
computers were delivered to the library with no printer set-up, and the
librarian was forced to wait until the one person from the district came to
format the printers for the computers. Without adequate tech staffing on site
at a school, little mistakes in protocol with a program will cause distrust to
form. A teacher cannot use class time to troubleshoot a projector, and must
have alternate plans in case the electronic item does not work. If she distrusts
the technology too much, she will forgo using it altogether, preferring
methods that are tried and true, that keep her on track for her pacing guide.
This is true of video tapes, and CD players, as well as smart boards and
PowerPoint presentations.

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Finding 3: Respondents were motivated to integrate technology;
however, lack of resources and lack of knowledge may prevent
integration of technology.
This group of teacher candidates believed that lack of motivation was not a
main barrier for not integrating technology into classrooms. Teacher candidates in
this study disagreed with the following statements (related to self-efficacy and
instructional technology): computers do not fit the course or curriculum that they
teach (77.1% disagreed), there is less control over classroom instruction when using
computers (59.4% disagreed), teachers are not interested in using computers for
instruction (53.1% disagreed), and teachers are unsure of how to integrate computers
into instruction (57.2% disagreed). Respondents expressed that their desire to
integrate technology may be hampered by lack of access to resources or lack of
knowledge. One respondent said, “I will definitely use the technology available as
much as I can. But technology tools that are in working order and available are very
scarce in my geographical area.” Another respondent expressed her concerns with
lack of knowledge:
I would like to be able to use technology in the classroom, but I don’t have
any idea how to incorporate it into my classes. It would be great if there was
a class that teaches us how to use the new technology. Offering classes on
using new technology would really be helpful for me as I want to keep up
with my students and also help them learn how to use new technology.

Research Question 2 was also analyzed using a 3 (age) by 2 (gender) by 2
(experience) by 3 (location) factorial ANOVA. The factor analysis analyzed to what
extent factors perceived as barriers to the adoption of technology in teaching (lack of

91
knowledge, motivation, resources, and rewards) relate to respondents’ age, gender,
teaching experience and location. The effect of each factor in the factorial ANOVA
was adjusted for the other factors and only adjusted means are presented in Table 11.
Significant (p < .05) age difference was found on responses related to
resources and rewards variables. Respondents from age groups 30-40 and over 40
perceived lack of resources as a greater barrier than respondents who are under 30-
years-old. Also, older respondents perceived lack of rewards as a higher barrier than
younger ones. Significant (p < .05) gender differences were also found in responses
on the resources and knowledge. Female respondents perceived the lack of resources
as a greater barrier than male respondents. Female respondents also perceived lack of
knowledge of how to use technology as a greater barrier than male respondents.
Overall, respondents reported perceived lack of resources as the highest barrier, and
lack of teacher motivation as the least likely barrier.

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Table 11
Adjusted Means for Age, Gender, Teaching Experiences and Location, Organized by
Variables/Perceived Barriers: Resources, Knowledge, Motivation, and Rewards
Age
< 30 30-40 >40 F-ratio (df) obs. prob.
Resources 3.51 3.88 3.84 5.078 (2, 135) 0.007
Knowledge 2.98 3.08 3.22 1.837 (2, 137) 0.163
Motivation 2.54 2.50 2.68 0.719 (2, 137) 0.489
Rewards 3.21 3.40 3.68 4.237 (2, 137) 0.016
Gender
Female Male F-ratio (df) obs. prob.
Resources 3.98 3.51 13.822 (1, 135) 0.0001
Knowledge 3.26 2.93 8.223 (1, 137) 0.005
Motivation 2.62 2.53 0.524 (1, 137) 0.470
Rewards 3.57 3.30 3.390 (1, 137) 0.068
Teaching Experiences
Yes No F-ratio (df) obs. prob.
Resources 3.65 3.84 2.609 (1, 135) 0.109
Knowledge 3.12 3.07 0.224 (1, 137) 0.637
Motivation 2.50 2.65 1.474 (1, 137) 0.227
Rewards 3.36 3.50 0.963 (1, 137) 0.328
Location
CA Other Unknown F-ratio (df) obs. prob.
Resources 3.81 3.79 3.63 1.111 (2, 135) 0.332
Knowledge 3.23 3.28 2.77 10.901 (2, 137) 0.0001
Motivation 2.66 2.67 2.39 2.630 (2, 137) 0.076
Rewards 3.59 3.36 3.35 1.618 (2, 137) 0.202
The F-ratio is a ratio of the average observed variability between the 3 means to the average
variability explained by chance. The observed probability (obs. prob.) is the probability that the
difference, as indicated by the size of the F-ratio, occurred by chance. If the probability is less than
.05, it is statistically significant.

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Research Question 3: What attributes of an online teacher education program
are perceived by teacher candidates as innovative, and to what extent do these
attributes relate to their sense of preparedness to adopt technology upon
graduation from the program?
The survey items for Research Questions 3 were organized in two broad
categories: what teacher candidates perceived as attributes of innovative teacher
education program, and how prepared teacher candidates feel about using
instructional technology. Table 12 and 13 provide the descriptive statistics for survey
items pertaining to Research Question 3. The survey items were then analyzed using
factorial analysis, which runs all possible correlations between the items in the
surveys related to Research Question 3 (questions 38-52) and group items which are
most closely correlated together (Table 14).

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Table 12
Frequencies: Attributes of Innovative Teacher Education Program
Attitudinal Questions Mean Median Mode
Std.
Dev. Var.
The online format offers relative advantages to
campus (Q.38)
4.24 4.00 4.00 .811 .659
The use of technology in MAT is relevant to my
career (Q.39)
4.05 4.00 4.00 .940 .885
Use of technology is compatible with my
teaching philosophy (Q.40)
4.13 4.00 4.00 .781 .610
Platform & software used in MAT is easy to use
(Q.41)
4.07 4.00 4.00 .866 .750
I was able to experiment & practice prior to
start of course (Q.42)
3.83 4.00 4.00 1.125 1.267
I was given sufficient time to learn software
(Q.43)
3.74 4.00 4.00 1.036 1.074
Technology used was modeled to me by my
professor (Q.44)
3.30 3.00 4.00 1.098 1.208
I was encouraged to collaborate with peers &
professor (Q.45)
4.40 5.00 5.00 .735 .540
I was given sufficient tech support if needed
(Q.46)
4.24 4.00 5.00 .890 .793
Technology used in MAT is innovative, useful,
cutting-edge (Q.47)
4.34 5.00 5.00 .855 .732
1 = Strongly disagree 2 = Disagree 3 = Neutral 4 = Agree 5 = Strongly agree

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Table 13
Frequencies: Teacher Candidates’ Sense of Preparedness
Attitudinal Questions Mean Median Mode
Std.
Dev. Var.
Having a separate course on computers help
me feel prepared (Q.48)
3.43 3.00 3.00 1.011 1.023
Degree to which tech was used in MAT helps
me feel prepared (Q.49)
3.94 4.00 4.00 .971 .944
I was given opportunity to observe use of
technology in MAT (Q.50)
3.30 3.00 3.00 1.129 1.275
My personal comfort with technology help
me feel prepared (Q.51)
4.12 4.00 5.00 .995 .991
I plan to use & integrate technology when I
graduate (Q.52)
4.45 5.00 5.00 0.656 .431
1 = Strongly disagree 2 = Disagree 3 = Neutral 4 = Agree 5 = Strongly agree

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Table 14
Rotated Component Matrix
a
: Attributes, Comfort, Sense of Preparedness
Attitudinal Questions Attributes Comfort Prepared
I was encouraged to collaborate with peers & professor
(Q.45)
.737
The use of technology in MAT is relevant to my career
(Q.39)
.734
Online format of MAT offers relative advantages to
campus (Q.38)
.729
Technology used in MAT is innovative, useful, cutting-
edge (Q.47)
.707
Use of technology is compatible with my teaching
philosophy (Q.40)
.637
I plan to use & integrate technology when I graduate
(Q.52)
.605
Platform & software used in MAT is easy to use (Q.41) .578 .398
I was given sufficient tech support if needed (Q.46) .439 .323
I was able to experiment & practice prior to start of
course (Q.42)
.867
I was given sufficient time to learn software to be
successful (Q.43)
.316 .863
Technology used was modeled to me by my professor
(Q.44)
.399 .517
My personal comfort with technology helps me feel
prepared (Q.51)
.489
Having a separate course on computers help me feel
prepared (Q.48)
.798
I was given opportunity to observe technology use in
teaching (Q.50)
.665
Degree to which tech was used in MAT helps me feel
prepared (Q.49)
.497 .631
Extraction Method: Principal Component Analysis.
Rotation Method: Varimax with Kaiser Normalization.
a. Rotation converged in 5 iterations.

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Finding 1: Respondents perceived technology used in the MAT@USC
program as innovative and highly collaborative.
Majority of the participants in the survey (86.7%) believed the technology
used in the MAT@USC program as innovative, useful and cutting-edge. When asked
during the interview if the respondents perceived the MAT@USC program as an
innovative teacher education program, all five of them unanimously said yes.
Approximately 73% of respondents indicated that the degree to which technology
was used in the MAT@USC program helped them feel prepared to use technology.
This finding is consistent with Rogers (1995) studies on the diffusion of innovation,
which identified five major attributes which affect adoption: relative advantage,
complexity, compatibility, observability, and trialability. In the context of this study,
teacher candidates are more likely to adopt technology used in their teacher
education program if they are perceived as having relative advantage over traditional
methods, easy to use, compatible with teachers’ attitudes and beliefs of technology,
and if they are able to observe how technology are used by their professors and peers
(modeled) and if they are able to experiment with technology first hand.
A respondent said during the interview:
Over the course of the program, my knowledge of videoconferencing and
learning management systems (LMS) definitely increased. The use of
videoconferencing in an online lecture/discussion setting changed my attitude
of what online education can be. Also, the MAT@USC LMS is different
from what I have experienced in other online courses (mainly, Blackboard
forums). The MAT@USC LMS still needs improvement, but I believe that its
layout is conducive to presenting an organized online course.

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Furthermore, 86% of these teacher candidates also believed that the online
format and delivery of the MAT@USC program offers relative advantages to a
campus-based program. One respondent commented, “I feel that the use of
technology in the MAT program actually makes the classroom setting more
interactive and supportive than the traditional classroom. I never had this level of
class interaction during my traditional college experience.” According to the
literature on the adoption of innovation, the classroom interaction provides
trialability space for teachers to learn how to use technology, teachers are
encouraged to experiment with technology and so, they are more comfortable
adopting it in classrooms (Plsek, 2003; Rogers, 1995).
Another respondent added:
Yes, I do believe the MAT@USC program is an innovative teacher education
program. I believe the videoconferencing discussions are what make the
program different from other online courses. For instance, I have several
classmates in Georgia who are familiar with the current cheating scandal in
Atlanta. They witness firsthand the scandal’s effect on school climate and are
able to bring their personal accounts to our discussions. Also, videotaping my
own lessons has been beneficial to my development as a teacher. While the
footage serves as a way of my professors to assess my lessons, it also gives
me a way to evaluate myself.

Becker (1994) reported the importance of a social network of computer-using
teachers for sustaining the work of exemplary computer-using teachers. The live
videoconferencing discussions among teacher candidates provide them with the
opportunity to share best practices and maintain a social network of computer-using
teachers.

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In general, respondents perceived the use of live video camera during class,
online break out groups, and the videotaping of lessons as some of the technological
tools that make the online MAT@USC program innovative. Some of the innovative
attributes of the program, as cited by a respondent during the interview, were:
Live-time courses with every participant present in video and audio, having
access to all amenities that are available to on-campus students (student card,
athletic facilities, discount tickets to events, clubs, etc.), having some
professors who also teach on campus, which gives a feeling of community
with USC…versus being separate, and the quality of faculty and instruction.

This is consistent with survey findings from Moursund & Bielefeldt (1999),
which revealed that integration factor (actual use of technology during teacher
training) was the best predictor of basic technology proficiency, and that, in order to
increase the technology proficiency of new teachers in K-12 classrooms, teacher
educators need to increase the level of technology integration in their own academic
programs.
Participants also perceived the online MAT@USC program as highly
collaborative. The survey results indicated that 90.4% of the participants agreed that
they were encouraged to collaborate with their peers and professor throughout the
course. One respondent said:
The live video camera during class, and break out groups (when they worked)
were exciting and innovative. Even better was the group writing project
during our first full term. Too bad there weren’t more group projects like
that- there were some study groups, but they were just for show. We worked
really hard on our paper, and everyone edited online, researched their section
and joined in the discussion. Because the group paper was so powerful, I do
want to incorporate it in my teaching. However, that plus other things that
were useful can only work in schools that have technology as a priority.

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According to Kay’s (2006) guiding model for incorporating technology into
preservice education, collaboration among preservice teachers, faculty, and mentor
teachers is an important ingredient for success. Without collaboration with peer and
faculty, it seems unlikely that gains in attitude and ability will translate to
meaningful use of technology (Kay, 2006).

Finding 2: Concerns over technological issues dampened teacher
candidates’ enthusiasm to use technology.
Although participants in the survey indicated that the platform and software
of the MAT@USC program are easy to use (83.1%), and that they were given
sufficient access to technological support when needed (83.1%), many of them also
voiced their concerns with regards to technological issues encountered when using
the online platform. A survey participant commented in the open ended question:
The technology may be cutting edge and I may have the skills and practice to
use it effectively when there aren’t problems. There are enough issues when
using the online platform to cause me to rate it poorly. It hinders my learning
and takes away from the limited class time we already have. I like the MAT
program but there are still things that need to be improved.

Another comment echoed similar concerns:
There are glitches in the system that were never addressed. Adobe is not a
system that is supported on all machines without patches or add-ins or
technical difficulties. In some cases for some students, this is problematic,
especially when using Skype. In some cases, my peers and I had a better grip
on technology and how to use the platform than our professors. This is
frustrating. Sometimes, for whatever reason and beyond student or teacher
control, video, audio, microphone cut out, fail, or don’t work or stop
working. We are told we have to attend classes via video and audio or we do
not get credit. This is also frustrating. Breakout groups never work right. I

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hate them and it is distracting. Any type of technical difficulty during class is
distracting and I feel like there were some classes where all we did was deal
with technical issues. I do not like that I no longer have access to last terms’
courses as those classes had links and videos I would want to access as a
resource or for reminders.

In general, students who have encountered technical issues during their
teacher program tend to be more critical about the use of technology in the program.
Once the issues are resolved, students rated the program better. As a participant
commented, “I am referring to the summer session: there were several platform
problems and often students were dropped from the conference and had to reenter the
room several times. If that problem has been rectified, then the system is very well.”
This finding is not surprising as innovation that are perceived as less complex, with
fewer barriers to be overcome, will be assimilated more easily (Rogers, 1995).
Hence, interventions to reduce the number and extent of such response barriers will
potentially improve the chances of successful adoption (Greenhalgh et al., 2004).
Rogers (1995) argued that the difference in perceptions of complexity by
teachers also depends on which five adopter categories along the continuum of
innovativeness the adopters belong to: innovators, early adopters, early majority, late
majority, and laggards. Furthermore, Geoghegan (1994) reported that in the context
of adoption of technology by teachers in classrooms, early majority teachers are
more concerned with the teaching and learning problems being addressed than the
technology used to address them; hence, these teachers view ease of use as critical.
Early majority teachers want proven applications with a low risk of failure,
compared to early adopters (teachers generally self-sufficient and interested in

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technology itself) who are more willing to take risks and experiment with technology
(Geoghegan, 1994).

Finding 3: Personal comfort level with technology affects respondents’
sense of preparedness to use and integrate technology into teaching upon
graduation.
A vast majority of respondents (92.5%) indicated that they plan to use and
integrate technology into their own classroom when they graduate from the
MAT@USC program. Many of them also indicated that the use of technology in the
MAT@USC program is relevant to their future teaching career and will improve
their task performances on the job (77.2%). Participants in this study also agreed that
their personal comfort level with technology helped them feel prepared to use and
integrate technology in teaching and learning (79.4%).
During the interview, a respondent attributed his own comfort level with
technology as the single most important factor for him to use instructional
technology in his teaching. However, he also expressed that his own technical skills
alone is insufficient to guarantee the effective use of technology in classroom. In the
interview, he said:
My own familiarity and experience with technology allow me to assess its
effectiveness. I am able to problem solve locally on my own without
involving tech support. I think part of the MAT education is shaping the
minds of candidates to think like teachers… viewing the world through
pedagogical or androgogical lens. Perhaps a week of direct instruction on
specifically integrating technology into the classroom would be a good idea

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to add to the program. Even though I am tech-savvy, I don’t naturally think
of the educational implications of tools like vlogs, wikis, etc.

This view is supported by Angeli and Valanides (2009), who suggested that teacher
educators need to explicitly teach how the unique features or capabilities of a tool for
educational technology can be used to transform specific content domain for specific
learners, and that teachers need to be explicitly taught about the interactions among
technology, pedagogy, content, and learners. In order to translate skills into practice,
teachers need specific ideas about how to use these skills to achieve meaningful
learning outcomes under normal classroom conditions (Carvin, 1999;
Marcinkiewicz, 1994).
Being able to see how instructional technology can be used to engage
students was also another factor cited as a reason to use instructional technology in
the classroom:
I felt extremely confident about my computer skills before heading into the
program. I enjoy working with computers and I am an avid user of social
media – it was one of the main reasons why I chose to enroll in an online
course over a traditional program. I want to engage students. When students
are engaged, meaningful learning occurs more easily. In my opinion, I
learned the most about theories and strategies in the MAT@USC by
implementing them in my own student teaching. Thus, integrating a
technology assignment/course/requirement into the curriculum would benefit
teacher candidates. For instance, including a technology component in a
lesson plan assignment. While the program’s instructors did not specifically
teach me how to use and integrate technology into my own teaching, the
classes they did teacher provided a grounds for sharing many useful
resources. I feel like my colleagues and being in the program itself prepared
me for integrating social media into my future classroom.

A study conducted by Moursund and Bielefeldt (1999) found that the best way for
new teachers to attain technology proficiency is to integrate technology into all

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course work. This is what the online MAT@USC program does. As teachers prepare
to enter their own classrooms to teach, the opportunity to observe how technology is
being used for instruction and to see their own professors model what they will be
expected to do in the future will enhance teacher’s sense of preparedness (Clark,
1994).
Another teacher candidate said during the interview:
Great lessons begin with a clear understanding of the desired outcome, and
student centered learning. Learning to plan these kinds of lessons first and
then bringing in the technology piece as an adjunct is essential. Otherwise,
one may end up with technology for technology’s sake, and we’ve all sat
through PowerPoint presentations that are just boring and pointless lectures.
Each program and tech tool is different and has its own set of
comfort/discomfort issues. In my case, email, conference calls, PowerPoint,
Word, and Excel are all tools that I use regularly and feel comfortable with
— even though there are aspects in each that I don’t know very well (tables
in Word, animations in PowerPoint, and formulas in Excel) — if asked to use
these tools within the programs then I have to learn and relearn as the
programs change. It’s a process of learning and re-learning that I can handle.
I intend to focus on the tools the students are already using so that they can
feel comfortable with the technology, and if possible share them with other
students. If I could, I would make sure that a word processing program is
used in class, do polls on cell phones, email student work, and have them go
to websites for homework. But this will depend on the administration, the
student’s resources and the school site. Otherwise, I will be inviting trouble
if students are using cell phones to translate words in a class when they are
not allowed to use them on campus. There is a huge gap within each class,
each school, and each district.

Ertmer (2003) suggested that unless teachers believe that they are capable of
implementing them in the classroom, even the best ideas about technology use will
remain unused. In particular, teachers' beliefs about their ability to use computers in
instruction may be key, given the role self-efficacy is proposed to play in
determining behavior. Teachers’ values, norms, and beliefs are also continually

105
shaped by their ongoing experiences as teachers, by the values and opinions
expressed by their peers, and by the expectations of influential others, all of which
are transmitted through formal and informal norms, rules, and procedures (Becker
&Riel, 1999). Hence, besides teachers’ self-efficacy, compatibility with
organizational or professional norms, values and ways of working is an additional
determinant of successful assimilation of innovation (Ferlie et al., 2001).

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CHAPTER FIVE
DISCUSSION, CONCLUSION AND RECOMMENDATION
This section begins with a brief overview of the problem and purpose of the
study. Next, findings of the study and implications for practice and research will be
discussed. Finally, recommendation for future studies and conclusions of the study
will be presented.

Overview of the Problem
Despite the fact that billions of dollars have been spent in purchasing,
equipping and supporting technology, education has been slow to catch up on the use
of instructional technology. Moreover, research has shown that increased access to
technology at schools has not translated into significant educational gain (McGrail,
2005; Selfe, 1999). While there are many theories as to why increased access to
technology has not resulted in proportionate educational gains, Christensen (2008)
and Rosen (2010) posit that one of the reasons is because teachers are not prepared to
use these technology in their classrooms and if they are, they are using them to do
low-level tasks that are not student-centered (Christensen, 2008; Rosen, 2010). In
order for instructional technology to transform teaching and learning, they need to be
integrated in the classroom with the intention of disrupting and fundamentally
altering current instructional environment, so that teaching and learning occur
differently than before the technology was introduced (Neuman, 1990).

107
Since teachers are not passive recipients of innovation when presented with
choices of whether to use technology in their own classrooms, Jacobsen (1998)
suggested that teachers’ adoption patterns are also influenced by their knowledge and
personal use of computers, availability or lack of technical support and training, and
also support by their peers. Hence, teacher education programs play an integral role
in preparing teacher candidates with the skills, knowledge, motivation and support
needed, in order to harness the power of instructional technology (Handler, 1992).
Considering that teacher candidates graduating from teacher education programs will
be teaching in classrooms and impacting student learning outcomes for potentially
the next 30 years, it is critical to ask if today’s teacher education programs are
preparing new teachers to incorporate technology into their classrooms and
instruction.
Therefore, the purpose of this study was to explore teacher candidates’
perceptions of computer technology usage in classrooms; their perceptions of the use
of technology in their teacher education program; and whether they feel that their
teacher education program prepares them to use computer technology effectively in
their classrooms. Specific research questions include:
 How do teacher candidates perceive the use of computer technology in
classrooms, and to what extend do their dispositions about technology
relate to their age, gender, teaching experience and location (in California
versus out of state)?

108
 What factors are perceived by teacher candidates as barriers to the
adoption of technology in teaching (lack of knowledge, motivation,
resources and rewards), and to what extend do they relate to teachers’
age, gender, teaching experience and location?
 What attributes of an online teacher education program are perceived by
teacher candidates as innovative, and to what extent do these attributes
relate to their sense of preparedness to adopt technology upon graduation
from the program?
This study provides insights into teacher candidates’ perceptions on the use
of instructional technology, factors as well as barriers for using instructional
technology, and whether experiences with innovative technology in teacher
preparation program help prepare new teacher candidates to integrate technology
into their classrooms. To study these factors, this study employed both quantitative
and qualitative methods. A cross-sectional study was done using a one-time survey
questionnaire, which was sent to all students of the online teacher education
program. Furthermore, a follow-up interview invitation was sent out to a smaller
sample, with students randomly selected from the student database. Together, the
data presented a richer picture of how teacher candidates perceived the use of
technology in classrooms, barriers to adoption of technology, attributes of an
innovative teacher education program and to whether they affect teacher candidates’
sense of preparedness.

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Findings of the Study
The first research question involves teacher candidates’ disposition about
technology and their perceived use of technology in classrooms. The data from the
survey showed that teacher candidates in the MAT@USC program have positive
attitudes towards technology, are highly receptive to the use of technology in
education, and have high levels of personal comfort with technology prior to entering
the program. Participants also believed that computers provide learning benefits that
will help students with learning tasks such as writing, analyzing data, or problem
solving. This is consistent with Jacobsen’s (1998) findings that the highest rated
incentives for using instructional technologies were related to providing enriched
learning opportunities for students and personal gratification teachers get when
learning new computer knowledge and skills. The qualitative data likewise
confirmed that teacher candidates believed that the use of technology is compatible
with their own teaching philosophy and that computer literacy is increasingly more
important for today’s students. Finally, attitudes towards technology differed by age
and location in which teacher candidates plan to teach. In this study, more positive
attitudes about technology were found as age increases. This finding contradicted
with Handler’s (1993) study in which age was reported as not a significant factor in
discriminating between teachers who believed they were prepared versus those who
were not. Qualitative data suggested that older participants viewed technology
favorably, even though their own comfort level with technology may be lower than
those of their younger counterparts, because they perceived technology as a norm in

110
the classroom today, and that there is a need to keep up with their students and peers.
More positive attitudes about technology were also reported by teacher candidates
who plan to teach in the state of California versus those who plan to teach out of
state. Qualitative data suggested that funding and access to technology based on
school districts may have influenced some of the respondents’ attitudes towards the
use of instructional technology. For example, the California State Board of
Education’s Education Technology Planning encourages districts to focus on using
technology to improve student achievement and to develop components of the
technology plan.
The second research question involves factors perceived by teacher
candidates as barriers to the adoption of instructional technology. Overall, lack of
resources was perceived as a top barrier to integration of technology. The data from
the survey showed that teacher candidates in the MAT@USC program ranked the
following as top five barriers to integration: too few computers for the number of
students, problems scheduling enough computer time and/or resources for different
teachers’ classes, inadequate financial support for the development of instructional
uses of computers, inadequate financial support for computer integration, and
scarcity of printers and/or other peripherals. This is consistent with Kay (2006) who
posits that good access to software, hardware and support is necessary to integration;
without good access, it is unlikely that other strategies will work. The qualitative
data likewise confirmed that teacher candidates perceived lack of funding as a direct
cause for lack of access to technology. Several respondents also noted that barriers to

111
integration of technology depend on the school districts, with teachers entering low
SES districts having less access to resources needed for integration. Finally, attitudes
towards barriers to integration of technology differed by age and gender of teacher
candidates. In this study, respondents aged 30 – 40, and those over 40 perceived lack
of resources as a greater barrier than younger respondents. Older respondents also
perceived lack of rewards as a higher barrier than their younger counterparts. Female
respondents in the survey perceived the lack of resources as a greater barrier than
their male counterparts. Female respondents also perceived lack of knowledge of
how to use technology as a greater barrier to integration. This difference in gender
may be due to the fact that 74% of the survey participants are female, as opposed to
26% are male. Overall, respondents were motivated to integrate technology;
however, lack of resources and lack of knowledge may prevent integration of
technology. According to the literature, organizational barriers that may affect
teachers’ adoption of technology include school leadership, school scheduling,
school planning and funding (Fox & Henri, 2005). Furthermore, lack of school
planning with regard to technology, limited access, and rigid school schedule
constrains the variety of learning modalities that teachers can design (Becker, 2000).
The third research question involves teacher candidates’ perceptions of the
innovative attributes of their online teacher education program, and whether these
attributes relate to their sense of preparedness to adopt technology upon graduation
from the program. In general, the findings show that majority of the respondents in
the survey perceived technology used in the MAT@USC program as innovative and

112
highly collaborative. The qualitative data likewise confirmed that respondents
perceived the use of live video camera during class, online break out groups, and the
videotaping of lessons as some of the technological tools that make the online
MAT@USC program innovative. A few respondents noted that the use of
technology in the online MAT@USC program makes the classroom more interactive
and supportive than the traditional classroom. However, many of the respondents in
the survey also voiced their concerns with regards to technological issues
encountered when using the online platform. Frustrations with technical issues seem
to dampen teacher candidates’ enthusiasm for the use of technology, but once those
issues are resolved, students rated the program higher. Interventions to reduce the
number and extent of technological issues will potentially improve the chances of
successful adoption of technology by teacher candidates. Finally, personal comfort
level with technology prior to entering the program also affects respondents’ sense of
preparedness to use and integrate technology into teaching upon graduation. Handler
(1993) reported that several factors contributed to a feeling of preparedness to use
technology among teachers; one of them being teachers’ personal comfort level with
technology prior to entering the program or taking an introductory course. Majority
of respondents in this study also reported the use of technology in the MAT@USC
program as relevant to their future teaching career and will improve their task
performances on the job. Those who were interviewed suggested that including a
technology component in lesson plan assignments and in the curriculum would
benefit teacher candidates. This is consistent with findings by Moursund and

113
Bielefeldt (1999) who found that the best way for new teachers to attain technology
proficiency is to integrate technology into all course work. Clark (1994) found that
as teachers prepare to enter their own classrooms to teach, the opportunity to observe
how technology is being used for instruction and to see modeling of what is expected
of them by their professors, will enhance teachers’ sense of preparedness.
To summarize, the findings of this study correlated with the findings of the
literature regarding the relationship between teacher candidates’ attitudes and
personal comfort level towards technology and their sense of preparedness in
integrating instructional technology. Findings of this study on the top perceived
barriers of integration also correlated with findings of the literature regarding
organizational barriers, school leadership, access to resources, and teacher’s adoption
of technology. Last but not least, findings on teacher candidates’ preparedness to
adopt technology learned in their teacher education program are also consistent with
Rogers’ (1995) studies on the diffusion of innovation, which identified five major
attributes which affect adoption: relative advantage, complexity, compatibility,
observability, and trialability.

Implications
The findings of this study lead to several recommendations for action by
teacher educators, teacher candidates, and school administrators in order to prepare
and encourage new teachers to use instructional technology to improve student
learning outcomes in their classrooms. Findings from this study identify factors that

114
will improve teachers’ sense of preparedness to use technology, organizational
barriers that may hinder use of instructional technology in classrooms, and
opportunities for teacher educators to improve online teacher education programs.
Teacher educators, teacher candidates, and school administrators should consider the
following:
1. The study suggested that teacher candidates with high levels of personal
comfort with technology tend to have positive attitudes towards
technology, are highly receptive to the use of technology in education,
and feel more prepared to use and integrate instructional technology. It
seems likely that teachers' self-efficacy for teaching with technology
depends, in part, on their self-efficacy for personal use of computers
(Albion, 1999). Hence, assisting teacher candidates to develop self-
efficacy for use of instructional technology is a vital step towards their
learning to use technology effectively in their teaching. Thus, teacher
educators need to find ways to encourage teacher candidates to spend
more time using computers. New teachers who are unfamiliar with
technology should spend more time experimenting and using technology
in their personal life to increase their self-efficacy for teaching with
technology.
2. This study found that lack of access to resources is a serious
organizational barrier towards successful integration of technology. In
other words, a supportive school environment is important for successful

115
technology integration as teachers need access to a healthy human
infrastructure and a functional and convenient technical infrastructure
(Zhao et al., 2002). If the integration of technology for teaching and
learning is a valued institutional goal, school districts and administrators
must recognize that in order to drive change, they will have to improve
easy access to resources, address the reward system and commit to a
system-wide investment in infrastructure and technical support (Jacobsen,
1998).
3. This study revealed that although there has been great progress in
bringing computers and networks to schools in recent years, access to
technology differ greatly between school districts. In many low SES
schools, teachers did not have easy access to technology nor
technological support. This digital divide is further fueled by the
quickening pace of technology. According to Pandolfo (2012), the term
"digital divide" was once used to compare classrooms that had computers
connected to the Internet, and those that do not. Now, as newer
applications and software programs require high-speed connections, and
WiFi-dependent hardware devices such as iPads and tablets make their
way into classrooms, the “digital divide” gap is wider than ever.
According to a 2010 report from the National Center for Education
Statistics, nearly every U.S. school has at least one instructional computer
with Internet access, with a ratio of 3:1 students for every computer

116
connected to the Internet. However, Pandolfo (2012) argued that on
almost every measure, ratios were worse in high-poverty schools, where a
high percentage of students are eligible for free or reduced-price lunch.
For administrators and policy makers, this has two implications: one,
annual funding on technology needs to be distributed equitably; two,
school leaders need to re-examine their budgets and allocation of funds to
ensure that urban schools have sufficient access to technology and
technical support.
4. Findings from this study also indicated that teacher candidates perceived
lack of resources as the number one barrier to integration of technology.
In this economic time where budgets have shrunk across the board for
most schools, teachers need to be more creative in their use and
deployment of technology in classroom. For example, instead of
purchasing expensive SmartBoards, which are popular tools in schools,
the resources would be better spent on purchasing iPads or laptops for
teachers and connecting them to existing projectors to achieve the same
learning effects as the interactive SmartBoards, but at a fraction of the
cost. Due to shrinking budgets, teachers need to be innovative with their
technology use and not let lack of resources be a deterrent to using
technology in class.
5. This study suggested that certain attributes of innovation and strategies
used in the online MAT@USC teacher education program have positive

117
effect on teacher candidates' attitudes, ability and preparedness to use
technology in classroom. These attributes of innovation, which affects
adoption of technology are: relative advantage of the program and
technology; complexity and ease of use; compatibility with teacher
candidates’ teaching philosophy; observability through modeling by
instructors and peers; and trialability through hands-on authentic teaching
activities (Rogers, 1995). Teacher educators need to keep these attributes
in mind when designing or incorporating technology education into
preservice or teacher education. In addition, Kay (2006) suggested that all
teacher education programs that wish to incorporate technology as part of
its curriculum should consider the following ingredients: ease of access to
technology and support, modeling and authentic teaching activities, and
collaboration between mentor and peers. Although technology is viewed
as an innovative tool in teaching and learning, most teachers get
frustrated when technology does not work. Hence, it is very important to
have a reliable system and a good 24/7 technical support.

Recommendations for Future Study
This study is limited in scope and time. First, it is recommended that future
studies on the perceptions and use of instructional technology by teachers and
teacher candidates be expanded for eventual generalizability. USC is one of the
leading private research universities in the United States, located in Los Angeles,

118
California. The MAT@USC program is an “award winning” online teacher
education program, which has won numerous awards for its innovative curriculum,
delivered 100% online through the use of cutting edge technology (Roshell, 2010).
Should a new study choose to include students from other online teacher education
programs, both in California and nationwide, a more thorough analysis may be
conducted that would have implications for a broader set of institutions.
Secondly, data collected in this study was limited because the
instrumentations only collected self-reported data about perceived use of
instructional technology practices, overall attitude toward the use of instructional
technology in teacher preparation, attitudes toward the use of instructional
technology by teacher education candidates, and influencing factors and barriers to
integrating technology as identified by the survey instruments. Future research
should include detailed data on other factors such as technology support, frequency
of use, and instructional technology preferences, which were not the focus of the
investigation of this study, and were not collected.
Third, data collected in this study provide an insight into the frustration faced
by teachers teaching in schools without proper access to technology and other
infrastructure support. While this is a huge barrier to the integration of technology
into learning, it also highlights a bigger problem of inequity between the haves and
the have-nots. Future study should explore the disparities among schools at the
district, state, and national level to estimate the actual costs of the digital divide, in
terms of student learning outcomes, college-preparedness, and graduation rates. It is

119
also recommended that future studies employ an evidence based model to compare
technology spending versus academic achievements among different schools to
justify for the use of instructional technology in schools.
Fourth, the findings of this study also suggest that there is much research yet
to be conducted to learn more about how implementation of new technological
resources, such as tablets, iPads, e-texts, etc. could lead to potentially more efficient,
effective, environmentally responsible and cost effective learning environment. It is
recommended that future researchers of technology in teacher education explore the
attitudes and use of new technology by the 21
st
century teacher, whose goal is to
make learning significant to the 21
st
century mind of students in a globalized,
interconnected society.

Conclusion
Teacher education programs play an integral role in equipping teacher
candidates with the skills, knowledge, motivation and support needed. The National
Council for Accreditation of Teacher Education (NCATE) emphasized the important
role of teacher education programs in the preparation of teacher candidates to
integrate technology in their classrooms. Considering that teacher candidates
graduating from teacher education programs will be teaching in classrooms and
impacting student learning outcomes for potentially the next 30 years, today’s
teacher education programs must be innovative and effective in preparing teachers to
preparing new teachers to practice instructional technology in classroom settings.

120
This study aimed to analyze a small population of teacher candidates, those graduate
students at the online MAT@USC program, in order to determine their disposition of
technology, barriers that hinder integration, and attributes of an innovative teacher
education program that affects teachers’ sense of preparedness to integrate
technology. This study was limited in scope, and as a result, not generalizable to the
larger population. However, for teacher educators, school administrators and new
teachers, this study provided useful suggestions for integration of technology in
teaching and learning. Future studies should broaden and expand the research to
allow for greater generalizability, as well as to address the digital divide among
schools.

121
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APPENDIX A
SURVEY INSTRUMENT
Teacher Candidates as Adopters of Innovation (Computer Technology)
The purpose of my study is to explore whether the MAT@USC online teacher
education program is perceived as innovative and preparing teacher candidates to
integrate technology into classrooms and instruction.

The purpose of this survey is to gather information about teacher candidates’
perceptions of knowledge of computer technology, self-efficacy, attitudes toward
teaching and learning with instructional technology, incentives, and barriers to usage.

Participant Information

The intent of this section is to obtain some information about individuals who
respond to this survey. Information gathered about participants will be treated
confidentially, and only GROUP data will be reported as an outcome of this
research.

1. What is your age (years)?
2. What is your gender?
 male
 female
3. Did you have any teaching experiences prior to enrolling to the teacher
education program?
 Yes
 No
4. How many courses have you taken at the MAT@USC?
5. Where do you plan to teach upon graduation from the teacher education
program?

133
Perceptions of Computer Use in
Classroom (Selected response)

Some research has indicated that technology has “no learning benefits” on student
learning outcomes (Clark, 1994), while others posit that technology may improve
learning, given its interactive capabilities (Kozma, 1994).

Please read each of the following statements, and then indicate the level of your
agreement as to how the integration and use of technology for teaching and learning
changes the K-12 classroom environment.

(1) Strongly Agree (2) Agree (3) Neutral (4) Disagree (5) Strongly disagree

1. Computers are a tool that helps students with learning tasks, such as writing,
analyzing data, or solving problems.
2. Students are enthusiastic about the subjects for which they use computers.
3. Computers enable me to make a subject more interesting.
4. Technology tools enable me to better diagnose learning problems.
5. I get personal gratification from learning new computer knowledge and skills.
6. Computers provide a means of expanding and applying what has been taught.
7. Computer tools enable me to communicate and interact more with students.
8. By integrating technology, I am helping students to acquire the basic
computer education they will need for future careers.
9. I enjoy figuring out how to use computers effectively for a variety of teaching
situations.
10. Computers provide more opportunities for gifted students.
11. Technology tools enable students to help each other and cooperate on
projects.
12. Computers provide an environment that appeals to a variety of learning
styles.

134
Barriers to Integrating Technology for
Teaching and Learning (Selected
response)

Many teachers are highly motivated to integrate computers for teaching and learning.
Although teachers have developed impressive expertise in using computers in their
classrooms, to a greater or lesser extent all teachers experience barriers when they
attempt to use and integrate computers in their teaching.

In your opinion, how significant is each of the following barriers, as identified in
previous research (Jacobsen, 1998), to the use of computers for teaching and learning
in the campus environment?

(1) Strongly
Agree, a major
barrier
(2)
Agree
(3)
Neutral
(4)
Disagree
(5) Strongly
disagree, not a
barrier

1. Teachers lack enough time to develop instruction that uses computers.
2. There are problems scheduling enough computer time and/or resources for
different teachers’ classes.
3. Hardware is unstable and always breaking down.
4. The reward structure does not recognize teachers for integrating computers
for teaching and learning.
5. There are too few computers for the number of students.
6. There are too few computers for individual teacher.
7. There is a scarcity of printers and/or other peripherals in order to effectively
use computers for teaching and learning.
8. There is not enough time in the course schedule for computer related
instruction.
9. There is limited research literature that shows significant improvements in
learning as a result of computer integration.
10. Financial support for computer integration from administration is inadequate.
11. There is not enough support for supervising student computer use.

135
12. There is inadequate financial support for the development of instructional
uses of computers.
13. Teachers are not interested in using computers for instruction.
14. I am unsure how to effectively integrate computers into instruction.
15. Available software is not adaptable to my instructional needs.
16. Computer manuals and materials are inadequate and unhelpful.
17. There are too few training opportunities for teachers to acquire new computer
knowledge and skills.
18. There is less control over classroom instruction when using computers.
19. Computers do not fit the course or curriculum that I teach.
20. There is no recognition for using computers for K-12 teaching and learning.

136
Attributes of Innovative Teacher
Education Program (Selected response)

One of the goals of the current research project is to gather additional information
about preservice teachers’ perceptions of the use of technology in their teacher
education program.

In your opinion, how relevant is each of the following attributes, as identified in
previous research (Rogers, 1995), to the adoption of instructional technology as an
innovation?

(1) Strongly Agree (2) Agree (3) Neutral (4) Disagree (5) Strongly disagree

1. The online format and delivery of the MAT@USC program offers relative
advantages to a campus-based program.
2. The use of technology in the MAT@USC program is relevant to my future
teaching career and will improve my task performance on the job.
3. The use of technology is compatible with my own values, norms and teaching
philosophy.
4. The platform and software used in the teacher preparation program is easy to
use.
5. I was able to experiment with and practice how to use the software prior to
the start of the course.
6. I was given sufficient time to learn how to use the software needed to be
successful in this program.
7. The technology used for this course was modeled to me by my professors.
8. I was encouraged to collaborate with my peers and professor throughout the
course.
9. I was given sufficient access to technological support if I needed any
assistance.
10. I find the technology used in the MAT@USC program as innovative, useful
and cutting-edge.

137
Factors Contributing to Teachers’ Sense
of “Preparedness” (Selected Response)

According to Handler (1993), several factors contribute to a feeling of preparedness
among teachers.

In your opinion, how relevant is each of the following attributes, as identified in
previous research (Handler, 1993)), to your own sense of feeling prepared to use and
integrate technology into your own teaching when you graduate?

(1) Strongly Agree (2) Agree (3) Neutral (4) Disagree (5) Strongly disagree

1. The value of having a separate course on introduction to computers in
education helped me feel prepared to use technology.
2. The degree to which technology was used in this program helps me feel
prepared to use technology.
3. I was given the opportunity to observe the use of technology in the teaching
field and that helps me feel prepared to integrate technology myself.
4. My personal comfort with technology prior to entering the program help me
feel prepared to use and integrate technology in teaching and learning.
5. I plan to use and integrate technology into my own classroom when I
graduate from the MAT@USC program.

Additional comments: I invite you to use the space below to comment on any item in
this questionnaire about which you would like to elaborate on your responses or
positions.

END OF SURVEY

138
APPENDIX B
INTERVIEW QUESTIONS
Teacher Candidates as Adopters of Innovation (Computer Technology)
Interview Questions for students of MAT@USC
The purpose of my study is to explore whether today’s teacher education programs
are innovative and preparing teacher candidates to integrate technology into
classrooms and instruction.

The purpose of this interview is to gather information about students’ perceptions of
their knowledge of computer technology, self-efficacy, attitudes to teaching and
learning with instructional technology, incentives, and barriers to usage.

DEMOGRAPHIC INFO:
1. What is your age?
2. What is your gender?
3. Where is your current location? (CA or out of state?)
4. Did you have any teaching experiences prior to enrolling to the teacher
education program? If so, how many years?
5. How many courses have you taken in the MAT@USC program?

ATTITUDE TOWARDS TECHNOLOGY:
1. How comfortable are you in using computer technology to complete your
assignments at the beginning of the course?
2. Do you feel that your level of comfort and ease with technology increase
during the duration of the course? If so, does any part of the program aids
with your comfort and attitude towards instructional technology?
3. What are some barriers that you think may hinder you from integrating
technology into teaching?

139
4. What is the single most influential factor for you to use instructional
technology in your own teaching?
5. How can teacher education program help teacher candidates feel prepared to
integrate technology into their own classroom?

MAT@USC PROGRAM:
1. Do you perceive the MAT@USC program as an innovative teacher education
program? If so, what attributes of the program do you perceive as innovative?
2. Does your own personal comfort level prior to entering the program affect
the way you view use of technology in the MAT@USC program? How and
in what ways?
3. What are some of the software/tool from the MAT@USC program that you
can use/integrate into your own classroom teaching in the future?
4. Do you feel that the MAT@USC program adequately prepare you to use and
integrate technology into your own teaching? How and in what ways?
5. Do you plan to adopt instructional technology into your own teaching upon
graduation from the program? If so, how and in what ways?

Asset Metadata

Creator Chong, Han Nee (author)

Core Title Perception and use of instructional technology: teacher candidates as adopters of innovation

Contributor Electronically uploaded by the author (provenance)

School Rossier School of Education

Degree Doctor of Education

Degree Program Education (Leadership)

Publication Date 03/21/2012

Defense Date 02/25/2012

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

Tag adoption of innovation,barriers to integration,Instructional Technology,OAI-PMH Harvest,online courses,Teacher education

Language English

Advisor Brewer, Dominic J. (committee chair), Picus, Lawrence O. (committee member), Sundt, Melora A. (committee member)

Creator Email hannee@hanneechong.com,honeydee21@yahoo.com

Permanent Link (DOI) https://doi.org/10.25549/usctheses-c127-676229

Unique identifier UC1385112

Identifier usctheses-c127-676229 (legacy record id)

Legacy Identifier etd-ChongHanNe-537.pdf

Dmrecord 676229

Document Type Dissertation

Rights Chong, Han Nee

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

Repository Email uscdl@usc.edu

Abstract (if available)

Abstract Education has been slow to catch up on the use of instructional technology. Despite the fact that billions of dollars have been spent in purchasing, equipping and supporting technology, increased access has not translated into significant educational gain (McGrail, 2005