Close
About
FAQ
Home
Collections
Login
USC Login
Register
0
Selected
Invert selection
Deselect all
Deselect all
Click here to refresh results
Click here to refresh results
USC
/
Digital Library
/
University of Southern California Dissertations and Theses
/
Confidence is key: peer observations and online teacher self-efficacy in higher education
(USC Thesis Other)
Confidence is key: peer observations and online teacher self-efficacy in higher education
PDF
Download
Share
Open document
Flip pages
Contact Us
Contact Us
Copy asset link
Request this asset
Transcript (if available)
Content
Confidence Is Key: Peer Observations and Online Teacher Self-Efficacy in Higher
Education
By
Joshua Eric Rivera
Rossier School of Education
University of Southern California
A dissertation submitted to the faculty
in partial fulfillment of the requirements for the degree of
Doctor of Education
August 2022
© Copyright by Joshua E. Rivera 2022
All Rights Reserved
The Committee for Joshua Eric Rivera certifies the approval of this Dissertation
Erika Patall
Thomas Cummings
Robert Filback, Committee Chair
Rossier School of Education
University of Southern California
2022
iv
Abstract
The purpose of this mixed-methods study was to investigate the perceived role that peer
observations have on online teacher self-efficacy beliefs. The theoretical framework for this
study includes Kolb’s experiential learning theory, Schön’s theory of reflective practice, and
Bandura’s self-efficacy model. The research questions investigate the role that Gosling’s
collaborative reflection model of peer observation has on higher ed online teachers’ self-efficacy
beliefs as well as the perceived benefits and challenges associated with this observation model’s
implementation. A total of six higher education faculty, all of whom had varying degrees of
online teaching experience, participated in this study. The survey used for this study was the
Michigan Nurse Educators Sense of Efficacy for Online Teaching, which uses factor analysis to
confirm four factors for self-efficacy. The results of the pre- and post-survey responses show no
significant difference in self-efficacy factors. However, data from the interviews show that the
attitudes and perceptions of both novice and expert online faculty confirm that participation in
Gosling’s peer observation model had an impact on their self-efficacy beliefs. Additional
findings from the interviews suggest that peer observations present many logistical challenges;
however, the benefits have the potential to foster an environment where teacher collective
efficacy can take root and flourish.
Keywords: self-efficacy, online learning, teacher observations
v
Dedication
To the three most inspirational women in my life: my wife, Adri; mom, Caridad; and nana,
Raquel. You three are my greatest supporters, cheerleaders, and mentors. When the road got
difficult, and I did not think I could continue, you pushed me to believe in myself.
To my kids, Dani and JJ. It is the greatest honor to be your dad and I cannot wait to see how the
million dreams that keep you up at night become the world you are going to make.
vi
Acknowledgements
I would like to express my sincerest appreciation to my chair, Prof. Rob Filback and
committee members, Prof. Erika Patall and Prof. Tom Cummings. I am also deeply grateful to
the coaches and mentors who have helped me along the way, including Craig Polin, Mike
Esparza, and Edmundo Litton. Finally, this achievement would not have been possible without
the love and support of my brothers, Rudy and Jeremiah. Though we did not have much growing
up, we had each other.
vii
Table of Contents
Abstract .......................................................................................................................................... iv
Dedication ....................................................................................................................................... v
Acknowledgements ........................................................................................................................ vi
List of Tables ................................................................................................................................. ix
List of Figures ................................................................................................................................. x
Chapter One: Overview of the Study .............................................................................................. 1
Statement of the Problem .................................................................................................... 2
Purpose of Study ................................................................................................................. 4
Methodology ....................................................................................................................... 5
Significance of the Study .................................................................................................... 5
Limitations .......................................................................................................................... 6
Delimitations ....................................................................................................................... 7
Definitions........................................................................................................................... 7
Conclusion .......................................................................................................................... 8
Chapter Two: Review of the Literature ........................................................................................ 10
Perspectives on Online Education .................................................................................... 10
Faculty Development in Higher Education....................................................................... 17
Teacher Observations........................................................................................................ 21
Theoretical Framework ..................................................................................................... 29
Chapter Three: Methodology ........................................................................................................ 37
Site Selection .................................................................................................................... 38
Population and Sample ..................................................................................................... 38
Participants ........................................................................................................................ 39
Convergent Parallel Mixed-Methods Design.................................................................... 40
viii
Data Collection ................................................................................................................. 41
Data Analysis .................................................................................................................... 42
Trustworthiness ................................................................................................................. 43
Limitations ........................................................................................................................ 44
Role of the Researcher ...................................................................................................... 44
Conclusion ........................................................................................................................ 45
Chapter Four: Results or Findings ................................................................................................ 46
Findings............................................................................................................................. 47
Pre- and Post-Survey......................................................................................................... 47
Research Question 1 ......................................................................................................... 50
Research Question 2 ......................................................................................................... 62
Summary ........................................................................................................................... 68
Chapter Five: Discussion .............................................................................................................. 70
Discussion ......................................................................................................................... 70
Recommendations ............................................................................................................. 75
Recommendations for Future Research ............................................................................ 79
Conclusion ........................................................................................................................ 79
References ..................................................................................................................................... 81
Appendix A: Interview Protocol ................................................................................................... 90
Closing .............................................................................................................................. 92
Appendix B: MNESEOT Survey .................................................................................................. 93
Appendix C: Email to Department Chairs and Center for Teaching Excellence ......................... 98
Appendix D: Recruitment Flyer.................................................................................................... 99
ix
List of Tables
Table 1: MNESEOT Survey Results 49
Table A1: Interview Questions With Transitions 90
x
List of Figures
Figure 1: Collaborative Model of Peer Observation 26
1
Chapter One: Overview of the Study
In the past year and a half, educational institutions across the globe have been forced to
cancel all face-to-face courses and quickly pivot all instruction to an online format in order to
keep their faculty, staff, and students safe from the spread of the deadly COVID-19 virus. This
transition came naturally for some as many colleges and universities have successful online
programs established and the necessary infrastructure in place to support such programs.
However, there are still many institutions that struggle to adapt to this new form of
instructional modality, especially since most quality online courses require months of careful
planning and development along with significant financial investments (Hodges et al., 2020).
The speed at which the transition from face-to-face to online instruction is unprecedented and,
therefore, forced many faculty to improvise quick solutions in less-than-ideal circumstances. As
a result, many instructors have found this process stressful and inefficient and fear that their
instructional efficacy might hinder students' performance in their course (Ma et al., 2021).
Despite the years of research showing otherwise, many people still believe that online
learning is less effective than face-to-face learning, and the hasty transition online by the
majority of the world’s educational institutions might reinforce this perception. The reality is,
however, that nobody making the transition to online teaching during the COVID-19 pandemic
will be designing and developing their instruction by optimizing the full potential that the online
format affords. Instead, the approach will function more as a stopgap to ensure that students can
receive the instructional materials and assessments needed to acquire and demonstrate learning
until the pandemic has abated. This pedagogical approach is vastly different from effective
online education, and most members of the academic community instead refer to this form of
instruction as emergency remote teaching (Hodges et al., 2020). Even as the pandemic begins to
2
abate and higher education institutions begin the process of welcoming students back to campus,
the lessons learned and experiences gained during the COVID-19 pandemic will have a
permanent impact on faculty, staff, and students across the world’s higher education institutions.
Statement of the Problem
Many online learning advocates feared the quick transition to emergency remote teaching
would leave students with a negative impression of online learning that would leave
administrators questioning their strategic decisions to invest in online learning programs, which
were made prior to the pandemic (Hodges et al., 2020). However, despite the challenges and
limitations associated with this instructional approach, a recent survey conducted by The Digital
Learning Pulse shows that a majority of post-secondary students want the option to continue
studying online post-pandemic (Hodges et al., 2020). Additionally, numerous studies have found
that higher education faculty have experienced various advantages to online teaching that
encourage student-centered learning; however, more training was needed to reinforce the
foundational concepts that were learned during the pandemic (Dhawan, 2020; Mukhtar et al.,
2020). Lastly, educational technology administrators have discovered and implemented
workflows that streamline the online course deployment process as well as systems that ensure a
consistent student experience across departments (Dhawan, 2020). These findings support the
need for higher education institutions to reevaluate their approach to faculty development in
order to meet the instructional and institutional needs and preferences across their multiple
stakeholders.
Additionally, the demand for online program offerings were steadily increasing prior to
the pandemic as higher education institutions continue to observe shifts in the student
demographics that they have traditionally served. The U.S. Department of Education (2017)
3
recently released data that provides insightful information about the profile of online students at
the undergraduate level. One key trend that emerged from this data is the older the student, the
more likely they are to be pursuing a fully online degree (Campbell & Wescott, 2019). For
example, among all undergraduate students aged 30–39 in U.S. higher education, 23% are
pursuing a fully online program, which is six times the rate of traditionally aged undergraduates.
Furthermore, students who are working full-time are also more likely to enroll in fully online
degree programs (Campbell & Wescott, 2019). U.S. News & World Report confirmed this data
by conducting its own study and reports that the average age of an online student is 32, and 84%
of students enrolled at the bachelor’s level are currently employed (Friedman, 2017). These
trends suggest that online students tend to be working adults who are often pursuing education
for career-related reasons. If higher education institutions are to fulfill their promise by creating
spaces that promote lifelong learning, then faculty need to feel empowered to reach these non-
traditional students through a non-traditional format.
Recognizing the increase in demand for online course offerings, higher education
institutions have positioned online educational delivery as a top academic priority and central to
their strategic plans in order to meet the needs of today’s students. In 2019, Inside Higher Ed and
Gallup produced a national survey that was distributed to chief academic officers (CAOs) across
the country and found that 83% planned to increase their emphasis on growing online programs
and offerings (Lederman, 2019). Additionally, the survey found that CAOs intend to make
greater academic investments in online education, with 56% strongly agreeing that they plan to
allocate major funding to online programs in 2019, up from 46% just 4 years earlier (Gallagher,
2019).
4
Though the trend in higher education has been to increase online and hybrid course
offerings, the current COVID-19 pandemic has expedited this process and forced most if not all
post-secondary institutions to go fully online. During this transition, a disproportionate amount
of faculty has shared concerns about their ability to positively impact student learning through
this new instructional medium (Ma et al., 2021). This problem is perpetuated by the isolating
nature of teaching online in higher education, which is particularly true for part-time faculty
(Allen & Seaman, 2007; McLean, 2005). Additionally, many institutions have invested a
significant amount of time, money, and resources to effectively make this transition indicating a
commitment to moving forward using this format (Hodges et al., 2020). These challenges, if not
ameliorated, can have detrimental effects on teacher satisfaction, retention, and stress levels,
which ultimately, and more importantly, impact student success (Bandura, 1997; Ma et al., 2021).
Purpose of Study
This study employs Bandura’s (1997) social cognitive theory framework to explore the
perceived role that peer observations have on higher ed online faculty’s teacher self-efficacy
beliefs. The goal of this study is to inform future research on using peer observations as an
intervention strategy for impacting online teacher self-efficacy beliefs. According to Zimmerman
(2002), self-efficacy refers to an individual’s belief about their capacity to perform or execute
behaviors at a particular level. The information that people use to assess their self-efficacy comes
from four sources which include mastery experiences, based on their interpretations of actual
performance; vicarious experiences, based on modeled performance; forms of social persuasion
based on feedback learners receive from others; and physiological indexes, based on feelings
about their personal abilities in a particular situation (Bandura, 1997). This mixed-methods study
uses these four aspects as a lens to investigate the perceptions of higher education faculty about
5
the influence of peer observation experiences on their online teaching self-efficacy beliefs.
Gosling’s (2005) collaborative reflection model of peer observation was used to inform this
study’s intervention program. Additionally, an investigation into the perceived benefits and
challenges associated with the peer observational model will also be included in the study.
Methodology
Two research questions guided this study:
1. What is the perceived role that the collaborative reflection model of peer observation
has on higher ed online teachers’ self-efficacy beliefs?
2. What are the perceived benefits and challenges associated with this observation
model’s implementation?
I used a convergent mixed-methods approach to collect both qualitative and quantitative
data, analyzed them separately, and then compared the results to determine if the findings
confirm or disconfirm each other (Creswell & Creswell, 2017). The instrument that was used to
measure teachers’ self-efficacy beliefs was the Michigan Nurse Educators Sense of Efficacy for
Online Teaching Survey (MNESEOT). The qualitative data for this study was collected in the
form of semi-structured interviews using an interview protocol to guide the conversation.
Significance of the Study
This study is significant to the field of higher education because the demand for online
programs continues to increase as student demographics continue to shift, surfacing a need to
identify developmental programs that will prepare faculty to be more efficacious online
instructors. A disproportionate amount of faculty in post-secondary education lacks the desire
and confidence to effectively teach in the online environment (Ma et al., 2021). It is important to
investigate the role that peer observations play in building teacher self-efficacy beliefs as this
6
information can inform curriculum and policy decisions around faculty development programs.
Additionally, little research has been conducted around the role peer observations play in
informing Bandura’s (1997) four sources of self-efficacy beliefs. Most research pertaining to
teacher observations has historically orbited around improving instructional quality within face-
to-face learning environments. As such, this study seeks to advance research in this field by
investigating how peer observation can be used to impact teacher self-efficacy beliefs in online
learning spaces.
Limitations
I identified four limitations in this study. The first is based on the small sample size used
in this study, which means that there is no way to determine statistical significance based on the
data collected from the survey results (Merriam, 2009). The second limitation is due to the
sampling strategy that was used in this study. According to Merriam and Tisdell (2016),
convenience sampling is highly vulnerable to selection bias and high levels of sampling error.
Additionally, I discovered that all participants had at least 1.5 years of online teaching experience
and were favorably oriented toward improving their teaching and to using new approaches to
develop their teaching. As such, participants may not be an accurate representation of post-
secondary faculty as a result of the sampling strategy used in this study.
Another limitation of this study is the result of the different instructional models that each
participant subscribes to which might not align and, therefore, might compound their responses
on the survey or interviews. For example, teachers that subscribe to the flipped-classroom model
of instruction might have a very different teaching experience than instructors that do not. A
potential fourth limitation is participant bias, which happens when the participants involved in
research respond in a manner that suggests they are trying to match up with the desired result of
7
the researcher. Since I had both personal and professional history with three of the six
participants, these phenomena might have impacted their responses.
Delimitations
The focus of this study was on part-time and full-time faculty at the University of
Southern California that are new to online teaching. This study was open to faculty across all
academic schools within the university. Faculty from outside this institution were not included.
Additionally, this study included instructors that teach undergraduate and/or graduate-level
courses in order to maximize and diversify the participant pool. The number of years the faculty
members have taught in a face-to-face setting was not considered as this study is concerned with
their self-efficacy beliefs within an online teaching environment.
Definitions
Below is a list of terms that will be used throughout this study:
• Asynchronous instruction: Anytime, anywhere learning that does not require the
instructor to be present. Students access learning materials, complete activities, and
submit assignments through a learning management system.
• Face-to-face instruction: Traditional approach to teaching whereby the teacher and
students are in the same physical environment in order for learning to occur.
• Faculty development: Process of providing educational and coaching opportunities to
faculty members to help them improve their quality of teaching.
• Higher education faculty: Instructors that teach at a post-secondary institution
whether it be at a community college or 4-year college or university.
8
• Online course: For the purposes of this study, an online course is one that is delivered
in a fully virtual format and uses both synchronous and asynchronous methods to
deliver instruction.
• Online faculty: An instructor that delivers at least 50% of their instruction remotely
through a virtual platform such as Zoom, WebEx, or Google Meet.
• Online teaching and learning: Faculty instruction delivered remotely via the internet.
Online instruction includes a variety of synchronous and/or asynchronous techniques
that guide student interactions and engagement.
• Peer observation: A formal observation model whereby the good practice of staff and
faculty members engage in learning and teaching activities is identified, disseminated,
and developed with the intent to improve instructional quality.
• Synchronous instruction: Real-time instruction whereby the instructor and students
are in the same virtual place, at the same time, in order for learning to take place.
• Teacher collective efficacy: A group of teachers’ shared belief that through their
collective action, they can positively impact student learning (Bandura, 1997).
• Teacher self-efficacy: The confidence teachers hold about their individual and
collective capability to influence student learning (Bandura, 1997).
Conclusion
Chapter One addresses the growing trends in higher education to develop their online
program portfolio despite the disproportionate percentage of faculty who are reluctant to teach in
this space. The introduction to this study also describes how peer observations may play a role in
shaping online teacher-efficacy beliefs. Chapter Two will review important literature related to
this study, including current and historical perspectives of online education and faculty
9
development, the role of structured observations in improving teacher quality, and applicable
adult learning and motivation theory. Finally, Chapter Three will review the methodological
approach used for this research study.
10
Chapter Two: Review of the Literature
The literature review that informed this study examined the current and historical
perspectives of online education and faculty development, the role of structured observations in
improving teacher quality, and applicable adult learning and motivation theory. The COVID-19
pandemic has permanently transformed the landscape of online education as it required post-
secondary institutions to cancel face-to-face classes and shift to a fully online format in order to
block the transmission of the virus (Magda et al., 2020). By examining the successes and failures
within online education, this theme seeks to identify the trends that will foster and promote a
promising future. Additionally, the rise of online programs has established a growing awareness
that effective online teaching requires specialized pedagogical knowledge and skills (Espinet et
al., 2020). Therefore, it is important to explore the literature around applicable and relevant
learning theories in order for this study to be grounded in best practice. Finally, motivation
theory, specifically teacher self-efficacy, is prevalent in literature examining K–12 teaching and
pre-service teachers; however, little is known about this phenomenon in online higher education
and the role structured observations play in shaping it. This review of literature seeks to define
each theme, demonstrate and reinforce their relationships, and substantiate the need for this study
given the current gap in literature.
Perspectives on Online Education
Online Education: Introduction
Within the United States, online education is one of the fastest-growing segments in
higher education, and there is no foreseeable future where this modern mode of instruction’s
momentum slows down (Ginder et al., 2017; Seaman et al., 2018). Research has proven time and
again that online students enjoy the flexibility, accessibility, convenience, and personalization
11
that online educational programs provide (Gallagher, 2019; Nduagbo, 2020; Song et al., 2004).
Additionally, online education has proven beneficial for many colleges and universities as it has
helped address troubling trends within higher education that include rising tuition costs and a
growing disconnect between the skills future employers desire and the skills students graduate
with (Kim & Maloney, 2020). Furthermore, many have argued that this mode of instruction has
the potential to democratize education by providing educational opportunities and access to
learners that have been traditionally marginalized (Barger, 2020).
Despite the many benefits of online education, there are still some challenges associated
with this delivery modality. In a study conducted by Song et al. (2004), students indicated
technical problems, a perceived lack of community, time constraints, and difficulty in
understanding the learning objectives in online courses as hindering their success. Despite these
challenges, the promising potential within this space is vast and has taken some time and a lot of
effort to get here. The following sections will explore lessons learned from the past, where we
are in the present, and the role online education will play in the future.
Online Education Yesterday
Some of the earliest forms of distance learning are traced back to the late 1800s when the
University of Chicago and the University of London would conduct correspondence courses,
which refers to a time when instructors would send lessons and assignments to students at a
different location via mail and would receive completed assignments via mail (McIsaac &
Gunawardena, 2013).
These courses allowed students to earn college credits while not actually having to visit
the college campus. Though many people considered correspondence courses to be inferior to
12
traditional on-campus courses, they nevertheless became a vital means of providing equal access
to educational opportunities to all students (Mclsaac & Gunawardena, 2001).
The industrial revolution boosted the popularity of correspondence courses as it gave rise
to more efficient ways to disseminate instructional material to students. It was during this period
(1820–1840) that the first semi-automated computing machines, radios, and motion pictures
were developed and leveraged to deliver instruction to students at distant locations (Ferrer,
2013). In 1922, Pennsylvania State University received a commercial license with Westinghouse
Electric to offer educational content over radio waves. This moment was instrumental to the
history of distance learning as it was the first time a higher ed institution was able to offer
advanced-degree work remotely, which ultimately helped Pennsylvania State University
establish their Graduate School during the same year (Ferrer, 2013). However, there was still
doubt around the effectiveness of this instructional method as the level of student engagement
was one-dimensional (Woolley, 1994). In other words, students were mainly engaging with the
instructional content of the course and there was no meaningful interaction between the students
and faculty. This method did not provide the necessary feedback from the instructor that helped
reinforce student learning. What we consider online teaching and learning today did not start
taking shape until the 1960s when the University of Illinois created a computer system known as
the intranet that connected many computer terminals, making it possible for students to access
course materials and listen to recorded lectures without being physically present (Nduagbo,
2020). The intranet later evolved into Programmed Logic for Automatic Teaching Operations
(PLATO), which is still considered to be the initial global computer-assisted learning system
(Woolley, 1994). The features available in today’s modern learning management systems such as
13
forums, message boards, online exams, emails, chat rooms, picture languages, instant messaging,
remote screen sharing, were first created on PLATO (Ferrer, 2013).
PLATO fundamentally changed the landscape of distance education as it allowed students
to engage with their instructors and peers remotely, which was an instructional component that
was missing in correspondence courses. However, the sophistication of this new technology
required focused planning, teaching and learning systems, and organizational systems in order
for it to be an effective instructional tool for faculty and students at varied locations (Nduagbo,
2020). As such, it is no coincidence that the field of instructional design began to take shape
during this time. Influential psychologists and educators that made significant contributions to
the field during this time include B.F. Skinner and Benjamin Bloom (Nduagbo, 2020). The
programmed instruction movement was greatly informed by B.F. Skinner’s requirements for
increasing human learning and requirements for effective instructional materials as well as
Benjamin Bloom’s taxonomy of learning (Nduagbo, 2020). Their early discoveries are still used
to inform instructional practices in online classrooms today.
With the invention of the world wide web in 1989, many institutions began to investigate
ways to leverage this new technology to improve their distance learning offerings. In 1994,
CalCampus introduced the first fully online curriculum that included real-time instruction and
interaction over the internet (Nduagbo, 2020). This model helped shape what we know as
synchronous and asynchronous online instruction today. Since then, many new and more
sophisticated technologies and pedagogies have emerged in the field of online education which
has elevated the field as a viable and effective instructional modality.
14
Online Education Today
It has been nearly 3 decades since the launch of the first fully online degree programs,
and in recent years, their numbers continue to increase along with the amount of students
enrolling in them (Ginder et al., 2017; Seaman et al., 2018). This trend is in large part due to
increased consumer awareness and employer acceptance of online degree programs (Seaman et
al., 2018). Today, higher education institutions have positioned online educational delivery as a
top academic priority and central to their strategic plans in order to meet the needs of today’s
students. In 2019, Inside Higher Ed and Gallup produced a national survey that was distributed
to CAOs across the country and found that 83% planned to increase their emphasis on growing
online programs and offerings (Lederman, 2019). Additionally, the survey found that CAOs
intend to make greater academic investments in online education with 56% strongly agreeing
that they plan to allocate major funding to online programs in 2019; this was up from 46% just 4
years earlier (Gallagher, 2019). According to Gallagher (2019), despite the immense growth in
online study, it has only been in the recent years that better data on the scale and scope of online
learning in the United States has been made available through the efforts of government,
researchers, and other parties. This data has provided valuable insights to the current state of the
online education market including its size, the characteristics of online students, and knowledge
about the quality of online educational outcomes (Gallagher, 2019).
The Department of Education reports that more than 3.1 million students enrolled in fully
online education programs as of Fall 2017, which represents 15% of all students enrolled in U.S.
colleges and universities (Ginder et al., 2017). This number represents a 4% annual enrollment
rate increase, which is significantly greater than the overall U.S. post-secondary enrollment rate
(Gallagher, 2019). Notably, this number does not include students that are taking online courses
15
in addition to their traditional on-ground courses, therefore the number of students in higher
education that have taken an online course is significantly greater. The growth in online program
offerings and the credibility of online education as an instructional model has been greatly
influenced by some of the most prominent colleges and universities in the country embracing it
over the last decade (Gallagher, 2019).
The impact of online education has not only changed the type of educational programs
students are opting to enroll in, but it has also changed the student demographic higher education
institutions have traditionally served. The U.S. Department of Education (2017) recently released
data that provides insightful information about the profile of online students at the undergraduate
level. One key trend that emerged from this data is the older the student, the more likely they are
to be pursuing a fully online degree (Campbell & Wescott, 2019). For example, among all
undergraduate students aged 30-39 in U.S. higher education, 23% are pursuing a fully online
program, which is six times the rate of traditionally aged undergraduates. Furthermore, students
who are working full-time are also more likely to enroll in fully online degree programs
(Campbell & Wescott, 2019). The U.S. News & World Report confirmed this data by conducting
its own study and reports that the average age of an online student is 32, and 84% of students
enrolled at the bachelor’s level are currently employed (Friedman, 2017). These trends suggest
that online students tend to be working adults who are often pursuing education for career-related
reasons.
Online Education During COVID-19
Even though the trend over the course of recent years has demonstrated a significant
increase in online program offerings among U.S. post-secondary institutions, the COVID-19
pandemic has forcefully shifted the mode of teaching and learning from face-to-face to online.
16
Since spring of 2020, most institutions across the globe opted to cancel all face-to-face classes,
including labs and other learning experiences, and have mandated that all faculties move their
courses online to help prevent the spread of the virus that causes COVID-19 (Hodges et al.,
2020). As a result, institutions have invested an exuberant amount of time, money, and resources
to establish emergency remote teaching protocol that will have long-lasting implications far
beyond the COVID-19 pandemic.
Emergency remote teaching (ERT) is unlike online education where instruction is
planned from the very beginning and intentionally designed to be online. Typical planning,
preparation, and development time for a fully online university course is 6 to 9 months before the
course is delivered. This approach is in stark contrast with ERT where Hodges et al. (2020)
defined it is as follows:
ERT is a temporary shift of instructional delivery to an alternate delivery mode due to
crisis circumstances. It involves the use of fully remote teaching solutions for instruction
or education that would otherwise be delivered face-to-face or as blended or hybrid
courses and that will return to that format once the crisis or emergency has abated. (p. 7)
In other words, the primary objective of ERT is not to recreate a robust educational infrastructure
but instead to offer temporary access to instructional materials and support systems in a way that
is quick and reliable during an emergency crisis.
One of the main challenges with ERT in higher education is the lack of resources
currently available to assist faculty in making this transition (Hodges et al., 2020). The campus
support teams that are dedicated to assisting faculty members learn about and implement online
learning strategies and techniques lack the capacity to provide the same level of support to all
faculties who need it during ERT. As such, the shift to ERT requires that faculty take more
17
control over the course design, development, and implementation process. This requirement is
also true for institutions that are looking to continue developing their online program offerings as
well. In the most recent 2020 Horizon Report by EDUCAUSE, an imperative is suggested that
higher education faculty be prepared to teach in a variety of learning environments including
online, blended, and face-to-face modes in order to meet the needs of the increasingly non-
traditional student population (Brown et al., 2020). It is expected that the rapid growth of online
education will continue into the foreseeable future; therefore, faculty development and support
teams must find ways to create and maintain instructional continuity while also assisting faculty
in developing the necessary skills to effectively work and teach in an online environment that
persist beyond the current COVID-19 pandemic (Hodges et al., 2020).
Faculty Development in Higher Education
Faculty development has seen a significant shift in recent years due to the many
challenges and opportunities the twenty-first century has introduced to higher education
institutions across the globe. Today’s post-secondary students are unlike those from the past
where 18–22-year-old students from upper-middle-class families dominated the landscape (Gaff
& Simpson, 1994). Instead, college campuses now serve older students that study part-time and
are from a variety of ethnic, cultural, and socioeconomic backgrounds (Gaff & Simpson, 1994).
Furthermore, students today want educational opportunities that require little effort to access,
align with their interest and career goals, and flexibility in order to manage the many other
obligations they have such as jobs and family (Levine, 2010). According to Austin and Sorcinelli
(2013), faculty “must respond to these new plans, support the learning of students with diverse
learning needs, and develop curricula and teaching strategies appropriate for a range of learning
environments” (p. 87). In the following section, we will briefly explore the historical
18
underpinnings of faculty development within higher education to better understand the current
trends that continue to strive to make college teaching more successful and satisfying in an ever-
changing industry.
Three Phases of Faculty Development
According to Gaff and Simpson (1994), the history of faculty development in higher
education can be summarized in three major phases. The first phase, which occurred during the
1960s, focused on helping faculty develop and reinforce their expertise within their specific
disciplines. However, research in cognitive science shows that being an expert in a particular
discipline does not necessarily translate into effective teaching and in fact, might hinder a
teacher’s ability to address the learning needs of novice students (Ambrose et al., 2010). When
experts approach tasks related to their discipline, they are able employ shortcuts that novices
cannot because of the sophisticated knowledge structures, which allow them to immediately
recognize meaningful patterns and configurations based on previous experiences (Koedinger &
Anderson, 1990). These knowledge structures are difficult for experts to break down, which is a
necessary step in scaffolding instruction that helps novice students gradually develop the
knowledge and skills necessary to become an expert (Ambrose et al., 2010). This phenomenon is
known as the expert blind spot (Koedinger & Anderson, 1990), which became the problem the
second phase of faculty development focused on addressing.
The 1970s sparked significant change in faculty development approaches for a variety of
reasons, including the ones already mentioned (Schuster, 1990). Changes in demographics and
declining number of students, rising costs, and shifting career expectations began to significantly
affect the climate of higher education institutions where faculty worked (Blackburn & Lawrence,
1995). These shifts sparked new approaches to faculty development that emphasized the role of
19
the teacher and drew greater attention to improved college instruction (Gaff & Simpson, 1994).
Colleges and universities established new programs intended to promote greater sophistication
and skill regarding teaching and learning, which Gaff (1975) conceptualized as faculty,
instructional, and organizational development programs. Programs focused on faculty members
sought to assist them in learning more about the teaching profession, their students, or their
institutions; acquire new instructional skills; gain feedback on their own teaching practices;
explore their attitudes, values, and feelings about teaching; or apply learning principles in their
course (Gaff & Simpson, 1994). Programs that focused on instructional development helped
faculty identify learning goals for their courses; design alternative learning experiences; produce
instructional materials using a variety of media; and develop instructional systems such as
mastery learning (Gaff & Simpson, 1994). Finally, programs that focused on organizational
development emphasized the fact that teaching and learning needs to occur in a supportive
environment and assisted faculty in establishing such a climate by creating group goals;
improving relationships with colleagues; training leaders; and establishing clear policies (Gaff,
1975). The changes that occurred within this phase were instrumental in grounding pedagogical
knowledge (ways to manage the classroom and present material) and pedagogical content
knowledge (ways to connect subject matter with teaching strategies) as effective ways to
improve student success.
The third and current phase of faculty development seeks to revive faculty and
institutional vitality which many thought was at an all-time low due to the changing nature of
higher education (Camblin & Steger, 2000). According to Schuster (1990), one notable change
from previous years is that faculty are graying and staying which meant that they were growing
older and becoming increasingly tenured. As a result, many institutions became concerned that
20
the static faculty population meant that colleges and universities were less able to bring in new
faculty members “to infuse new ideas, provide leadership potential, or introduce innovative
teaching techniques” (Sullivan, 1983, p. 21). Another notable change was the widening gap
between the skills recent college graduates possessed and the skills employers needed (Kim &
Maloney, 2020). Colleges and universities looked to close this gap by redesigning their
curriculum to make it more meaningful and relevant to today’s workforce (Kim & Maloney,
2020). As such, faculty development became the vehicle that drove curriculum change, which
was a shift from previous phases as it required groups of faculty to work together to locate where
their individual interests reside within the context of the department or institution (Gaff &
Simpson, 1994). As such, improving the curriculum within higher education became a
collaborative effort to improve both faculty and institutional vitality (Camblin & Steger, 2000).
Building Faculty and Institutional Vitality
One program that found early success in building faculty and institutional vitality was
offered through the Associated Colleges of the South (ACS), which is a consortium of 16 liberal
arts colleges and universities in 12 states across the south (Persellin & Goodrick, 2010). This
program ran from 1997 to 2007 and sought to rekindle faculty energies and develop strategies
that promote opportunities for lifelong learning and self-renewal activities through the practice of
video-microteaching (Camblin & Steger, 2000). Originally developed by Allen and Ryan in
1969, video-microteaching allows teachers at all levels to practice and give one another
immediate feedback (Bell, 2007). Microteaching groups at the ACS workshops consisted of five
or six faculty members across different disciplines as well as two staff facilitators. Facilitators
were former participants who were invited back to lead training sessions (Persellin & Goodrick,
2010). Each faculty member in the group was videotaped teaching a 7-minute segment of a
21
lesson, which was later viewed by the entire group (Camblin & Steger, 2000). After the lesson
was viewed, the faculty member had an opportunity to comment or ask questions before
soliciting feedback from other members of the group (Camblin & Steger, 2000). Participants of
these workshops reported having more awareness and thoughtfulness about their teaching as well
as an increased willingness to take instructional risks by fusing new teaching techniques into
their curriculum (Persellin & Goodrick, 2010). Additionally, participants reported having
stronger relationships with their colleagues, which is a fundamental goal of the ACS (Persellin &
Goodrick, 2010).
Microteaching as a model of faculty development closely resembles teacher observations,
which has a rich history in education. Though the two practices share many similarities, they also
have important and substantive differences. The following section takes a closer look at the
history of teacher observations and offers recommendations based on best practices that have
been identified across multiple studies.
Teacher Observations
Teacher Observation Origins
Early studies of teacher quality started in the 1940s through the 1960s and focused on
personal characteristics and experience variables of teachers (Blanton et al., 2006). It was not
until the late 1960s when researchers focused on understanding the links between specific
teacher behaviors and students’ outcomes (Cochran-Smith & Lytle, 1990). This process-product
approach was grounded in behavioral psychology and child development, which enabled
researchers to begin systematically addressing the complexities of teaching, classrooms, and
schools (Blanton et al., 2006). As such, the roots of teacher quality assessment, where teacher
observations are a primary component, are grounded in K–12 research where accountability and
22
performance standards dominate the agenda. That is, the purpose for teacher observations within
this space focuses on holding teachers accountable in meeting specific performance standards as
opposed to helping them improve their practice to become more efficacious teachers. Though the
practice of teacher observations proved to have a positive impact on teacher quality at the K–12
level, it was met with much resistance in higher education.
Resistance to Teacher Observations in Higher Education
The findings and recommendations within these early studies showed promising results
in using observations to improve teacher quality; however, this practice became problematic
when applied to higher education for a variety of reasons (Berge, 1998). First, higher education
students have different learning outcomes that require more advanced self-regulation skills since
ultimately, learning is the students’ responsibility (Ramsden, 2003). Additionally, because the
ownership of learning is transferred from teacher to student, good teaching is an “elusive, many
sided, idiosyncratic and ultimately, undeniable quality” (Ramsden, 2003, p. 85). Lastly, much of
a student’s learning experience takes place apart from lectures and other formal classes and
instead, occurs through individual or collaborative study (Ramsden, 2003). These differences
make the transferability of findings from earlier studies, which were conducted in primary and
secondary education, very limited.
In addition to the differences in learning environments between K–12 and post-secondary
education mentioned above, teacher observations have been met with much resistance by higher
education faculty because of issues related to its implementation process. There exists a history
of hostility toward teacher observations within higher education because it is associated with
management processes that determine promotion and performance-related pay (Gosling &
D'Andrea, 2001). Additionally, within some contexts in higher education, observations are
23
conducted to achieve a summative judgment of the teaching observed whereby no formative
feedback is provided by the reviewer, nor is there any reflective practice by the teacher observed
(Gosling & D'Andrea, 2001). Furthermore, observations did not provide the observer with the
holistic learning experience of the students but rather, only a single moment in time by which to
assess the quality of a teacher’s instruction (Barrow, 1999). These problems are exacerbated by
having a stranger judging a teacher’s work, lending little to no educational value to this process
(Barrow, 1999).
From Teacher Observation to Collaborative Peer Review
In order for teacher observations to meet their full instructional potential, the focus
needed to shift from a performance-based accountability model to a collaborative professional
development model. Gosling’s (2005) influential work on models of teaching observation helped
accomplish this goal by acknowledging the unbalanced power structure inherent in the historical
approach. Gosling identified three main models of peer review, which are located along a
continuum from power (evaluation model) to expertise (development model) to
equality/mutuality (peer review/collaborative model). The evaluation observation model serves
managerial purposes and is generally judgmental where managerial staff monitors teacher quality
to ensure compliance with standards (Yiend et al., 2014). Gosling’s two other models focus less
on judging and more on developing the teacher. The developmental model involves an
educational expert assuming the role of observer, while the peer review/collaborative model
involves academic colleagues observing each other in a reciprocal arrangement (Yiend et al.,
2014). Gosling argued the term “peer” is a central concept for understanding the development
potential of observation (Weller, 2009).
24
There are many benefits to the peer teaching observation model. Donnelly (2007) defined
peer observation of teaching as “the formal process by which the good practice of staff and
faculty members engage in learning and teaching activities is identified, disseminated, and
developed” (p. 117). It is through the observation of teaching and joint reflection with colleagues
where teaching skills can be developed and refined in a supportive and collaborative
environment (Martin & Double, 1998). Furthermore, the reciprocal nature of this approach
benefits both the observed and the observer; the observed receives valuable instructional
feedback which is focused and content specific while the observer is able to refine their ability to
identify the attributes that promote a quality experience for the students. Additionally, studies
have shown that implementing peer observation of teaching within an institution contributes to
the development of the wider teacher community as individual instructors strengthen their
instructional practice and skills (McMahon et al., 2007).
Although many studies have demonstrated the benefits of peer observation of teaching,
there are also challenges associated with this approach in higher education. Hatzipanagos and
Lygo-Baker (2006) shared their uncertainty about the extent to which participation in formative
teaching observation could contribute to the development of critical reflection and legitimate
enhancement of instruction. Furthermore, Gosling (2005) asserted that without ongoing training,
most faculties are not prepared to provide substantive and targeted feedback on the effectiveness
of others’ teaching. In other words, while scholars become increasingly convinced of the benefits
of peer observation of teaching, there are still concerns about instructors’ ability to assess the
teaching of others while providing constructive feedback on the teaching practice of their
colleagues. Lastly, Weller (2009) argued that for teaching observation to contribute to the
legitimate improvement of the teaching practice, “such processes must be underpinned by
25
pluralist models of professional development that tolerate, and indeed require, critical differences
of perspectives that challenge rather than affirm the existing professional ‘self-concept’ of
experienced practitioners” (p. 25).
The Collaborative Reflection Model of Peer Observation
Despite these challenges, many institutions have successfully implemented a Peer
Observation Teaching model that has helped improve teacher quality (Bell, 2001; Donnelly,
2007; Martin & Double, 1998). Each model is based on Gosling’s (2005) collaborative reflection
model of peer observation mentioned above. Although the models have minor variations
(number of participants involved, quantity of observation occurrences, qualifications of the
observer, etc.) to meet their institution’s unique needs, the framework is consistent across all of
them, which includes a three-step process of (a) pre-observation meeting, (b) observation, and (c)
feedback meeting (post-observation). These steps are intended to maximize the instructional
potential of the observation experience (Donnelly, 2007). Each step in the process is explored in
greater detail below along with the key elements that were shared across all models.
Figure 1
Collaborative Model of Peer Observation
Note. From Peer Observation of Teaching by D. Gosling, 2005. Staff and Educational Development Association.
26
27
The first step includes a pre-observation meeting where the observed faculty is able to
provide the observer context about the lesson as well as any specific features that he/she should
be aware of. It is important that the observed faculty provide a clear picture of what has been
covered in the course already, the learning outcomes for the particular lesson and the teaching
strategies that will be used (Martin & Double, 1998). It is also important in this step to establish
expectations around how and when the lesson will be documented and shared with the observed
faculty. For example, common practice in most studies was that observation notes became the
property of the observed faculty after the session, so they had enough time to review and reflect
on the information before moving to the second step in the process. The notes that the observer
provides to the observed should capture the essence of the pedagogy techniques to provide the
foundation for reflection (Martin & Double, 1998).
The second step in the process is the observation. This should be a formative procedure
where the observer recognizes strengths and suggests areas for improvement or alternative
approaches (Martin & Double, 1998). A systematic approach of note taking at fixed intervals
(every 2 to 3 minutes) will help the faculty see the contours of the event later when they reflect
on the notes (Donnelly, 2007). Additionally, the observer must avoid using judgment statements
therefore, it is important for them to beware of assuming an expert role during the process
(Martin & Double, 1998). Finally, Whitlock and Rumpus (2004) suggested that “the observers do
not need to be experts in education—they are not required to make judgments on ability, but to
provide constructive comments to help the observed think about how they are helping their
students” (p. 5).
The last step in the process is the feedback stage and if the peer observation of teaching
experience is to be productive, this step must be truthful and constructive. Ideally, the feedback
28
meeting should be conducted soon after the observation, so the information is still fresh in the
observer’s mind (Martin & Double, 1998). The location should be quiet, comfortable, and
protected from any distractions or interruptions. Studies have shown that it is best practice to
begin the conversation by recalling the learning objectives for the lesson and asking the observed
faculty to reflect on how they feel about their students meeting them. Asking faculty to identify
strengths and areas for improvement within their lesson is also recommended. Finally, the
feedback session should include some feedback on the role and behavior of the observer to make
the experience mutually beneficial (Martin & Double, 1998).
According to McGill (1994), the process should be cyclical, and the benefits are
congruent to the number of purposeful experiences faculty engages in. That is, repetition in this
process will allow faculty to become exposed to more opportunities to reflect and analyze their
performance, which can ultimately improve their pedagogical knowledge and instructional
quality. Below is a graphic that best illustrates the cyclical process of the collaborative reflection
model of peer observation that was used in this study.
Though there are a few variations of this model that were created to fit a specific
institution’s unique needs, each variation emphasizes the following criteria that must be in place
prior to having staff engage in the collaborative reflection model of peer observation scheme.
The first is to ensure that there is mutual respect and a degree of tact between the observer and
the observed. In order for the experience to be mutually beneficial, the relationship between the
two must be positive and productive and the elements mentioned above are a prerequisite for
such a relationship. Additionally, we cannot assume that participants are prepared to engage in
the observation process without having clearly defined the process and established agreed upon
29
norms (Martin & Double, 1998). That said, providing a brief training session to accomplish this
is highly recommended.
Given the cyclical and reflective nature of the collaborative reflection model of peer
observation scheme, along the success it has found in improving teacher quality, this study seeks
to employ this model to investigate and answer its research questions. This study differs from
previous studies by investigating how this scheme might impact Bandura’s (1997) four sources
of efficacy attainment within the context of teacher self-efficacy. Lastly, the collaborative
reflection model of peer observation scheme is grounded in the theoretical framework supporting
this study.
Theoretical Framework
The theoretical underpinnings addressed in this study include (a) Kolb’s experiential
learning theory, (c) Bandura’s self-efficacy model, and (c) the reflective practice model. The
following sections will explore each topic in greater detail to establish the conceptual framework
for this study.
Kolb’s Experiential Learning Theory
Adult education has been a popular topic of research since the 1920’s and since then,
many theories and models have been developed that attempt to explain how adults learn best
(Merriam & Caffarella, 1999). Though these theories vary in instructional strategies and
approaches, they share a fundamental belief that there exist significant differences in learning
characteristics and situational contexts between children and adults (Dewey, 1938; Knowles,
1990; Piaget, 1999). Examples of adult learning characteristics include self-directed learning,
pre-existing learning structures (schemata), problem-centered learning, goal and relevancy
orientation, and internal motivation (Knowles, 1990). Additionally, there are lifestyle and
30
biological differences that must be considered when designing instruction for adult learners. For
example, many adult learners have responsibilities such as full-time employment and families,
and other situational challenges such as transportation and childcare that can interfere with the
learning process (Merriam & Caffarella, 1999). Biological changes also impact adult learners as
many studies have shown that memory decreases with age (Merriam & Caffarella, 1999). Kolb’s
(1984) experiential learning theory considers these unique opportunities and challenges that adult
learners present and establishes a practical framework that practitioners can use to create
effective and meaningful learning experiences that guide learners toward meeting complex
learning outcomes.
Kolb’s experiential learning theory is grounded in the works of influential learning
theorists such as Dewey, Piaget, and Lewin who helped shift the conception of learning from
behaviorism and passive learning to cognitive, social, constructivist and active learning (Chan,
2012). Building on the discoveries of his renowned theoretical predecessors, Kolb (1984)
developed a holistic model of experiential learning, which he defined as “the process whereby
knowledge is created through the transformation of experience. Knowledge results from the
combination of grasping and transforming experience” (p. 41). Kolb’s model consists of a four-
stage learning cycle: (a) concrete experience, (b) reflective observation, (c) abstract
conceptualization, and (d) active experimentation (Chan, 2012).
Concrete experience is gained when the learner actively experiences and performs a
learning task (Kolb, 1984). In the context of teaching, this occurs when an instructor experiences
something for the first time in the classroom. In this stage, it is important for the instructor to
play an active role to gain first-hand knowledge of the experience. The goal of this stage should
be for an instructor to test out new ideas or teaching strategies, which they can use in the
31
subsequent steps of the cycle (Chan, 2012). The reflective observation stage occurs when the
learner consciously reflects and draws conclusions on their experience (Kolb, 1984). In this step,
it is important for the instructor to consider the strengths of the experience and areas for
improvement. The goal of this stage is to gain an understanding of what part(s) of their lesson
helped or hindered student learning (Chan, 2012). The abstract conceptualization stage is when
the learner can conceptualize a theory or model that guides further action (Kolb, 1984). To
accomplish this instructor should draw connections between what they have done, what they
already know, and what they need to teach (McCarthy, 2010). The active experimentation stage
occurs when the learner utilizes a theory or model to experiment with different scenarios (Chan,
2012). In other words, the ideas generated from the observations and conceptualizations are
incorporated into future teaching experiences where they are tested and experimented with.
This four-stage process is ongoing and involves both concrete and conceptual
components that require students to reflect, abstract, and test in a cyclical process (McCarthy,
2010). Additionally, Kolb argued that learners must engage in each of these steps in order for
effective learning to occur; however, the learning cycle can begin at any of the four stages (Kolb
& Fry, 1975). Over the past 20 years, this simple and adaptable framework has been adopted by
educational program designers in a variety of fields such as management, education, information
science, psychology, medicine, nursing, accounting, and law (Morris, 2020). Kolb’s experiential
learning cycle lies at the heart of the collaborative reflection model of peer observation scheme
as it engages participants in a continuous cycle of reflection, abstraction, and testing. That is, the
collaborative reflection model of peer observation scheme enables participants to reflect on their
current practice, share their experience with supportive peers, engage in risks and experiment in
a supportive and nurturing learning environment, all while coming to an understanding of new
32
ideas to analyze, adapt, and experiment with in their teaching practice. This scheme facilitates
the use of new information in authentic situations and can lead to increased learning for
participants, which is at the heart of experiential learning.
The Reflective Practice Model
Donald Schön’s theory of reflective practice has gained an enormous amount of attention
in professional discourses around health and social sciences (Kinsella, 2007). In the United
Kingdom, the reflective practice model is considered the dominant model in fields such as
teacher education, higher education, and medical and health education (Bleakley, 1999). For
many, the attractiveness of this theory is that it fosters an inquiry approach to professional
development and allows one to assess the effects of their practice while acting (Kinsella, 2007).
In the teacher education context, the reflective practice implies that the teacher examines their
teaching practice against how well students are learning, and consults with colleagues to
determine ways to improve their practice (Pitsoe & Maila, 2013).
Practitioners are drawn to Schön’s reflective practitioner model because it acknowledges
that application of theory to practice is not always simple and neat but rather, complex, and
oftentimes messy (Kinsella, 2007). Schön’s (1987) model involves the reconstruction of one’s
experiences; the honest acceptance and analysis of feedback; the evaluation of one’s skills,
attitudes, and knowledge; and the identification and exploration of new possibilities of
professional action. As such, he describes his model as “a dialogue of thinking and doing through
which I become more skillful” (Schön, 1987, p. 31). Ashcroft and Foreman-Peck (2013) argued
that the most important piece of the reflective practice is that it requires a commitment to
learning from experience and evidence rather than ‘recipes’ for action.
33
A key tenant of Kolb’s experiential learning cycle is to use the practice of reflection to
draw conclusions and ideas from an experience. The reflective practice model and its role in
personal, professional, and organizational development is fundamental to the collaborative
reflection model of peer observation scheme. Theorists of the reflective practice model report
that the reflective component of peer observation of teaching has the potential to become a key
process in the professional development of academic staff and faculty by fostering a consciously
reflective learning environment (Donnelly, 2007). Given the transformative potential of the
reflective practice model, and its integral role in Kolb’s learning cycle, this has become a
common theoretical framework underpinning several of the peer observation schemes, including
the one employed in this study (Bell, 2002).
Bandura’s Self-Efficacy Model
According to Zimmerman (2002), Self-efficacy refers to an individual’s belief about their
capacity to perform or execute behaviors at a particular level. The information that people use to
assess their self-efficacy comes from four sources which include mastery experiences
(interpretations of actual performance), vicarious (modeled) experiences, forms of social
persuasion, and physiological indexes (Bandura, 1997). Mastery experiences refer to past
performance attainments and are considered to be the most influential source of one’s self-
efficacy beliefs (Usher & Pajares, 2008). Vicarious experiences refer to observing a social model,
or oneself, perform a task (Bandura, 1997). Social persuasions refer to evaluative feedback
(positive or negative) that individuals receive after performing a task (Bandura, 1997). Finally,
people also acquire self-efficacy beliefs through physiological and/or emotional reactions such as
anxiety and stress (Bandura, 1997). It is important to note that these four sources do not impact
self-efficacy directly. Instead, their influence is moderated by how individuals cognitively
34
process their experiences through environmental, behavioral, and personal factors (Bandura,
1997).
When applied to education, teacher-efficacy refers to the confidence teachers hold about
their individual and collective capability to influence student learning. Teacher-efficacy is
considered to be one of the key motivational forces influencing teachers’ professional behaviors
(Klassen et al., 2011). Teachers with high self-efficacy have positive beliefs have positive beliefs
about teaching and are more willing to experiment with promising instructional strategies
whereas those with low self-efficacy experience greater difficulties in teaching, lower levels of
job satisfaction, and higher levels of job-related stress (Klassen et al., 2011).
A study conducted by Donnelly (2007) at the Dublin Institute of Technology researched
participant perceptions around the impact of the collaborative reflection model of peer
observation scheme, which was offered as part of an accredited postgraduate certificate in
teaching for academic staff and faculty members in higher education. This study found that
participants gained confidence and were more willing to experiment with instructional
techniques which they observed as having a positive impact on student teaching (Donnelly,
2007). Furthermore, this study found that the climate where peer observations take place is vital
to its effectiveness in improving teacher quality. According to Donnelly (2007), in order to
mitigate participant resistance and increase engagement, participants must feel comfortable and
safe during the entire process. Though Donnelly’s study did not specifically measure teacher
self-efficacy, the impact the peer observation intervention program had with faculty corresponds
with the characteristics of teachers with high self-efficacy beliefs.
There exists a rich body of literature that validates teacher-efficacy in the K–12, face-to-
face learning space, however there is still much to be discovered around this phenomenon
35
specifically around online education. According to Corry and Sella (2018), three areas of
research have emerged over the past 15 years that pertain to teacher-efficacy in online education,
which include (a) ease of adopting online teaching, (b) online teaching-efficacy in comparison to
demographic and experience variables, and (c) changes in online education, which include: (a)
ease of adopting online teaching, (b) online teaching-efficacy in comparison to demographic and
experience variables, and (c) changes in teacher-efficacy in professional development scenarios
where self-efficacy was measured before and after treatment.
The first area of research that has emerged around teacher self-efficacy in online
education investigates whether teachers might adopt online education readily (Corry & Stella,
2018). The purpose of these studies was to determine if organizations could predict which
individuals might be resistant to adopting a particular technology so training and/or counseling
programs could be offered prior to the implementation in order to achieve better results (Corry &
Stella, 2018). The second area of research investigates whether a teacher’s
demographics/experience has an impact on their self-efficacy beliefs (Corry & Stella, 2018). The
purpose of these studies was to examine how, if at all, a teacher’s demographics or experience
might impact teacher self-efficacy (Corry & Stella, 2018). The third area of study investigates
changes in teacher self-efficacy beliefs before and after an online teacher education event (Corry
& Stella, 2018). These studies are most concerned with determining the effects an intervention
program has in developing online teacher self-efficacy.
The research questions that drive this study seek to contribute to the third area of research
by investigating the role collaborative reflection model of peer observations play in influencing
Bandura’s (1997) four sources of efficacy attainment within the context of teacher self-efficacy.
Current literature suggests that online teacher education programs and professional development
36
are beneficial in developing online teacher self-efficacy, however little is known how and/or if
the collaborative reflection model of peer observation scheme can impact teacher self-efficacy
particularly within the online teaching/learning context. This study seeks to employ this
observation scheme as an intervention program to determine if, and to what degree, it can have
on impacting any of the four sources of efficacy attainment.
37
Chapter Three: Methodology
The purpose of this study is to understand the experiences of online faculty that are new
to teaching online and how the collaborative reflection model of peer observation impacts their
self-efficacy beliefs. Research shows that teachers with high self-efficacy have positive beliefs
about teaching and are more willing to experiment with promising instructional strategies
whereas those with low self-efficacy experience greater difficulties in teaching, lower levels of
job satisfaction, and higher levels of job-related stress (Klassen et al., 2011). These factors
ultimately impact student persistence and performance therefore, it is important to conduct
research that explores this phenomenon because more colleges and universities are expanding
their online program portfolios and administrators have an obligation to ensure academic success
for online students (Brown et al., 2020).
The theoretical lens used to frame this study is Bandura’s (1977) self-efficacy theory.
Self-efficacy is a person’s belief in their ability to succeed in a particular situation (Bandura,
1977). When applied to education, teacher self-efficacy refers to the confidence teachers hold
about their individual and collective capability to influence student learning (Bandura, 1997).
Understanding how the collaborative reflection model of peer observation impacts online
faculty’s self-efficacy beliefs will inform institutions of higher education about how they might
develop professional development programs that improve instructional quality.
Two research questions guide this study:
1. What is the perceived impact of the collaborative reflection model of peer
observation on online teachers’ self-efficacy beliefs?
2. What are the perceived benefits and challenges associated with this observation
model’s implementation?
38
Site Selection
The University of Southern California (USC), is one of the world’s leading private
research universities and is the state’s oldest, having been founded in 1880. The Wall Street
Journal and Times Higher Education ranked USC 19th among more than 1,000 public and
private universities. The university is accredited by the Western Association of Schools and
Colleges, the Senior College and University Commission and is composed of one liberal arts
school, Dornsife College of Letters, Arts, and Sciences, and 22 undergraduate, graduate, and
professional schools. The average enrollment is 19,500 undergraduate students and 26,500
postgraduate students. The university is ranked among the top universities in the United States.
In recent years, the online course offerings across all schools at USC has significantly
increased in response to university-wide mandate to create online graduate programs. As a result
of this mandate, USC currently offers 118 online masters and doctoral degrees, and certification
programs across 28 disciplines, and 13 schools. Because many of these programs are relatively
new, and ostensibly so too are the faculty that are teaching in these online spaces, this site
provides me with a potentially large number of suitable participants for this study. Additionally,
as a result of the COVID-19 pandemic, USC, like most other universities, moved all courses to
an online format during the 2020–2021 academic year. This transition further increases the pool
of potential participants for this study.
Population and Sample
The target population for this study is all part-time and/or full-time faculty members
across USC colleges that teach at least 50% of their instructional content remotely. In order to
ensure that participants meet this criteria, Purposeful and Convenience sampling was used.
According to Merriam and Tisdell (2016), “purposeful sampling is when settings, persons, or
39
activities are selected deliberately to provide information that is particularly relevant to your
questions and goals, and that can’t be gotten as well from other choices” (p. 99). Since this study
is interested in how the collaborative reflection model of peer observation impacts online
faculty’s self-efficacy beliefs, purposeful sampling was the most appropriate choice. According
to Merriam and Tisdell (2016), convenience sampling is sampling based on time, money,
location, availability of sites and participants, and so on. Because this study was constrained by
many of the variables that Merriam and Tisdell listed to justify convenience sampling, this
approach was used to select respondents and setting.
Participant recruitment strategy included three methods. The first was an email that will
be distributed by department chairs within the colleges. The second was an email distributed by
the university’s Center for Excellence in Teaching (CET). The third was personal emails that
were sent to faculty members that I had a personal and/or professional history with. The third
method was used after I exhausted the first two recruitment methods and still needed to find
three additional participants to conduct the study. All participants received a $100 Amazon e-gift
card as well as be eligible for a $500 Amazon e-gift card raffle upon completion of the study.
Participants
A total of six faculty members participated in this study. Four of the participants teach at
USC’s Rossier School of Education and two teach at USC’s Marshall School of Business. The
academic ranks for participants teaching at Rossier include two associate professors and two
senior lecturers. The academic ranks for participants teaching at Marshall include associate
professor and senior lecturer. The participants’ experience in online teaching varied greatly with
two having 1.5 years of online teaching experience, one having 2 years of online teaching
40
experience, one having 5 years of online teaching experience, one having 8 years of online
teaching experience, and one having 10 years of online teaching experience.
Convergent Parallel Mixed-Methods Design
Because the intent of this study is to explore faculty perceptions on how the collaborative
reflection model of peer observation might impact their online teacher’s self-efficacy beliefs, the
convergent parallel mixed-methods approach was used in this study. According to Creswell
(2017), the key assumption of this approach is that both quantitative and qualitative data provide
different types of information and when used together should yield similar or identical results. In
the convergent parallel mixed-methods approach the researcher collects both qualitative and
quantitative data, analyzes them separately, and then compares the results to determine if the
findings confirm or disconfirm each other (Creswell & Creswell, 2017).
There are three main reasons why this approach was adopted. The first reason is because,
according to Creswell and Creswell (2017), mixed-methods studies can provide, “more insight
into a problem … from mixing or the integration of quantitative and qualitative data” (p. 213). In
other words, this approach allows the researcher to obtain a more complete understanding of a
phenomena by analyzing two different databases. A second reason why this approach was
adopted is because it allows the researcher to triangulate the methods by directly comparing and
contrasting quantitative results with qualitative findings, thereby improving the validity of the
study’s findings. The final reason why this approach was adopted was because of the time
constraints associated with this study. The convergent parallel model allows the researcher to be
more efficient during the data collection process.
41
Data Collection
A pre- and post-survey was used for the quantitative portion of this study. The instrument
that was used in this study was the MNESEOT. The MNESEOT uses factor analysis to confirm
four factors for self-efficacy and has been used in previous studies to compare self-efficacy
against demographic variables and experience for higher ed faculty teaching online. The four
factors for self-efficacy that the survey measures include online student engagement, self-
efficacy in online instructional strategies, self-efficacy for online classroom management, and
self-efficacy in the use of computers (Robinia & Anderson, 2010). The survey has 29, 5-point
Likert scale questions including 24 items based on the Teachers’ Sense of Efficacy Teaching
Scale (TSES) and five extra items to include technology application (Robinia & Anderson,
2010). This instrument was selected for two reasons. The first is because it considers both the
pedagogical and technical aspects of online teaching, and the second is because both dimensions
of the survey have high internal consistency with a Cronbach alpha of 0.97 and 0.86, respectively
(Ma et al., 2021). Participants were asked to report their online teacher self-efficacy via
MNESEOT at the beginning and end of the instructional intervention in order to explore how the
intervention impacted self-efficacy beliefs. The survey was distributed online via Qualtrics,
which is an online survey tool that is made available through the university.
The qualitative data for this study was collected in the form of semi-structured interviews
with participants. This type of interview was selected because it allows the researcher to respond
to and explore the emerging worldview of the respondent while also being able to investigate any
new ideas on the topics that might surface during the interview. According to Merriam and
Tisdell (2016), “this format allows the researcher to respond to the situation at hand, to the
emerging worldview of the respondent, and to new ideas on the topic” (p. 111). The same semi-
42
structured interview protocol was used in all one-on-one interviews. The questions within the
interview protocol were informed by the MNESEOT in order to ensure that both forms of data
are using the same variables around teacher self-efficacy (Creswell & Creswell, 2017). Finally,
all interviews were conducted virtually via the web conferencing tool Zoom and recorded for
transcription purposes.
Data Analysis
Convergent design data analysis consists of three phases (Creswell & Creswell, 2017). In
the first phase the qualitative database is coded and collapsed into broad themes. To accomplish
this, phenomenological analysis was used to capture the essence of the phenomenon by using a
variety of techniques (Creswell & Creswell, 2017; Merriam & Tisdell, 2016). Audio recordings
were submitted to REV , which is an online transcription service, to be professionally transcribed.
A priori codes were used to start with, which are considered first level and are based on the
research questions, literature, and conceptual frameworks. Cycle coding was then used in the
second round to identify patterns and themes (Creswell & Creswell, 2017). Once this round of
coding was complete, themes were created based on sources including the literature, participant
responses, and my knowledge. According to Creswell (2017), in qualitative inquiry, theories are
used as a lens for questions asked, and they are used in a more varied way throughout the study.
As such, data was analyzed through the lens of Bandura’s (1997) self-efficacy framework and
themes were focused on the purpose of the study. Data analysis software was not used in this
study since the sample size was small and manageable.
The second phase in convergent design analysis consists of analyzing the quantitative
results of the survey (Creswell & Creswell, 2017). Because the sample size of the study is six, it
was determined that a visual analysis of the results was adequate to serve the purpose of this
43
study. The visual analysis explored individual variation to check how teacher self-efficacy
changed over time.
The third and final stage in convergent design analysis consists of merging the results
from both the qualitative and quantitative findings (Creswell & Creswell, 2017). To accomplish
this, a side-by-side comparison will be presented in the findings section of this study that first
reports the quantitative results and then discusses the qualitative findings (Creswell & Creswell,
2017).
Trustworthiness
According to Lincoln and Guba (1985) the trustworthiness of a research study is critical
in evaluating its worth. In order to ensure trustworthiness, four criteria must be considered and
established. The first criterion is credibility, which is confidence in the truth of the findings. The
second is transferability, which demonstrates that the findings have applicability in other
contexts. The third is dependability, which shows that the findings are consistent and can be
repeated, and the fourth is confirmability, which is the degree of neutrality present in the study
(Lincoln & Guba, 1985). To establish credibility, member checking was done by taking the
themes that were identified in the study back to the participants to assess their accuracy. This
process was conducted via email for a few participants. To establish transferability, the use of
rich, thick descriptions was used as data is interpreted and findings are reported. To establish
dependability, an external audit was conducted whereby an outside researcher examined the
study’s data collection and data analysis process, as well as its results to verify accuracy. Finally,
to establish confirmability, triangulation data was done by comparing the quantitative data
gathered through the MNESEOT survey against the qualitative data collected through the semi-
structured interviews to determine if the findings are consistent.
44
Limitations
Despite the strengths of the validity protocols inherent in this study, there are four
limitations that exist. The first is based on the small sample size used in this study, which means
that there is no way to determine statistical significance based on the data collected from the
survey results (Merriam, 2009). The second limitation is due to the sampling strategy that was
used in this study. According to Merriam and Tisdell (2016), convenience sampling is highly
vulnerable to selection bias and high levels of sampling error. Another limitation of this study is
the result of the different instructional models that each participant subscribes to which might not
align and therefore, might compound their responses on the survey or interviews. For example,
teachers that subscribe to the flipped-classroom model of instruction might have a very different
teaching experience than instructors that do not. A potential fourth limitation is participant bias,
which happens when the participants involved in research respond in a manner that suggests they
are trying to match up with the desired result of the researcher. Since I had both personal and
professional history with three of the six participants, these phenomena might have impacted
their responses.
Role of the Researcher
Because the primary instrument in a qualitative study is the researcher, Merriam (2009)
suggested that the researcher examine and recognize their personal assumptions and biases.
There are two main identities that I continuously reflected on as this study was conducted, which
include being an instructional designer at the institution where the study took place as well as an
online faculty member at a neighboring large, private, 4-year institution. As an instructional
designer that has worked on designing, developing, managing, and assessing a number of fully
online programs I have my own perceptions of what quality online instruction should look like.
45
Additionally, I have spent a significant amount of time in this role developing faculty to be more
efficacious in their online instruction. As an adjunct faculty member that teaches fully online
courses, it is important for me to reflect on how this role might impact the way I interpret the
data in this study. I have a certain teaching style that might not match those of the study’s
participants and reminding myself that my role in this study is the researcher and not faculty
member is important to revisit to mitigate any potential biases.
Though I recognize these experiences influence my thoughts and opinions in online
teaching, I was able to remain neutral throughout the study by reflecting on these two identities
and taking field notes throughout the data collection process. These notes allowed me to identify
any potential biases that might impact the validity of the study’s findings. Ethical standards were
followed per the rules and regulations of the institutional review board at USC.
Conclusion
Chapter Three outlined the methodological approach of this study. In addition to
reiterating the purpose of this study, Chapter Three shared the site and sample selection
strategies, data collection and analysis methodologies, data validation techniques, the role of the
researcher, and the limitations of this study. The results of the data collection and analysis will be
presented and discussed in Chapter Four.
46
Chapter Four: Results or Findings
The purpose of this study is to use Bandura’s (1997) social cognitive theory framework to
explore the perceived role that Gosling’s (2005) collaborative reflection model of peer
observation has on online faculty’s self-efficacy beliefs. In addition, this study sought to
understand the perceived challenges and benefits associated with this peer observation model’s
implementation. This study is significant to the field of higher education because the demand for
online programs continues to increase as student demographics continue to shift, surfacing a
need to identify faculty developmental programs that will prepare online instructors to be more
efficacious. A disproportionate amount of faculty in post-secondary education lacks the desire
and confidence to effectively teach in the online environment (Ma et al., 2021). It is important to
investigate the role that peer observations play in building teacher self-efficacy beliefs as this
data can inform curriculum and policy decisions around faculty development programs which
can ultimately enable post-secondary institutions to meet the ever-growing demand of online
programs.
While there are several key stakeholders that contribute to helping higher ed
institutions employ quality online programs, this study focused specifically on the perceptions
of higher ed faculty that teach at least one online course. The research questions listed below
were used to guide this study:
1. What is the perceived impact of the collaborative reflection model of peer
observation on higher ed online teachers’ self-efficacy beliefs?
2. What are the perceived benefits and challenges associated with this observation
model’s implementation?
47
Findings
The findings of this study suggest that online teaching experience played an important
role on how Gosling’s (2005) collaborative reflection model of peer observation impacted
participants' four sources of self-efficacy beliefs. According to Zimmerman (2002), self-efficacy
refers to an individual’s belief about their capacity to perform or execute behaviors at a particular
level. The information that people use to assess their self-efficacy comes from four sources
which include (a) mastery experiences, based on their interpretations of actual performance; (b)
vicarious experiences, based on modeled performance; (c) forms of social persuasion, based on
feedback learners receive from others; and (d) physiological indexes, based on feelings about
their personal abilities in a particular situation (Bandura, 1997). This study employed these four
sources as a lens to investigate research question 1 and the findings are presented using this
framework as an outline.
Pre- and Post-Survey
A pre- and post-survey was used for the quantitative portion of this study. The
MNESEOT uses factor analysis to confirm four factors for self-efficacy and has been used in
previous studies to compare self-efficacy against demographic variables and experience for
higher ed faculty teaching online. The four factors for self-efficacy that the survey measures
include online student engagement, self-efficacy in online instructional strategies, self-efficacy
for online classroom management, and self-efficacy in the use of computers (Robinia &
Anderson, 2010). The survey has 29, 5-point Likert scale questions including 24 items based on
the TSES and five extra items to include technology application (Robinia & Anderson, 2010).
The table below illustrates the average of the four self-efficacy factors for each
participant as well as the combined average for all four participants. The results of the pre- and
48
post-survey responses show no significant difference in self-efficacy factors. A complete list of
survey questions is available in the appendix for review and reference. Despite the lack of
statistical significance, the survey added value both to prime participants to engage in the study
as well as to frame probing questions during the interview process of data collection.
49
Table 1
MNESEOT Survey Results
Pre-survey avg. Post-survey avg. Change
Survey category: Student engagement
P1 4.75 4.88 0.13
P2 4.13 4.50 0.38
P3 4.38 4.50 0.13
P4 4.13 5.00 0.88
Total 4.34 4.72 0.38
Survey category: Online instructional strategies
P1 4.40 4.88 0.48
P2 4.00 4.25 0.25
P3 4.40 4.13 -0.28
P4 4.30 4.63 0.33
Total 4.28 4.47 0.19
Survey category: Online classroom management
P1 5.00 5.00 0.00
P2 4.17 4.33 0.17
P3 4.17 4.00 -0.17
P4 5.00 5.00 0.00
Total 4.58 4.58 0.00
Survey category: Use of computers
P1 4.75 5 0.25
P2 4.25 4.5 0.25
P3 4.5 3.5 -1.00
P4 3.5 5 1.50
Total 4.25 4.5 0.25
Note. The table shows the pre- and post-survey results for each participant (P), along with the
total average and change.
The pre-survey data suggests that the participants entered this study already having some
online teaching experience and felt relatively efficacious employing this instructional modality.
Through conversations with participants during the interviews it was confirmed that all had
50
online teaching experience with the minimum being 1.5 years and the maximum being 10. This
information was particularly helpful during the interview process since I was able to ask probing
questions pertaining to participants’ mastery experiences, which would have otherwise been
omitted. Additionally, the high scores of the pre-survey data suggest that all participants, even
novice, had a high level of expertise in online instruction and were already favorably oriented
toward improving their teaching by testing new and creative instructional approaches. This
finding prompted me to include participant bias as a possible limitation in this study. Another
way the survey contributed to this study surfaced during the interview process when it became
clear that participants found value in the survey as it helped prepare them to actively engage in
the study. Participants used the survey questions as a preview of what knowledge and skills their
partners might look for when observing their online class. As such, the survey served to help
prime participants around study expectations.
Research Question 1
The first research question in this study explored the perceived impact of the
collaborative reflection model of peer observation on higher ed online teachers’ self-efficacy
beliefs. I used the four sources of self-efficacy as a lens to answer this research question. The
following findings emerged which helped to understand the extent to which peer observations
impacted the force sources of self-efficacy beliefs for participants:
• Peer observations played a critical role in affirming expert online instructors’ mastery
experiences while allowing them to position themselves as mentors when working
with novice online instructors.
• The observation checklist played a critical role in supporting the vicarious
experiences for novice online instructors.
51
• Social persuasions in the form of timely verbal feedback played an important role in
impacting both novice and experienced online instructors’ perceptions of self-
efficacy.
• Emotional states were impacted by the time in which observations occurred and
influenced both novice and expert participants’ perceptions of self-efficacy.
Peer Observation Affirmed Mastery Experiences for Expert Online Teachers and
Positioned Them as Mentors and Coaches
From four of the six interviews with participants, it was clear that their participation in
peer observations served to affirm expert online teachers’ mastery experiences. According to
Bandura (1997), “Mastery experiences are the most influential source of self-efficacy
information because they provide the most authentic evidence of whether one can muster
whatever it takes to succeed. Success builds a robust belief in one’s personal efficacy” (p. 191).
The data from the study shows the greatest source of affirmation came from when experienced
online instructors assumed the role of observer during the observation process of the study.
Additionally, during the post-observation meeting, the expert online instructors leveraged their
expertise when working with less experienced online instructors to mentor them toward
developing advanced online teaching skills.
Affirming Mastery Experiences as an Observer
Although Gosling’s (2005) collaborative reflection model of peer observation has minor
variations (number of participants involved, quantity of observation occurrences, qualifications
of the observer, etc.) to meet institution’s unique needs, the framework is consistent across all of
them, which includes a three-step process of (a) pre-observation meeting, (b) observation, and (c)
feedback meeting (post-observation). During Step 2 of the process participants assume two roles:
52
the observed and the observer. As the observer, participants are responsible for critically
watching and listening to their partner deliver their lesson. It is during this stage where
experienced online instructors gained the most affirmation of their mastery experiences. For
example, one of the participants that had 8 years of online teaching experience shared,
During our pre-observation meeting, my partner and I went into great detail about how
the flow of our lessons would go. This was important because we both use breakout
rooms a lot during our synchronous sessions and Zoom does not record what’s
happening in breakout rooms. So, when we observed each other's lessons, we had the
context that we needed in order for us to understand the purpose behind each breakout
room activity. I didn’t realize until after the observation that my partner used many of
the same online engagement strategies that I’ve come to embrace over the many years
I’ve taught online. Watching my partner use these strategies affirmed the things I feel I
do well. … So, yeah, in general being the observer affirmed my own feelings about my
own teaching and gave me some insights that I might not have otherwise had.
Another participant, having 10 years of online teaching experience, shared the following
perceptions as she assumed the role of observer in this study:
There are checks and balances when teaching online and when observing someone who
is a peer and colleague within the same organization teaching their online course, I
would expect that they were being held to similar standards and expectations. To
observe that she was aligned on how I conduct my own online class tells me that
collectively we are a very collegial faculty. We are comfortable enough to share best
practices, and I know her, and I both felt affirmed that we have grown into great online
instructors through our experience.
53
Both of these faculty members’ perceptions of mastery experiences being affirmed when
assuming the observer role in this study was consistent with the other two faculty members’
accounts, who had at least 5 years teaching experience. In other words, faculty used the role of
the observer to affirm their belief that they are not only capable of carrying out difficult tasks
associated with teaching online, but through their many years of teaching online, have gained
enough practice to do so at a very high level.
Assuming the Role of Mentor During the Post-Observation Meeting
According to the participants in this study, the third step of the observation model, which
is the post-observation meeting, was especially important for instructors that were new to online
teaching. During the post-observation meeting participants shared the notes that were captured
while observing their partners deliver their online lesson. For participants with less than 2 years
of teaching experience that were partnered with faculty that had at least 5 years of online
teaching experience, the nature of the meeting became that of mentor/mentee. Faculty that were
new to online teaching not only acknowledge the expertise of the more experienced online
instructors but leaned into that experience to up-skill their abilities to effectively maneuver in
this space. For example, one participant with 1.5 years of online teaching experience shared the
following account of her post-observation meeting:
I knew that I struggled with many of the logistics around teaching online. I really
wanted to offer engaging learning opportunities for my students but didn’t know how to
effectively leverage the technology that would enable me to do so. During the meeting I
had with my partner she showed me how she sets up breakout rooms, polls, and other
interactive tools within her online class. She also gave me awesome tips on how I can
delegate some of the online class management responsibilities to my students. For
54
example, I’m really bad at monitoring the chat area during class because there are so
many things going on at once. She suggested that I assign one of my students to be the
chat monitor to field any questions that might come up in the chat. This tip really
alleviated my stress of teaching while tending to the chat box.
Meanwhile, her partner’s perspective on the post-observation meeting captured her
enthusiasm around sharing the knowledge she gained through the many years of teaching online
with her partner because ultimately, they were working toward the same goals.
I was thrilled that I could share some of the tips that I learned through the years that I’ve
taught online. To be honest, I wish I had someone to do the same when I started teaching
online. The truth is, we as faculty don’t have many opportunities to observe other
professors teach, so when the opportunity to participate in this study came up, I was
excited to do so. I know that if I can help a teacher feel better and be better at teaching
online, all of our students will win.
It became clear during participant interviews that the role the collaborative reflection
model of peer observation played in impacting the first source of self-efficacy beliefs was to
affirm the mastery experiences of expert online instructors while positioning them as mentors
during the post-observation meetings.
The Observation Checklist Played a Critical Role in Supporting the Vicarious Experiences
for Novice Online Instructors
Participants in the study were encouraged to use USC CET’s synchronous online teaching
observation checklist as a tool to analyze the learning taking place in a synchronous online
setting. From the interviews with novice online faculty, it became clear that an observation
checklist was important to help focus participant attention on critical elements of successful
55
synchronous online instruction. According to Bandura (1977), “Seeing people similar to oneself
succeed by sustained efforts raises observers’ beliefs that they too possess the capabilities to
master comparable activities to succeed” (p. 212). The observation checklist used in this study
ultimately served to support the vicarious experiences of participants as it helped them
understand and identify what successful online instruction looked like. Additionally, the data
from this study suggests that the observation checklist was extremely valuable for novice online
faculty particularly during the post-observation meeting as it provided a useful framework
whereby meaningful feedback can be identified and conveyed to their more experienced
partners. Ultimately, the post-observation meeting served to reinforce vicarious experiences for
novice participants in this study.
Using the Observation Checklist During the Observation Process to Gauge What Success
Looks Like
Because vicarious experiences involve observing other people successfully completing a
task, it is essential for participants to know what success looks like. Therefore, I paired the only
two novice online teaching participants (< 2 years online teaching experience) with experienced
online instructors (> 5 years online teaching experience) to emphasize peer modeling. Through
the interviews it was discovered that novice online instructors relied on the observation checklist
to understand what success looks like, which is essential for vicarious experiences to have an
impact on self-efficacy beliefs. Below is the perspective of one novice online instructor:
Prior to observing my partner teach her lesson, I had a very basic idea of what successful
online instruction looked like. I knew I should avoid lecturing at my students for 3 hours
and I should try to use as many engaging activities as possible, but I wasn’t entirely sure
what was available in the online space. Before I watched my partner’s recording of her
56
class, I reviewed the checklist that you provided, and it really helped me in terms of
what I should be looking for when I watched the recording. There were elements in the
checklist that I wouldn’t have even considered like time management and classroom
climate. Reviewing the particular standards within each category helped me better
understand what success looked like and when I was able to see these standards in action
when observing my partner, I realized that these skills and techniques are not elusive
and can be learned with more practice.
The other novice online instructor shared similar sentiments further validating that the
observation checklist helped novice online instructors visualize what successful online
instruction looks like, which is necessary for vicarious experiences to play a role on one’s self-
efficacy beliefs.
The Post-Observation Meeting Served to Reinforce Vicarious Experiences for Novice
Participants
Data from this study shows that the observation checklist was valuable for novice online
faculty during the post-observation meeting because it provided a useful framework whereby
meaningful feedback can be identified and conveyed to their more experienced partners.
Furthermore, it was discovered that the post-observation meeting served to reinforce vicarious
experiences for novice participants in this study. A participant with 1.5 years teaching experience
states,
I learned a lot during the post-observation meeting. It really didn’t matter whether I was
receiving or giving feedback. I think both exercises were super valuable for me.
Although, I know that I wouldn’t have been able to provide constructive feedback if not
for the checklist. I added all my notes when observing to the checklist and this really
57
helped me structure my feedback during the post-observation meeting. In fact, my
partner who had a lot more online teaching experience than me thought that my
suggestion to use a randomizer tool when cold-calling on students was an excellent idea.
I guess her validating my suggestions gave me stronger beliefs in my own ability to
teach online. The checklist also helped me identify the many, many areas that my partner
was doing exceptionally well in like breakout sessions. The checklist helped me talk like
an online expert.
These findings were further validated when interviewing the second novice online
faculty that had 2 years teaching experience:
The observation checklist pretty much shaped the feedback I gave during the post-
observation meeting. I wanted to make sure that I added value to my partner’s experience
and the checklist helped me identify some talking points that I would not have considered
without it. When I observed my partner teach, I knew she was really great at engaging her
students and the checklist helped me identify the key components that helped her be so
successful.
Through the interviews with two novice online instructors, it was discovered that the
observation checklist played a critical role in supporting the vicarious experiences for novice
online instructors by establishing what success in online instruction looks like. Additionally, the
checklist enabled novice online instructors to provide meaningful feedback to their more
experienced peers which further reinforced the vicarious experience information that was gained
through the peer observation.
58
Social Persuasions in the Form of Timely Verbal Feedback Played an Important Role in
Impacting Both Novice and Experienced Online Instructors’ Perceptions of Self-Efficacy
According to Redmond (2010), self-efficacy is influenced by encouragement and
discouragement pertaining to an individual’s performance or ability to perform. The data from
this study shows that social persuasions in the form of timely verbal feedback played an
important role in impacting both novice and experienced online instructors’ self-efficacy beliefs.
Another theme that appeared in this study is the medium in which feedback is delivered (written
vs verbal) plays an important role in forming social-persuasion information. These findings will
be further discussed in the data analysis
The data from this study shows that timely and structured feedback played an important
role in impacting self-efficacy beliefs for all participants, novice and experienced. Of the three
groups, two completed their post-observation meetings the same week the lessons were
delivered. Each participant in these groups agreed that the timing of the post-observation meeting
was beneficial because it enabled them to recall details of their lesson that they might have
otherwise forgotten. One of the novice faculties shared,
My partner is an amazing online teacher and has been teaching online for so many years.
When she was giving me feedback on my lesson, I was able to remember every moment
that she referred to in her notes and even how I felt at that moment in the lesson. …
Like, she mentioned a time when I was trying to share a Google document with my
class, and they were not able to access it because I didn’t choose the right settings. I
remember feeling flustered and somewhat embarrassed, but my partner said that I did a
good job keeping my composure. I think having our post-observation meeting right after
59
the lesson really helped me match my partner’s feedback to my actions and helped me
identify areas that I did well and areas that I can improve.
There was one group that conducted their post-observation meeting nearly 1 month after
the observations took place. This group echoed the importance that timing has on social
persuasions as one of the participants in this group shares,
We [my partner and I] were not able to meet for a month after we observed each other.
To be honest, I think the gap really impacted my ability to give and receive feedback. It
was difficult to remember what areas of the lesson that my partner was referring to when
she gave me feedback. Luckily, she added timecodes to her notes, so we were able to
rewatch that segment of my lesson’s recording and I was able to connect the dots.
Unfortunately, I didn’t think about adding timecodes to my notes, so I think my
feedback was less impactful because there were moments that I mentioned something in
my notes and neither one of use was able to remember what I was referring to.
Another theme that appeared in this study is the medium in which feedback is delivered
(written vs verbal) plays an important role in forming social-persuasion information. Most
participants reviewed their partner’s observation notes prior to the post-observation meeting and
were not able to decipher what points were being made. In other words, the written notes alone
were not enough to provide the information necessary to assess their instructional performance.
However, when the notes were coupled with verbal explanation the participants were able to
make meaning of the feedback and action on it. One of the participants shared,
All of the documents that we used during the study were located in a shared Google
drive folder that we (the two partners) had access to. Just before our post-observation
meeting, I looked at the notes that my partner took on her observation guide hoping that
60
it would prepare me for our meeting, but it really didn’t. It wasn’t until my partner
explained her notes to me that I was able to see how I can include these suggestions into
my practice.
Through the interviews it was discovered that both timing and medium played an
important role in forming social-persuasion information for participants. Ideally, feedback will
be provided soon after observations take place and will be delivered verbally to optimize social-
persuasion information.
Emotional States Were Impacted by the Time in Which Observations Occurred and
Influenced Both Novice and Expert Participants’ Perceptions of Self-Efficacy
According to Bandura (1997), the emotional, physical, and psychological well-being of a
person can influence how people feel about their personal abilities in a particular situation. The
data from the study shows that the time in which observations occurred during the school year
impact participants’ emotional states and how they perceived their self-efficacy when teaching
online. Two of the six participants delivered their observed lessons during the week of midterms,
which they admit is a very stressful time of year for them. Both participants shared that during
the time of the observations, they were also designing and/or grading their midterm assessments.
Furthermore, they shared how their reaction to stress made them question the quality of their
performance during the observed lesson, many of whom had doubts about their instructional
effectiveness. One of the expert online instructors shared the following story:
If there is one thing I would change in this experience, it would be when I decided to
deliver the lesson that my partner was going to observe. To be honest, I don’t think I was
fully present when delivering the lesson because my mind was busy thinking about the
midterms for all of my classes at the time. I had about 70 essays that I needed to grade,
61
and I promised my students that I would give them their grades the following week. I
was also in the middle of designing a midterm for another class, which was the first time
I was teaching that content. I was pretty stressed when I was teaching that lesson and I
thought my students were picking up on that, which made me question if I was being as
effective as I know I can be.
These sentiments were shared with the other participants in the study whose observations
occurred near midterm’s week. The following is an account of a novice online instructor, who
had just finished grading her midterms:
I literally just finished grading my last midterm 5 minutes prior to starting my online
class [the one being observed]. I noticed that most of my students did not grasp one of
the foundational concepts in my class, which was on critically reflective teaching. This
is a core concept in my class that most other theories are built upon. We covered this
content during the first 3 weeks of class and have built on this information during the
following weeks leading up till now. Knowing that they didn’t fully understand the
lessons on critically reflective teaching shows me that I need to reteach the concepts,
which also means I need to restructure the second half of the semester. … I wasn’t sure
if I was stressed or frustrated but I didn’t feel at my best when I was delivering my
[observed] lesson.
In both of these accounts, the participants acknowledge the role timing played in
impacting their emotional state as they delivered their observed lesson. Ultimately, their
emotional states had them question their instructional effectiveness, and hence, their perceived
self-efficacy.
62
Research Question 2
The second research question in this study explored the perceived benefits and challenges
associated with the collaborative reflection model of peer observation’s implementation. Using
data collected through the interviews with participants, the following findings emerged which
helped answer the second research question:
Benefits
• The reciprocal nature of the observation model facilitated adoption of a collegial
mindset between partners
• Collegial mindsets encouraged constructive conversations and laid the foundation for
improved performance
Challenges
• The three phases of the observation model require a significant amount of logistical
considerations around scheduling, time commitment, and technology constraints
• Logistical considerations ultimately impact the scalability of this particular
observation model’s implementation
The Reciprocal Nature of the Observation Model Facilitated Adoption of a Collegial
Mindset Between Partners That Encouraged Constructive Conversations and Laid the
Foundation for Improved Performance
The data from the study shows that the reciprocal nature of this study’s peer observation
model facilitated adoption of a collegial mindset between partners. According to Robinson
(2015), there are five attributes that define collegial behaviors which include caring about others,
expanding, collaborative, unifying others, and being future-oriented. These attributes surfaced
while interviewing participants, which ultimately encouraged constructive conversations that
63
were mutually beneficial to participants as they helped to define specific and actionable steps to
improve instructional performance in a virtual setting.
Reciprocity Facilitated Adoption of a Collegial Mindset
Gosling’s (2005) collaborative reflection model of peer observation asks participants to
reciprocate targeted efforts that focus on improving instructional quality and student success.
Data from interviews suggest that reciprocity facilitated adoption of a collegial mindset between
partners. I used Robinson’s (2015) five attributes to identify collegial behaviors that surfaced
during interviews. The five collegial attributes include
● Caring about others: sharing concern about the success of others
● Expanding: increasing perspectives and opportunities with others
● Collaborative: two or more parties working together toward a common goal
● Unifying others: being inclusive and sharing the load
● Future-oriented: investing in a shared vision
These attributes surfaced during interviews with participants as they described the
reciprocal nature of Gosling’s (2005) collaborative reflection model of peer observation. Below
is the account of one of the expert participants:
The first interaction I had with my partner was when she emailed me her lesson plan for
the class that I was going to observe. I was really impressed by the level of detail she
included in her plans. I know she put a lot of time and thought into her lesson, so I
wanted to provide as much feedback as possible to help make sure her lesson went as
smoothly as possible. … During our pre-observation meeting I was able to show her
how to use Google slides as a ‘fish-bowl’ activity which she ended up using in her
lesson and students seemed to really like it. My partner also gave me awesome feedback
64
on how I could improve the assessment in my lesson, which I ended up using. The
feedback we gave each other in the pre-observation meeting just helped create better
learning opportunities for our students.
The quote above suggests that the participant was motivated to reciprocate the efforts that
her partner exerted when creating their lesson plan by providing substantive feedback that would
optimize the lesson’s instructional effectiveness. Three collegial attributes surfaced from this
quote, which include caring about others, expanding, and collaborative. The expert participant’s
desire to make sure that her partner’s lesson “went as smooth as possible” shows concern about
the success of her partner. Additionally, the suggestion to include a fish-bowl activity created
new instructional perspectives and opportunities for her partner. Finally, both partners worked
together to create better learning opportunities for their students, which was a shared goal.
Another quote that highlights the reciprocal nature of Gosling’s (2005) collaborative
reflection model of peer observation was shared by a novice participant. The collegial attributes
that surfaced from the following quote include caring about others, unifying others, and being
future-oriented:
I really appreciated the level of detailed feedback my partner gave me during the
post-observation meeting. I felt like she had a real interest in seeing me do well. She even
offered to do another observation with me during the summer term as a follow-up to see
if I’m doing better in the areas we identified that I needed to work on. She also
introduced me to an instructional designer for the Center of Excellence in Teaching that
she said helped her become more confident when she transitioned to online teaching. …
My partner knew that I was new to online teaching, and I tried my best to be as valuable
to her in this process as she was to me.
65
This participant shared their desire to reciprocate the value that her partner brings to this
process despite her limited online teaching experience. The expert partner’s willingness to
participate in another observation during the summer term not only suggests that she cares about
the growth and development in her profession, but also shows that she is invested in her success.
Finally, introducing the instructional designer from the Center of Excellence in Teaching
increased inclusion and allowed the expert participant to share the load of developing the novice
instructor.
Constructive Conversations Laid the Foundation for Improved Performance
Data from the interviews provide a clear indication that the pre- and post-observation
meetings create a space where constructive conversations can occur and criteria for improved
performance can be identified and shared. This was true for both novice and expert online
instructors as both perspectives were able to provide valuable insights on areas of strengths and
opportunities for improvement. For expert online instructors, constructive conversations
validated the areas of online teaching that they felt confident in allowing them to focus on areas
where they felt less self-efficacious. For example, one of the expert participants came into this
study feeling confident in her ability to actively engage students through the use of different
media in her online course. However, she did not feel confident in her ability to maintain
compliance when sharing copyrighted materials in her online course. During the post-
observation meeting her ability to effectively use different media to optimize instruction was
validated, which allowed her to focus her attention on learning compliance enablement strategies
when using copyrighted materials.
In addition to validating perceived strengths, constructive conversations allowed both
expert and novice instructors to identify and share criteria for improved performance. This was
66
particularly true during the post-observation meetings where participants used the observation
checklist to share their observation discoveries with their partner. Through the interviews it was
clear that participants intend to use the feedback collected through the observation checklist as
criteria to monitor their progress toward becoming a more effective online instructor. Some
participants worked with their partners to prioritize which criteria would have the greatest impact
on their instruction. These dialogues provide a roadmap that participants can use to improve their
performance as an online educator.
The Three Phases of the Observation Model Require a Significant Amount of Logistical
Considerations Which Ultimately Impacts the Scalability of This Particular Observation
Model’s Implementation
Gosling’s (2005) collaborative reflection model of peer observation consists of three
phases: (a) pre-observation meeting, (b) observation, and (c) feedback meeting (post-
observation). Data from the interviews show that this observation model required participants to
make many logistical considerations which impacted their perceptions around the efficiency and
scalability of this model’s implementation. Three themes surfaced that impacted participants’
perceptions: scheduling, time commitment, and technology.
Scheduling
Because each phase of this observation model is intended to be completed synchronously,
all of the participants struggled to find times in their already busy calendars to meet this
requirement, either virtually or in-person. At times, I had to step in to support the coordination of
these phases for some participant groups. There were some cases where the participants had no
availability to complete a phase synchronously by the given deadline, so I helped brainstorm
asynchronous solutions that would still allow each phase of the process to be completed. These
67
accommodations were not uncommon and occurred in each group because of the participants'
impacted schedules.
Time Commitment
This observation model is designed to be cyclical whereby each partner completes all
phases of the process as an observer or observed and then repeats the entire process again
assuming the opposite role. In essence, each group had to complete the observation cycle twice
which perpetuated the scheduling struggles that each participant was already experiencing. I
made accommodations for some groups given their limited availability which allowed groups to
debrief the pre- and post-observation meetings once rather than having to schedule two meetings
for each phase. This accommodation required participants to have slightly longer meetings but
lessened the logistical burden of finding and scheduling time.
Technology
Logistical concerns around secure file sharing and accessing synchronous classes arose
for most groups. Since faculty were sharing access to electronic files that could contain student
information, it was important for them to identify safe ways to share such files that maintain
FERPA compliance. Identifying a platform that each partner in a group felt comfortable using
was not always possible, so I helped facilitate file sharing for these groups. Additionally, for
participants that opted to complete a synchronous observation (as opposed to watching a
recording of the lesson) many had trouble accessing the Zoom link that was shared with them
due to authentication issues. I later learned that the integration between Zoom and Blackboard
(the university’s learning management system) requires people to log in to Zoom using their
usc.edu email accounts in order to access a USC administered Zoom link.
68
Scheduling, time commitment, and technology presented many logistical challenges for
participants which impacted their perceptions around the efficiency and scalability of this
model’s implementation.
Summary
The results and findings of this study were presented in this chapter. Data collected from
this study show that Gosling’s (2005) collaborative reflection model of peer observation had an
impact on each of the participants' four sources of self-efficacy beliefs. The following findings
emerged that helped answer the first research question.
The results and findings of this study were presented in this chapter. Data collected from
this study show that Gosling’s (2005) collaborative reflection model of peer observation had an
impact on each of the participants' four sources of self-efficacy beliefs. The following findings
emerged that helped answer the first research question:
• Peer observations played a critical role in affirming expert online instructors’ mastery
experiences while allowing them to position themselves as mentors when working
with novice online instructors.
• The observation checklist played a critical role in supporting the vicarious
experiences for novice online instructors.
• Social persuasions in the form of timely verbal feedback played an important role in
impacting both novice and experienced online instructors’ perceptions of self-
efficacy.
• Emotional states were impacted by the time in which observations occurred and
influenced both novice and expert participants’ perceptions of self-efficacy.
69
Additionally, the following themes emerged that help answer the second research
question:
o Benefits: The reciprocal nature of the observation model facilitated adoption
of a collegial mindset between partners that encouraged constructive
conversations and laid the foundation for improved performance.
o Challenges: The three phases of the observation model require a significant
amount of logistical considerations which ultimately impacts the scalability of
this particular observation model’s implementation.
In the following chapter, I will discuss the findings in greater detail, offer
recommendations, and offer suggestions for future research.
70
Chapter Five: Discussion
Chapter Four presented the findings that resulted from the MNESEOT as well as the
qualitative interviews with online faculty at USC. The findings were presented in the form of
themes that were discovered from the data that helped answer the two research questions.
We will discuss the study’s findings in Chapter Five. Additionally, I will present
recommendations for post-secondary institutions that are interested in using peer observations,
and more specifically, Gosling’s (2005) collaborative reflection model of peer observation, as a
way to prepare faculty to teach online. Lastly, this chapter will present suggestions for future
research.
Discussion
The purpose of this study is to use Bandura’s (1997) social cognitive theory framework to
explore the perceived role that Gosling’s (2005) collaborative reflection model of peer
observation has on online faculty’s self-efficacy beliefs. In addition, this study sought to
understand the perceived challenges and benefits associated with this peer observation model’s
implementation. Overall, the attitudes and perceptions of both novice and expert online faculty
confirm that participation in Gosling’s peer observation model had an impact on their self-
efficacy beliefs. Several insights and implications can be drawn from an analysis of the findings
of this study. The following discussion section presents these points and discusses why critical
elements such as feedback, automaticity, scaffolds, instructional media, and timing should be
considered when planning and implementing peer observation models to improve teacher quality
at post-secondary institutions. Additional discussion around the long-term benefits of this
observation model is also offered below.
71
The Importance of Feedback in Peer Observation
Though all four sources of self-efficacy beliefs were impacted by this study for novice
and expert online instructors, the greatest source of self-efficacy information seemed to have
come from social-persuasion data, which refers to evaluative feedback (positive or negative) that
individuals receive after performing a task (Bandura, 1997). This might seem counterintuitive
since the nature of any observation model ostensibly would make a greater contribution to
vicarious experience information, which is based on modeled performance. However, this
finding further reinforces the importance of providing feedback when in pursuit mastery
development. According to Ambrose et al. (2010), “goal directed practice must be coordinated
with targeted feedback in order to promote the greatest learning gains” (p. 137). The feedback
that was provided to participants by their peers encouraged them to be more innovative in their
online instructional approaches, which is a key indicator of strong self-efficacy beliefs.
Furthermore, novice faculty had perceptions of themselves struggling while teaching
online prior to participating in this study, which created stress and anxiety whenever having to
teach online. However, the conversations that took place during the post-observation meetings
highlighted their instructional strengths in online teaching and bolstered their confidence in this
instructional space. This discovery corroborates Klassenm et al.’s (2011) findings that teachers
with high self-efficacy have positive beliefs about teaching and are more willing to experiment
with promising instructional strategies whereas those with low self-efficacy experience greater
difficulties in teaching, lower levels of job satisfaction, and higher levels of job-related stress. As
such, it can be stated that the post-observation meetings played a critical role in the development
of participants in this study.
72
Implications of Automaticity
The findings in this study suggest that the theory of automaticity, which claims that most
of all human knowledge is automated and unconscious (Moors & De Houwer, 2006), has
implications on expert online faculty sensitivity to cues that indicate student performance when
teaching synchronous lessons. One of the four sources of self-efficacy that was examined in this
study was mastery experiences, which are actual teaching accomplishments in which teachers
witness student performance improvement (Horvitz et al., 2015). Data from the interviews show
that, in many instances, expert online faculty used the reinforcing feedback provided by their
novice peers to identify cues of student performance improvement that might have otherwise
gone unnoticed because of their expertise in this domain. For example, appreciation for the
critically reflective conversations that occurred in breakout rooms were not fully realized
amongst expert online faculty until it was discussed during the post-observation meetings. Expert
online faculty agreed that these conversations are indicators of improved student performance
which they might have taken for granted because of regular and ongoing exposure to this level of
engagement within breakout rooms.
Using Scaffolds for Learning
This study’s findings suggest that scaffolds should be used to set instructional
expectations with novice online faculty. Another source of self-efficacy that was examined in this
study was vicarious experiences, which novice online faculty relied on the USC CET’s
synchronous online teaching observation checklist to inform their self-efficacy beliefs. In order
for one’s self-efficacy beliefs to be impacted by vicarious experiences, one must witness a peer
succeed in comparable activities (Bandura, 1977). In this case, an online faculty member needed
to see a peer be successful in teaching online in order for there to be the potential of vicarious
73
experiences. However, this study found that novice online faculty in this study were not sure of
what successful online instruction looked like, so they relied on the synchronous online teaching
observation checklist to help establish online instruction success criteria. This finding suggests
that novice online faculty might require scaffolds such as checklists and exemplars to help
establish expectations around successful online instruction which they can effort toward.
Instructional Media Implications
This study found that written feedback had little to no impact on social-persuasion
information as perceived by the participants in this study. It is true that each participant had their
own method of taking observation notes and formatted them in a way that made the most sense
to them. However, when sharing the notes with their partners it became clear that meaning
making was not done through text alone and required an audio narration for learning to occur.
This finding supports Mayer’s (2011) personalization principle, which states that “people
learn better from multimedia lessons when words are in conversational style rather than formal
style” (p. 70). Discovering that another medium was required, specifically audio, in order to
enable the observation notes as a learning tool can have a significant impact on future iterations
of this peer observation model.
Implications of Timing
The stress levels that many faculty were experiencing during the time of their
observations are important to consider when designing future iterations of this peer observation
model’s implementation. This discovery contributes to the body of literature around teacher self-
efficacy as previous studies were unclear of the role peer observations had on informing
emotional and psychological states, which is the fourth and final source of self-efficacy. Because
the time in which certain steps of the peer observation model take place could impact participant
74
perceptions on performance, regardless of their level of online teaching and learning expertise,
this discovery has the potential to mitigate misperceptions of instructional performance which
can have detrimental effects on self-efficacy beliefs.
The Benefits Outweigh the Challenges
The benefits of this observation model’s implementation have the potential to outweigh
its challenges, if appropriate support mechanisms are in place that enable faculty participation
and shift negative perceptions established through historical iterations. During the interviews,
each participant said that they valued their experience participating in this study and would be
willing to volunteer in another peer observation cycle if their schedules permit. This finding
suggests that Gosling's peer observation model fosters an environment where teacher collective
efficacy can take root and flourish. According to Bandura (1997) teacher collective efficacy
refers to a group of teachers’ shared belief that through their collective action, they can positively
impact student learning. Previous studies have shown that teacher collective efficacy is
significantly related to student achievement and academic climate (Klassen et al., 2011). As such,
using Gosling's peer observation model as a vehicle to promote teacher collective efficacy has
the potential to have a significant positive impact at higher education institutions.
However, the logistical challenges associated with this peer observation model creates
roadblocks for scalable implementation. Participants were very resourceful in meeting the
requirements of this study while also managing the many other obligations they had. Some
participants used scheduling tools such as Calendly where their partners were able to schedule
appointments for the pre- and post-observation meetings without having to go back and forth via
email to find a time that works for both partners. Additionally, some participants shared
recordings of their lessons so their partners can complete the observations asynchronously.
75
Similar strategies are described within the recommendations section and are intended to mitigate
participation barriers and increase the scalability of implementation.
In addition to logistical challenges, institutions might also consider ways to shift current
mindsets around observations, which have been negatively influenced by historical iterations that
use this tool as a performance-based accountability measure as opposed to collaborative
professional development opportunity. Early studies showed promising results in using
observations to improve teacher quality in K–12 education; however, this practice became
problematic when applied to higher education for a variety of reasons (Berge, 1998).
Historically, observations within higher education have been conducted to achieve a
summative judgment of the teaching observed and often had significant bearing on the faculty
member’s tenure and promotion status, which had a negative impact on faculty’s motivation to
participate in this process (Yiend et al., 2014). This study found that the peer observation
approach supports collaboration and collegiality amongst participants and promotes performance
improvement. If higher education institutions are able to present the peer observation model as a
collaborative professional development opportunity, as opposed to performance-based
accountability assessment, then it is feasible to assume that more faculty would be less likely to
resist and more willing to participate.
Recommendations
Based on the findings of this study, the following three recommendations are presented to
optimize the effectiveness for future iterations of this peer observation model’s implementation:
• Maximize asynchronous collaboration opportunities for participants in order to
accommodate busy schedules and increase engagement and learning potential
76
• Participants should consider using different forms of media when providing feedback
to accommodate busy schedules
• Classroom video recordings should be allowed for observation purposes to increase
engagement and learning potential
• Administrators should consider the timing of when each step of the peer observation
takes place to optimize feedback and mitigate performance misperceptions
These recommendations are discussed in greater detail below.
Maximize Asynchronous Collaboration Opportunities for Participants to Accommodate
Busy Schedules and Increase Engagement and Learning Potential
All participants in this study described the challenges associated with conducting the pre-
and post-observation meetings synchronously because of scheduling conflicts. There are a total
of four pre- and post-observation meetings that this peer observation model requires participants
to complete and each takes approximately 1 hour. Allowing participants to complete these
meetings asynchronously will help accommodate faculty’s busy schedules and improve the
scalability of this model’s implementation. To accomplish this, faculty can use screen capture
software such as Camtasia or QuickTime to record themselves walking through the details of
their lesson plans (for the pre-observation meetings) as well as their observation notes (for the
post-observation meeting). Once the recordings are complete faculty can upload them to a cloud
service such as Google Drive or DropBox and share the recording with their partners so they can
watch at a time that fits their schedules. Participants can email follow-up questions to their
partners if necessary.
Another way to maximize asynchronous collaboration opportunities is by encouraging
participants to record their synchronous lessons. The link to access the recordings can then be
77
shared with their partners so they can complete the observation at a time that works for them. It
is recommended that faculty have students remove their full names within the web conferencing
platform and replace them with initials prior to starting the recording in order to avoid potential
FERPA violations.
Incorporating asynchronous collaboration opportunities by leveraging video recordings
not only ameliorates the need for groups to sync their schedules in order to participate but it can
also increase engagement and learning potential. First, participants have the ability to control
how they engage with recorded videos by pausing, rewinding, slowing down/speeding up the
playback speed, etc. This control can enable participants to engage with the observation process
more deeply as they have time to critically observe their partner’s instruction as well as think
about the feedback they provide.
Another way that using recordings can increase learning potential is by using the
annotation tools that are available in some screen recording tools to create callouts during a
lesson. For example, one of the expert faculty that participated in this study used Camtasia to
record herself explaining her observation notes. A suggestion that the expert faculty made to her
partner was to remove a mirror that was positioned in the frame of her webcam because the
reflection could be distracting for students. She then took screenshots of reflections from the
mirror that she found distracting such as the ceiling fan and pets and described them in detail
within her recording. This example shows how the use of multiple forms of media can increase
participants’ understanding of the feedback they receive on their instructional performance.
78
Administrators Should Consider the Timing of When Each Step of the Peer Observation
Takes Place
This study’s findings show that timing played an important role in impacting participant’s
sources of self-efficacy beliefs. First, it was discovered that the timing in which the pre and post
observations meetings occurred was important when informing social persuasions. Groups that
waited more than 2 weeks to observe their partners after the pre-observation meeting had a
difficult time recalling important details that they were asked to observe and notate during the
observations. Similarly, groups that waited more than two weeks after their observations took
place to have their post-observation meetings had a difficult time making meaning of their
observation notes. Therefore, it is recommended that pre- and post-observation meetings occur
within 2 weeks of the observations taking place. This will help ensure that (a) observers are able
to recall and attend to the specific parts of the lesson their partners asked for feedback on, and (b)
observers are able to recall the details from their observation notes so they can provide their
partners with meaningful and actionable feedback.
Timing also had an impact on the emotional states of participants and influenced their
perceptions of instructional performance. As such, it is recommended that administrators
consider the timing in which participants complete their observations. I recognize the complexity
of this recommendation especially considering that faculty are all managing a number of
professional and personal obligations. However, administrators can mitigate the potential of
performance misperceptions by considering when observations occur in relation to the academic
calendar. Additional considerations that administrators might want to investigate when recruiting
participants for this professional development opportunity is whether faculty are undergoing
tenure and/or promotion review.
79
Recommendations for Future Research
The findings made through the analysis phase of this study show that peer observations
impact online faculty’s perceptions of self-efficacy beliefs, however, questions remain regarding
whether and how peer observations benefit online students. Therefore, it is recommended that
future studies investigate the longer-term impact that peer observations have on students'
performance by including them as participants in the study. Such a study can extend the findings
of this research by looking at what, if any, real benefits are produced through peer observations
to improve the performance of online student learning as well as define optimum online teaching
practices.
Previous studies demonstrate a positive relationship between teacher self-efficacy and
collective efficacy (Chan, 2008; Kurz & Knight, 2004; Skaalvik & Skaalvik, 2007). Additionally,
studies have shown that collective efficacy is significantly related to student achievement and
academic climate (Klassen et al., 2011). Therefore, it is recommended that similar studies are
conducted on a larger scale over a longer period of time and with groups of faculty from across
different colleges across campus to investigate whether peer observations can in aggregate
influence teachers’ collective efficacy beliefs, and thereby lead to improved student outcomes.
Conclusion
The COVID-19 pandemic forced colleges and universities across the globe to close their
doors, forcing students and faculty to pivot to ERT. This transition reinforced what numerous
studies have discovered prior to the pandemic, which is that a disproportionate amount of faculty
in post-secondary education lack the desire and confidence to effectively teach in the online
environment (Ma et al., 2021). This is problematic to the field of higher education because the
demand for online programs continues to increase as student demographics continue to shift,
80
surfacing a need to identify developmental programs that will prepare faculty to be more
efficacious online instructors. This research found that Gosling’s (2005) collaborative reflection
model of peer observation can impact online faculty perceptions of self-efficacy beliefs. This
discovery is significant as it can inform professional development opportunities offered at post-
secondary institutions, which in turn can increase the desire and confidence faculty have when
teaching in the online space. As colleges and universities return to campus, administrators can
leverage the findings and recommendations within this study to design, develop, and deploy
professional development programs that prepare their faculty to meet the increasing demand for
online program offerings that are shared amongst post-secondary institutions across this nation.
81
References
Allen, I. E., & Seaman, J. (2007). Making the grade: Online education in the United States,
2006. Sloan Consortium.
Ambrose, S. A., Bridges, M. W., DiPietro, M., Lovett, M. C., & Norman, M. K. (2010). How
learning works: Seven research-based principles for smart teaching. John Wiley & Sons.
Ashcroft, K., & Foreman-Peck, L. (2013). Managing teaching and learning in further and higher
education. Routledge. https://doi.org/10.4324/9781315043098
Austin, A. E., & Sorcinelli, M. D. (2013). The future of faculty development: Where are we
going?. New directions for teaching and learning, 2013(133), 85-97.
Bandura, A. (1977). Self-efficacy: Toward a unifying theory of behavioral change.
Psychological Review, 84(2), 191–215. https://doi.org/10.1037/0033-295X.84.2.191
Bandura, A. (1997). Self-efficacy: The exercise of control. Freeman.
Barger, R. P. (2020). Democratization of education through massive open online courses in Asia.
IAFOR Journal of Education, 8(2), 29–46.
Barrow, M. (1999). Quality‐management systems and dramaturgical compliance. Quality in
Higher Education, 5(1), 27–36. https://doi.org/10.1080/1353832990050103
Bell, M. (2001). Supported reflective practice: A programme of peer observation and feedback
for academic teaching development. The International Journal for Academic
Development, 6(1), 29–39. https://doi.org/10.1080/13601440110033643
Bell, N. D. (2007). Microteaching: What is it that is going on here? Linguistics and Education,
18(1), 24–40. https://doi.org/10.1016/j.linged.2007.04.002
Berge, Z. L. (1998). Barriers to online teaching in post-secondary institutions: Can policy
changes fix it. Online Journal of Distance Learning Administration, 1(2), 2.
82
Blackburn, R. T., & Lawrence, J. H. (1995). Faculty at work: Motivation, expectation,
satisfaction. Johns Hopkins University Press.
Blanton, L., Sindelar, P. T., Correa, V., Hardman, M., McDonnell, J., & Kuhel, K. (2003).
Conceptions of beginning teacher quality: Models for conducting research (COPSSE
Document Number RS-6). University of Florida, Center on Personnel Studies in Special
Education.
Bleakley, A. (1999). From reflective practice to holistic reflexivity. Studies in higher education,
24(3), 315-330.
Brown, M., McCormack, M., Reeves, J., Brooks, D. C., & Grajek, S. (2020). 2020 EDUCAUSE
horizon report: Teaching and learning edition. EDUCAUSE.
https://library.educause.edu/resources/2020/3/2020-educause-horizon-report-teaching-
and-learning-edition
Camblin, L. D., Jr., & Steger, J. A. (2000). Rethinking faculty development. Higher Education,
39(1), 1–18. https://doi.org/10.1023/A:1003827925543
Campbell, T., & Wescott, J. (2019). Profile of undergraduate students: Attendance, distance and
remedial education, degree program and field of study, demographics, financial aid,
financial literacy, employment, and military status: 2015–16. National Center for
Education Statistics. https://nces.ed.gov/pubsearch/pubsinfo. asp
Chan, C. K. Y. (2012). Exploring an experiential learning project through Kolb’s Learning
Theory using a qualitative research method. European Journal of Engineering Education,
37(4), 405–415. https://doi.org/10.1080/03043797.2012.706596
83
Chan, D. W. (2008). General, collective, and domain-specific teacher self-efficacy among
Chinese prospective and in-service teachers in Hong Kong. Teaching and Teacher
Education, 24(4), 1057–1069. https://doi.org/10.1016/j.tate.2007.11.010
Cochran-Smith, M., & Lytle, S. L. (1990). Research on teaching and teacher research: The issues
that divide. Educational Researcher, 19(2), 2–11.
https://doi.org/10.3102/0013189X019002002
Corry, M., & Stella, J. (2018). Teacher self-efficacy in online education: A review of the
literature. Research in Learning Technology, 26. Advance online publication.
https://doi.org/10.25304/rlt.v26.2047
Creswell, J. W., & Creswell, J. D. (2017). Research design: Qualitative, quantitative, and mixed
methods approaches. Sage publications.
Dewey, J. (1938). Experience and education. Colliers Books.
Dhawan, S. (2020). Online learning: A panacea in the time of COVID-19 crisis. Journal of
Educational Technology Systems, 49(1), 5–22.
https://doi.org/10.1177/0047239520934018
Donnelly, R. (2007). Perceived impact of peer observation of teaching in higher education.
International Journal on Teaching and Learning in Higher Education, 19(2), 117–129.
Espinet, T., Vuong, P. M., & Filback, R. A. (2020). Beyond onboarding: Building a culture of
continuous professional development for effective online instruction. In Y. Inoue-Smith
& T. McVey (Eds.), Optimizing higher education learning through activities and
assessments (pp. 97–114). IGI Global.
Ferrer, D. (2013). The One World Schoolhouse by Salman Khan—A review. Twelve/Hachette
Book Group.
84
Friedman, J. (2017, April 4). U.S. News data: The average online bachelor’s student. U.S. News
& World Report. https://www.usnews.com/higher-education/online-
education/articles/2017-04-04/us-news-data-theaverage-online-bachelors-student.
Gaff, J. G. (1975). Toward faculty renewal. Jossey-Bass.
Gaff, J. G., & Simpson, R. D. (1994). Faculty development in the United States. Innovative
Higher Education, 18(3), 167–176. https://doi.org/10.1007/BF01191111
Gallagher, S. (2019). Online education in 2019: A synthesis of the data. Center for the Future of
Higher Education and Talent Strategy, Northeastern University.
Ginder, S. A., Kelly-Reid, J. E., & Mann, F. B. (2017). Enrollment and employees in
postsecondary institutions, Fall 2016; and financial statistics and academic libraries,
fiscal year 2016. First look (Provisional data; NCES 2018-002). National Center for
Education Statistics.
Gosling, D. (2005). Peer observation of teaching (SEDA Paper 118). Staff and Educational
Development Association.
Gosling, D., & D’Andrea, V. M. (2001). Quality development: A new concept for higher
education. Quality in Higher Education, 7(1), 7–17.
https://doi.org/10.1080/13538320120045049
Gunawardena, C. N., & McIsaac, M. S. (2013). Distance education. In Handbook of research on
educational communications and technology (pp. 361-401). Routledge.
Hatzipanagos, S., & Lygo‐Baker, S. (2006). Teaching observations: promoting development
through critical reflection. Journal of Further and Higher Education, 30(4), 421-431.
Hodges, C., Moore, S., Lockee, B., Trust, T., & Bond, A. (2020). The difference between
emergency remote teaching and online learning. EDUCAUSE Review, 27, 1–12.
85
Horvitz, B. S., Beach, A. L., Anderson, M. L., & Xia, J. (2015). Examination of faculty self-
efficacy related to online teaching. Innovative Higher Education, 40(4), 305–316.
https://doi.org/10.1007/s10755-014-9316-1
Kim, J., & Maloney, E. (2020). Learning innovation and the future of higher education. JHU
Press.
Kinsella, E. A. (2007). Technical rationality in Schön’s reflective practice: Dichotomous or non‐
dualistic epistemological position. Nursing Philosophy, 8(2), 102–113.
https://doi.org/10.1111/j.1466-769X.2007.00304.x
Klassen, R. M., Tze, V., Betts, S. M., & Gordon, K. A. (2011). Teacher efficacy research 1998–
2009: Signs of progress or unfulfilled promise? Educational Psychology Review, 23(1),
21–43. https://doi.org/10.1007/s10648-010-9141-8
Knowles, M. (1990). The adult learner: A neglected species (4th ed.). Gulf Publishing.
Koedinger, K. R., & Anderson, J. R. (1990). Abstract planning and perceptual chunks: Elements
of expertise in geometry. Cognitive Science, 14(4), 511–550.
https://doi.org/10.1207/s15516709cog1404_2
Kolb, D. A. (1984). Experiential learning: Experience as the source of learning and
development. Prentice-Hall.
Kolb, D. A., & Fry, R. E. (1975). Toward an applied theory of experiential learning. MIT Alfred
P. Sloan School of Management.
Kurz, T. B., & Knight, S. L. (2004). An exploration of the relationship among teacher efficacy,
collective teacher efficacy, and goal consensus. Learning Environments Research, 7,
111–128. https://doi.org/10.1023/B:LERI.0000037198.37750.0e
86
Lederman, D. (2019, January 23). Provosts count more on online programs. Inside Higher Ed.
https://www.insidehighered.com/digital-learning/article/2019/01/23/provosts-aim-lean-
more-heavily-online-programs
Levine, A. (2010). Higher education at a crossroads: Earl Pullias lecture in higher education.
Center for Higher Education Policy Analysis.
Lincoln, Y. S., & Guba, E. G. (1985). Naturalistic inquiry. sage.
Ma, K., Chutiyami, M., Zhang, Y., & Nicoll, S. (2021). Online teaching self-efficacy during
COVID-19: Changes, its associated factors and moderators. Education and Information
Technologies, 26, 6675–6697. https://doi.org/10.1007/s10639-021-10486-3
Magda, A. J., Capranos, D., & Aslanian, C. B. (2020). Online college students 2020:
Comprehensive data on demands and preferences. Wiley Education Services.
Martin, G. A., & Double, J. M. (1998). Developing higher education teaching skills through peer
observation and collaborative reflection. Innovations in Education & Training
International, 35(2), 161–170. https://doi.org/10.1080/1355800980350210
Mayer, R. E. (2011). Applying the science of learning. Pearson/Allyn & Bacon.
McCarthy, M. (2010). Experiential learning theory: From theory to practice. Journal of Business
& Economics Research, 8(5). https://doi.org/10.19030/jber.v8i5.725
McGill, I. (1994). Developing reflective practice: Observing teaching as a component of
professional development. University of Brighton. Media Services.
McLean, J. (2005). Addressing faculty concerns about distance learning. Online Journal of
Distance Learning Administration, 8(4), 1–13.
Merriam, S. B. (2009). Qualitative research: A guide to design and implementation. Jossey-Bass.
87
Merriam, S. B., & Caffarella, R. S. (1999). Learning in adulthood: A comprehensive guide.
Jossey-Bass.
Merriam, S. B., & Tisdell, E. J. (2016). Qualitative research: A guide to design and
implementation (4th ed.). Jossey-Bass.
Moors, A., & De Houwer, J. (2006). Automaticity: A theoretical and conceptual analysis.
Psychological Bulletin, 132(2), 297–326. https://doi.org/10.1037/0033-2909.132.2.297
Morris, T. H. (2020). Experiential learning–a systematic review and revision of Kolb’s model.
Interactive Learning Environments, 28(8), 1064–1077.
https://doi.org/10.1080/10494820.2019.1570279
Mukhtar, K., Javed, K., Arooj, M., & Sethi, A. (2020). Advantages, limitations and
recommendations for online learning during COVID-19 pandemic era. Pakistan Journal
of Medical Sciences, 36(COVID19-S4), S27.
Nduagbo, K. C. (2020). Online education past, current, and future. In Handbook of research on
creating meaningful experiences in online courses (pp. 85-100). IGI Global.
Persellin, D. C., & Goodrick, T. (2010). Faculty development in higher education: Long-term
impact of a summer teaching and learning workshop. The Journal of Scholarship of
Teaching and Learning, 10(1), 1–13.
Piaget, J. (1999). The psychology of intelligence. Routledge.
Pitsoe, V., & Maila, M. (2013). Re-thinking teacher professional development through Schön’s
reflective practice and situated learning lenses. Mediterranean Journal of Social
Sciences, 4(3), 211–218. https://doi.org/10.5901/mjss.2013.v4n3p211
Ramsden, P. (2003). Learning to teach in higher education (2nd ed.). Routledge.
https://doi.org/10.4324/9780203507711
88
Redmond, B. F. (2010). Self-efficacy theory: Do I think that I can succeed in my work? Work
attitudes and motivation. The Pennsylvania State University, World Campus.
Robinia, K. A., & Anderson, M. L. (2010). Online teaching efficacy of nurse faculty. Journal of
Professional Nursing, 26(3), 168–175. https://doi.org/10.1016/j.profnurs.2010.02.006
Robinson, R. D. (2015). The collegial effect: An exploratory study of how faculty members
perceive collegiality and its effects on individuals and departments. Michigan State
University.
Schön, D. A. (1987). Educating the reflective practitioner: Toward a new design for teaching
and learning in the professions. Jossey-Bass.
Schuster, J. H. (1990). The need for fresh approaches to faculty renewal. In J. H. Schuster & D.
W. Wheeler Enhancing faculty careers: Strategies for development and renewal (pp. 3–
19). Jossey-Bass
Seaman, J. E., Allen, I. E., & Seaman, J. (2018). Grade increase: Tracking distance education in
the United States. Babson Survey Research Group.
Skaalvik, E. M., & Skaalvik, S. (2007). Dimensions of teacher self-efficacy and relations with
strain factors, perceived collective teacher efficacy, and teacher burnout. Journal of
Educational Psychology, 99(3), 611–625. https://doi.org/10.1037/0022-0663.99.3.611
Song, L., Singleton, E. S., Hill, J. R., & Koh, M. H. (2004). Improving online learning: Student
perceptions of useful and challenging characteristics. The Internet and Higher Education,
7(1), 59–70. https://doi.org/10.1016/j.iheduc.2003.11.003
Sullivan, L. T. (1983). Faculty development: A movement on the brink. College Board Review.
20–21, 29–30.
89
U. S. Department of Education. (2017). Enrollment and employees in postsecondary institutions,
Fall 2016; and financial statistics and academic libraries, fiscal year 2016.
https://nces.ed.gov/pubs2018/2018002.pdf
Usher, E. L., & Pajares, F. (2008). Sources of self-efficacy in school: Critical review of the
literature and future directions. Review of Educational Research, 78(4), 751–796.
https://doi.org/10.3102/0034654308321456
Wankat, P. C., & Oreovicz, F. S. (Eds.). (2015). Teaching engineering. Purdue University Press.
Weller, S. (2009). What does “peer” mean in teaching observation for the professional
development of higher education lecturers? International Journal on Teaching and
Learning in Higher Education, 21(1), 25.
Whitlock, W., & Rumpus, A. (2004). Peer observation: Collaborative teaching quality
enhancement. Educational Initiative Centre, University of Westminster.
Woolley, D. R. (1994). PLATO: The emergence of online community. Social Media Archeology
and Poetics. MIT Press.
Yiend, J., Weller, S., & Kinchin, I. (2014). Peer observation of teaching: The interaction between
peer review and developmental models of practice. Journal of Further and Higher
Education, 38(4), 465–484. https://doi.org/10.1080/0309877X.2012.726967
Zimmerman, B. J. (2002). Becoming a self-regulated learner: An overview. Theory into Practice,
41(2), 64–70. https://doi.org/10.1207/s15430421tip4102_2
90
Appendix A: Interview Protocol
Hi, and thanks for offering your time to help with this study. I will be asking you a series
of questions about your experiences with the collaborative reflection model of peer observation
that you recently completed with a USC colleague. As a reminder, the purpose of this study is to
examine how this particular observation model might impact online teacher self-efficacy beliefs.
Additionally, we are interested in the perceived challenges and benefits associated with this
model’s implementation. The questions that are asked during this interview will help shed light
on these topics and pseudonyms will be used, so please be as open and honest with your
responses as possible. The goal is for us to use the information from this interview to design
relevant and effective faculty development opportunities for faculty that will make them more
confident and effective online instructors.
Do you mind if I record this interview?
Table A1
Interview Questions With Transitions
Question Applicable RQ
question type
The first few questions I am going to ask you pertain to
the observer role you assumed in this study. Let’s start
by having you tell me a little bit about your experience
being an observer. What were some key takeaways
that resonate with you?
Q1 and Q2
experience
Can you describe how observing another faculty
member teach in their online course impacted your
own level of comfort with teaching online?
Q1
experience
Were there any perceived power dynamics that might
have influenced your role as being the observer? If
not, what would you attribute that to? If so, what did
you do to foster a collegial, collaborative, and
equitable environment?
Q2
opinion
91
Some participants might say that too much feedback
creates anxiety and cognitive overload. What steps, if
any, did you take to make your feedback accessible
and actionable for the faculty that you observed?
Q1 and Q2
devil’s advocate
In your opinion, to what degree do you think providing
peer feedback played in helping you become a more
efficacious online instructor?
Q1
opinion
Now I am going to ask you a few questions that focus
specifically on your role as the person being observed.
Let’s start by having you tell me a little bit about this
experience. What were some key takeaways that
resonate with you?
Q1 & Q2
experience
Can you describe the role the pre-observation meeting
had in the preparation and delivery of your
synchronous lesson?
Q1
opinion
Let’s pretend that you had to reteach the lesson that was
observed with the option of incorporating the
feedback provided in the post-observation meeting.
What post-observation feedback do you think was
most valuable and why?
Q1
hypothetical
Were there any perceived power dynamics that might
have influenced your receptiveness of the feedback? If
not, what would you attribute that to? If so, what did
you do to foster a collegial, collaborative, and
equitable environment?
Q2
hypothetical
In your opinion, to what degree do you think reflecting
on your lesson during the post-observation meeting
played in helping you become a more efficacious
online instructor?
Q1
opinion
The last two questions relate to your overall experience
of the intervention. In your opinion, what role had a
great impact in building your confidence in online
teaching? Observer, observed, or both? Why?
Q1
opinion
How do you feel about teaching online after having
completed this program?
Q1
opinion
If you were asked to participate in a peer observation
again in the future, would you accept? Why or why
not?
Q2
hypothetical
92
Closing
Those are all the questions for the study. I want to extend my sincerest gratitude for your
participation. Our hope is the information that you have provided will help faculty develop the
confidence necessary to be effective online instructors, which will benefit the overall student
experience. Would it be ok with you if I contact you once data analysis for the interviews is
complete so you can verify its accuracy? If so, can you please confirm the best contact
information we can reach you at? Thanks again for your participation.
93
Appendix B: MNESEOT Survey
These questions are concerned with understanding how study participants (select USC
faculty) judge their current capabilities for teaching online courses. Even if you have little to no
experience with online teaching, please try to answer each question. This questionnaire is
designed to help you gain a better understanding of the current self-perceptions you have
regarding your abilities to successfully teach in an online environment. Please indicate your
opinion about each of the statements below. Your answers are confidential.
A helpful prefix to each question is, “I can do …”
Adopted from the Michigan Nurse Educators Sense of Efficacy for Online Teaching Scale
(MNESEOT)
1. How much can you do to help your students think critically in an online class?
Nothing Very little Some Quite a bit A great deal
1 2 3 4 5
2. How much can you do to get through to disengaged students in an online class? (e.g.,
passive learners who might lurk online, but fail to actively contribute to their own
learning.)
Nothing Very little Some Quite a bit A great deal
1 2 3 4 5
3. How much can you do to control disruptive behavior (e.g., disrespectful posting or
failure to adhere to outline policies for posting) in an online environment?
Nothing Very little Some Quite a bit A great deal
1 2 3 4 5
94
4. How much can you do to motivate students who show little interest in online work?
Nothing Very little Some Quite a bit A great deal
1 2 3 4 5
5. To what extent can you make your expectations clear about student behavior in an
online class?
Nothing Very little Some Quite a bit A great deal
1 2 3 4 5
6. How much can you do to get students to believe that they can do well in an online
class?
Nothing Very little Some Quite a bit A great deal
1 2 3 4 5
7. How well can you respond to difficult questions from online students?
Nothing Very little Some Quite a bit A great deal
1 2 3 4 5
8. How well can you establish routines (e.g., facilitate or moderate student participation)
in coursework to keep online activities running smoothly?
Nothing Very little Some Quite a bit A great deal
1 2 3 4 5
9. How much can you do to help online students' value learning?
Nothing Very little Some Quite a bit A great deal
1 2 3 4 5
10. How much can you gauge student comprehension of what you have taught in an
online course?
Nothing Very little Some Quite a bit A great deal
1 2 3 4 5
95
11. How well can you craft questions or assignments that require students to think by
relating ideas to previous knowledge and experience?
Nothing Very little Some Quite a bit A great deal
1 2 3 4 5
12. How much can you do to foster individual students’ creativity in an online course?
13. How much can you do to get students to follow the established rules for assignments
and deadlines during an online class?
Nothing Very little Some Quite a bit A great deal
1 2 3 4 5
14. How much can you do to improve the understanding of a student who is failing in an
online class?
Nothing Very little Some Quite a bit A great deal
1 2 3 4 5
15. How much can you do to control students dominating online discussions?
Nothing Very little Some Quite a bit A great deal
1 2 3 4 5
16. How well can you establish an online course (e.g., convey expectations, standards,
course rules) with each group of students?
Nothing Very little Some Quite a bit A great deal
1 2 3 4 5
17. How much can you do to adjust your online lessons for different learning styles?
Nothing Very little Some Quite a bit A great deal
1 2 3 4 5
18. How much can you do to use a variety of assessment strategies for an online course?
Nothing Very little Some Quite a bit A great deal
1 2 3 4 5
96
19. How well can you develop an online course that facilitates student responsibility for
online learning?
Nothing Very little Some Quite a bit A great deal
1 2 3 4 5
20. To what extent can you provide an alternative explanation or example when students
in an online class seem to be confused?
Nothing Very little Some Quite a bit A great deal
1 2 3 4 5
21. How well can you respond to defiant students in an online setting?
Nothing Very little Some Quite a bit A great deal
1 2 3 4 5
22. How well can you structure an online course that facilitates collaborative learning?
Nothing Very little Some Quite a bit A great deal
1 2 3 4 5
23. How well can you structure an online course that provides good learning experiences
for students?
Nothing Very little Some Quite a bit A great deal
1 2 3 4 5
24. How well can you provide appropriate challenges for very capable students in an
online environment?
Nothing Very little Some Quite a bit A great deal
1 2 3 4 5
25. To what extent can you use knowledge of copyright law to provide resources for
online students?
Nothing Very little Some Quite a bit A great deal
1 2 3 4 5
97
26. How well can you navigate the technical infrastructure at your institution to
successfully create an online course?
Nothing Very little Some Quite a bit A great deal
1 2 3 4 5
27. How well can you navigate the technical infrastructure at your institution to
successfully teach an online course?
Nothing Very little Some Quite a bit A great deal
1 2 3 4 5
28. To what extent can you use asynchronous discussions to maximize interactions
between students in an online course? (Asynchronous means not online at the same
time)
Nothing Very little Some Quite a bit A great deal
1 2 3 4 5
29. To what extent can you use synchronous discussions (e.g., same time chat rooms) to
maximize interactions between students in an online course?
Nothing Very little Some Quite a bit A great deal
1 2 3 4 5
98
Appendix C: Email to Department Chairs and Center for Teaching Excellence
Dear (Name),
I hope this email finds you doing well. I was referred to you by (name, title) from
(campus). (name) is a former colleague of mine. I used to work at USC’s Marshall School of
Business for 4 years in their online learning department. The reason why I am emailing you is
because I am a 4th-year doctoral candidate at USC’s Rossier School of Education, and I am
currently working on my dissertation. My research focuses on the role peer observations play in
positively impacting online teacher self-efficacy. I am looking to recruit six to eight full-time or
part-time faculty to participate in this study. Having worked in higher education for over 10
years, I understand how valuable faculty time is therefore, each will receive a $200 e-gift card
for their time. Would you be willing to help me recruit participants by including the following
message in your department newsletter? Thanks so much for the consideration and I look
forward to your reply.
Fight On!
Joshua E. Rivera
(INSERT RECRUITMENT FLYER HERE)
99
Appendix D: Recruitment Flyer
Hello (Name),
Your experience teaching online during the COVID-19 pandemic matters. A doctoral
student from Rossier’s School of Education is currently seeking six to eight full-time or part-time
faculty to participate in a study to understand the role peer observations play in positively
impacting online teacher self-efficacy. This is a mixed-methods study and will require
approximately 5 to 6 hours over the course of 3 months to complete. Interested faculty must be
new to online teaching with limited familiarity in this space. Participants will receive a $200 e-
gift card for their time. Those interested in participating should email Joshua Rivera at
jerivera@usc.edu no later than (DATE).
Abstract (if available)
Abstract
The purpose of this mixed-methods study was to investigate the perceived role that peer observations have on online teacher self-efficacy beliefs. The theoretical framework for this study includes Kolb’s experiential learning theory, Schön’s theory of reflective practice, and Bandura’s self-efficacy model. The research questions investigate the role that Gosling’s collaborative reflection model of peer observation has on higher ed online teachers’ self-efficacy beliefs as well as the perceived benefits and challenges associated with this observation model’s implementation. A total of six higher education faculty, all of whom had varying degrees of online teaching experience, participated in this study. The survey used for this study was the Michigan Nurse Educators Sense of Efficacy for Online Teaching, which uses factor analysis to confirm four factors for self-efficacy. The results of the pre- and post-survey responses show no significant difference in self-efficacy factors. However, data from the interviews show that the attitudes and perceptions of both novice and expert online faculty confirm that participation in Gosling’s peer observation model had an impact on their self-efficacy beliefs. Additional findings from the interviews suggest that peer observations present many logistical challenges; however, the benefits have the potential to foster an environment where teacher collective efficacy can take root and flourish.
Linked assets
University of Southern California Dissertations and Theses
Conceptually similar
PDF
The relationship of students' self-regulation and self-efficacy in an online learning environment
PDF
Better together: teacher attrition, burnout, and efficacy
PDF
Exploring primary teachers' self-efficacy and technology integration in early reading instruction
PDF
What is the relationship between early childhood teachers' training on the development of their teaching self-efficacy?
PDF
The relationships between teacher beliefs about diversity and opportunities for culturally and linguistically diverse students, reflectiveness, and teacher self-efficacy
PDF
What is the relationship between self-efficacy of community college mathematics faculty and effective instructional practice?
PDF
Self-efficacy beliefs and intentions to persist of Native Hawaiian and non-Hawaiian science, technology, engineering, and mathematics majors
PDF
Cultural intelligence and self-efficacy of trip leaders on short-term international educational programs
PDF
Teacher efficacy and classroom management in the primary setting
PDF
An examination of factors that affect online higher education faculty preparedness
PDF
Technology integration and self-efficacy of in-service secondary teachers in an international school
PDF
Media literacy education: a qualitative inquiry into the perspectives teachers hold about teaching media literacy
PDF
Teacher well-being matters: an explorative study of early childhood teacher well-being, their experiences, and perspectives
PDF
Urban teacher persistence: self-efficacy, affect, and values
PDF
Teacher self-efficacy and instructional coaching in California public K-12 schools: effective instructional coaching programs across elementary, middle, and high schools and the impact on teacher...
PDF
The effect on teacher career choices: exploring teacher perceptions on the impact of non‐instructional workload on self‐efficacy and self‐determination
PDF
What are the relationships among program delivery, classroom experience, content knowledge, and demographics on pre-service teachers' self-efficacy?
PDF
Support for English learners: an examination of the impact of teacher education and professional development on teacher efficacy and English language instruction
PDF
A comparison of student motivation by program delivery method: self-efficacy, goal orientation, and belongingness in a synchronous online and traditional face-to-face environment
PDF
Leadership and implementation of 1:1 technology: considering teacher self-efficacy in the implementation process
Asset Metadata
Creator
Rivera, Joshua E.
(author)
Core Title
Confidence is key: peer observations and online teacher self-efficacy in higher education
School
Rossier School of Education
Degree
Doctor of Education
Degree Program
Educational Leadership
Degree Conferral Date
2022-08
Publication Date
07/19/2022
Defense Date
06/02/2022
Publisher
University of Southern California
(original),
University of Southern California. Libraries
(digital)
Tag
OAI-PMH Harvest,online learning,self-efficacy,teacher observations
Format
application/pdf
(imt)
Language
English
Contributor
Electronically uploaded by the author
(provenance)
Advisor
Filback, Robert (
committee chair
), Cummings, Thomas (
committee member
), Patall, Erika (
committee member
)
Creator Email
jerivera@usc.edu,jerivera2002@gmail.com
Permanent Link (DOI)
https://doi.org/10.25549/usctheses-oUC111373227
Unique identifier
UC111373227
Legacy Identifier
etd-RiveraJosh-10867
Document Type
Dissertation
Format
application/pdf (imt)
Rights
Rivera, Joshua E.
Type
texts
Source
20220719-usctheses-batch-956
(batch),
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 author, as the original true and official version of the work, but does not grant the reader permission to use the work if the desired use is covered by copyright. It is the author, as rights holder, who must provide use permission if such use is covered by copyright. The original signature page accompanying the original submission of the work to the USC Libraries is retained by the USC Libraries and a copy of it may be obtained by authorized requesters contacting the repository e-mail address given.
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
cisadmin@lib.usc.edu
Tags
online learning
self-efficacy
teacher observations