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Examining student beliefs and behaviors in online and on-campus courses: measuring openness to diversity, voluntary peer collaboration, and help seeking
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Examining student beliefs and behaviors in online and on-campus courses: measuring openness to diversity, voluntary peer collaboration, and help seeking
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Content
EXAMINING STUDENT BELIEFS AND BEHAVIORS IN ONLINE AND ON-
CAMPUS COURSES: MEASURING OPENNESS TO DIVERSITY, VOLUNTARY
PEER COLLABORATION, AND HELP SEEKING
by
Nina Kang
A Dissertation Presented to the
FACULTY OF THE ROSSIER SCHOOL OF EDUCATION & THE AMERICAN
LANGUAGE INSTITUTE
UNIVERSITY OF SOUTHERN CALIFORNIA
In Partial Fulfillment of the
Requirements for the Degree
DOCTORATE OF EDUCATION
May 2015
Copyright 2015 Nina Kang
ii
Copyright page
iii
Acknowledgements
My sincerest thanks to my advisors, Drs. Helena Seli and Kimberly Hirabayashi
for their guidance through this process. I am especially obliged to Dr. Seli for her support
and prompt responses (giving me no time to slack off!).
Thank you to my esteemed committee members Dr. Emmy Min and Dr. Jim
Valentine for their advice and direction throughout my dissertation process. I would also
like to acknowledge the M.A. TESOL program for their willingness to participate in my
study. Thank you! In particular, I am ever grateful to my director and committee member
Jim and the rest of the faculty at the American Language Institute for their continued
support and encouragement through the process.
I would also like to thank my friends and colleagues I have had the pleasure of
meeting during the past three past years. You have not only made the process easier but
also enjoyable & memorable. Lastly, I would like to thank my husband and my mother
for their continuous love and support. And a shout-out to my three wonderful kids who
have no idea what I went through to get here.
iv
Table of Contents
Acknowledgements ............................................................................................................ iii
List of Tables ..................................................................................................................... vi
List of Figures ................................................................................................................... vii
Abstract ............................................................................................................................ viii
Chapter One ........................................................................................................................ 1
Introduction ..................................................................................................................... 1
Background of the Problem ............................................................................................ 2
Statement of the Problem ................................................................................................ 7
Purpose ............................................................................................................................ 7
Research Questions ......................................................................................................... 7
Significance of the Study ................................................................................................ 8
Methodology ................................................................................................................... 9
Definition of Terms ....................................................................................................... 10
Organization of Study ................................................................................................... 10
Chapter Two ...................................................................................................................... 12
Review of Literature ..................................................................................................... 12
Current Research in Online Education ......................................................................... 14
An overview ............................................................................................................. 14
Inconsistencies in findings ....................................................................................... 15
Benefits of Online Education. ....................................................................................... 17
Benefits to students .................................................................................................. 17
Benefits to institutions ............................................................................................. 18
Educational outcomes .............................................................................................. 18
Challenges of Online Education ................................................................................... 19
Conclusion .................................................................................................................... 20
Openness to Diversity in Learning Contexts ................................................................ 20
An Overview ................................................................................................................. 21
Diversity in Instituitons of Higher Education ............................................................... 22
Campus climate ........................................................................................................ 23
Diversity in the classroom ....................................................................................... 23
Diversity in Learning Environments ............................................................................. 24
Voluntary Peer Collaboration in Learning Contexts .................................................... 25
Voluntary Peer Collaboration in Higher Education ...................................................... 26
The voluntary nature of peer collaboration ............................................................. 26
Learning outcomes related to voluntary peer collaboration .................................... 27
Voluntary peer collaboration in online contexts ..................................................... 27
Help Seeking Behaviors in Learning Contexts ............................................................. 29
Help Seeking Behaviors in Context of Higher Education ........................................... 30
Types of Help Seeking .................................................................................................. 31
Help Seeking among International Students ................................................................. 33
v
Help Seeking Behaviors in Online Learning Context ................................................... 34
Conclusion .................................................................................................................... 35
Chapter Three .................................................................................................................... 37
Methodology ................................................................................................................. 37
Research Questions ....................................................................................................... 37
Research Design ............................................................................................................ 38
Population and Sample ................................................................................................. 38
Descriptive characteristics of respondents.................................................................39
Instrumentation ............................................................................................................. 42
Demographic questions ............................................................................................. 42
Openness to diversity ................................................................................................ 42
Voluntary peer collaboration .................................................................................... 43
Help seeking .............................................................................................................. 44
Procedure and Data Collection ..................................................................................... 45
Data Analysis ................................................................................................................ 46
Chapter Four ..................................................................................................................... 49
Results .......................................................................................................................... 49
Intercorrelations ............................................................................................................ 49
Analysis of Results ....................................................................................................... 50
Research question 1 ................................................................................................. 50
Research question 2 ................................................................................................. 51
Research question 3 ................................................................................................. 56
Sumary .......................................................................................................................... 58
Chapter Five ...................................................................................................................... 61
Discussion ..................................................................................................................... 61
Discussion of demographic composition ................................................................. 62
Discussion of degree of openness to diversity ......................................................... 64
Discussion of voluntary peer collaboration ............................................................. 66
Discussion of help seeking. ...................................................................................... 68
Implications ................................................................................................................... 70
Recommendation for Future Research ......................................................................... 72
Limitations .................................................................................................................... 74
Conclusion .................................................................................................................... 76
References ......................................................................................................................... 78
Appendices
Appendix A: Demographic questions ......................................................................... 91!
Appendix B: Openness to diversity measure .............................................................. 93
Appendix C: Voluntary peer collaboration measure .................................................. 94
Appendix D: Help seeking measure ........................................................................... 95
vi
List of Tables
Table 1: Participant demographics: Age……….…….…….…….…….…….……...………....
Table 2: Participant demographics: Countries of origin…….…….…….……..….…………...
Table 3: Research questions: Independent and dependent variables, levels of measurement,
and statistical test…………………………………………...…….…….…….……..….…………...
Table 4: Means, Standard Deviations, and Pearson Product Correlations of Measured
Variables……………………………………………………………………………………….
Table 5: Results of t-tests and descriptive statistics: Openness to diversity..………………….
Table 6: Results of t-tests and descriptive statistics: Voluntary peer collaboration
Belief……………………………………………………………………………………………
Table 7: Results of t-tests and descriptive statistics: Voluntary peer collaboration
behavior…………………………………………………………………………………………
Table 8: Chi-square test: Voluntary collaboration in-person…….……..……….…….………..
Table 9: Chi-square test: Voluntary collaboration via phone or text…………………………….
Table 10: Chi-square test: Voluntary collaboration via email or discussion board……...……
Table 11: Chi-square test: Voluntary collaboration via social media…………...……....……..
Table 12: Chi-square test: Voluntary collaboration via videoconferencing….…………...……
Table 13: Results of t-tests and descriptive statistics: Help seeking behaviors.…………..……
Table 14: Chi-square test: Seeking help from instructor or teaching assistant.…………..….…
Table 15: Chi-square test: Seeking help from peers ………………...…………………………
Table 16: Chi-square test: Seeking help from others………………...…………………………
40
41
48
50
51
52
53
54
54
55
55
56
56
57
58
58
vii
List of Figures
Figure 1: Projection of Students Taking Online Courses: 2013…….…….……....……….......
Figure 2: Online Enrollment as a Percent of Total Enrollment: 2002-2012…….………….....
13
14
viii
Abstract
The overall growth in the demand for online education has greatly impacted
institutions of higher education. The number of students taking at least one online course
exceeds the growth of overall higher education enrollment, and online students now make
up nearly 32% of the enrollment. Large institutions of higher education are particularly
invested in online education as they educate 64% of all online students. This study
examines the literature surrounding the growth of online education highlighting key
findings on student learning and benefits and challenges of online education. In particular,
the concepts of openness to diversity, voluntary peer collaboration, and help seeking are
three measures studied in the current research. Comparing these three measures in online
and face-to-face learning settings provides a valuable knowledge pertaining to online
education contexts.
The study results indicate that there is no statistically significant difference in the
levels of student engagement between online and on-campus students. Where the study
did yield statistically significant differences of voluntary peer collaboration and help
seeking behaviors, the differences can be explained by the course delivery method. For
example, on-campus students were more likely to collaborate in-person whereas online
students were more likely to collaborate via videoconferencing. The implications of this
study can be valuable in the field of education specifically focusing on teacher training
for graduate program.
1
CHAPTER ONE
Introduction
The overall growth in the demand for online education has greatly impacted
institutions of higher education (Allen & Seaman, 2014; Bernard, et al., 2009; Brown,
2012; Campbell, Gibson, Hall, Richards, & Callery, 2008; Conchar, Meric, & Wright,
2015; McGuire & Castle, 2010). In fact, the number of students taking at least one online
course exceeds the growth of overall higher education enrollment, and online students
now make up nearly 32% of the enrollment (Allen & Seaman, 2010, 2013, 2014). Large
institutions of higher education are particularly invested in online education as they
educate 64% of all online students (Allen & Seaman, 2013). Data indicate an increased
demand for the use of technology especially emerging e-learning technologies in higher
education (Anderson, 2008; Campbell et al., 2008). By extension, there has been an
increased demand for online education, leading institutions to aggressively make online
education as part of their long-term strategic planning (Allen & Seaman, 2010; Campbell
et al., 2009).
With the growth of online education, there is increased interest in understanding
how student learning takes places in online environment (Anderson, 2008; Cho & Cho,
2014; Kim & Bonk, 2006; Robinson & Hullinger, 2008). This requires going beyond
evaluation of online programs to considering the quality of student learning experience.
From the perspective of student learning, certain behaviors or the degree of students’
engagement in academic context can largely influence the level of learning that takes
place (Astin, 1984; Hu & Kuh, 2003; Kuh 2001; Robinson & Hullinger, 2008). While the
range and types of behaviors greatly vary, three of the critical variables include openness
2
to diversity, voluntary peer collaboration, and help seeking. These variables can be
broadly categorized as social behaviors in academic context which impact learning in
online and on-campus environment.
Background of the Problem
As online education grows at an unprecedented rate (Allen & Seaman, 2010, 2013,
2014; Bernard, et al., 2009; Brown, 2012; Campbell et al., 2008; Conchar, Meric, &
Wright, 2015; McGuire & Castle, 2010), discussions about the quality and effectiveness
of online education are critical to developing a high quality curriculum that reflects the
desired learning outcomes. However, there seem to be inconsistencies in findings about
whether online education is as effective in producing desired outcomes as traditional, on-
campus education (Chen, Lambert, & Guidry, 2010). While some research findings
(McGuire & Castle, 2010; Robinson & Hullinger, 2008) indicate that on-campus students
are more engaged and experience more face-to-face contact, there is also research (Lei &
Gupta, 2010; Robinson & Hullinger, 2008) indicating that online students’ overall
academic engagement is as good as or even better than on-campus students (Lei & Gupta,
2010; McGuire & Castle, 2010; Robinson & Hullinger, 2008). Recent findings (Allen &
Seaman, 2014) indicate a growing consensus among academic leaders that learning
outcomes in online education is the same or superior to face-to-face instruction, and they
remain generally positive about the learning outcomes for online courses. Uncontestable
is the fact that online learning can be a viable means to achieve learning outcomes and
ensure student satisfaction.
Some of the key benefits of online education include increased access to higher
education for non-traditional student population (Capra, 2014; Chen et al., 2010; Hachey,
3
Wladis, & Conway, 2014) and the flexibility and convenience of the online delivery
method (Brown, 2012; Picciano, Seaman, & Allen, 2010). Institutions benefit from online
education because it increases student enrollment, which in turn provides additional
institutional revenue (El Mansour & Mupinga, 2007; Lanier, 2006). Moreover, the online
delivery method allows for campuses to deal with overcrowded classrooms and schedule
issues while meeting the student needs for flexible access (Allen & Seaman, 2010; Brown,
2012; Picciano et al., 2010).
The context of the growth in online education is the demographic reality of an
increasingly more diverse population. The United States is projected to become a
majority-minority nation by 2043 (U.S. Census Bureau, 2013). The Census Bureau
reports: “the next half century marks key points in continuing trends – the U.S. will
become a plurality nation, where the non-Hispanic white population remains the largest
single group, but no group is in the majority” (U.S. Census Bureau, 2013, para. 2). This
trend is also reflected on college and university campuses where the students are diverse
in terms of race, culture, and values and must also engage with others of diverse race,
culture, and values. By 2015, students of color are projected to comprise nearly two-fifths
of student population at a growth rate of 81% (Carnevale & Fry, 2000). Faced with such
dramatic demographic shift, colleges and universities are called to prepare students to
effectively function in a diverse society (Pike & Kuh, 2006). It is then vitally important to
examine postsecondary students’ degree of openness to diversity which is foundational to
identity development and cognitive growth, and the means to foster students’ academic
and social growth (Gurin, Dey, Hurtado, & Gurin, 2002; Hurtado, 2007).
4
While research findings have shown that students generally become more open
and tolerant of diverse race, culture, and values during their college years (Pascarella,
Edison, Nora, Hagedorn, & Terenzini, 1996), there is little research examining how the
online learning environment impacts students’ openness to diversity. Studies (Hurtado,
Milen, Clayton-Pedersen, & Allen, 1999) have found that college experience is
significant in developing students’ openness to diversity via the inherent structural
representation of diverse groups and the opportunities to meaningfully engage with a
diverse group of people. Hence, the degree to which students display openness to
diversity can correspondingly have a positive impact on learning outcomes (Astin, 1993a,
1993b; Pascarella et al., 1996).
Compounding the issue of openness to diversity in relation to learning outcomes
is how it is impacted in online learning environment. The question here is whether and
how the online learning context influences students’ openness to diversity. Online
learning, which employs a diversified form of instruction through technology, can give
students opportunities to engage with diverse, worldwide peer groups as much as, if not
more, than the on-campus experience. Yet, very little research exists about the degree to
which openness to diversity is influenced by online settings.
Along with openness to diversity, there are other academic beliefs and behaviors
that are critical to success, such as a willingness to engage in help seeking and
collaborative learning activities. They represent forms of social behaviors students
engage in during their educational experience and are shown to have positive
consequences in learning outcomes (Hurtado et al., 1999; Hurtado, Dey, Gurin, & Gurin,
2003; Pike & Kuh, 2006). As such, it is important to examine how different learning
5
environments, namely online and on-campus programs, can foster meaningful
opportunities for students to engage in social behaviors such as displaying openness to
diversity, peer collaboration, and help-seeking. In particular, graduate programs that train
future educators must recognize the need for teachers to acquire the knowledge, skills,
and attitudes leading to culturally responsive teaching (McAllister & Irvine 2000; Nelson
& Guerra, 2013; Pohan & Aguilar, 2001) as well as proactively engage in collaborative
and help seeking behaviors as critical components of their professional training.
Voluntary peer collaboration refers to students learning from each other and in the
process moving away from independent learning to interdependent learning (Boud 2001;
Boud, Cohen, & Sampson, 1999). The key to voluntary peer collaboration is that students
initiate collaboration with peers outside of instructor’s initiation or facilitation. This can
take place as students explain their ideas, participate in activities, receive and give
feedback, and seek help. Peer collaboration is an important pedagogy which has been
shown to improve performance and contribute to student achievement (Astin, 1993a;
Cabrera et al., 2002; Tinto, 1997). As such, it has largely become a core of academic and
social experiences, contributing to meaningful learning and outcomes (Astin, 1993a,
1993b; Tinto, 1997). In the online learning context, the need and expectation of
collaboration is heightened as students feel a greater need for social connection and sense
of presence to make up for physical distance from peers (Palloff & Pratt, 1999; Walker &
Fraser, 2005). The availability of innovative learning technologies (e.g., Skype, email,
text messaging, discussion boards) promotes interaction with peers and can lead to more
effective learning outcomes in the online context. However, the degree to which students
6
engage in voluntary collaboration in online versus on-campus settings remains to be
studied.
Another academic behavior, considered a critical developmental skill for students
is help seeking behavior (Karabenick & Dembo, 2011; Karabenick & Newman, 2006;
Nelson-Le Gall, 1981). It is an essential strategy for students engaging in online
programs because they must display willingness and ability to seek help where there is an
information gap as well as a physical distance. The widespread use of communication
technologies has contributed to an increase in help seeking behaviors among college
students (Karabenick, 2011; Kitsantas & Chow, 2007). This can be exemplified in
students using technology-mediated forms of communications such as discussion boards
and emails to contact instructors and peers about questions they may have on particular
assignments. However, relatively little is known about how the online learning context
influences help seeking behaviors and what types of instrumental approaches to learning
are utilized in the students’ help seeking behaviors. Provided that help seeking is
inherently a social practice (Butler, 1998; Karabenick & Knapp, 1991; Karabenick &
Newman, 2006), it can also exemplify the degree to which students engage in informal
interactional diversity as they seek assistance from their peers in and outside of the class.
Openness to diversity and the social academic behaviors of voluntary
collaboration and help seeking are important topics to be examined in the context of
emerging online education. This is especially important in the context of graduate
programs that train future educators because they must be able to understand and apply
the personal and professional behaviors in their own learning to be able to teach future
students to do the same.
7
Statement of the Problem
Several studies (Allen & Seaman, 2010, 2013, 2014; Bernard, et al., 2009; Brown,
2012; Campbell et al., 2008; Conchar, Meric, & Wright, 2015; McGuire & Castle, 2010)
have examined the exponential growth of online education in higher education and
addressed the potential differences in learning outcomes between the online and on-
campus ways of delivery. However, there is a lack of research about academic beliefs and
behaviors such as openness to diversity, voluntary peer collaboration, and help seeking
by mode of delivery among students in higher education. The study was partly in
response to the paucity of research examining the current state of online education and its
impact on student learning from the perspective of openness to diversity, voluntary peer
collaboration, and help seeking behaviors.
Purpose
The purpose of this study was to assess openness to diversity, voluntary peer
collaboration, and help seeking beliefs and behaviors in online versus on-campus learning
settings among students in higher education. Specifically, the study examined a Masters
in Teaching English to Speakers of Other Languages (TESOL) program at a large private
university (LPU) in a major urban city in Southern California. The study investigated
whether openness to diversity, voluntary peer collaboration, and help seeking behaviors
differed by program delivery methods.
Research Questions
The study aimed to answer the following three questions:
1. Is there a difference in student openness to diversity by program delivery method?
2. Is there a difference in student help seeking beliefs and behaviors by program
8
delivery method?
3. Is there a difference in the student voluntary peer collaboration beliefs and
behaviors by program delivery method?
Significance of Study
The research questions posed above are critically relevant to understanding the
nature and practice of social behaviors in online learning contexts. By gaining a deeper
understanding of the relationship between students’ openness to diversity and course
delivery methods, institutions of higher education through their faculty and curriculum
can ensure that the core values of diversity are incorporated and communicated in the
delivery of the course or program. Moreover, understanding the role of voluntary peer
collaboration and help seeking in student learning can help online educators to design
courses and programs that provide opportunities for discussions and engagement and
encourage students to use appropriate learning strategies.
The answers to the research questions are also relevant to the field of teacher
education as they examine beliefs and behaviors related to teacher preparation. In
particular, graduate students in the English language teaching programs are expected to
teach English to students of different racial and ethnic backgrounds composing of various
cultural values; hence, learning to engage with diverse ideas and peoples is a critical part
of the profession. The expectation is that the degree to which the students display
openness to diversity in their courses is a direct reflection of how they will conduct their
own classrooms in the future. The results of the current study can greatly benefit faculty
and course designers to inform decision-making as they strive to prepare effective
teachers of diverse student population. Finally, as online learning grows in the field of
9
teacher education, it is important to investigate whether the method of delivery impacts
desired outcomes.
Methodology
Since the research questions seek to compare student beliefs and behaviors in two
different settings, online and on-campus, the researcher adopted a quantitative approach
to determine whether statistical differences existed. Data was gathered via surveys that
included valid and reliable instruments as well as demographic questions. All the surveys
were administered online. All data was analyzed in SPSS using statistical tests including
t-test, chi-square, and regression.
Definition of Terms
Asynchronous
Learning environment in which students do not participate at the same time due to
constraints of time and place. It is a learning approach which combines self-study with
peer interaction via use of tools such as emails and discussion boards.
Help Seeking
An achievement behavior involving the search for and employment of a strategy to obtain
success (Ames & Lau, 1982).
Online Learning
A course or a program delivered to students who are not physically present in traditional
classroom settings. It generally incorporates use of various forms of electronic media and
information and communication technology.
Openness to Diversity
Greater openness to racial, cultural, and value diversity (Pascarella et al., 1996).
10
Synchronous
Learning environment in which students participate at the same time (e.g., lectures or
group discussions in traditional face-to-face learning environment; web conferencing
tools such as Adobe Connect and Skype in online learning environment).
Voluntary Peer Collaboration
Peer-to-peer collaborative activities that are not initiated or facilitated by the
instructor or required for the course or course assignments, such as creating study
groups and peer reviews of assignments.
Organization of Study
Chapter one in this study provides an introduction to the topic of growth in online
education, in addition to an overview of the proposed study. In particular, beliefs and
behaviors surrounding openness to diversity voluntary peer collaboration, and help
seeking are discussed in context of online learning. This section also discusses the
significance of the study, limitations, and provides definitions of relevant terms.
Chapter two provides an in-depth discussion of online education in higher
education. This chapter also examines factors that may contribute to student learning in
online contexts; in particular, openness to diversity, voluntary peer collaboration and help
seeking are examined with regard to their impact by instructional delivery methods.
Chapter three describes the methodology used in this study. This chapter
discusses the sample used, instrumentation, research design, and data collection process.
Plans for data analysis and as well as the strengths and weaknesses of this study are also
described.
11
Chapter four provides a description of the results from the data analysis. Chapter
five is a discussion of these results, in addition to recommendations for further research
and limitations of the study.
12
CHAPTER TWO
Review of Literature
There is a growing demand for online education to provide increased access
nationwide (Allen & Seaman, 2010, 2013, 2014; Bernard, et al., 2009; Brown, 2012;
Campbell, et al., 2008; McGuire & Castle, 2010). In response, colleges and universities
have moved into the online arena through expansion of programs and existing course
offerings (Allen & Seaman, 2010). According to Carnegie classification (Allen &
Seaman, 2014), there are 458 Baccalaureate programs with online offerings compared to
160 with no online offerings, 607 Masters programs with online offerings compared to 21
with no online offerings, and 270 Doctoral programs with online offerings compared to 5
with no online offerings. The economy also plays an important role in not only increasing
the overall demand for college education but also highlighting the greater demand and
need for online courses and programs (Allen & Seaman, 2010, 2013).
Online education in higher education shows continued growth as the enrollment
rates of students in online education courses have exceeded those of students in on
campus programs. Findings indicate that the number of students taking at least one online
course continues to grow, exceeding the growth of overall higher education enrollments
(Allen & Seaman, 2010, 2013, 2014). With approximately 6.7 million students (or 32%
of students) taking at least one online course, the growth of online education is
uncontestable (Allen & Seaman, 2013; Bernard, et al., 2009; Brown, 2012; Campbell et
al., 2008; Hachey et al., 2014; McGuire & Castle, 2010). The projection is that the
number of students taking online courses will grow to a majority in the next five years
(Allen & Seaman, 2014).
13
Figure 1. Projection of Students Taking Online Courses: 2013
In particular, there has been a growing demand for online education in large
institutions of higher education. The pattern of growth indicates that the largest
institutions (i.e., with greater than 15,000 total enrollments) educate proportionately more
online students at 64% of the total online students (Allen & Seaman, 2013). Seeing the
effectiveness and growth potential of online learning, these large institutions have made
online education as part of their long-term strategic planning as they continue to have a
more positive outlook on online learning (Allen & Seaman, 2010, 2014; Campbell et al.,
2008). As academic leaders become increasingly favorable towards online education and
support decisions to implement and support online programs, enrollment in online
courses and programs will likely grow (Allen & Seaman, 2014). While small private
colleges have not placed high priority in the development of online education, this can
change as online education is increasingly viewed to be profitable (Allen & Seaman,
2010; Picciano et al., 2010).
Very%likely%
Likely%
Somewhat%likely%%
Not%at%all%likely%
A"Majority"of"All"Higher"Educa5on"Students"Will"
Be"Taking"at"least"One"Online"Courses:"2013"
14
Figure 2. Online Enrollment as a Percent of Total Enrollment: 2002-2012
The surge of interest in online education has led to significant changes in
institutional strategy and long term planning. Given the current economic downturn
where there is increased demand for more people to seek education under strict budgetary
constraints, online education has filled the need for opportunities to learn and advance in
their education (Allen & Seaman, 2010, 2013). Moreover, with research showing
increased demand for the use of technology in higher education (Campbell et al. 2008;
Chen et al., 2010), continual growth is expected in online education as a means to widen
access and increase opportunities for non-traditional students (Capra, 2014; Chen et al.,
2010; Hachey et al., 2014).
Current Research on Online Education
An overview. Higher education in the United States was initially and solely a
face-to-face proposition (Bernard et al., 2009). At the core was the importance placed on
instruction and learning to constitute an educational experience. Before online education,
distance education was the non-traditional form of education that received its fair share of
0.00%%
10.00%%
20.00%%
30.00%%
40.00%%
2002% 2003% 2004% 2005% 2006% 2007% 2008% 2009% 2010% 2011% 2012%
Online"Enrollment"in"Degree"Gran5ng""
Postsecondary"Ins5tu5ons""
Fall"2002"through"Fall"2012"
15
discussion in regards to its quality, value, and effectiveness (Bernard, et al., 2009; Lou,
Bernard, & Abrami, 2006).
Online education has emerged as a natural evolution of older methods of distance
education, such as mailed correspondence and broadcasted radio or television programs
(Bernard et al. 2009; Lou et al., 2006). Beginning in the 1990s with the widespread use of
high-speed Internet, web-based applications for classroom instructions and online courses
have significantly increased (Lou et al., 2006; Tamim, Bernard, Borokhovski, Abrami, &
Schmid, 2011).
In the current digital age, new technologies have changed the instructional design
and delivery methods of online education (Bernard et al., 2009; Lou et al., 2006). The
widespread use of content management system/learning management system
(CMS/LMS) such as Moodle or Blackboard is an example of technology becoming part
of classroom instruction (Graham & Dziuban, 2007). In terms of delivery methods which
include synchronous, asynchronous, hybrid and blended, the question of how the
different types of learning environments impact learning is yet to be fully explored.
Notwithstanding, new technologies have certainly had an impact on the quality of online
education.
Inconsistencies in findings. A number of studies (Astin, 1984; Hu & Kuh, 2003)
has confirmed the importance of student engagement in the construction and
development of learning regardless of whether the learning is on-campus or online.
However, there are contradictory findings about whether online education is as effective
in producing desired outcomes as traditional on-campus education (Chen et al., 2010).
Some of the research seems to indicate on-campus students are more engaged and
16
experience more student-to-student contact than their online peers. This may largely be
due to the lack of social cues and face-to-face communication with heavy reliance on
written communication in online learning (Brown, 2012; Lei & Gupta, 2010). The
common assumption is that online students often lack support from instructors and peers
(Cho & Cho, 2014) and feel emotionally isolated (Artino & Jones, 2012, Dabbagh &
Kitsantas, 2012) compared to traditional face-to-face classroom settings.
However, other research findings (Lei & Gupta, 2010; McGuire & Castle, 2010;
Robinson & Hullinger, 2008) indicate that on-line students’ level of student-to-faculty
contact and overall academic engagement is as good or even better than on-campus
students. In fact, the commonly held view of online quality as “inferior” has considerably
improved with many academic leaders reporting their perceptions about the relative
quality of online education (Allen & Seaman, 2014). The findings suggest that online
learning can be a viable means to achieve learning outcomes and ensure student
satisfaction.
In regards to the inherent role of multimedia and technology in online education,
research shows that the use of media alone does not improve learning (Bernard et al,
2009; Clark & Feldon, 2005; Clark, Yates, Early, & Moulton, 2010). Despite its
popularity and attractiveness among online programs, multimedia instruction cannot be
assumed to produce more learning simply for its unique and innovative methods (Clark et
al., 2010). For example, it is unclear as to whether students’ information literacy and
computer skills are necessarily improved as a result of taking online courses (Chen et al.,
2010). Hence, caution must be taken in considering the positive effects associated with
17
online education and consider instructional methods and design in multimedia instruction
to meaningfully aid student learning.
Benefits of Online Education
Benefits to students. One of the key benefits of online education has been the
increased access to higher education for non-traditional student population (Capra, 2014;
Chen et al., 2010; Hachey et al., 2014). This includes those who may be older, returning-
adult students with part-time status (Chen et al., 2010; Hachey et al., 2014). Online
education may be optimal for non-traditional students (Picciano et al., 2010) as they are
generally more attracted to online courses because this delivery method may help them to
balance their personal lives (families and jobs) with their desire to advance their
education. The assumption is that the structure of online courses will allow them greater
flexibility to pursue their educational goals (Brown, 2012; Picciano et al., 2010).
Moreover, perceiving online courses as easier and more convenient than on-campus
courses (Brown, 2013), non-traditional students are more likely to enroll in online
courses (Chen, et al., 2010; Hachey et al., 2014).
Another key benefit of online education is that research on academic success in an
on-line learning environment found a positive relationship between student-faculty
interaction and the student’s engagement in the course (McGuire & Castle, 2010). Studies
(Lei & Gupta, 2010; Robinson & Hullinger, 2008) have found that faculty feedback in
online settings was frequent and prompt, strongly predicting student satisfaction with the
level of faculty interaction.
18
Benefits to institutions. Online education offers many benefits not only to
students but also to institutions such as providing revenue (El Mansour & Mupinga,
2007; Lanier, 2006) and increasing student enrollment. Given the hard economic times,
institutions across the board reported increased demand for courses and programs with
higher demand for online courses (Allen & Seaman, 2010, 2013, 2014). As online
education reaches a larger student population living far away from campus and helps deal
with overcrowded classrooms and scheduling issues, it also allows institutions of higher
education to meet student needs for flexible access (Allen & Seaman, 2010; Brown,
2012; Picciano et al., 2010). Colleges and universities view online education as an
inexpensive way to increase enrollment which has steadily been on the rise for online
courses (Allen & Seaman, 2010, 203; Picciano et al., 2010). As a result, many colleges
and universities are increasingly incorporating online education programming as part of
their long-term strategic planning (Allen & Seaman, 2010, 2014; Campbell et al., 2008;
Picciano et al., 2010).
Educational outcomes. Online learning has been shown to support deeper
learning by creating environment that is much more student-centered than a typical
lecture class with the flexibility of allowing students to go at their own pace (Kirtman,
2009). Other research (McGuire & Castle, 2010) has indicated that online learning is
more conducive to self-reflection than on-campus learning, leading to deeper learning.
Students often find that they are able to increase their reflective thinking and engage
more meaningfully in the online classroom. Findings (Kirtman, 2009; McGuire & Castle,
2010; Rabe-Hemp, Woollen, & Humiston, 2009; Robinson & Hullinger, 2008) seem to
indicate that online courses can provide increased opportunities for higher-level thinking
19
and positively reinforce student engagement with content, faculty, and each other when
properly encouraged and supported.
Challenges of Online Education
Despite the advantages discussed in the previous section, there are several
drawbacks to online education as well. One of the most significant drawbacks is the
demographic differences between online and face-to-face student populations (Chen et al.,
2010; Hachey et al., 2014). As discussed above, online education tends to be more
appealing to non-traditional students who are more likely to have jobs and families that
interfere with full-time studies. Consequently, the attrition rates of online courses are
higher than on campus programs (Bowden, 2008; Lei & Gupta, 2010). Studies (Angelino,
Williams, & Natvig, 2007; Carr, 2000) examining student persistence in online learning
program find that attrition rates for distance education courses are 10-20% higher than
courses taught on-campus.
Related to the demographic issue is another challenge which has to do with
students’ varying degree of technological skills ranging from technologically challenged
to highly proficient. As previously discussed, the use of technology, in and of itself, does
not improve learning (Clark & Feldon, 2005; Clark et al., 2010), despite its popularity
and attractiveness among online programs. In fact, gaps in technological knowledge and
skills can largely undermine the educational experience of online learners. Moreover,
faculty encounter great challenges in navigating the technological skills needed to fully
participate in online learning (McGuire & Castle, 2010).
Finally, there are many concerns regarding the quality of online courses which are
often perceived as inferior to on-campus courses (Kirtman, 2009; Picciano et al., 2010).
20
This is especially true among senior education leaders including faculty who view online
education as lower in quality compared to face-to-face courses. The perception may
largely be related to the individual faculty’s experience designing and teaching an online
course which takes more time and effort as well as the evolving nature of online
education (Allen & Seaman, 2013). However, there has been slow but steady
improvement in viewing learning outcomes for online learning as comparable and “at
least as good” (Allen & Seaman, 2010, p. 10).
Conclusion
Online education has evolved and grown with technology to improve and meet
the demands of a diverse, growing population of college students. This is especially true
in higher education context where students have come to expect flexibility and
convenience in pursuing their educational goals. There are, however, challenges ranging
from demographic differences to technological issues. The concern over the quality of
education in online context is another major challenge that studies need to address.
Openness to Diversity in Learning Contexts
A critical value of American higher educational system is openness to diversity
which is foundational to identity development and cognitive growth, and the means to
foster students’ academic and social growth (Gurin et al., 2002, Hurtado, 2007). Studies
(Hurtado et al., 1999) have found that college experience is significant in developing
students’ openness to diversity via the inherent structural representation of diverse groups
and the opportunities to meaningfully engage with a diverse group of people. This
section provides a concise overview of the role of openness to diversity, its relation to
21
campus climate and classroom environment. It also discusses sources that impact students’
openness to diversity, including online learning context and method of delivery.
An Overview
Colleges and universities are becoming increasingly diverse with dramatic
demographic shift signaling the United States to become a majority-minority nation by
2043 (U.S. Census Bureau, 2013). Diversity, in terms of student population as well as the
various cultures, values, and beliefs, is one of the hallmarks of the American higher
educational system (Gollnick, Chinn, Kroeger, & Bauer, 1998; Gurin et al., 2002;
Hurtado, 2007; Pascarella et al., 1996). Given the multifaceted ways to examine
diversity issues, there has been a trend of moving towards viewing diversity through the
lens of equity by examining issues of social class, gender, religion, languages, and sexual
orientation (Jones & McEwen, 2000; Reynolds & Pope, 1991). This view of diversity
serves as a framework in which to understand students’ identity development and
cognitive growth and considers the critical importance of educational experience as a
means to foster students’ academic and social growth (Gurin et al., 2002, Hurtado, 2007).
Provided the common assumption that a student’s interpersonal environment has a
great impact on developing a sense of openness to diversity defined as displaying a
greater openness to racial, cultural, and value diversity (Pascarella et al., 1996), the role
of higher education is critical to understanding the process of identity development.
Studies (Chickering, 1969, 1971; Hurtado, 2007; Pascarella et al., 1996) have found that
college experience is significant to developing students’ openness to diversity as they
become less authoritarian, dogmatic, and ethnocentric and more tolerant and supportive
of individual rights. The inherent structural representation of diverse groups provides a
22
context for students to be exposed to and interact with those of diverse backgrounds,
notwithstanding the quality and meaningfulness of the interaction (Hurtado et al., 1999).
Correspondingly, development of students’ openness to racial, cultural, and value
diversity can positively impact college outcomes (Astin, 1993a, 1993b; Pascarella et al.,
1996). The one caveat to generalizing diversity research is that most of the research to
date has focused on undergraduate student experiences. Given the different life stages
and places on the student development continuum for graduate students, there is a need to
explore and further understand how graduate students relate to openness to diversity.
Diversity in Institutions of Higher Education
Given the primacy of diversity as a core value in education, institutions of higher
education pursue diversity to provide an effective environment for learning (Hurtado,
2001; Hurtado, Griffin, Arellano, & Cuellar, 2008) by employing multicultural
curriculum and learning opportunities with diverse peers. To this end, institutions engage
in assessment practices to measure campus climate in attempt to create a positive learning
environment and to further foster openness to diversity (Hurtado et al., 2008; Hurtado,
Alvarez, Guillermo-Wann, Cuellar, & Arellano, 2012). Seeking measurable outcomes,
institutions often pursue structural diversity (referring to the numeric representation of
minority students) as the focal point in determining diversity in higher education (Gurin
et al., 2002; Hurtado et al., 2008). Notwithstanding the importance of structural diversity,
there is a great need to examine diversity beyond the structural level of the number of
underrepresented minorities present on campus to examine the values and practices that
impact campus climate (Denson & Chang, 2009; Hurtado et al., 2008).
23
Campus climate. Conceptualization of campus climate can be used to explain the
degree of openness to diversity on college campuses. Understanding and improving
campus climate is key to developing diverse learning environments for students expected
to engage in an increasingly complex and diverse society (Hurtado, 2001; Hurtado et al.,
1999). The concept can be approached from different perspectives. For example, campus
climate can determine between welcoming and alienating learning environments (Cress,
2008); it can refer to the diversity and richness of academic and social interactions within
given graduate programs (Solem, Lee, & Schlemper, 2009); and it can also entail students’
general perceptions of safety, both physical and psychological (Veilleux, January,
VanderVeen, Reddy, & Klonoff, 2012). But ultimately, campus climate is critical to
promoting openness to diversity insofar as it refers to the presence or absence of
conditions amenable to academic, cognitive, and affective growth of students.
Diversity in the classroom. Campus climate and diversity also affect students
within the classroom, namely the effects of classroom diversity and interaction among
different races/ethnicities (Gurin et al., 2002). Interaction among diverse groups of
students during the college years is important as it fosters students’ academic and social
growth (Gurin et al., 2002; Hu & Kuh, 2003). Furthermore, interactional diversity has
positive effects on all students, regardless of race or ethnicity (Hu & Kuh, 2003; Pike &
Kuh, 2006). In fact, studies (e.g., Denson & Chang, 2002) have found positive
educational benefits to be associated with interactions with others from different racial or
ethnic backgrounds. From this perspective, it is important to understand the unique
classroom dynamics taking into account classroom activities and peer groups to promote
interaction (Hurtado, 2001).
24
Diversity in Learning Environments
Studies point to a variety of sources which impact students’ openness to diversity,
ranging from the types of courses they take and where they live to the quality of their
interactions with peers (Pascarella et al, 1996; Pascarella & Terenzini, 1991). The online
learning context is yet another influence which impacts students’ development of
openness to diversity. Online learning can be seen as a diversified form of instruction
using diverse methods and curriculum to give students opportunities to engage with
diverse peer groups. Given the perception that online courses are less traditional and
more collaborative in nature (Palloff & Pratt, 1999; Walker & Fraser, 2005), students
may expect more involvement and interactions with peers which is also a key
determinant of openness diversity (Astin 1984, 1993b).
Collaborative learning can also be incorporated to promoted diversity. The
structure of small group work is particularly significant in creating a learning
environment that maximizes peer interaction and involvement. The effort to promote
openness towards diversity (Pascarella et al., 1996; Whitt, Edison, Pascarella, Terenzini,
& Nora, 2001) has been linked to collaborative learning. It has been argued that
collaborative learning can positively improve tolerance and openness to diversity of
people, ideas, and values (Vogt, 1997). One of great values of collaborative learning is
the opportunity for students to collaborate as equal participants. Positive connection
between collaborative learning and openness to diversity can be exemplified in successful
collaborative learning environments which support voluntary peer collaboration.
As the research specifically undertakes M.A. in TESOL program, the assumption
is made that students are being trained to teach a potentially diverse group of students.
25
The nature of program implies that students enrolled have an overall sense of
appreciation and acceptance of racial, sociocultural, and value diversity. Another
assumption is that there are broadly-based policies of diversity and expectations at the
program level. There is also the expectation of students to engage in practices displaying
openness to diversity.
With the growth of online education and by extension online teacher education
programs, teacher preparedness in dealing with openness to diversity is of great
importance. As openness to diversity is a key belief and especially critical for students
who become teachers, it is important to examine whether openness to diversity can be
successfully developed in both online and face-to-face learning settings.
Voluntary Peer Collaboration in Learning Contexts
The literature review will now turn to voluntary peer collaboration which refers to
collaborative activities that are not initiated or facilitated by the instructor or required for
the course or course assignments. It works under the common consensus that working in
groups can be effective in academic and other organizational contexts (Cabrera et al.,
2002; Roger & Johnson, 1994; Shea & Guzzo 1987; Van den Bossche, Gijselaers, Segers,
& Kirshchner, 2006). Collaborative learning can be defined broadly as participants
working together on a task through which learning takes place (Van den Bossche et al.,
2006). It is the idea of learning from each other in everyday contexts through informal
communication and sharing of information. As a form of informal learning, peer
collaboration can occur inside and outside the classroom where students can develop
important skills to effectively learn from each other (Boud, 2001; Cabrera et al., 2002;
Roger & Johnson, 1994; Van den Bossche et al., 2006).
26
Voluntary Peer Collaboration in Higher Education
In educational context, peer collaboration may be synonymously used to refer to
different types of collaborative work that requires interaction with peer. Peer
collaboration can be referred to as a process of moving away from independent learning
to interdependent learning (or mutual learning where peers mutually benefit from each
other (Boud, 2001; Boud et al., 1999). In a typical peer collaboration model, students
learn from each other by explaining their ideas, participating in activities, receiving and
giving feedbacks, and seeking help from peers for their learning. Peer collaboration can
occur formally through systematic instruction or informally as students voluntarily seek
out opportunities to learn from each other (Boud, 2001; Cabrera et al., 2002).
Occurrences of peer collaboration exemplify students taking responsibility of their own
learning in understanding the importance of learning how to learn (Boud, 2001).
The voluntary nature of peer collaboration. Of greater interest is to understand
the voluntary nature of peer collaboration in which there is a paucity of literature. As a
form of learning strategy focusing on the experience of informal learning as students
voluntarily engage in conversations, group projects, study groups, and other course
related activities (Boud, 2001; Boud & Lee, 2005), voluntary peer collaboration can also
indicate informal interactional diversity (Pike & Kuh, 2006). For the purpose of this
paper, voluntary peer collaboration is defined as peer to peer activities that are not
initiated or facilitated by the instructor or required for the course or course assignments,
such as creating study groups and peer reviews of assignments. In approaching voluntary
peer collaboration as having “universal value” for students (Boud, 2001; Cabrera et al.,
2002; Johnson, Johnson, & Smith, 1991), it is important to consider the varying degrees
27
of effectiveness of voluntary peer collaboration in different learning environments,
including face-to-face and online.
Learning outcomes related to voluntary peer collaboration. Voluntary peer
collaboration as an extension of collaboration has become part of students’ educational
experience starting from elementary to college (Cabrera et al., 2002; Slavin, 1989, 1990).
It has become one of the most important pedagogies in higher education as learning has
been restructured away from traditional lecture style classes to small group work (Cohen,
1994; Johnson & Johnson, 1990; Webb, 1982). The assumption is that peer collaboration
improves performance and contributes to student achievement (Astin, 1993a; Cabrera et
al., 2002; Tinto, 1997). Boud (2001) highlights several learning outcomes that are
promoted through peer collaboration: 1) working with others; 2) critical inquiry and
reflection; 3) communication and articulation of knowledge, understanding, and skills; 4)
managing learning and how to learn; and 5) self and peer assessment. Another key
contribution of peer collaboration is that it encourages students to become life long
learners as they develop reflective practices and critical self-awareness (Candy, Crebert,
& O’Leary, 1994). Peer collaboration in the classroom has largely become a core of
academic and social experiences contributing to meaningful learning and outcomes
(Astin, 1993a; Tinto, 1997). In recognizing how environmental factors and social context
influence collaborative learning behaviors, it is then important to examine how the online
environment influences collaborative learning.
Voluntary peer collaboration in online context. Online programs have a
distinctive social structure, highlighting the need and expectations of collaboration as a
component of the learning experience (Walker & Fraser, 2005). This can be seen in the
28
dozens of e-learning technologies (e.g., interactive multimedia, text messaging, wikis,
blogs, discussion boards) being introduced to incorporate collaborative components in the
online learning context. They are in part a response to students who desire a more
engaging online learning experience with enhanced pedagogy and innovative
technologies (Kim & Bonk, 2006). In this regard, peer collaboration is especially helpful
in considering its relation to supporting and enhancing technology-mediated learning.
Stephenson (2001) finds new media cannot effectively deliver substantial amount of
content, and that technology is most effective when direct interaction with peers takes
place. Voluntary peer collaboration meets this need for interaction as groups of students
work together.
Another factor to consider is the psychosocial need of students to feel as though
they are in fact in a classroom where learning of knowledge and sharing of experience
takes place (Coates, 2007). In fact, students enrolled in online courses generally express a
need for social connection and sense of presence, especially given the technology
mediated learning environment (Palloff & Pratt, 1999; Walker & Fraser, 2005). This
suggests that voluntary peer collaboration can be especially useful in providing
opportunities for students to connect with each other. Given that cooperative learning
stems from developmental psychology, voluntary peer collaboration can be approached
from the perspective of skill development through group interaction and social learning.
Furthermore, voluntary peer collaboration can also be examined to determine the degree
to which students employ it as part of their repertoire of learning strategies (O’Donnell &
O’Kelly, 1994). This is especially important in understanding the degree to which
voluntary peer collaboration supports and enhances learning in online contexts.
29
Considering the emphasis placed on social interaction and peer collaboration in
the online M.A. in TESOL program, voluntary peer collaboration behaviors need to be
further examined. Stemming from a belief that collaborative learning is foundational to a
student’s learning and success (Boud, 2001; Cabrera et al., 2002; Johnson et al., 1991), it
encourages behaviors linked to interdependent learning (Bruffee, 1999) where students
learn from each other by constructing knowledge as they talk, discuss, and exchange
feedback. The frequency with which students choose to collaborate with their peers can
further explain whether or not their beliefs surrounding the importance of collaboration
influence their learning behaviors in the classroom context. To the varying degree in
which students participate in voluntary peer collaboration, it can ultimately promote and
cultivate learning in the online context.
Help Seeking Behaviors in Learning Contexts
The final measure considered in exploring the characteristics of online student
learning is help seeking behavior. The topic of academic help seeking has been
established as a critical developmental skill that students must acquire (Karabenick &
Dembo, 2011; Karabenick & Newman, 2006; Nelson-Le Gall, 1981) to become self-
regulating, engaged learners. It is a topic that is equally important, if not more important,
for students engaging in online programs because they must display willingness and
ability to seek help where there is an information gap. Since online students do not have
the benefit of relying on physical, face-to-face interaction where visual and auditory cues
may communicate the need for clarification, the willingness and frequency of help
seeking behavior is critical to student learning (Cheng, Liang, & Tsai, 2013; Karabenick,
2011).
30
Academic help seeking can be defined as a process of asking for help which can
operate on a continuum of less to more adaptive as students seek help for immediate
results which subsequently decreases need for help and increases the likelihood for long-
term success (Cheng et al., 2013; Karabenick, 2003; Kitsantas & Chow, 2007). It is a
critical learning strategy that can develop self-efficacy and help in coping with academic
difficulties (Skinner & Zimmer-Gembeck, 2007). In more simple terms, help seeking is
the process of asking for help in learning contexts. Like other learning strategies, the
process of help seeking is an inherently social practice that requires the use of cognitive
and interpersonal skills to communicate the need for assistance (Butler, 1998; Karabenick
& Knapp, 1991; Karabenick & Newman, 2006). As such, help seeking behaviors can
align with voluntary peer collaboration behaviors exemplifying openness to diversity
which ultimately promote and cultivate learning.
Help Seeking Behaviors in Context of Higher Education
Help seeking is a critical academic behavior which is positively correlated with
learning and academic performance (Cheng et al., 2013; Karabenick, 2003, 2011;
Kitsantas & Chow, 2007). In traditional face-to-face settings, physical proximity to the
instructor and the teaching assistant, as well as visual and auditory cues may create an
environment that is more conducive to help seeking behavior (Cheng et al., 2013;
Dabbagh & Kitsantas, 2013; Karabenick, 2011). However, a shift in delivery method to
online may result in changes in help seeking behaviors (Cheng et al., 2013; Dabbagh &
Kitsantas, 2013; Karabenick, 2011). For example, the online course delivery method may
create a feeling of distance (Artino & Jones, 2012), and consequently lessen students’
propensity to seek help from formal sources (Cheng et al., 2013; Karabenick, 2011).
31
Hence, examining the varying degrees to which online and face-to-face settings influence
help seeking behaviors can be helpful to understand how students seek help through
formal and informal interactions.
Provided that help seeking is an inherently social practice requiring cognitive and
interpersonal skills to communicate, the nature and quality of group interaction within
learning contexts (face-to-face or online classroom) is important. While the most direct
factor in help seeking behavior is the perceived receptivity of instructors (Karabenick,
2004; Karabenick & Sharma, 1994), such direct interactions with the instructors are not
as common in college classrooms; hence, help seeking behaviors are observed in a
variety of settings outside the classrooms (e.g., office hours, study groups, writing center)
with peers, tutors, and other student affairs service providers (Karabenick & Knapp,
1991). The classroom environment and the degree to which it facilitates a climate for
help seeking largely influences a student’s help seeking behavior and aligns class goals
with mastery oriented approach.
Types of Help Seeking
Help seeking behaviors are organized into several categories: formal, informal,
instrumental, and executive (Cheng et al., 2013; Karabenick, 2003; Kitsantas & Chow,
2007). Goal orientation theory (Pintrich, 2000) is helpful in explaining how students are
influenced by what they perceive as an emphasis on performance goals (concerned with
social comparisons and not appearing incompetent) or mastery goals (concerned with
learning and self-improvement with an emphasis on long-term gain). For example,
students perceiving emphasis on performance are likely to display avoidance of help
seeking as well as expedient help seeking (focused on avoiding poor performance); in
32
contrast, students perceiving emphasis on mastery are likely to seek help in autonomous
orientations (i.e., focused on understanding and increased competency) (Butler, 1998;
Karabenick, 2004).
Also related to goal orientation is an important distinction to be made between
executive and instrumental help seeking goals as proposed by Nelson Le-Gall (1981,
1985). Executive help seeking refers to asking for help to avoid work or embarrassment
from mistakes (e.g., asking for answers to a problem) while instrumental help seeking
refers to asking for help to decrease the subsequent need for help (e.g., asking for
clarification or explanation). This dual help seeking model operates on a continuum of a
less to more adaptive (also autonomous) help seeking behaviors that can impact the view
on the relationship between personal goal orientations and perceived classroom goal
structure. Moreover, contextual influences also play an important role in determining
instrumental help seeking behaviors favorable to all learning environments and
experiences (Karabenick, 2004; Karabenick & Knapp, 1991; Nelson Le-Gall, 1981,
1985) given that students are directly and indirectly influenced by their learning
environment which is inherently both social and cultural (Nelson Le-Gall, 1981, 1985).
Provided these factors that influence help seeking behaviors, the ideal adaptive
help seeker can be described as “one who begins by accurately assessing that help is
necessary, formulates an appropriate request for help, understandings the best resources
available, designs strategies for successful requests, and productively processes the help
received to mastery of the material or the ability to solve problems” (Karabenick &
Dembo, 2011, p. 35). Ideally, the help seeker utilizes learning strategies that support
instrumental approach to learning and is motivated by the desire to learn and grow. The
33
key question that remains is then how to provide a learning environment that supports
student questioning through increased self-esteem, effort, and persistence thereby raising
student achievement.
Help Seeking among International Students
Since the M.A. in TESOL program enrolls an overwhelming number of
international students (mostly from mainland China) in the traditional face-to-face
program, research examining the learning behaviors and strategies among international
students needs to be further explored. Literature (Andrade, 2006; Sherry, Thomas, &
Chui, 2010) about international students generally focuses on socio-cultural differences
that impact acculturation. International students are generally viewed as a “vulnerable”
population having to deal with a host of issues ranging from language barriers and
financial problems to lack of cultural adjustment These adjustment issues become an
overarching challenge for international students and specific learning strategies such as
help seeking that can positively contribute to academic achievement need to be addressed.
In fact, in regards to help seeking strategies among international students, the
discussion is grounded in research that views help seeking as a language learning issue
(i.e., does the student have the language proficiency to ask for help when needed?)
(Chamot & O’Malley, 1994; Skinner & Madden, 2010). Help seeking can be categorized
as a metacognitive strategy allowing students more opportunities to use the language as
well as helping to control their own learning by mediating their learning experience
(Flavell, 1979; Oxford, 1990). It is viewed as a helpful strategy for language learning and
a good predictor of learning. However, compounding the language issue are the social
factors which inhibit help seeking behaviors. For example, international students
34
generally lack confidence in their language abilities (Robertson, Line, Jones, & Thomas,
2000), experience cross-cultural anxiety (Lewthwaite, 1996; Robertson et al., 2000) and
have less social support (Hechanova-Alampay, Beehr, Christiansen, & Van Horn, 2002)
which largely affect help seeking behaviors.
Research (Karabenick & Knapp, 1988, 1991) also indicates that all college
students, including international students, want help and support to overcome their lack
of skills and knowledge. For example, in situations where the faculty are not available
due to the large class size, students may seek support outside of their immediate contacts
by going to support services, tutors, help centers, and even peers despite the seeming lack
of expertise. However, international students also highly value support they are able to
receive from their course instructors which can profoundly impact their learning and
participation in their academic experience (Kingston & Forland, 2008) indicating the
importance of understanding the international student-faculty interaction. An important
question that remains is what are the help seeking patterns that international students
employ to successfully complete their academic tasks and how help seeking behaviors
can be encouraged and promoted. For the purpose of this research, the focus is on how
help seeking behaviors of students compare in the online and on-campus programs
accounting for the differences between domestic and international students.
Help Seeking Behaviors in Online Learning Context
The widespread use of communication technologies has contributed to an increase
in help seeking behaviors among college students (Kitsantas & Chow, 2007; Karabenick,
2011). Research findings (Anderson & Lee, 1995; Dede, 1996; Karabenick & Knapp,
1988) have shown that students generally feel less threatened using technology mediated
35
forms of communication such as discussion boards and emails when compared to
interactions in person. The relative anonymity of electronic forms of communication
make it easier for students to take risks that may result in failure (Kitsantas & Chow,
2007) and also lift the burden of time and distance constraints, contributing to the
students’ preference for formal help seeking though these modes (Kitsantas & Chow,
2007).
Provided that students are directly and indirectly influenced by their learning
environment which is inherently both social and cultural (Nelson Le-Gall, 1981, 1985), it
is important to understand how online learning context influences help seeking behaviors.
It is also important to consider what types of learning strategies or instrumental
approaches to learning are utilized in the students’ help seeking behaviors. Finally, the
key question that needs to be answered is whether face-to-face or online learning context
provides a favorable learning environment that supports student questioning.
Conclusion
The significant growth of online education in institutions of higher education has
created a need for more research on the topic. In the context of increasingly diverse
college and university campuses, it is of great interest to understand how openness to
diversity is impacted in online and face-to-face learning environments. As indicative of
informal interactional diversity (Hu & Ku, 2003: Pike & Kuh, 2006), voluntary peer
collaboration and help seeking can also reveal a great deal about how learning
environments impact student beliefs and behaviors. This chapter has examined the
literature surrounding the growth of online education highlighting key findings on student
learning and benefits and challenges of online education. It has also explored the
36
concepts of openness to diversity, voluntary peer collaboration, and help seeking which
are the three measures to be studied in the current research. Comparing these three
measures in online and face-to-face learning settings may provide valuable knowledge
pertaining to online education contexts.
37
CHAPTER THREE
Methodology
The growth of online education in higher education has impacted student learning
in various disciplines and fields of studies, including the field of English Teaching to
non-native speakers. In particular, the global nature of English teaching in various parts
of the world to a culturally and racially diverse student population necessitates a deeper
understanding of how students’ beliefs and behaviors impact their learning. The study
was designed to examine whether differences exist in students’ beliefs and behaviors
related to their openness to diversity, voluntary peer collaboration, and help seeking in
the online or on-campus method of instruction delivery. This chapter includes the
research questions, the hypotheses, and a description of the research methodology. The
latter includes the sampling procedure and population, instrumentation, and procedures
for data collection and analysis.
Research Questions
While much discussion has been had in the area of online education, there is little
research examining student academic behaviors according to program delivery. In
particular, openness to diversity, voluntary peer collaboration, and help seeking are
considered to be key academic attributes contributing to learning. Using these constructs,
the study is designed to examine whether there is a difference in students’ beliefs and
behaviors according to program delivery methods. The following proposed research
questions guided the study:
1. Is there a difference in the degree of openness to diversity by type of program
delivery?
38
2. Is there a difference in voluntary peer collaboration beliefs and behaviors by type
of program delivery?
3. Is there a difference in help seeking beliefs and behaviors by type of program
delivery?
Research Design
In order to examine potential differences between course-related beliefs and
behaviors between online and on-campus settings, a quantitative, non-experimental
design was used, using correlational data garnered from self-report surveys. Data was
analyzed for statistical significance. The independent variables in this study were the
types of program delivery, specifically online or on-campus courses. The dependent
variables in this study were 1) beliefs about openness to diversity, 2) beliefs and
behaviors (expressed in frequency and modes) of voluntary peer collaboration, and 3)
beliefs and behaviors (expressed in frequency and modes) of help seeking.
Population and Sample
The population for this study was master’s level graduate students in both online
and on-campus programs in the School of Education at Large Private University (LPU).
LPU is a large, top-tier research institution located within an urban city in Southern
California. The specific sample for this study was drawn from students in the M.A. in
Teaching English to Speakers of Other Languages (TESOL) program enrolled in the
same course (Foundations of Learning for the TESOL Classrooms). The students were
enrolled in either the online or on-campus program during the summer or fall session of
2014. Both the online and on-campus sample populations were approached to participate
in the study via electronic mail sent by the principal investigator or from the course
39
instructor at the School of Education. The principal investigator also visited the on-
campus site to briefly introduce the survey and encourage participation. However, all
surveys were distributed via email and conducted online. The email provided a link to
the survey so as to be accessed anonymously. The surveys were distributed at
approximately the same time in their coursework (launched at week 8 and closed at the
end of the term in week 12).
Descriptive Characteristics of Respondents
The survey respondents (n = 44) were in their first semester of M.A. in TESOL
program. On-campus respondents (n = 20) were sampled from a satellite campus located
2.8 miles off the main campus. The online respondents (n = 24) were sampled from a
synchronous program with the same exact course of instruction as the on-campus course.
The synchronous component of the online program is unique to the TESOL program in
that the online program required the same number of contact hours (3 hours per week) of
student participation in virtual face-to-face learning via Adobe Connect. The response
rate for the study was 48% with 44 out of a total of 92 students completing the survey.
The response rate for the online program (52%) was higher than the response rate for the
on-campus program (43%).
Significant differences in the respondents’ age were reported between groups.
Whereas the on-campus cohort entirely consisted of students ranging from ages 22-28
with a mean of 24 years of age, the online cohort consisted of students ranging from ages
22-58 with a mean of 37 years of age. See Table 1 for information on participant
demographics by age.
40
Table 1
Participant demographics: Age
Instructional Delivery Method
Age Online % On-campus % Total %
18-24 1 4 14 70 15 34.1
25-29 7 29 6 30 13 29.5
30-34 4 17 0 0 4 9.1
35-39 4 17 0 0 4 9.1
40-44 2 8 0 0 2 4.5
45-49 2 8 0 0 2 4.5
50+ 4 17 0 0 4 9.1
Total 24 20 44
Other demographic differences were noted through the Pearson’s Chi-square
analysis with regard to relationship status, χ
2
= 6.833, df = 2, p<.033. Forty-two percent
(n = 10) of students enrolled in the online program were married or with a domestic
partner at the time they took this survey as compared to 10% (n = 2) enrolled in the on-
campus program.
Another demographic difference between students in the online and on-campus
program was related to the students’ places of origins. Eighty-eight percent of students
(n = 21) in the online program reported the United States as their places of origin with
12% (n = 3) reporting other places of origin. However, the ethnic breakdown of the
online students was quite diverse with 42% (n = 10) White, 25% (n = 6) Black or African
American, 21% (n = 5) Asian, and 12% (n = 3) Hispanic or Latino. As for the on-campus
program, 10% of students (n = 2) reported the United States as their places of origin with
ninety percent (n = 18) reporting other places of origin. Of the 18 respondents, seventy-
eight percent (n = 14) were from China with the remaining four reporting Taiwan, Japan,
Thailand, and England as their countries of origin. The ethnic breakdown was similar
with 85% (n = 17) Asian, 10% (n = 2) two or more races, and 5% (n = 1) Hispanic or
41
Latino. Related to this is the significant difference noted through the Pearson’s Chi-
square analysis with regard to countries of origin, χ
2
= 25.392, df = 4, p = .000. See Table
2 for information on participants’ places of origin.
Table 2
Participant demographics: Countries of origin
Instructional Delivery Method
Country of
Origin
Online % Traditional % Total %
USA
Canada
21
1
87.5
4.2
2
0
10
0
23
1
52.2
2.3
China
Egypt
0
1
0
4.2
14
0
70
0
14
1
31.8
2.3
England
Japan
0
0
0
0
1
1
5
5
1
1
2.3
2.3
Philippines
Taiwan
1
0
4.2
0
0
1
0
5
1
1
2.3
2.3
Thailand 0 0 1 5 1 2.3
Total 24 20 44
Given the noticeable difference in the students’ ethnic backgrounds between the
delivery methods, three English language proficiency questions were included in the
demographics section of the survey to ascertain students’ own perception of their
language proficiency. A t-test was performed to examine potential differences in the
students’ English language proficiency between delivery methods. A significant
difference was found in the perceived English language proficiency between online
(M = 4.74, SD = .50 ) and on-campus (M = 3.97, SD = 1.11) students, t(25) = 2.86,
p = .008.
The chi-square test also showed significance with regard to employment status,
χ
2
= 23.377, df = 2, p = .000. Of the 24 respondents in the online program, 15 reported
working full-time and five reported working part-time. In contrast, of the 20 respondents
42
in the on-campus program, no one reported working full-time and three reported working
part-time.
In summary, the demographic section of the survey revealed that participants
enrolled in the online program were more likely to be older, married, employed, and from
the United States. On the other hand, respondents enrolled in the on-campus program
were likely to be younger, single, unemployed, and from China or other Asian countries.
Instrumentation
Participants were asked to complete a self-report questionnaire consisting of a
number of demographic questions, and three subscales aimed to measure the constructs
of openness to diversity, voluntary peer collaboration, and help seeking. Self-report
measures were used.
Demographic questions. A number of demographic questions were asked in
order to determine possible socio-cultural influences on the constructs being measured.
These questions asked questions regarding the individual’s gender, racial-ethnic group,
nationality, and employment status. Additionally, participants were asked about prior
experiences with online courses/programs, program type they are enrolled in, and the
reasons for choosing the program type. These questions allowed for comparison of
potential demographic differences between programs, and were relevant to understanding
the results.
Openness to diversity. The instrument that was used to measure openness to
diversity is the Openness to Diversity/Challenge as originally developed by Pascarella et
al. (1996). The original eight-item survey was used to measure a total of approximately
3,300 randomly selected first year students. The Cronbach’s alpha for the original scale
43
was .83. The reliability analysis performed for this study reported an alpha of .87 which
was slightly higher than the .83 reported in the literature and greater than the minimum
level of acceptability of .70. Openness to diversity in this study was measured with a
modified version of the word “background” added to the statements to reflect diverse
backgrounds of people students were expected to be interacting with in their courses. The
word “college” was omitted, as this study sampled graduate level students. The last item
was also omitted, as it did not address the topic of diversity but of challenge. Sample
items from the measure included, “I enjoy having discussion with people whose values
and backgrounds are different from my own” and “I enjoy taking courses that challenge
my beliefs and values.”
Voluntary peer collaboration. The instrument that was used to measure
voluntary peer collaboration was Voluntary Peer Collaboration as collaboratively
developed by a thematic dissertation group under the supervision of two faculty members
in the School of Education. The instrument was designed to measure students engaging in
collaboration in voluntary context. The survey was piloted to a group of Ed.D. students
enrolled in an Inquiry I course. The original Cronbach’s alpha for the scale was .93. The
reliability analysis performed for this study reported an alpha of .78 which was lower
than the .93 reported in the pilot but greater than the minimum level of acceptability
of .70. A sample item included in the survey was, “It is important to collaborate with my
peers in this course even if it is not required.”
Beliefs. Students’ beliefs were measured using the three-items Voluntary Peer
Collaboration survey instructing students to indicate the degree to which they agree or
disagree with statements provided.
44
Mode of contact. The different modes of voluntary collaborative behavior were
measured using the Voluntary Peer Collaboration survey instructing students to indicate
the modes in which they voluntarily collaborated with peers during the academic term.
The choices included not applicable, in person, via phone or text, via email or discussion,
via social media, via videoconferencing, and other.
Frequency. Students’ frequency of voluntary collaborative behavior was
measured using the Voluntary Peer Collaboration survey instructing students to indicate
the frequency in which they collaborated with peers ranging from “Not at all” to “More
than twice a week”.
Help seeking. Help-seeking beliefs was measured with the four items from the
help seeking section of the Motivated Strategies for Learning Questionnaire (MSLQ), an
81-item scale developed by Pintrich (1991). The Cronbach’s alpha for the original MSLQ
help seeking scale was .52. The reliability analysis performed for this study reported an
alpha of .76 which was higher than the .52 reported in the literature and greater than the
minimum level of acceptability of .70. Sample items from the MSLQ include “When I
can’t understand the material in this course, I ask another student in this class for help”
and “I try to identify students in this class whom I can ask for help if necessary.” The
“Help seeking scales” measure developed by Karabenick (2003) was also used to
measure formal and informal help seeking behaviors. A subset “Formal versus informal
help seeking” which included three items was used to distinguish formal and informal
help seeking behaviors. The Cronbach’s alpha for Karabenick’s informal versus formal
help seeking scale was .66. The reliability analysis performed for this study reported an
alpha of .68 which was slightly higher than the .66 reported in the literature.
45
The instrument that was used to measure help seeking behavior was Help Seeking
Assessment as collaboratively developed by a thematic dissertation group under the
supervision of two faculty members in the School of Education. The instrument was
designed using concepts of formal versus informal help seeking from Karabenick (2003).
Beliefs. Students’ beliefs regarding help seeking was measured using four items
from the MSLQ and three items from Karabenick’s Formal versus informal help seeking
scale instructing students to indicate the degree to which they agree or disagree with
statements provided regarding help seeking
Frequency. Students’ frequency of help seeking behavior was measured using the
Help Seeking Assessment instructing students to indicate the frequency in which they
sought help during the academic term ranging from “Not at all” to “More than once a
week”.
Procedure and Data Collection
Upon approval from the institution’s IRB board, data collection began with the
distribution of the online survey which included demographic information and self-report
questionnaires on the three constructs. Data collection first began for the online cohort in
session during the summer term of 2014. The survey was launched during week 8 and
closed at the end of the term (week 12). Data collection continued for both the online and
on-campus cohorts in session during the fall term of 2014. Again, survey was launched
during week 8 and closed at the end of the term (week 12). Students enrolled in the online
or on-campus course were sent an email from either the principal investigator or the
course instructor. This email contained a link to the online survey and a brief description
of the purpose of the study. This email also explained that participation was voluntary,
46
and completely anonymous; additionally, it explained that there was no immediate
benefit for them to participate in the study and that they would not be penalized for not
participating. If students chose to participate in the study, they were asked to follow a
link to an online survey. The survey was administered online using the Qualtrics Survey
Tool (www.qualtrics.com). Expected time to complete the survey was approximately 10
minutes.
Data Analysis
Once survey data was collected via Qualtrics Survey Tool, the results were
uploaded to Statistical Package for the Social Sciences (SPSS) 22 program. The
independent variables in this study were 1) online delivery method and 2) on-campus
delivery method. The corresponding dependent variables were students’ beliefs and
behaviors concerning 1) openness to diversity, 2) voluntary peer collaboration, and 3)
help seeking. These independent and dependent variables were coded and inputted to
SPSS. For research question one, t-test was performed to determine whether differences
existed in students’ openness to diversity by program delivery methods. For research
question two, t-tests were performed to determine whether differences existed in students’
beliefs about voluntary peer collaboration and voluntary peer collaboration frequency.
Chi-square tests were also performed to determine whether differences existed in the
voluntary peer collaboration modes of contact according to program delivery method.
Finally, for research question three, t-test was performed to determine whether
differences existed in students’ frequency of help seeking behaviors and chi-square tests
were performed to determine whether differences existed in the mode and frequency of
help seeking according to program delivery method.
47
The table below specifies the independent and dependent variables and their
corresponding level of measurements for each research question. It also provides the
statistical test that was performed.
48
Table 3
Research questions: Independent and dependent variables, levels of measurement, and
statistical test
Research
Question
IV(s)
Level of
Measurement
DV(s)
Level of
Measurement
Statistical
Test
1. Is there a
difference in
students’
openness to
diversity by
program delivery
methods?
Program
delivery
method
Nominal Openness to
Diversity
Interval t-test
2. Is there a
difference in
student voluntary
peer
collaboration
beliefs and
behaviors by
program delivery
method?
Program
delivery
method
Nominal Voluntary
peer
collaboration
beliefs
Interval t-test
Voluntary
peer
collaboration
frequency
Interval t-test
Voluntary
peer
collaboration
mode of
contact
Nominal Chi-
square
3. Is there a
difference in
student help
seeking beliefs
and behaviors by
program delivery
method?
Program
delivery
method
Nominal Help seeking
beliefs
Interval
t-test
Help seeking
frequency
Interval
t-test
Help seeking
mode
contact
Nominal Chi-
square
49
CHAPTER FOUR
Results
The purpose of this study was to assess openness to diversity, voluntary peer
collaboration, and help seeking beliefs and behaviors in online versus on-campus learning
settings among students in higher education, specifically focusing on a Masters in
Teaching English to Speakers of Other Languages (TESOL) program at a large private
university (LPU) in a major urban city in the west coast. This study investigated whether
openness to diversity, voluntary peer collaboration, and help seeking behaviors differed
by program delivery methods.
The purpose of this chapter is to report the findings of this study. The first section
will provide significant findings to help understand the strength of relationship between
variables. The following section will include statistical analyses of these results organized
according to the research questions.
Intercorrelations
The mean, standard deviations, and correlations of all the measured variables are
presented in Table 4. Students’ perceived degree of openness to diversity was
significantly correlated with voluntary collaboration (r = .39, p = .008), indicating that
students who reported greater degree of openness to diversity also engaged in more
voluntary peer collaboration. Age was significantly associated with the level of parents’
education and the number of previous graduate degrees. Those students who were older
reported having either parents with less education (r = -.30, p = .035) and less number
of previous graduate degrees (r = -.34, p = .017). Overall, there were few significant
correlations found in the study.
50
Table 4:
Means, Standard Deviations, and Pearson Product Correlations of Measured Variables
Variables M SD 2 3 4 5 6 7
1. Age 29.98 9.64 -.300* .148 -.338* -.107 -.032 -.290
2. Parent education 6.56 1.66 -- -.127 -.279 -.186 .202 .240
3. No. of diversity
courses
2.88 1.05 -- -.267 .020 .143 .014
4. No. of previous
degrees
1.86 .354 -- -.211 .123 .089
5. Openness to
diversity
4.62 .440 -- .395** .049
6. Voluntary
collaboration
4.48 .616 -- .217
7. Help seeking 4.14 0.69 --
*p<.05 **p<.01
Analysis of Results
The self-report survey data collected as described in the previous chapter was
analyzed in order to address the research questions posed for the study. The quantitative
findings presented in this chapter will be organized according to the research questions.
Research Questions 1: Is there a difference in students’ openness to diversity
by program delivery methods? This research question sought to examine potential
differences in students’ degree of openness to diversity between program delivery
methods. An independent-samples t-test was conducted to compare students’ openness to
diversity in online and on-campus conditions. See Table 5 below for details regarding the
t-test results.
51
Table 5
Results of t-tests and descriptive statistics: Openness to diversity
Group Statistics
Program
Format
N Mean
Std.
Deviation
Std. Error
Mean
Mean
Diversity
Online 24 4.6429 .43981 .08978
On-campus 20 4.6000 .45080 .10080
Independent Samples Test
Lavene’s test
for Equality
of Variances
t-test for Equality of Means
F Sig t df
Sig.
(2-
tailed)
Mean
Difference
Std. Error
Difference
95% Confidence
Interval of the
Difference
Lower Upper
.441 .510 .318 42 .752 .04286 .13467 -.22893 .31464
No significant difference was found as can be seen in the scores for online
(M = 4.64, SD = .44 ) and on-campus (M = 4.60, SD = .45) delivery methods;
t(42) = .32, p = .752. The results suggest that there are no differences in the students’
degree of perceived openness to diversity between the two program delivery methods.
Research Questions 2: Is there a difference in student voluntary peer
collaboration beliefs and behaviors by program delivery method? This research
question sought to examine potential differences in students’ voluntary peer collaboration
beliefs and behaviors between program delivery methods. An independent-samples t-test
was conducted to compare students’ voluntary peer collaboration beliefs in online and
on-campus conditions. See Table 6 below for details regarding the t-test results.
52
Table 6
Results of t-tests and descriptive statistics: Voluntary peer collaboration beliefs
Group Statistics
Program
Format
N Mean
Std.
Deviation
Std. Error
Mean
Mean
Vol. Collab.
Online 24 4.4444 .70654 .14422
On-campus 20 4.5333 .50029 .11187
Independent Samples Test
Levene’s Test
for Equality of
Variances
t-test for Equality of Means
F Sig t df
Sig.
(2-
tailed)
Mean
Difference
Std.
Error
Differen
ce
95% Confidence
Interval of the
Difference
Lower Upper
2.104 .154 .472 42 .639 -.08889 .18825 -.46879 .27972
No significant difference was found as can be seen in the scores for online
(M = 4.44, SD = .71) and on-campus (M = 4.53, SD = .50) delivery methods;
t(42) = .47, p = .639. The results suggest that there are no differences in the students’
voluntary peer collaboration beliefs between the two program delivery methods.
An independent-samples t-test was also conducted to compare students’ voluntary
peer collaboration behaviors as measured by frequency of more than twice a week, 1-2
times per week, 1-2 times per month, 1-2 times per semester, or not at all. See Table 7
below for details regarding the t-test results.
53
Table 7
Results of t-tests and descriptive statistics: Voluntary peer collaboration behaviors
Group Statistics
Program
Format
N Mean
Std.
Deviation
Std. Error
Mean
Mean
Vol. Collab.
Online 24 3.54 1.141 .233
On-campus 20 3.85 .988 .221
Independent Samples Test
Levene’s Test
for Equality of
Variances
t-test for Equality of Means
F Sig t df
Sig.
(2-
tailed)
Mean
Difference
Std. Error
Difference
95%
Confidence
Interval of the
Difference
Lower Upper
1.702 .199 -.948 42 .349 -.308 .325 -.965 .348
No significant difference was found as can be seen in the scores for online
(M = 3.54, SD = 1.14) and on-campus (M = 3.85, SD = .99) delivery methods;
t(42) = -.95, p = .349. The results suggest that there are no differences in the students’
voluntary peer collaboration behaviors between the two program delivery methods.
Mode of voluntary peer collaboration. Additional analyses were conducted to
determine if there were differences according to the modes of contacts in the students’
voluntary peer collaboration behavior. This research question sought to examine
potential differences in students’ voluntary peer collaboration behaviors between
program delivery methods according to the different modes of collaboration which
included in-person, via phone or text, via email or discussion board, via social media (e.g.,
Facebook, Twitter), and via videoconferencing (e.g., Skype, Adobe Connect). A set of
five chi-square tests was performed.
54
Results indicate a significant relationship between course delivery method and
voluntary collaboration in-person, χ
2
(1, N = 44) = 23.18, p < .001. This indicates that
students in the on-campus program were more likely to voluntarily collaborate in-person.
See Table 8 below for details.
Table 8
Chi-square test: Voluntary collaboration in-person
Chi-Square Tests
Value df Asymp. Sig. (2-sd)
Pearson Chi-Square 23.178
a
1 .000
Continuity Correction
Likelihood Ratio
20.308
25.750
1
1
.000
.000
Linear-by-Lin. Assoc. 22.652 1 .000
N of Valid Cases 44
a. 0 cells (0.0%) have expected count less than 5. The minimum expected count is 8.18
However, no significance was found between course delivery method and
voluntary collaboration via phone or text, χ
2
(1, N = 44) = .013, p = .911. See Table
9 below for details.
Table 9
Chi-square test: Voluntary collaboration via phone or text
Chi-Square Tests
Value df Asymp. Sig. (2-sd)
Pearson Chi-Square .13
a
1 .911
Continuity Correction
a
Likelihood Ratio
.000
.013
1
1
1.000
.911
Linear-by-Lin. Assoc. .012 1 .912
N of Valid Cases 44
a. 0 cells (0.0%) have expected count less than 5. The minimum expected count is 8.18.
No significance was found between course delivery method and voluntary
collaboration via email or discussion board, χ
2
(1, N = 44) = .52, p = .469. See Table
10 below for details.
55
Table 10
Chi-square test: Voluntary collaboration via email or discussion board
Chi-Square Tests
Value df Asymp. Sig. (2-sd)
Pearson Chi-Square .524
a
1 .469
Continuity Correction
Likelihood Ratio
.154
.523
1
1
.695
.470
Linear-by-Lin. Assoc. .512 1 .474
N of Valid Cases 44
a. 0 cells (0.0%) have expected count less than 5. The minimum expected count is 5.91.
Again, no significance was found between course delivery method and voluntary
collaboration via social media (e.g., Facebook, Twitter), χ
2
(1, N = 44) = 1.93,
p = .165. See Table 11 below for details.
Table 11
Chi-square test: Voluntary collaboration via social media
Chi-Square Tests
Value df Asymp. Sig. (2-sd)
Pearson Chi-Square 1.925
a
1 .165
Continuity Correction
Likelihood Ratio
1.115
1.929
1
1
.291
.165
Linear-by-Lin. Assoc. 1.881 1 .170
N of Valid Cases 44
a. 0 cells (0.0%) have expected count less than 5. The minimum expected count is 5.91.
Finally, significance was found between course delivery method and voluntary
collaboration via videoconferencing (e.g., Skype, Adobe Connect), χ
2
(1, N = 44)
= 18.59, p < .001. This indicates that students in the online program were more likely to
voluntarily collaborate via videoconferencing. See Table 12 below for details.
56
Table 12
Chi-square test: Voluntary collaboration via videoconferencing
Chi-Square Tests
Value df Asymp. Sig. (2-sd)
Pearson Chi-Square 18.590
a
1 .000
Continuity Correction
Likelihood Ratio
16.061
20.637
1
1
.000
.000
Linear-by-Lin. Assoc. 18.168 1 .000
N of Valid Cases 44
a. 0 cells (0.0%) have expected count less than 5. The minimum expected count is 9.09.
Research Questions 3: Is there a difference in student help seeking behaviors
by program delivery method? This research question sought to examine potential
differences in students’ help seeking behaviors between program delivery methods. An
independent-samples t-test was conducted to compare students’ frequency of help-
seeking behaviors in online and on-campus conditions. See Table 13 below for details
regarding the t-test results.
Table 13
Results of t-tests and descriptive statistics: Help seeking behaviors
Group Statistics
Program
Format
N Mean
Std.
Deviation
Std. Error
Mean
Mean
Help Seek
Online 24 4.0278 .49065 .10015
On-campus 20 4.2667 .86923 .19437
Independent Samples Test
Levene’s
Test for
Equality of
Variances
t-test for Equality of Means
F Sig t df
Sig.
(2-
tailed)
Mean
Difference
Std. Error
Difference
95%
Confidence
Interval of the
Difference
Lower Upper
.602 .442 1.093 28.755 .284 -.23889 .21865 .68625 .20847
57
No significant difference was found as can be seen in the scores for online
(M = 4.03, SD = .49) and on-campus (M = 4.27, SD = .87) delivery methods; t(29) = 1.09,
p = .284. The results suggest that there are no differences in the students’ self-reported
frequency of help seeking behaviors between the two program delivery methods.
Mode of help seeking. Additional analyses were conducted to determine if there
were differences according to the modes of contacts in the students’ help seeking
behavior. This research question sought to examine potential differences in students’
help seeking behaviors between program delivery methods depending on the sources of
help from the instructor or teaching assistant, from a peer, and from unspecified others.
A set of three chi-square tests was performed.
No significance was found between course delivery method and frequency of help
seeking from the instructor or teaching assistant, χ
2
(4, N = 43) = 1.75, p = .781. See
Table 14 below for details.
Table 14
Chi-square test: Seeking help from instructor or teaching assistant
Chi-Square Tests
Value df Asymp. Sig. (2-sd)
Pearson Chi-Square 1.753
a
4 .781
Likelihood Ratio 1.822 4 .768
Linear-by-Lin. Assoc. .320 1 .571
N of Valid Cases 43
a. 0 cells (0.0%) have expected count less than 5. The minimum expected count is 9.09.
However, results indicated a significant relationship between course delivery
method and frequency of seeking help from a peer, χ
2
(4, N = 44) = 11.02, p = .026.
This indicates that students in the on-campus program were more likely to seek help from
a peer. See Table 15 below for details.
58
Table 15
Chi-square test: Seeking help from peers
Chi-Square Tests
Value df Asymp. Sig. (2-sd)
Pearson Chi-Square 11.020
a
4 .026
Likelihood Ratio 13.893 4 .008
Linear-by-Lin. Assoc. 2.589 1 .108
N of Valid Cases 44
a. 5 cells (50.0%) have expected count less than 5. The minimum expected count is .45.
Results also indicated a significant relationship between course delivery method
and frequency of seeking help from others, χ
2
(4, N = 40) = 11.86, p = .02. This
indicates that students in the on-campus program were more likely to seek help from
unspecified others. See Table 16 below for details.
Table 16
Chi-square test: Seeking help from others
Chi-Square Tests
Value df Asymp. Sig. (2-sd)
Pearson Chi-Square 11.861
a
4 .018
Likelihood Ratio 13.002 4 .011
Linear-by-Lin. Assoc. 5.054 1 .025
N of Valid Cases 40
a. 6 cells (60.0%) have expected count less than 5. The minimum expected count is .45.
Summary
This chapter reported the results of the statistical analyses performed to answer
the research questions of this study. An overview of the research questions and
methodology was provided. The first analysis presented in this chapter was the
intercorrelations to identify any significant correlations of measured variables. As
established in the literature review, students enrolled in the online program were more
likely to be older, married, and employed. A unique attribute to this particular M.A.
TESOL program was that majority (88%) of the students enrolled in the online program
59
reported the United States as their place of origin, whereas the majority of students (90%)
enrolled in the on-campus program reported non-US places of origin with China most
frequently reported (78%). While significance was found in students’ perception of their
language proficiency between the delivery methods, this did not appear to affect the
students’ beliefs and behaviors concerning openness to diversity, voluntary peer
collaboration, and help seeking.
Each of the research questions were introduced individually, and analysis
results were presented with tables. The first research question asked about potential
differences in students’ degree of openness to diversity according to delivery method. No
significant differences were found in the degree of openness to diversity between delivery
methods.
The second research question asked about potential differences in students’
voluntary peer collaboration beliefs and behaviors according to delivery method. No
significant differences were found in reported voluntary peer collaboration beliefs and
behaviors between delivery methods. Additional analyses were conducted to examine
potential differences in the ways the students engaged in voluntary peer collaboration.
Results indicated a significant relationship between course delivery method and voluntary
collaboration in-person, indicating that students in the on-campus program were more
likely to voluntarily collaborate in-person. Similarly, results indicated a significant
relationship between course delivery method and voluntary collaboration via
videoconferencing, indicating that students in the online program were more likely to
voluntarily collaborate via videoconferencing. However, no significance was found
60
between course delivery method and voluntary collaboration via phone or text, via email
or discussion board, and via social media.
The final research question asked about potential differences in students’ help-
seeking behaviors according to delivery methods. No significant differences were found
in reported help-seeking behaviors between delivery methods. Again, additional analyses
were conducted to examine potential differences according to the sources in which
students sought help. No significance was found between course delivery method and
frequency of seeking help from the instructor or teaching assistant. However, significance
was found between delivery method and frequency of seeking help from peers and others
for students in the on-campus program. This indicates that students in the on-campus
program were more likely to engage in help-seeking behaviors.
The results of this analysis showed a non-significant relationship for M.A.
TESOL students enrolled in the online and on-campus programs. However, significant
results were found for some parts of the research question examining the modes of
contact. The implications of these results will be discussed in the next chapter.
61
CHAPTER FIVE
Discussion
This section will begin with a brief overview of the results to understand the
importance of social behaviors in academic contexts which impact learning in online and
on-campus environments. Differences and similarities in the learners and learning
environments for both online and on-campus courses will be examined through the
perspective of student learning. The constructs of degree of openness to diversity,
voluntary peer collaboration, and help seeking beliefs and behaviors as measured in the
survey will be discussed. The chapter will conclude with implications, limitations, and
recommendations for future research.
The purpose of the study was to compare online and on-campus programs
considering the quality of student learning experience. Having established that certain
behaviors or the degree of students’ engagement in academic context can largely
influence the level of learning that takes place (Astin, 1984; Hu & Kuh, 2003; Kuh 2001;
Robinson & Hullinger, 2008), the study was designed to evaluate potential differences
according to program delivery method. While some research findings (McGuire & Castle,
2010; Robinson & Hullinger, 2008) have indicated that on-campus students are more
engaged and experience more face-to-face contact, there have also been research findings
(Lei & Gupta, 2010; Robinson & Hullinger, 2008) that indicate that online students’
overall academic engagement is comparable to or even better than on-campus students
(Lei & Gupta, 2010; McGuire & Castle, 2010; Robinson & Hullinger, 2008). The study
was partly in response to the inconsistencies in the findings and to better understand the
role of student beliefs and behaviors.
62
The study results indicate that there is no statistically significant difference in the
levels of student engagement between online and on-campus students. Where the study
did yield statistically significant differences of voluntary peer collaboration and help
seeking behaviors, the differences can be explained by the nature of the delivery method.
For example, analysis indicated significant difference in students’ voluntary peer
collaboration behaviors via face-to-face mode of contact for on-campus students as they
were required to be on campus. Conversely, there was a significant difference in students’
voluntary peer collaboration behaviors via videoconferencing mode of contact for online
students as it was the means of course delivery as well as a primary means of
communication. Significant differences were also found for help seeking behaviors of on-
campus students seeking help from peers and unspecified others. This may be explained
by the self-reported level of English language competence and the degree of importance
of sharing the same native language, which will be discussed in detail in the following
section.
The research questions developed for this study were based on well-established
constructs related to academic social behaviors in student learning. In order to answer the
research questions posed in this study, quantitative data was collected from participants
in the online and on-campus programs. The following sections provide a discussion based
on the results of the study.
Discussion of Demographic Composition of Students by Delivery Method
Demographic information was collected to gather pertinent data to better
understand the typical learner characteristic according to program delivery method. The
data was designed to either confirm or disconfirm certain learner characteristics about
63
online and on-campus students as established in literature. Online education is often
associated with non-traditional student population (Capra, 2014; Chen et al., 2010;
Hachey et al., 2014) who can more benefit from the flexibility and convenience of the
online delivery method (Brown, 2012; Picciano et al., 2010). As expected, the results
indicated significant differences in demographics between online and on-campus students.
The online students were more likely to be older, married, and employed, whereas the on-
campus students were more likely to be younger, single, and unemployed. While the
characteristics of the non-traditional student population may suggest an overall lack of
student persistence and higher attrition rates (Astin 1993a; Tinto 1997), there are
compounding factors, such as graduate level studies and professional motivation and
goals.
One notable difference among students by program delivery was the students’
countries of origin. Data indicate overwhelming majority of the students were from the
U.S. in the online program and overwhelming majority of the students were from outside
of the U.S. (mostly from China) in the on-campus program. To account for potential
discrepancy in language ability of students, the demographic section included questions
to measure the degree of confidence of student’s English Language competence. In fact,
significant difference was found between the confidence level of online and on-campus
students. However, despite the significant difference, further analysis indicated that there
was no statistical difference in student beliefs and behaviors as measured by degree of
openness to diversity, voluntary peer collaboration, and help seeking by program delivery.
This seems to imply that students’ self-perception of their language competence does not
affect academic beliefs and behaviors. In other words, a student’s reported level of
64
English competence did not affect their behaviors in voluntarily collaborating with a peer
and seeking help from an outside source.
To further explore the role of culture and language, another question was
designed to determine the degree to which factors, such as age, gender, and native
language play a role in influencing student engagement. The question specifically asked
the degree of importance of age, gender, and native language when choosing to
voluntarily collaborate with peers. The results indicated differences by delivery method.
Online students viewed age as neither important nor unimportant and gender and
language as somewhat unimportant. On-campus students similarly viewed age and
gender as somewhat unimportant but language as somewhat important. Results indicate
that language is the only factor that may influence student behavior in choosing to
voluntarily collaborate with peers, especially among the on-campus students who feel
less secure about their language competence to successfully understand course concepts
and complete their assignments.
Discussion of Degree of Openness to Diversity by Delivery Method
The study results did not find a statistically significant difference in students’
degree of openness to diversity by delivery methods. Students in both the online and on-
campus programs indicated a strong view of agreement on statements regarding the value
of diversity and its importance as a component of their educational experience. The
results also indicated a strong sense of enjoyment of courses that incorporate diverse
views, beliefs, and people. The finding supports research that has shown that students
generally become more open and tolerant of diverse race, culture, and values during their
college years (Pascarella et al., 1996). It appears students in graduate programs continue
65
along the trajectory of being more open to diversity, particularly in the field of education,
which tends to view diversity as important.
While there has been little research examining how the online learning
environment impacts students’ openness to diversity, this study suggests that the degree
of openness to diversity remains equally strong for both online and on-campus students.
The finding is particularly interesting given that the online program consisted of an
ethnically diverse student population while the on-campus program consisted of a largely
Asian (majority Chinese) student population. Despite the lack of diversity within the on-
campus program, students still viewed diversity as an important core value in their
education. This finding further supports the idea that diversity cannot be measured simply
by the structural representation of a diverse student population but by the values and
importance placed on the opportunities to meaningfully engage with a diverse group of
people (Hurtado et al., 1999). As reported in the study, despite the lack of a structural
representation of diverse groups providing a context for exposure and interaction with
those of diverse backgrounds, the on-campus students reported a great sense of openness
to diversity. The findings highlight the importance of the quality and meaningfulness of
interaction in developing students’ openness to diversity (Hurtado et al., 1999) and
fostering students’ academic and social growth (Gurin et al., 2002, Hurtado, 2007).
A possible explanation for this may be self-selection of international students who
intentionally chose to study abroad in a field that generally values diversity. In fact, the
students had already studied diversity during the course of the term which indicates some
primacy. The findings may not be the same in a field such as Engineering or Computer
Science which may not explicitly teach values of diversity as part of the course
66
curriculum. Under the assumption that students in the MA in TESOL will engage in
teaching English to speakers of other languages in domestic and international settings, it
is more likely for students to be predisposed to diversity.
In summary, students degree of openness to diversity was strong with a mean
score of 4.62 on a 1-5 scale for both online and on-campus programs. This indicates a
high priority placed on diversity and supports the school’s commitment to diversity as
communicated in the delivery of the course programs. The study also suggests that indeed
students’ degree of openness to diversity remains high as they progress from college to
graduate school.
Discussion of Voluntary Peer Collaboration by Delivery Method
The study results did not find a statistically significant difference in students’
beliefs and behaviors on voluntary peer collaboration by delivery methods. Students in
both the online and on-campus programs indicated a positive view on the importance of
collaboration with peers and its subsequent importance to academic success with the
assumption that peer collaboration improves performance and contributes to student
achievement (Astin, 1993a, 1993b; Cabrera et al., 2002; Tinto, 1997). This finding
supports the commonly held view that peer collaboration is an important academic skill
to effectively learn from each other (Boud, 2001; Cabrera et al., 2002; Roger & Johnson,
1994; Van den Bossche et al., 2006). Recognizing the importance of peer collaboration
may indicate students taking responsibility of their own learning as they learn from each
other by explaining their ideas, participating in activities, receiving and giving feedbacks,
and seeking help from peers for their learning.
Students in both the online and on-campus programs also did not display a
67
significant difference in their voluntary peer collaboration behaviors. They reported a
similar frequency of 1-2 times per month for voluntarily collaborating with peers.
Although there is little research discussing the voluntary nature of collaboration, this
study seems to suggest that students are in fact engaging in informal learning as they
voluntarily engage in conversations, group projects, study groups, and other course
related activities (Boud, 2001; Boud & Lee, 2005). The current study suggests that peer
collaboration in the classroom has become a core of academic and social experiences
contributing to meaningful learning (Astin, 1993a, 1993b; Tinto, 1997).
In regards to the mode of contact in voluntary peer collaboration behavior,
similarities as well differences were noted by program delivery. No significant
differences were noted in voluntarily collaborating with peers via phone or text, via email
or discussion board, and via social media. However, differences were noted for
voluntarily collaborating with peers in-person for the on-campus students and via
videoconferencing for the online students. The findings were not surprising given the
nature and limitations of the delivery methods. On-campus students had weekly
opportunities to meet in person and voluntarily collaborate with their classmates during
or outside of class time, whereas the online students had access to videoconferencing
technology, such as the online course platform Adobe Connect, to videoconference with
their classmates during and outside of class time. The findings show how environmental
factors do in fact influence collaborative learning behaviors.
Although a significant difference was not noted in the frequency of voluntary peer
collaboration behavior, findings show that the on-campus students generally engaged in
the behavior more frequently than the online students. In considering the frequency in
68
which the on-campus class met - twice a week for 3 hours - the students likely had more
opportunities to be in close physical proximity to other peers with more opportunities to
engage with each other. This does not disprove the finding that online students generally
express a need for social connection and sense of presence in the technology mediated
learning environment (Palloff & Pratt, 1999; Walker & Fraser, 2005), as they also
regularly engaged in voluntary peer collaboration with peers. This finding suggests that
voluntary peer collaboration can be useful in providing opportunities for students to
engage with each other and find a sense of presence for online students who may feel a
greater need to connect.
In summary, the study indicates that both online and on-campus students value and
engage in voluntary collaborative behavior with peers. The study also supports the role of
e-learning technologies, which enhance collaborative components in the online learning
experience (Kim & Bonk, 2006). In examining how the online environment influences
collaborative learning, it is helpful to consider how peer collaborative learning can be
enhanced and encouraged from the perspective of skill development through group
interaction and social learning in both online and on-campus programs.
Discussion of Help Seeking by Delivery Method
The study results did not find a statistically significant difference in students’ help
seeking behaviors by delivery methods. Students in both the online and on-campus
programs positively viewed help seeking behaviors. The finding seems to suggest an
overall high frequency of help seeking behaviors and further suggests that online students
are not at a disadvantage as a result of not being physically present with others to engage
in help seeking behaviors. As suggested (Karabenick, 2011; Kitsantas & Chow, 2007),
69
the widespread use of communication technologies seems to have contributed to an
increase in help seeking behaviors among students. This can be exemplified in students
using technology-mediated forms of communications such as discussion boards and
email to contact instructors and peers about questions they may have on particular
assignments. The finding is reassuring insofar as help seeking is a critical academic
behavior positively correlated with learning and academic performance (Cheng et al.,
2013; Karabenick, 2003, 2011; Kitsantas & Chow, 2007). It is also reassuring in that
online students did not seem to experience a noticeably lesser propensity to seek help
from different sources (Cheng et al., 2013; Karabenick, 2011) as they also engaged in
help seeking behavior.
However, in examining the modes of help seeking behaviors, differences were
found in help seeking behaviors of on-campus students who were more likely to seek
help from peers and unspecified others. The findings may suggest that the traditional
face-to-face settings which provide physical proximity to instructor and peers, as well as
visual and auditory cues may create an environment that is more conducive to help
seeking behavior (Cheng et al., 2013; Dabbagh & Kitsantas, 2013; Karabenick, 2011).
Another possible explanation for why on-campus students are more likely to seek help
from peers and others may include language factors. For example, non-native English
speaking students may feel more inclined to seek help from fellow classmates in the same
language group to check for comprehension and clarification. However, survey finding
does not conclusively support this explanation with on-campus students on average
indicating “neither agree nor disagree” to the question of preference of seeking help from
students whose native language is the same. This finding is in comparison to the online
70
students leaning more towards “disagree” on the same question.
Another finding worth noting is the varying degrees of difference depending on the
source of help. Both online and on-campus students did not seek help from their
instructors as readily as they sought help from their peers and others. This supports the
idea of help seeking as an inherently social practice and the importance of group
interaction within learning contexts. Hence, classroom environment and the degree to
which it facilitates a climate for help must be carefully considered.
In summary, no significant differences were found in help seeking behaviors of
students in online and on-campus programs. Both groups positively viewed help seeking
as an important component of learning and understanding course content. Both groups
also indicated a slight preference for seeking help from peers than instructors. However,
on-campus students generally engaged in help seeking behavior more often.
Implications
The study yields important implications for not only graduate programs but more
specifically for programs that train future educators. In recognizing the need for teachers
to acquire the knowledge, skills, and attitudes leading to culturally responsive teaching
(McAllister & Irvine 2000; Nelson & Guerra, 2013; Pohan & Aguilar, 2001), suggestions
are made to further develop a culturally engaging curriculum and experience for students.
Moreover, the importance of proactively engaging in collaborative and help seeking
behaviors as critical components of professional training is also taken into consideration.
The following recommendations are made to instructors, course designers, and
administration from the perspective of sociocultural theory in the context of online
education focusing on but not limited to teacher training in graduate programs.
71
• Encourage student interaction with instructor and each other by intentionally
forming small groups representing various cultures, language, ethnicity, and other
demographic characteristics such as age and gender. Results indicated that
students’ scores on beliefs were generally higher than behaviors, implying
intentional efforts need to be made to create opportunities for students to engage
with each other through collaboration and help seeking.
• Conduct needs analysis via informal class surveys and discussion to determine
student needs where there may be an underlying issue that can undermine an open
and positive learning environment.
• In situations where English language competency may be a factor, accommodate
students who may feel less confident by incorporating systems of support among
peers and with instructors. For example, non-native speakers can be paired up
with native speakers who can provide language support and instructors can also
make necessary adjustments to class assignments and projects to cater to non-
native speaking students.
• Provide opportunities for online students to freely engage with students in class
by opening up the class 10-15 minutes before and after class. In other words,
encourage students to log-in earlier or remain online in the virtual classroom after
class hours to promote free flowing and spontaneous conversations and discussion
with classmates. This is in response to the results indicating online students were
less likely to engage in voluntary peer collaboration and help seeking. Efforts
need to be made to create a space and time for students to interact with each other
and in so doing meet the need for online students to feel less isolated and more
72
connected. For example, providing opportunities for students to virtually share
the same space and time with peers to collaborate on an assignment or dialogue
about their learning in the course can help to build relationship and fill the need
for social and emotional connection.
• Encourage students to use other forms of e-learning technologies to communicate
with each other and make it a regular component of class communication.
• Promote instructor office hours and encourage early one-on-one interaction with
students which can in turn promote seeking help seeking from instructors. This
can be done by making at least one office visit early on in the term a mandatory
component of the course. The finding that both online and on-campus students
were less likely to seek help from instructors suggests that student-faculty
interaction can be improved through such means.
These recommendations are designed to place an overall emphasis on peer
interaction and collaborative group work to increase student involvement and student
learning. Giving considerations to these factors may help to design and facilitate a class
environment that is culturally engaging, collaborative, and unthreatening for the entire
community of learners regardless of their race, age, gender, language proficiency, and
method of course delivery.
Recommendation for Future Research
The dramatic increase in online programs, particularly in graduate and
professional programs, highlights the need for comparative studies examining student
learning behavior by program delivery method. Future studies are recommended to
expand on the student learning constructs of this study by including qualitative and
73
longitudinal research. Qualitative data can potentially explain the reasons for certain
student beliefs and behaviors as participants expand upon their answers and provide
meaningful insights that are often difficult to obtain via quantitative surveys. The
longitudinal component of the research can also help to capture the changes of student
behavior and beliefs over a period of time. For example, changes in students’ degree of
openness to diversity can be tracked to help researchers identify the progression of
students’ beliefs and behavior related to learning. It can further help researchers to
identify specific points within a period where students are most malleable and receptive
to developing certain values and beliefs connected to behavior. This in turn can help to
develop relevant curriculum and intervention strategies that can be most effective. The
qualitative and longitudinal types of studies can help to not only validate the findings of
this study but also allow for generalizability of findings to other graduate programs and
populations. Similar studies can be conducted in different fields outside of education and
TESOL to better understand how students’ beliefs and behaviors potentially differ
according to fields of study.
Another suggestion is to consider the role of e-learning technologies. The
availability of innovative learning technologies (e.g., Skype, email, text messaging,
discussion boards) promotes interaction with peers and can lead to more effective
learning outcomes in the online context. However, there was variability in the frequency
in which students used certain technologies to interact with instructors and peers. The
study suggests that the learning environment can potentially influence student beliefs and
behaviors, which in turn can have an effect on the overall interaction in and outside the
class, especially related to voluntary peer collaborative efforts. With this in mind, more
74
studies are needed to understand which technologies are more likely to be used by whom
and for what purpose, as well as the degree to which students take advantage of these
tools in online versus on-campus settings.
A final recommendation for further studies is to consider other academic beliefs
and behaviors that are critical to academic success. Goal orientation, which refers to a
student’s reason for engaging in an academic task, is an important motivational factor
which can largely impact student learning. Self efficacy, which refers to a student’s own
sense of self competency, is yet another critical motivational factor in student learning.
These aforementioned factors represent other forms of learning characteristics students
engage in during their educational experience and are shown to have positive
consequences in learning outcomes. Moreover, they can shed light on how motivational
factors promote student engagement and opportunities for interaction.
Limitations
This study was designed to understand how specific academic beliefs and
behaviors can influence learning in the online and on-campus environments. The study
examined sociocultural components of student beliefs and behaviors in group context.
Given this complex task, there are several limitations to the study. The major limitation to
this study is that it was correlational; therefore no causal relationships can be determined.
The researcher can only determine that the independent and dependent variables are
related, but cannot conclude that the changes in the dependent variables are a result of the
independent variables. Also related to the design of the study is the effect of social
desirability. Social desirability bias occurs when participants report answers they believe
75
are acceptable. The researcher could not ensure the participants to honestly complete the
survey as several of the items included value statements reflecting their personal views.
Another major limitation has to do with the generalizability of the study. The
participants in the study were enrolled in a graduate program in the School of Education
at LPU, a large, metropolitan city in Southern California known for its emphasis on
diversity and urban education. Given the target population of MA in TESOL students
who may be more predisposed to diversity and receptive to certain social behaviors in
academic context, the results may not be as relevant to other fields. In terms of the
specific mode of delivery, the synchronous component to the online program may make
the study less applicable to online programs that are entirely asynchronous. The study
was also limited to a small size of the respondents. Although each cohort group
represented the overall program features and the student demographics, the small
participant number may limit interpretation of findings to specific programs and contexts.
Overall, the specificity and the number of participants may limit generalizability.
One final limitation related to the study design has to do with the one-time data
collection. As the study was not longitudinal, it did not take into account how academic
beliefs and behaviors influence learning over a course of time. The study did not assess
student learning via means of end of the term grade or self-report questionnaire to
determine the potential impact of students’ academic beliefs and behavior on their
academic performance. The study also did not take into account the changes that students
may undergo as they progress in the program. Without a longitudinal perspective on how
student beliefs and behaviors influence learning, the effects of academic beliefs and
behavior remain unexplained in terms of their potential impact on students learning.
76
Moreover, as a quantitative study, it lacked the detailed, qualitative comments which can
shed valuable light on the results of the quantitative analysis. For example, as follow-up
to the quantitative survey items, it would valuable to interview students about how
language factored into their decision to seek or not seek help.
Although the study had several limitations, the researcher could control several
factors such as how many students received the survey to ensure adequate sample size,
how the survey was administered, what topics the survey addressed and how the
questions were asked. To control how the questions were asked, the researcher carefully
developed the questions based on existing valid and reliable surveys and distributed the
same survey to all the participants. To encourage the participants to answer honestly, an
information sheet was attached explaining the confidentiality of the study between the
researcher and the participants. The factors the researcher controlled provided internal
and external validity as well as reliability by reducing the possible limitations of the study.
Conclusion
The purpose of this study was to assess openness to diversity, voluntary peer
collaboration, and help seeking beliefs and behaviors in online versus on-campus learning
settings among students in higher education. Specifically, the study examined a Masters
in TESOL program at LPU, a major urban city in Southern California. The study was
partly in response to the paucity of research examining the current state of online
education and its impact on student learning from the perspective of openness to diversity,
voluntary peer collaboration, and help seeking behaviors. The study found no statistical
differences in openness to diversity, voluntary peer collaboration, and help seeking
behaviors by program delivery methods.
77
Openness to diversity and the social academic behaviors of voluntary
collaboration and help seeking are not only important topics to be examined in the
context of emerging online education, but they are especially important in the context of
graduate programs that train future educators because they must be able to understand
and apply the personal and professional behaviors in their own learning to be able to
teach future students to do the same. As discussed, the implications of the findings are
significant and relevant to not only the field of online learning but also in the field of
graduate teacher education programs, as instructional designers and educational
practitioners alike may account for these critical factors in fostering an effective learning
environment.
78
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Appendix A
Demographic Questions
Q1 What is your gender?
! Male (1)
! Female (2)
! Other (Please specify) (3) ____________________
Q2 What is your age in years?
Q3 What is your current employment status?
! Not currently working (1)
! Working part-time (2)
! Working full-time (3)
Q4 What is your country of citizenship?
Q5 Please choose indicate your ethnicity
! Black or African American (1)
! Hispanic/Latino (2)
! Asian (3)
! Native Hawaiian/Pacific Islander (4)
! American Indian or Alaska Native (5)
! White (6)
! Two or more races (7)
! Other (Please specify) (8) ____________________
Q6 Please indicate your relationship status
! Single (1)
! Married/Domestic Partner (2)
! Separated/Divorced (3)
! Widowed (4)
Q7 I am currently enrolled as a
! Part-time student (currently enrolled in less than 12 units) (1)
! Full-time student (currently enrolled in 12 or more units) (2)
Q8 What is your major
! Undeclared (1)
! Please Specify (2)
92
Q9 What is the highest level of education either of your parents has completed?
! Primary school or less (1)
! Middle school (2)
! Some high school (3)
! High school (4)
! Associate Degree (5)
! Some college (6)
! Bachelor's Degree (7)
! Master's Degree (8)
! Doctoral Degree (9)
Q10 How many diversity or multicultural classes have you taken in higher education?
! 0 (1)
! 1 (2)
! 2 (3)
! 3+ (4)
Q11 Do you have a previous graduate degree?
! Yes (1)
! No (2)
Q12 How many online courses have you taken previously?
93
Appendix B
Openness to Diversity Measure
Q1 Indicate the degree to which you agree or disagree with the following statements.
Scale of 1-5: Strongly Disagree (1) – Disagree (2) – Neither Agree nor Disagree (3) –
Agree (4) – Strongly Agree (5)
1. I enjoy having discussions with people whose values and backgrounds are different
from my own.
2. The real value of education lies in being introduced to different values and
backgrounds.
3. I enjoy talking with people who have different values and backgrounds from mine
because it helps me understand myself and my values better.
4. Learning about people from different cultures is a very important part of my education.
5. I enjoy taking courses that challenge my beliefs and values.
6. The courses I enjoy the most are those that make me think about things from a
different perspective.
7. Contact with individuals whose background (e.g., race, national origin, sexual
orientation) is different from my own is an essential part of my education.
94
Appendix C
Voluntary Peer Collaboration Measure
Please answer the following questions in the context of your experience in this course.
Q1 Indicate the degree to which you agree or disagree with the following statements.
1. It is important to collaborate with my peers in this course.
2. I believe that teaching and learning from each other is important to succeed in this
course.
3. It is important to both give and receive peer feedback related to work in this course.
For the next two questions, think about your voluntary collaboration with your peers. By
voluntary collaboration, we mean collaborative activities that are NOT initiated or
facilitated by the instructor or required for the course or course assignments.
Q2 In what ways did you voluntarily collaborate in this course/program? (Check all that
apply)
" Not applicable (1)
" In Person (2)
" Via Phone or Text (3)
" Via Email or Discussion Board (4)
" Via Social Media (e.g., Facebook, Twitter, etc.) (5)
" Via Videoconferencing (e.g., Skype, Adobe Connect, etc.) (6)
" Other (please indicate below) (7) ____________________
Q3 On average, how often do you voluntarily collaborate with your peers in this course?
! Not at all (1)
! 1-2 times per semester (2)
! 1-2 times per month (3)
! 1-2 times per week (4)
! More than twice a week (5)
95
Appendix D
Help Seeking Measure
Q1 Indicate the degree to which you agree or disagree with the following statements.
1. Even if I have trouble learning the material in this class, it is important that I try to do
the work on my own, without help from anyone.
2. It is important to ask the instructor to clarify concepts I don't understand well.
3. If I don’t understand the material in this course, it is important that I ask another
student in this class for help.
4. It is important to identify students in this class whom I can ask for help if necessary.
5. If I were to seek help in this class, I would ask the teacher rather than another student.
6. I would prefer asking another student for help in this class rather than the instructor.
7. In this class, the teacher would be better to get help from than would a student.
Q2 During this class, how often did you seek help from:
Scale of 1-5: Not at all – 1-2 times per semester – 1-2 times per month – 1-2 times per
week – More than twice a week
1. Instructor/Teaching Assistant
2. Peer
3. Other
Abstract (if available)
Abstract
The overall growth in the demand for online education has greatly impacted institutions of higher education. The number of students taking at least one online course exceeds the growth of overall higher education enrollment, and online students now make up nearly 32% of the enrollment. Large institutions of higher education are particularly invested in online education as they educate 64% of all online students. This study examines the literature surrounding the growth of online education highlighting key findings on student learning and benefits and challenges of online education. In particular, the concepts of openness to diversity, voluntary peer collaboration, and help seeking are three measures studied in the current research. Comparing these three measures in online and face-to-face learning settings provides a valuable knowledge pertaining to online education contexts. ❧ The study results indicate that there is no statistically significant difference in the levels of student engagement between online and on-campus students. Where the study did yield statistically significant differences of voluntary peer collaboration and help seeking behaviors, the differences can be explained by the course delivery method. For example, on-campus students were more likely to collaborate in-person whereas online students were more likely to collaborate via videoconferencing. The implications of this study can be valuable in the field of education specifically focusing on teacher training for graduate program.
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Examining student beliefs and behaviors in online and on-campus courses: measuring openness to diversity, voluntary peer collaboration, and help seeking
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