Self-. Disclosure. (SD). Sharing personal information, expressing vulnerability or feelings ...... 109 120 (1.10) 153 (1.40) 186 (1.71) 459 (4.21) ...... Homewood, IL:.
SOCIAL PRESENCE: WHAT IS IT? HOW DO WE MEASURE IT? by Patrick Ryan Lowenthal B.A., Georgia State University, 1997 M.A., University of Colorado Boulder, 1999 M.A., University of Colorado Denver, 2003
A thesis submitted to the Faculty of the Graduate School of the University of Colorado Denver in partial fulfillment of the requirements for the degree of Doctor of Philosophy Educational Leadership and Innovation 2012
UMI Number: 3506428
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This thesis for the Doctor of Philosophy degree by Patrick Ryan Lowenthal has been approved for the Educational Leadership and Innovation by
Joanna C. Dunlap, Chair Joanna C. Dunlap, Advisor Rodney Muth Ellen Stevens Patti Shank
Date
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Lowenthal, Patrick Ryan (Ph.D., Educational Leadership and Innovation) Social Presence: What is it? How do we measure it? Thesis directed by Associate Professor Joanna C. Dunlap
Social presence theory is a central concept in online learning. Hundreds of studies have investigated social presence and online learning. However, despite the continued interest in social presence and online learning, many questions remain about the nature and development of social presence. Part of this might be due to the fact that the majority of past research has focused on students' perceptions of social presence rather than on how students actually establish their social presence in online learning environments. Using the Community of Inquiry Framework, this study explores how social presence manifests in a fully asynchronous online course in order to help instructional designers and faculty understand how to intentionally design opportunities for students to establish and maintain their social presence. This study employs a mixed-methods approach using word count, content analysis, and constant-comparison analysis to examine threaded discussions in a totally online graduate education course. The results of this study suggest that social presence is more complicated than previously imagined and that situational variables such as group size, instructional task, and previous relationships might influence how social presence is established and maintained in threaded discussions in a fully online course. The form and content of this abstract are approved. I recommend its publication. Approved: Joanna C. Dunlap
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DEDICATION I dedicate this thesis to the ladies of my life. First, I dedicate this to my mother. I would not be the person I am today if it was not for her. Second, I dedicate this to my wife, Alison, for (among other things) her unfaltering support and patience while I was avoiding completing this thesis. I could not have completed this without her love and support. Third, I dedicate this to my daughters, Jordan and Ashlyn. I hope they understand one day why Daddy spent so much time on the computer. And over time I hope they see me spend less time on the computer and more time with them. Last but not least, I dedicate this to the two greatest dogs in the world, Beezer and Nikita. They both supported me in their own way throughout this process over the years, and I miss them dearly now that they are gone.
.
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ACKNOWLEDGEMENT I want to thank my advisor, Joanna C. Dunlap, for her guidance, support, and patience over the years. Joni taught me how to be a scholar and has been a great colleague and friend. I look forward to continuing our relationship for years to come. I also want to thank Ellen Stevens for never giving up on me and always asking those tough questions over the years. I want to thank Rodney Muth for his unending support. I took my first EDLI course with Rod, I published my first article with Rod, and I finished my dissertation with Rod. I would also like to thank Marcia Muth for teaching me to be a writer when that was the last thing I thought I would ever become. And finally I would like to thank Patti Shank for her continued professional support over the years.
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TABLE OF CONTENTS FIGURES ............................................................................................................... xi TABLES .............................................................................................................. xiii CHAPTER 1. INTRODUCTION ...............................................................................................1 Background ..................................................................................................3 Social Presence Theory ....................................................................3 The Evolution of Social Presence Theory .......................................5 Limitation of Previous Studies.....................................................................6 Statement of the Problem .............................................................................9 Conceptual Framework ..............................................................................10 Goal of the Study .......................................................................................14 Overview of Methods ................................................................................16 Sample............................................................................................16 Data Analysis .................................................................................16 Reliability and Validity ..................................................................18 Significance of Study .................................................................................18 Limitations .................................................................................................19 Chapter Summary ......................................................................................19 2. LITERATURE REVIEW ..................................................................................21
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A Brief History of Social Presence Theory ...............................................21 Theoretical Foundations of Social Presence Theory .....................21 Intimacy .............................................................................22 Immediacy..........................................................................22 Influential and Related Research on Social Presence ....................23 Competing Theories of Social Presence Theory ........................................26 Cuelessness ....................................................................................26 Media Richness ..............................................................................27 Social Information Processing .......................................................28 Defining Social Presence ...........................................................................31 Measuring Social Presence ........................................................................33 Gunawardena’s Social Presence Scale...........................................34 Rourke et al.’s Social Presence Indicators .....................................35 Tu and The Social Presence and Privacy Questionnaire ...............37 Research on Social Presence ......................................................................40 Social Presence and Student Satisfaction ......................................40 Social Presence and Interaction .....................................................44 Social Presence and Student Learning ...........................................47 Establishing and Maintaining Social Presence ..........................................53 Some Gaps in the Literature ......................................................................57 Chapter Summary ......................................................................................60
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3. METHOD .........................................................................................................61 Research Question .....................................................................................61 Research Design.........................................................................................61 Sample........................................................................................................62 Sampling Scheme...........................................................................62 Sampling Design ............................................................................65 Data Collection ..........................................................................................67 Data Analysis .............................................................................................67 Word Count....................................................................................68 Content Analysis ............................................................................69 Constant Comparison Analysis ......................................................77 Reliability and Validity ..............................................................................79 Reliability.......................................................................................79 Validity ..........................................................................................80 Chapter Summary ......................................................................................81 4. RESULTS .........................................................................................................82 Word Count................................................................................................82 Content Analysis ........................................................................................87 Stage One: Social Presence Categories and Indicators Across All Threaded Discussions ....................................................................89
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Stage Two: Social Presence Categories and Indicators by Threaded Discussion ......................................................................................94 Stage Three: Social Presence Categories and Indicators by Students ........................................................................................101 Constant Comparison Analysis ................................................................106 Chapter Summary ....................................................................................111 5. DISCUSSION ..................................................................................................112 Key Findings ............................................................................................112 Group Size ...................................................................................114 Instructional Task.........................................................................116 Past Relationships ........................................................................119 One Size Does Not Fit All ...........................................................120 Limitations of Studying Social Presence .................................................121 Situational Variables of CMC......................................................122 Unit of Analysis ...........................................................................126 Problems with the Social Presence Indicators and Treating Them Equally .........................................................................................128 Problems with Measuring the Community of Inquiry .................130 Limitations of the Study...........................................................................132 Concluding Thoughts and Implications ...................................................133
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APPENDIX A. APPENDIX A .................................................................................................136 B. APPENDIX B .................................................................................................142 C. APPENDIX C .................................................................................................146 REFERENCES ................................................................................................................150
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LIST OF FIGURES Figure 1.1
Community of Inquiry Framework ........................................................................11
1.2
Visual Depiction of Initial Conceptual Framework of Social Presence Developed by Rourke et al., 2001a ..........................................................................................14
2.1
Communication Media and Information Richness Diagram .................................28
2.2
Timeline of Competing Theories of Social Presence Preceding the Development of the Community of Inquiry Framework..............................................................30
2.3
Continuum of Definitions of Social Presence........................................................33
3.1
Steps Followed to Complete Constant Comparison Analysis of Online Discussions ............................................................................................................78
4.1
Word Cloud of Word Count Results Without the Discussions Headings .............84
4.2
Frequency of Possible Social Presence Indicators Across the Three Major and Most Frequented Threaded Discussions .........................................................85
4.3
Stages of Disaggregation of Content Analysis Used to Explore Use of Social Presence Indicators in a Fully Online Asynchronous Course ................................88
4.4
A Visual Depiction of the Frequency of Each of the Three Social Presence Categories ..............................................................................................................90
4.5
Frequency of Social Presence Indicators Across All Threaded Discussions ............................................................................................................92
4.6
Social Presence Indicators Separated by Category ................................................93
4.7
Visual Depiction of the Average Social Presence Indicators Group by Category in Closed Threaded Discussions ................................................................................97
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4.8
Ranking of Social Presence Indicators Used By the Three Students with the Highest Overall Social Presence Per Post Average .............................................104
4.9
Disaggregation of Three Students with Highest Social Presence per Post Average ................................................................................................................106
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LIST OF TABLES Table 1.1 Categories and indicators of social presence ...............................................................12 1.2 Alignment of research questions to data analysis ........................................................18 2.1 Phases of social presence research ...............................................................................30 2.2
Example of social presence indicators ...................................................................36
2.3
Social presence dimension of the Community of Inquiry Questionnaire ..............39
2.4
Strategies to establish and develop social presence ...............................................53
2.5
Strategies to establish and maintain social presence..............................................55
3.1
Online descriptions ................................................................................................64
3.2
Threaded discussions raw data...............................................................................66
3.3
Overview of data analysis ......................................................................................68
3.4
Original social presence categories and example indicators..................................70
3.5
Rourke et al.’s categories and indicators of social presence ..................................71
3.6
Evolution of the indicators of social presence .......................................................72
3.7
Swan and Hughes et al. combined list of categories and indicators of social presence .......................................................................................................73
3.8
Coding sheet used for content analysis ..................................................................75
4.1
Top 20 words used across all threaded discussions ...............................................83
4.2
Top 20 words across project groups ......................................................................86
4.3
Top 20 words across pairs......................................................................................86
4.4
Top 20 words across reading groups .....................................................................87
4.5
Social presence frequency across all forums .........................................................91
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4.6
Social presence indicators ranking from highest to lowest frequency ...................92
4.7
Open vs. closed threaded discussions ....................................................................95
4.8
Average social presence indicators per post across open and closed threaded discussions .............................................................................................................96
4.9
Average social presence indicators across closed threaded discussions ................97
4.10
Ranking of average social presence indicators across closed threaded discussions98
4.11
Average social presence indicator per threaded discussion .................................100
4.12
Student’s use of social presence categories .........................................................102
4.13
Groups of codes resulting from the constant comparison analysis of reading Group E ................................................................................................................108
4.14
Groups of codes resulting from the constant comparison analysis of Pair 9 ....................................................................................................................110
5.1
Teaching presence categories and indicators .......................................................113
5.2
Instructor vs. student postings in small discussions.............................................117
5.3
Measuring social presence in a Community of Inquiry .......................................131
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CHAPTER 1 INTRODUCTION I can remember when I started teaching online. I was a full believer in online education. I had been teaching face-to-face courses and even taken a few courses online myself. I was excited to teach online. At the same time, I was scared. I was scared that somehow my personality, my classroom presence, my empathy, my ability to connect with my students—all things that I attributed to my success teaching face-to-face—would not translate to an online environment. I regularly meet faculty now who have similar fears. They fear that what they do in the classroom cannot translate to an online environment. Fears like these, though, are not restricted to faculty. I meet people all the time who make claims like, “I just can’t learn that way” or “I need to talk to people face-to-face” or “online learning is just not for me.” For some time, people have had the choice to avoid learning online if it was not their preferred way to learn. But the growth of online education (see Allen & Seaman, 2006, 2010), legislative trends that require students to learn online (Walters, 2011; Watson, 2006), and the blurring of boundaries between fully online and traditional faceto-face courses (Woo, McNeill, Preston, Green, & Phillips, 2008), suggest that in the near future faculty and students will no longer have the choice to avoid online education. Based on my research and experience, I contend that one’s success learning online—specifically in formal online education settings—begins and ends with one’s ability to communicate effectively online. In my experience, students who struggle communicating online (whether within a Learning Management System or using email) struggle learning online in formal online educational settings. Communicating online is
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simply different from communicating face-to-face (Suler, 2004). I am interested in these differences and how people—specifically faculty and students—take advantage of these differences in formal education settings. In other words, I am interested in how faculty and students leverage the strengths and minimize the limitations of a computer-mediated communication (CMC) medium when teaching and learning online. A supposed limitation of CMC and online education in general is that it is difficult to establish one’s presence as a “real” person and “connect” with others— generally called social presence (Kear, 2010). One reason people struggle learning online, I posit, is related to this concept of social presence or the lack there of. For instance, isolation and loneliness—which are in part due to a lack of presence—are often cited as reasons why students do not persist online (Ali & Leeds, 2010; Ludwig-Hardman & Dunlap, 2003). I have set forth to investigate the big question of how people establish their presence online by examining how people present themselves as real people in formal online education environments (which predominantly rely on asynchronous CMC). Ultimately, my hope is that my research can help others learn how to establish their social presence in formal online education environments. In the following pages of this chapter, I provide a formal rationale for and overview of this study by beginning with some background literature on social presence, addressing limitations of previous research, presenting my conceptual framework, and finally providing an overview of the methodology used for this study.
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Background In the late 1980s and early 1990s, researchers began to study the effects of computer-mediated communication (CMC) (Daft & Lengel, 1984, 1986; Rutter, 1984, 1987; Walther, 1996). Some concluded that CMC was inherently antisocial and impersonal (Walther, 1996; Walther, Anderson, & Park, 1994). While Hiltz and Turoff (1993), two early key researchers of CMC, acknowledged that interpersonal relationships might be fostered through CMC, early research suggested—and convinced others—that CMC was better at task-oriented communication than interpersonal communication (Walther & Parks, 2002). To make sense of findings like these, CMC researchers turned to theories like Cuelessness Theory (Rutter, 1984, 1987), Media Richness Theory (Daft & Lengel, 1984, 1986; Daft, Lengel, & Trevino, 1987), Social Information Processing Theory (Walther, 1996; Walther & Parks, 2002) and Social Presence Theory (Short, Williams, & Christie, 1976). Overtime, social presence theory appealed to more researchers of online learning (as is evidenced in the growing body of research on social presence and online learning). And today, social presence theory is the most often referenced theory explaining the social nature of CMC in online educational environments (Lowenthal, 2010). Social Presence Theory Short, Williams, and Christie (1976) originally developed the theory of social presence to explain the effect telecommunications media have on communication. They defined social presence as the degree of salience (i.e., quality or state of being there) between two communicators using a communication medium. They posited that communication media differ in their degree of social presence and that these differences
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play an important role in how people interact. They conceptualized social presence primarily as a quality of a communication medium that can determine the way that people interact and communicate. From their perspective, people perceive some media as having a higher degree of social presence (e.g., video) and other media as having a lower degree of social presence (e.g., audio) and still other media having even a lower degree of social presence (e.g., text). More importantly, Short et al. believed that a medium with a high degree of social presence is seen as being sociable, warm, and personal, whereas a medium with a low degree of social presence is seen as less personal. While people might want a less intimate or immediate communication medium from time to time (see Williams, 1975), formal education is a very social process that involves high interpersonal involvement. Past research, for example, has specifically stressed the importance of contact and cooperation between faculty and students (Chickering & Gamson, 1987). Thus, early on social presence theory appeared to have direct implications for educators in online environments. In the late eighties and early nineties, relying on this theory, researchers began concluding that CMC was inherently impersonal because the nonverbal and relational cues (common in face-to-face communication) are filtered out of CMC (Walther & Parks, 2002). Later though in the mid-nineties, researchers began to notice, even though CMC lacks nonverbal and relational cues, that it can still be very social and interpersonal (Gunawardena, 1995; Gunawardena & Zittle, 1997) and at times even hyperpersonal (Walther, 1996). Further, as researchers (Gunawardena, 1995; Tu, 2000) began examining the sociability of online education, they started questioning the degree to which the attributes of a communication medium—in this case the cues filtered out of
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CMC systems—determine how people socially interact (Danchak, Walther, & Swan, 2001; Gunawardena, 1995; Gunawardena & Zittle, 1997; Richardson & Swan, 2003; Tu, 2000). The Evolution of Social Presence Theory Researchers of online learning (e.g., Gunawardena, 1995; Gunawardena & Zittle, 1997; Tu, 2000) began questioning the theory of social presence developed by Short et al. (1976). These researchers argued, based on their experience and research, that participants in online asynchronous discussions, using text alone, are able to project their personalities into online discussions and create social presence. They found that online learners are able to present themselves as being “real” as well as “connect” with others when communicating in online learning environments by doing such things as using emoticons, telling stories, and even using humor (Rourke et al., 2001a; Swan, 2003). Thus, a user’s personal perceptions of social presence—which are influenced over time and with experience using a communication medium—and the behaviors one learns to use to make up for the cues that are filtered out matter just as much, if not more, than a medium’s supposed capabilities. This new line of research sparked a renewed interest in the sociability of online learning, social presence, and CMC as evidenced in the increased amount of literature focused on social presence. Given the research stream, social presence is now a central concept in online learning. For instance, social presence has been listed as a key component in theoretical frameworks for distance education (Akyol & Garrison, 2009; Benbunan-Fich, Hiltz, & Harasim, 2005; Vrasidas & Glass, 2002). Researchers have shown—to varying degrees— a relationship between social presence and student satisfaction (Gunawardena, 1995;
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Gunawardena & Zittle, 1997; Hostetter & Busch, 2006; Richardson & Swan, 2003; So & Brush, 2008), social presence and the development of a community of learners (Rourke, Anderson, Garrison, & Archer, 2001a; Rovai, 2002; Ryman, Hardham, Richardson, & Ross, 2009), and social presence and perceived learning (Caspi & Blau, 2008; Richardson & Swan, 2003). Just as earlier researchers of CMC (Kiesler, 1986; Kiesler, Siegel, McGuire, 1984) used social presence theory to explain why CMC was inherently impersonal, later researchers (Gunawardena, 1995; Tu, 2000) reconceptualized social presence theory—focusing less on the medium and more on how people adapted to the medium—to explain how CMC in online learning environments can be very personal and social. Limitations of Previous Studies Despite the intuitive appeal and overall popularity of social presence theory, research on social presence still suffers from a few problems. Early studies of social presence and CMC had contradictory findings (see Walther et al., 1994). For instance, studies conducted in laboratory settings tend to support cues-filtered-out perspectives that suggested that CMC was inherently anti-social (Connolly, Jessup, & Valacich, 1990; Hiemstra, 1982), whereas studies conducted in the field often did not (Walther, 1992; Walther et al., 1994; Weedman, 1991). Walther et al. (1994) explain that contradictory findings like these are likely due to the abbreviated time periods and unrealistic experimental settings researchers used to study CMC. In much the same way, later research on the sociability of online learning, social presence, and CMC suffers from a number of limitations. First, researchers of social presence cannot agree upon a single definition of social presence (Biocca & Harms,
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2002; Biocca, Harms, & Burgoon, 2003; Rettie, 2003; Lane, 2011; Tu, 2002b). Instead, researchers continue to redefine social presence (Lowenthal, 2010; Picciano, 2002). Second, the majority of research conducted on social presence has various conceptual or methodological limitations. For example, Gunawardena (1995; Gunawardena & Zittle, 1997), one of the foundational and most often cited researchers on social presence, primarily investigated learners’ feelings toward CMC as a medium of communication (e.g., asking students the degree to the which they agree to statements like “CMC is an excellent medium for social interaction”) rather than specifically asking about how people adapted the medium for social purposes. Other researchers studied social presence in hybrid courses (e.g., Hughes et al., 2007; Shea & Bidjerano, 2010; So & Brush, 2008), online courses that had face-to-face meetings at the beginning of the course (e.g., Tu, 2001; Wise et al., 2004), or non-traditional learning environments (e.g., 6-week. self-paced, faculty-directed courses consisting of a single student) (e.g., Wise, Chang, Duffy, & Del Valle, 2004). Each of these contexts would inevitably influence how one establishes his or her own social presence as well as how one perceived the social presence of others, but researchers (e.g., Richardson & Swan, 2003; Swan & Shih, 2005) have not explicitly acknowledged how these differences influence social presence. In addition, most researchers studying social presence (e.g., Arbaugh & Benbunan-fich, 2006; Garrison, Cleveland-Innes, & Fung, 2010; Gunawardena, 1995; Tu 2002a; Richardson & Swan, 2003) have used similar data-analysis techniques. The majority of research has relied either on content analysis or on self-report data (obtained through a questionnaire). Relying solely on one type of analysis can lead researchers to make interpretive errors about the underlying phenomenon they are studying (Leech &
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Onwuegbuzie, 2007). Studies of social presence might benefit from employing multiple or mixed methods (see Lowenthal & Leech, 2009). Third, foundational research on social presence is dated (Gunawardena, 1995; Gunawardena & Zittle, 1997; Rourke et al, 2001a; Tu, 2001, 2002a, 2002b). The majority of the foundational research on social presence is over five to ten years old, and during the past five years alone CMC and online learning have grown exponentially. CMC is no longer a fringe activity used by a select group of users (Smith, 2010); rather, CMC, issues of the digital divide aside, is commonplace. As people use the Internet and email to communicate with others more each day, it is logical to assume that they become more adept at communicating, becoming literate with this medium. This is not simply a case of supposed “digital natives” (i.e., those who have grown up with technology) using CMC differently than “digital immigrants” (i.e., those who are new to technology) (Brown, 2002; Prensky, 2001). Rather, it is an issue of how people learn to use any communication medium better over time: The cell phone is a perfect example with millions of users worldwide, from the slums of India to the penthouses of New York City—nearly everybody seems to have a cell phone these days. The increased amount of time spent online has led online users of all ages and all generations to adjust their perceptions, expectations, and day-to-day use of CMC. Just as research in the early 1990s (e.g., Gunawardena, 1995; Walther, 1992, 1994, 1996) began to call into question CMC research in the 1980s (i.e., Kiesler, 1986; Kiesler, Siegel, McGuire, 1984; Rutter, 1984, 1987), additional research on social presence might begin to question research conducted in the late 1990s and early 2000s (e.g., Gunawardena & Zittle, 1997; Rourke et al, 2001a; Tu, 2000). Researchers need to continue to study social
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presence, and at times even replicate previous studies (unfortunately rarely done), in order to ensure that current assumptions about social presence are still correct across various contexts. Finally, and most important, some research on social presence contradicts other research (see Lowenthal, 2010). For instance, some researchers have found that socialpresence behaviors used by online learners decrease over time (Rourke, Anderson, Garrison, & Archer, 2001a), while others have found that social presence behaviors do not decrease over time (Stacey, 2002). In addition, Picciano (2002) found a relationship between social presence and student learning, while Wise et al. (2004) did not. For all of these reasons, additional research on social presence in online learning environments is needed—and especially in asynchronous learning environments, the dominant form of online education (National Center for Education Statistics, 2008)—to help clarify what social presence is and its role in online learning. Statement of the Problem Despite the continued interest in social presence and CMC, many questions remain about the nature and development of social presence (Lowenthal & Dunlap, 2011; Swan & Shih, 2005; Rourke & Kanuka, 2009). In addition, some of what researchers and practitioners think they do know is questionable due to the limitations of past research. The majority of research on social presence (e.g., Gunawardena, 1995; Na Ubon & Kimble, 2003; Picciano, 2002; Richardson & Swan, 2003; Rourke & Anderson, 2002b; Russo & Campbell, 2004; Tu, 2002b; Wheeler, 2005; So & Brush, 2008) has focused on faculty and students perceptions of social presence. Fewer studies by comparison (e.g., Hughes, Ventura, & Dando, 2007; Lomicka & Lord, 2007; Rourke et al., 2001a; Swan,
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2002, 2003a) have actually studied observable indicators of social presence in online discussions. While it is important to understand perceptions of social presence, it is also important to study what students do and say online (Kramer, Oh, & Fussell, 2006). However, not enough studies do just this and the few studies that have done this have failed to describe adequately how social presence manifests itself in asynchronous online courses. Researchers (e.g., Hughes et al., 2007; Rourke et al., 2001a) have typically sampled only one part of a course and analyzed it with only one type of analysis, typically content analysis. As a result, I posit that both researchers and practitioners may have a very limited understanding of social presence. Given these reasons, I set forth to conduct a mixed methods exploratory study of social presence. I chose to do this in hopes of learning more about the observable indicators of social presence in online course discussions. Conceptual Framework Many researchers (Arbaugh, 2007; Delfino, & Manca, 2007; Lomicka & Lord, 2007; Nippard & Murphy, 2007; Rourke & Anderson, 2002a, 2002b; Swan et al., 2008) have argued for some time that the community of inquiry (CoI) framework is the most popular framework to study social presence. The CoI framework is a comprehensive guide (Garrison, Anderson, & Archer, 2000) for research on the practice of online learning (Garrison & Arbaugh, 2007). Garrison et al. (2000) argued that meaningful learning takes place in a CoI, comprised of teachers and students, through the interaction of three core elements: cognitive presence, social presence, and teaching presence (see Figure 1.1).
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Cognitive presence, the first element in the model, is “the extent to which the participants in. . . a community of inquiry are able to construct meaning through sustained communication” (Garrison et al., 2000, p. 89). Social presence, the second element in the model, is the “ability of participants in a community of inquiry to project their personal characteristics into the community, thereby presenting themselves to other participants as ‘real people’” (p. 89). Finally, teaching presence, the third element in the model, is the ability of a teacher or teachers to support and enhance social and cognitive presence through instructional management, building understanding, and direct instruction.
Social Presence
Cognitive Presence Educational Experience
Teaching Presence
Figure 1.1. Community of inquiry framework Garrison et al. (2000) initially developed three categories of social presence (i.e., Emotional Expression, Open Communication, and Group Cohesion). They later developed specific indicators of social presence (e.g., use of humor, continuing a thread, or the use of vocatives) (Rourke et al., 2001a) to help identify observable instances of social presence in CMC (see Table 1.1). They later renamed these categories (e.g.,
11
Emotional Expression was renamed Affective Responses) and tested the validity of the categories and indicators of social presence (Rourke et al., 2001a). Swan (2003) expanded the indicators even further, and then Hughes et al. (2007) later (though apparently unaware of Swan’s work) made some changes to Rourke et al.’s indicators as well. Despite the renaming of the categories and some minor changes to the social presence indicators (which are discussed in more detail in Chapters 2 and 3), Garrison et al.’s (2000) original categories and the later complete list of indicators (Rourke et al., 2001) of social presence have—for the most part—remained unchanged (see Table 1.1). Table 1.1 Categories and Indicators of Social Presence Category
Indicators
Definition of Indicators
Affective Responses
Expression of emotions
Conventional expressions of emotion, or unconventional expressions of emotion, includes repetitious punctuation, conspicuous capitalization, emoticons
Use of Humor
Teasing, cajoling, irony, understatements, sarcasm
Self-Disclosure
Presents details of life outside of class, or expresses vulnerability
Continuing a Thread
Using reply feature of software, rather than starting a new thread
Quoting from Other Messages
Using software features to quote others entire message or cutting and pasting sections of others’ messages
Referring explicitly to other messages
Direct references to contents of others’ posts
Asking questions
Students ask questions of other students or the moderator
Complimenting, expressing appreciation
Complimenting others or contents of others’ messages
Expressing agreement
Expressing agreement with others or content of others’ messages
(originally “Emotional Expression”)
Interactive Responses (originally “Open Communication”)
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Table 1.1 (con’t.) Cohesive Responses (originally “Group Cohesion”)
Vocatives
Addressing or referring to participants by name
Addresses or refers to the group using inclusive pronouns
Addresses the group as we, us, our, group
Phatics / Salutations
Communication that serves a purely social function; greetings, closures
Note. From “Assessing Social Presence in Asynchronous Text-based Computer Conferencing,” by L. Rourke, D. R. Garrison, and W. Archer, 2001a, in Journal of Distance Education, 14. Garrison, though, pointed out in 2008 that these indicators have not been revisited since their initial development and that they might need to be revised (Arbaugh et al., 2008)— which in many ways is a possible outcome of this study. Rourke et al. (2001a) were the first to test and validate the indicators of social presence. However, Garrison et al. (2000) and later Rourke et al. (2001a) did not clearly identify the relationship between the indicators of social presence. In other words, they left researchers wondering whether certain categories or indicators of social presence are better examples than others. When faced with the need to calculate a social presence score—from the frequency of indicators found in the coded transcripts of CMC—they decided to treat all indicators equally and simply sum the frequencies of all 12 indicators (Rourke et al., 2001a). This appeared to have been more of a pragmatic decision rather than a theoretical or empirical decision to find a way to create a social presence score from the indicators in order to quantify and compare transcripts of CMC. Rourke et al., 2001a though openly admitted their uncertainty about weighting all 12 indicators equally. Despite this admitted uncertainty, researchers have followed the same process in
13
developing a social presence score, though Hughes et al. (2007) was openly critical of this practice. Following the work of researchers like Rourke et al. (2001a), I conceptualize social presence as an additive process in which all categories and indicators of social presence are of equal importance (see Figure 1.2). However, like Hughes et al. (2007), I am skeptical of this conceptualization and hope that among other things my research will (by using multiple forms of analysis) help support or challenge the assumed additive nature of Rourke et al.’s conceptualization of social presence.
Affective
Cohesive
Interactive
of emotions • Use of Humor • Self-‐ Disclosure
• Vocatives • Use of Inclusive Pronouns • Phatics / Salutations
• Continuing a Thread • Quoting from Other Messages • Referring Explicitly to Other Messages • Asking Questions • Complimenting / Expressing Appreciation
Responses • Expression
+
+
Social Presence
=
Figure 1.2. Visual depiction of initial conceptual framework of social presence developed by Rourke et al., 2000a. Goal of the Study The goal of this study is to understand better how social presence manifests in threaded discussions in asynchronous online courses. However, all CMC is not the same (Herring, 2007). While researchers can generalize about CMC at some level, they should
14
recognize the situated and changing nature of social presence. Given this and to accomplish the goal of this study, I study social presence in an intentional, socially situated, specific context. Thus, the goal of this study is to explore the phenomenon known as social presence by investigating how it manifests during online discourse in an asynchronous online graduate education course. The following research question guides this exploratory study: How does social presence manifest in an asynchronous, online graduate-education course? This specific question was chosen because the majority of research on social presence has either relied solely on self-report data of faculty and student perceptions of social presence or has been confined to a monomethod approach—usually using content analysis—to analyze a few weeks of online threaded discussions. Both of these approaches fail to explore and describe how social presence manifests in threaded discussions over the length of a course. In other words, what are faculty and students actually doing to establish their social presence? The focus of this study, given this research question, is on developing a rich description of social presence by using multiple types of data analysis in order to help faculty and students have better experiences in online courses and to enable course designers to develop better online courses. Overview of Methods In the following paragraphs, I briefly describe the methods used for this study. I specifically focus on the sample, data analysis, reliability, and validity. Each of these topics is addressed in greater detail in Chapter 3.
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Sample A single, completely online graduate course in education was purposefully and conveniently sampled for this study. Thus, a non-random (non-probability) criterion sampling scheme was used in this study (Onwuegbuzie & Collins, 2007). A section of EDLI 7210 Educational Policy Making in a Democratic Society—which was taught online in the spring of 2007—was identified as an appropriate sample for this study. The course was a graduate-level online course in the School of Education and Human Development at the University of Colorado Denver delivered via eCollege. All of the threaded discussions in the eCollege course shell for this course were used for this study. The population of the course primarily consisted of graduate students completing coursework for an Educational Specialist (EdS) degree or a PhD. Many of the EdS students were also seeking their principal license. Nineteen graduate students were enrolled in the course. Data Analysis The majority of research on social presence has relied primarily on self-report survey data (e.g., Gunawardena, 1995; Richardson & Swan, 2003). While self-report survey measures are useful and have their place in educational research, as Kramer, Oh, and Fussell (2006) point out, they “are retroactive and insensitive to changes in presence over the course of an interaction [or semester]” (p. 1). In this study, rather than focus on students’ perceptions of presence (which I have done in other studies such as Lowenthal & Dunlap, 2011; Lowenthal, Lowenthal, & White, 2009), I focused instead on what was “said” in the online threaded discussions.
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I used a mixed-methods exploratory methodology (Miles & Huberman, 1994; Onwuegbuzie & Leech, 2005b) that employed both quantitative and qualitative methods to conduct this study. In order to explore social presence in a specific situated asynchronous learning environment in great detail, I analyzed the online threaded discussions (now archived in the discussion forums) using word count, content analysis, and constant comparison analysis (Leech & Onwuegbuzie, 2007). More specifically, multiple forms of data analysis were used to address the research question— How does social presence manifest in a graduate education asynchronous online course? (see Table 1.2 above for an illustration of this). First, I analyzed all of the discussions with word count (in conjunction with basic descriptive statistics of each forum) to identify which threaded discussion had a higher frequency of words and posts as well as which one’s had a higher number of social presence indicators (types of words). Second, I used content analysis to analyze every threaded discussion, using a modified version of the social presence indicators developed by Garrison et al. (2000) and later modified by Swan (2003) and Hughes et al. (2007). Based on the results of the word count and content analysis, I then selected two discussion threads—one with a high number of social presence indicators and one with a low number of social presence indicators—to analyze in more depth with a grounded theory constant comparison analysis technique.
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Table 1.2 Alignment of Research Questions to Data Analysis Research Question
Data Analysis
Type of Data
How does social presence manifest in a graduate education asynchronous online course?
•
Word Count (Quantitative)
•
All course discussions
•
Content Analysis (Quantitative)
•
All course discussions
•
Constant Comparative • Analysis (Qualitative)
One discussion threads with high social presence & one with low social presence
DD DDD Reliability and Validity
Reliability and validity are key considerations for any researcher. The most common method used to calculate interrater reliability is a percent agreement statistic (Rourke et al., 2001b). Two researchers (me and another researcher) coded the threaded discussions using content analysis. A percent agreement statistic was calculated using Holsti’s (1969) coefficient of reliability. A large component of establishing validity— which is often described as trustworthiness in qualitative literature—is developing a sound theoretical framework (Garrison, Cleveland-Innes, Koole, & Kappelman, 2006). I have established the validity of this study by working from Garrison et al.’s CoI framework. Further, the coding schemes I used for this study also came directly from the literature (Hughes et al., 2007; Rourke et al., 2001a; Swan, 2003). Significance of the Study Learning is a very human and social activity (Dunlap & Lowenthal, 2009b). Online learning environments, though, can feel isolating and impersonal. Given this, educators must find ways to make formal online learning environments more personal
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and less isolating not only to help students persist but also to increase engagement and satisfaction. To accomplish this, educators have focused on establishing social presence in online courses (Dunlap & Lowenthal, 2009b). The significance or educational value of this research lies in its ability to help researchers better identify and study instances of social presence as well as to help faculty who teach online better understand how they can identify and establish social presence by using specific indicators of social presence. Further, the results of this study can help instructional designers design and develop online courses that utilize specific instructional approaches to help students establish their social presence online. Limitations All studies suffer from some type of limitation. Perhaps the most obvious limitation is the time that has passed between when the course was offered and when I analyzed the data. Related to this limitation is my inability to check with students (whether through specific interviews or member checking) to verify whether or not what I found in the course discussions is actually what they intended. However, one of the main reasons to focus on the language students use is because students rarely clarify what they mean by a posting; rather, other students simply do their best to make sense of what they read. In other words, in my experience very little member checking occurs in a typical online discussion so this limitation might actually end up being a very realistic component to this study. Chapter Summary Researchers have been studying social presence in online learning environments for a number of years now (Lowenthal, 2009). However, research on social presence to
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date suffers from a host of problems—ranging from inconsistent and contradictory findings to strange sampling decisions. Part of the problem might be the methodological decisions made by researchers. Instead of using a monomethod approach like the majority of past research, I employed a mixed-methods approach to studying social presence, utilizing both quantitative and qualitative methods to investigate the complex nature of social presence. In addition, this study specifically focused on how social presence manifests during threaded discussions in asynchronous online courses. In Chapter 2, I present a review of the literature. In Chapter 3, I go over the methods used for this study. In Chapters 4 and 5 I present the results, discuss the findings, and provide recommendations for faculty and instructional designers as well as for future research on social presence.
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CHAPTER 2 LITERATURE REVIEW In the following chapter, I synthesize past research on social presence in general and specifically research on the community of inquiry (CoI) framework to provide a foundation and some background for my study. I begin by addressing the history of social presence theory. After that, I address some early competing theories of social presence and some differences in how researchers define and measure social presence. I then conclude this chapter by synthesizing some of the research conducted on the community of inquiry in general and social presence in particular and addressing some gaps in the literature. A Brief History of Social Presence Theory As mentioned in Chapter 1, Short, Williams, and Christie (1976) developed the initial theory of social presence in their book, The Social Psychology of Telecommunications. While this book often serves as the foundational text to understand the initial theory of social presence, it is important to look at the foundations of this theory as well as later research conducted by Short et al. to understand how the theory of social presence has evolved over the years. Theoretical Foundations of Social Presence Theory The collective work of Short et al. (1976) that is presented in The Social Psychology of Telecommunications as well the work Short, Williams, and Christie (e.g., Short, 1974; Christie & Kingan, 1977; Williams, 1975; Wilson & Williams, 1977) conducted individually or with other colleagues before and after their seminal text was influenced by the social psychology concepts of intimacy and immediacy. Short et al.
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openly acknowledge that their concept of social presence is related to these two concepts. Thus, each of these concepts is discussed in more detail in the following paragraphs. Intimacy. Argyle and Dean (1965) were the first to use the concept of intimacy to explain communication behavior. They developed a theory of intimacy and equilibrium to explain how people communicating with each other will adjust their behavior to maintain a sense of equilibrium. They explain that aspects of intimacy are governed by both approach and avoidance forces, and are kept in a condition of equilibrium for any two people…if this equilibrium is disturbed along one of its constituent dimensions, e.g., by increasing physical proximity, there will be compensatory changes along the other dimensions. (p. 304) According to Argle (1969), people establish intimacy in a number of ways when communicating, such as proximity, eye contact, smiling, and personal topics of conversation. Short et al. (1976) argue that the social presence of a communication medium also effects intimacy and therefore should be added to this list of ways that people establish intimacy. Immediacy. Wiener and Mehrabian (1968) developed the concept of immediacy. They conceptualized immediacy as the psychological distance people put between themselves and others when communicating. While Wiener and Mehrabian (1968) were initially focused on speech communication, Mehrabian (1972) later distinguished between three types of immediacy: verbal, nonverbal, and technological immediacy. Verbal immediacy describes how people use their choice of words to reduce or increase psychological distance between them and others. For example, the use of the words “let us” or “we” can create more immediacy between two people than simply using “you” or “I.”
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People also convey immediacy nonverbally through their dress, facial expressions, or physical proximity (Mehrabian, 1972). Finally, technological immediacy suggests that a medium of communication can convey immediacy. According to Mehrabian (1972), communicating face-to-face is more immediate than communicating with video; further, communicating with a video is more immediate than communicating by phone. While immediacy in general, and technological immediacy in particular, is similar to social presence, Short et al. (1976) argue that important differences exist. For instance, Short et al. argue that “for any given medium of communication (e.g., telephone) and situation (e.g., long-distance call), immediacy may vary even when social presence does not” (p. 73). While Short et al. (1976) claim that important differences are found between immediacy and social presence, the distinction is not very clear. Further, they spend only a few paragraphs addressing the similarities and differences between social presence, intimacy, and immediacy. Not surprisingly, subsequent researchers often fail to differentiate clearly between intimacy, immediacy and social presence; in fact, researchers often appear to use the terms immediacy and social presence synonymously (e.g., Gunawardena, 1995). Influential and Related Research on Social Presence Short et al. (1976) were all part of the Communications Studies Group at University College in London. The Communications Studies Group consisted of an estimated 30 people who conducted a number of experiments in the early 1970s on communication media (Pye & Williams, 1978). Interestingly, The Social Psychology of
23
Telecommunications appears to be the only joint publication by these three researchers. However, each of them published, as individuals or with other colleagues, a number of other studies on the effects of communication media (e.g., Short, 1974; Christie & Holloway, 1975; Christie & Kingan, 1977; Williams, 1975; Williams, 1977; Wilson & Williams, 1977). The majority of this research focused on comparing people’s attitudes toward different communication media (e.g., face-to-face, audio, video). The following paragraphs briefly summarize a few key findings from this early research that later influenced the development of and people’s understandings of social presence theory. The majority of this early research focused on the assumed importance of the visual channel of communication. Given the importance placed on the visual channel in previous literature, Short et al. (1976) and colleagues not surprisingly found that the visual channel of communication was an advantage of a communication medium and therefore highly important (Christie, 1974; Short, 1974; Williams, 1975). Christie (1974) reports from one study that visual media were judged more useful for complex group discussions, private conversations and non-private dyadic conversations. Thus, the presence of visual channel appears to be perceived as an important advantage of a communications medium. (p. 367) Additional research (Christie, 1974; Christie & Kingan, 1977; Williams, 1975), though, began to show that the importance of a communication medium depended largely on the task at hand. In fact, according to Christie (1974), “it is clearly misleading to conceptualize different media as lying along a single dimension of acceptability or usefulness. Their perceived usefulness varies according to the application considered” (p. 368). Williams (1975) argued that people might want a less intimate or immediate communication medium for certain tasks. For instance, Williams (1975) suggests “that
24
with tasks of very high intimacy—perhaps very embarrassing, personal or conflictual ones—the least immediate medium, the telephone, would lead to more favorable evaluations than either of the more immediate media” (p. 128). Further, their research showed that tasks that are low on interpersonal involvement but still cooperative in nature can easily be accomplished by audio or video conferencing (Williams, 1978a); however, tasks that require more interpersonal involvement “are sensitive to the substitution of telecommunications for face-to-face interaction” (p. 127). Other than the suggestions made by Williams (1978a), very little was written in these early articles about the role of the visual channel for instructional tasks. However, Williams (1978a) argued that “tele-education seems especially promising since educational activities are primarily for cooperative problem-solving and the transmission of information—activities which have been shown to be almost unaffected by the medium of communication used” (p. 129). Williams (1978a) went on to point out that our knowledge about the role of mediated communication is far from complete—as was our understanding of how people learned in the late 1970s. Later research conducted by Christie and Kingan (1977), showed, among other things, that while visual cues are helpful, they are not necessary for people to communicate effectively. In fact, physical presence (i.e., being close to someone physically) may be even more important for two people communicating than visual cues (i.e., seeing another person) (Williams, 1978b). Results like these began to call for a more complex explanation for the role of visual cues in the communication process. Williams (1978b) suggested that the answers might be found in the theory of social presence.
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Competing Theories of Social Presence The theory of social presence developed by Short et al. was only one of a number of theories used to explain the influence a communication medium can have on communication. The three most popular competing theories of social presence— especially during the 1980s—were Cuelessness Theory developed by Rutter (1984, 1987), Media Richness Theory developed by Daft and Lengel (1984, 1986; Daft, Lengel, & Trevino, 1987), and Social Information Processing Theory developed by Walther (1996; Walther & Parks, 2002). The first two theories (like Social Presence Theory) have been described as deficit models because they focus on the cues that are filtered out and idealize face-to-face communication as the gold standard (Thurlow, Lengel, & Tomic, 2004), whereas the third theory focuses not only on what is filtered out but what is gained through CMC. Each of these theories are addressed briefly in the following sections to illustrate the zeitgeist of the 1980s and early 1990s when researchers of online learning reinvented the theory of social presence developed by Short et al. Cuelessness Working from a similar theoretical framework, Rutter (1984, 1987; Rutter, Pennington, Dewey, & Swain, 1984; Kemp & Rutter, 1986) developed what he called the Cuelessness Model. Rutter was concerned with the over emphasis placed on the importance of eye-contact when two people were communicating. As a result, he and his colleagues (1984) set forth to challenge the intimacy model developed by Argyle and Dean (1965) and later Argyle and Cook (1976). Rutter and his colleagues argued that previous research had focused too much on looking and eye-gaze and not enough on the mutual gazing back and forth. Like Williams before, Rutter et al. (1986) found that what
26
mattered was visual access to the entire person rather than simply access to another’s eyes. They argued that it was the combined social cues—from vision and other senses— that mattered. The Cuelessness Model essentially claims that the fewer social cues, the greater the psychological distance between two communicators (Rutter et al., 1986). Further, the greater the psychological distance, the more communication turns to task-oriented depersonalized content (Kemp & Rutter, 1986; Rutter, 1984; Rutter et al., 1986). In fact, Rutter and colleagues (Rutter, 1989) found that the number of social cues (i.e., both visual and physical presence cues) decreased when comparing how people communicated in certain situations (e.g., closed-circuit television, curtain, and audio). Media Richness Another competing theory that emerged during the 1980s is the theory of Media Richness. Media Richness Theory was developed by Daft and Lengel (1984, 1986). Whereas Rutter and colleagues were aware of the work of Short et al., Daft and Lengel never seem to explicitly acknowledge the work of Short et al. Daft and Lengel (1984) were focused primarily on the information processing behaviors in organizations. Therefore, they were interested in a concept called information richness: Richness is defined as the potential information-carrying capacity of data. If the communication of an item of data, such as a wink, provides substantial new understanding, it would be considered rich. If the datum provides little understanding, it would be low in richness. (p. 196) They posited that a communication medium can determine the richness of information (Daft & Lengel, 1986). They argued that face-to-face communication had the highest richness and numeric communication (e.g., spreadsheet with numbers) the lowest; see Figure 2.1 for a complete list of media richness by media.
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Information Medium
Information Richness
Face-to-Face
Highest
Telephone
High
Written, Personal (bulletins, documents)
Moderate
Written, Formal (bulletins, documents)
Low
Numeric Formal (computer output)
Lowest
Figure 2.1. Communication media and information richness diagram Note. From “Information Richness: A New Approach to Managerial Behavior and Organizational Design,” by R. L. Daft and R. H. Lengel, 1984, in L. L. Cummings & B. M. Staw (Eds.), Research in Organizational Behavior (191-233). Homewood, IL: JAI. Social Information Processing The last of the three competing models is the Social Information Processing model developed by Walther (1992, 1994, 1996). Walther developed his model in response to the previous so-called “deficit” theories. Whereas previous researchers were interested in media effects across various communication media, Walther focused primarily on CMC. He criticized previous research, like that addressed earlier in this chapter, for a number of reasons. First, the majority of the early research was conducted in experimental settings that did not mirror how people communicate with different media in real life (1992). Second, these early studies and researchers assumed that the absence of visual cues led to an absence of sociability. Third, they assumed that taskoriented communication lacked relational and social communication. Finally, they failed to acknowledge that just as cues are filtered out, other cues are filtered into CMC and
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therefore CMC has some affordances that face-to-face communication does not (Walther, 1996; Walther & Parks, 2002). Walther (1992) argued that Humans’ social nature is the same in CMC and faceto-face environments. Given enough time, he believed that people will find ways to compensate for any cues that are filtered out in CMC. The social information processing model essentially posits that given enough time, CMC can be very personal and even hyperpersonal (Walther, 1992, 1996). Previous research tended to put time restrictions on how people communicated that Walther believed diminished the possibility of interpersonal and relational communication. Walther’s research on the other hand suggested that •
Previous interaction between communicators influenced how people communicated online;
•
The possibility of future interaction influenced the degree to which people socially interacted online;
•
The way users used emoticons influenced interpersonal communication online.
These competing theories help illustrate the way that thinking about a medium’s effect on communication—especially interpersonal and social communication—change over time. The research that began with the work of Gunawardena (1995; Gunawardena & Zittle, 1997)—which I refer to as the third phase of social presence research (see Table 2.1 and Figure 2.2)—was influenced by previous research and theories, especially that of Walther. Rather than conceptualizing social presence as Short et al. did, Gunawardena and those that followed her (like Garrison et al., 2000, whose work serves as the
29
conceptual framework for this study) began reconceptualizing social presence theory— focusing more on how people appropriate technology rather than simply on what a technology allows us to do. In fact, the work of Garrison et al. and the CoI really represent a fourth phase of research on social presence (see Table 2.1 and Figure 2.2). Table 2.1 Phases of Social Presence Research Phase
Period
Key Figures
Focus of Research
Phase 1
1970s
Short et al.
Focused on Telecommunications
Phase 2
1980s-early1990s
Rutter Daft & Lengel Kiesler Walther
Focused on CMC
Phase 3
1990 - 1999
Gunawardena Rourke et al. Tu
Focused on Online Learning
Phase 4
2000s - Present
Garrison et al. Karen Swan Peter Shea
Focused on Social Presence’s Role in establishing a community of inquiry in Online Learning
Figure 2.2. Timeline of competing theories of social presence preceding the development of the community of inquiry framework.
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Defining Social Presence Given the evolution of social presence theory, it is probably not surprising that there is not a clear, agreed upon, definition of social presence (Rettie, 2003; Tu, 2002b). In fact, nearly everyone who writes about social presence seems to define it just a little differently. Presence is a key theoretical construct used in a variety of disciplines besides communication and online learning—most notably virtual reality (see Biocca, 1997). In fact, Lombard and Ditton (1997) identified six interrelated but distinct ways that people understand “presence”: (a) presence as social richness, (b) presence as realism, (c) presence as transportation, (d) presence as immersion, (e) presence as social actor within medium, and (f) presence as medium as social actor. They even attempted to create one all encompassing definition of presence. According to Lombard and Ditto, the following definition takes into consideration all six ways presence is understood; presence is “the perceptual illusion of nonmediation” (presence explicated section). To date, though, their all encompassing definition has not been widely adopted by others. Biocca, Harms, and Burgoon (2003) also recognized the different ways researchers across different fields define presence. They attempted to create an all-encompassing definition of social presence as well; they defined social presence as simply a “‘sense of being with another’” (p. 456) whether that other is human or artificial. Despite attempts by Lombard and Ditto (1997) and Biocca et al. (2003) to develop some conceptual clarity when it comes to discussions of presence in general or social presence in particular, researchers of social presence and CMC in educational environments continue to redefine social presence (Picciano, 2002). Gunawardena (1995)
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defined social presence as “the degree to which a person is perceived as a ‘real person’ in mediated communication” (p. 151). Garrison et al. (2000), on the other hand, originally defined social presence “as the ability of participants in a community of inquiry to project themselves socially and emotionally, as ‘real’ people (i.e., their full personality), through the medium of communication being used” (p. 94). Tu and McIsaac (2002) define social presence as “the degree of feeling, perception, and reaction of being connected by CMC to another intellectual entity through a text-based encounter” (p. 140). Finally, Picciano (2002) defines social presence as “a student’s sense of being in and belonging in a course and the ability to interact with other students and an instructor” (p. 22). The differences in how researchers define social presence might seem minor but they are important (see Ice, Gibson, Boston, & Becher, 2011). For instance, Rourke et al. (2001) focus on students (or instructors) ability to project themselves as “real” whereas Picciano focuses more on students’ sense of belonging to a community. Issues of definition are important because the way researchers define social presence influences how they measure social presence and the conclusions they draw. Definitions of social presence, at least for researchers of social presence and online learning, tend to fall on a continuum (see Figure 2.3). At one end of the continuum, researchers tend to conceptualize social presence as the degree to which a person is perceived as being “real” and being “there.” These definitions tend to focus on whether someone is able to project himself or herself as being “real” in an online environment and whether others perceived this person as being there and being real. In fact, Williams (1978a) defined social presence in this way when he defined social
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presence as “the feeling of contact obtained. . .” across various communication media (p. 127). At the other end of the continuum, researchers tend to go beyond whether someone is perceived as being “present”—that is, simply “there” or “real”—instead focusing on whether there is an interpersonal emotional connection between communicators. It is important to note, though, that on this end of the continuum, there tends to be an assumption that the interpersonal and emotional connection that communicators establish when there is social presence is a positive connection. Finally, like most continuums, the majority of researchers find themselves somewhere in the middle—placing some emphasis on an emotional connection—rather than on the ends of the continuums. Sense that someone is real Sense that someone is there (present) No focus on emotion
Sense that someone is real Sense that someone is there (present) Emotional Connection
Figure 2.3. Continuum of Definitions of Social Presence Measuring Social Presence After all the theorizing, researchers need to be able to identify, measure, and test their theories about social presence. As researchers began to conceptualize social presence differently, rather than use techniques developed and utilized by past researchers—perhaps because of Walther’s critique of these techniques—they began to look for new ways to study social presence. Gunawardena (1995), Rourke et al. (2001), and Tu (2002b) have been three foundational researchers in developing ways to study
33
social presence. But just like in the mid-1970s—when researchers either studied social presence by observing user behavior or examining users attitudes (Christie, 1974)— researchers in the third and fourth wave of social presence research have tended to focus either on studying users’ attitudes or their behaviors online. For instance, Gunawardena and Tu focused primarily on studying users’ attitudes whereas Rourke et al. focused on studying users’ behaviors (though it is important to note that while Garrison early on focused on studying users’ behaviors with his colleagues Rourke et al., he later turned to studying students attitudes). Regardless of their focus, the work of each of these researchers has heavily influenced most of the studies on social presence and CMC during the past ten years. In the following paragraphs, I will address how each of these researchers studied social presence. Gunawardena’s Social Presence Scales Gunawardena (1995; Gunawardena & Zittle, 1997) conducted some of the earliest studies on social presence and CMC in an education setting. In her first article, Gunawardena (1995) reported on two different studies she conducted in the early 1990s. In the first study, she measured users’ perceptions of CMC using a survey. She had students rank 17 bi-polar scales on a 5-point likert-type scale (from negative to positive). For instance, she asked students whether CMC was more socialable or unsocialable or more warm or cold (see Table A1 in Appendix A for the complete list). The bi-polar scales she used focus on users’ perceptions of the medium more than the degree to which users perceive others as “real” or “there.”
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Gunawardena (1995) reports in the same article about a second study in which she qualitatively analyzed some data; however, she does not elaborate on what data she analyzed or how she analyzed the data that she reported. In a later article, Gunawardena and Zittle (1997) reported on additional data collected from an earlier sample. However, with this study, Gunawardena and Zittle created an instrument they called the Social Presence Scale (see Appendix A). The Social Presence Scale was similar to the previous scale used by Gunawardena, but instead of responding to bi-polar scales, students were asked to rank 14 questions on a scale of 1 to 5. For instance, one question asked students to rank on a scale of 1 to 5 to what degree they agree or disagree that CMC is an excellent medium for social interaction. The Social Presence Scale was tested for internal consistency (Alpha = .88) and appears to investigate the construct of social presence more directly than the previous scale. Rourke et al.’s Social Presence Indicators Unlike Gunawardena who measured social presence through a self-report questionnaire, Rourke et al. (2001) sought to measure social presence through analyzing online discussions. As touched on in Chapter 1, Rourke et al. identified three different categories of social presence: affective responses, interactive responses, and cohesive responses. They then developed twelve indicators that researchers could use to analyze transcripts of CMC (primarily through content analysis). An example of these indictors can be seen in Table 2.2 (see Appendix A for the complete list of indicators). Rourke et al. developed these categories and indicators based on their previous work (Garrison, Anderson, & Archer, 2000; Rourke, et al., 2001a), other literature in the field, and finally their experience reading online transcripts.
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Table 2.2 Example of Social Presence Indicators Category
Indicators
Definition of Indicators
Affective Responses
Expression of emotions
Conventional expressions of emotion, or unconventional expressions of emotion, includes repetitious punctuation, conspicuous capitalization, emoticons
Use of Humor
Teasing, cajoling, irony, understatements, sarcasm
Self-Disclosure
Presents details of life outside of class, or expresses vulnerability
Rourke et al. (2001a) tested and measured the “efficacy and reliability” of their categories and indicators by using them with participants in two graduate education online courses. One single week from each course was identified, and all of the discussion postings for those two weeks were analyzed. The first course had more than twice the number of postings and words as the second course; as a result, in order to compare the two, Rourke et al. (2001a) summed the raw number of instances and divided by the total number of words and then multiplied it by 1000 to come up with a social presence density score. They had high interrater reliability. Rourke et al. (2001a), though, cautioned readers about generalizing their results because their main purpose was to “develop and test the efficacy of a tool for analyzing the social presence component of educational computer conferences” (Discussion section) rather than to draw conclusions specifically about the samples in question. They also acknowledged that they were still unclear whether all 12 indicators should be weighted equally, as well as whether or not there was an optimal level of social presence. In fact, Garrison mentioned in a round table presentation at the 2008 annual meeting of
36
the American Educational Research Association (AERA) that these indicators might need to be revisited to ensure that they do not need to be revised (Arbaugh et al., 2008) Tu and The Social Presence and Privacy Questionnaire Tu (2002b) criticized early research on social presence (e.g., Short et al., 1976, and even Gunawardena’s 1995 study) in which researchers adopted the same semantic differential technique that simply had people respond to a bi-polar scale. Tu argued that this technique is not adequate to measure one’s perception of social presence when it comes to CMC. He also argued that the questionnaire used by Gunawardena and Zittle (1997) failed to take into consideration different variables cited in the research (e.g., recipients, topics, privacy, task, social relationships, communication styles). As a result, Tu (2002b) developed “The Social Presence and Privacy Questionnaire (SPPQ).”1 Tu developed the SPQQ by using parts of Steinfield’s (1986) CMC attitude instrument and Witmer’s (1997) work on privacy. Tu used a panel of five qualified content experts to test the content validity of the instrument. However, he did not elaborate on what made these content experts “qualified.” He then used 310 inservice and preservice teachers to test the construct validity. Five factors emerged from the factor analysis: social context, online communication, interactivity, system privacy, and feelings of privacy; these five factors accounted for 82.33% of the variance with Cronbach’s alpha values ranging from .74 to .85. Tu acknowledged that online privacy had a weak correlation and therefore might not need to be included as a dimension of social presence. However, he continued to use
1
In a different article, Tu (2002a) refers to the SPPQ as the CMC Questionnaire; however, he tends to refer to it more often as the SPPQ and therefore SPPQ will be used to refer to this instrument. 37
online privacy as a dimension of social presence in later studies (Tu & Corry, 2004; Tu & McIsaac, 2002). Despite the strengths of his survey, Tu and McIsaac (2002) later determined as the result of a mixed method study, using the SPPQ and a dramaturgy participant observation qualitative approach, “there were more variables that contribute to social presence” (p. 140) than previously thought. Therefore, Tu and McIsaac concluded that social presence was more complicated than past research suggested. Appendix A outlines the new variables identified by Tu and McIsaac. Specifically, they found that the social context played a larger role than previously thought. Among other things, the preceding literature illustrates what other researchers have pointed out—that there is still little agreement on how to measure social presence (Lin, 2004; Stein & Wanstreet, 2003). Just as Tu criticized how Gunawardena measured social presence, others have criticized and modified Tu’s work (Henninger & Viswanathan, 2004). Also, while social presence has been presented as a perceptual construct, Hostetter and Busch (2006) point out that relying solely on questionnaires (i.e., self-report data) can cause problems because “respondents may be providing socially desirable answers” (p. 9). Further, Kramer, Oh, and Fussell (2006) point out that selfreport data “are retroactive and insensitive to changes in presence over the course of an interaction [or semester]” (p. 1). But at the same time, even the scale created by Rourke et al. (2001a) has been modified by Swan (2003) and later by Hughes, Ventura, and Dando (2007) for use in their own research. During the past few years, researchers have focused less on studying social presence by itself—opting instead to study social presence as one aspect of a CoI. As a result and likely due to the difficulty of coding large samples, these researchers have
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focused almost predominantly on studying students attitudes toward the CoI as a whole and each of the components of the CoI (i.e., social presence, teaching presence, and cognitive presence). In 2008, a group of researchers came together to develop an instrument to study the community of inquiry, called the Community of Inquiry Questionnaire (see Arbaugh et al., 2008; Swan et al., 2008). Table 2.3 lists the part of the Community of Inquiry Questionnaire used to assess students’ perceptions of social presence in a CoI (see Appendix A for the entire instrument). Table 2.3 Social Presence Dimension of the Community of Inquiry Questionnaire Affective expression 14. Getting to know other course participants gave me a sense of belonging in the course. 15. I was able to form distinct impressions of some course participants. 16. Online or web-based communication is an excellent medium for social interaction. Open communication 17. I felt comfortable conversing through the online medium. 18. I felt comfortable participating in the course discussions. 19. I felt comfortable interacting with other course participants. Group cohesion 20. I felt comfortable disagreeing with other course participants while still maintaining a sense of trust. 21. I felt that my point of view was acknowledged by other course participants. 22. Online discussions help me to develop a sense of collaboration
Over five years ago and before the work of Arbaugh et al., Russo and Benson (2005) argued that researchers need “a multifaceted presence instrument, one that examines presence more than single items and addresses the construct more by evaluating specific behaviors rather than a global effect” (p. 60). And while Arbaugh et al. (2008) hope that the Community of Inquiry Questionnaire is a step in that direction, as a whole
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their survey and the research in which it is used for the most part focuses on looking at the CoI as a whole rather than at its parts (e.g., social presence). In the end, though, the instrument that researchers use largely influences what they find. Therefore, any study of social presence should at least acknowledge how its methodology has been influenced by these early pioneers. Despite the varied methodologies employed and some contradictions, some trends emerge when looking at the research on social presence. The following section focuses first on the results of some research on social presence and then on some recent research focused on social presence in a CoI. Research on Social Presence Despite the differences previously noted, researchers have identified a number of pedagogical implications—in most cases, benefits—of social presence. In the following sections, the literature on social presence is summarized and synthesized around three main themes: (a) social presence and student satisfaction, (b) social presence and interaction, and (c) social presence and student learning. Social Presence and Student Satisfaction Over the years, a number of researchers have shown that there is a consistent relationship between social presence and student satisfaction (Gunawardena, 1995; Gunawardena & Zittle, 1997; Hostetter & Busch, 2006; Richardson & Swan, 2003; So & Brush, 2008). While their conceptualization and methodology differ at times, most researchers agree that social presence is a predictor of student satisfaction in CMC environments, which in turn is a key component of online learning. More specifically, in online learning environments student satisfaction has been connected to student
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persistence (Levy, 2007; Willging & Johnson, 2004). Levy (2007) has shown that student satisfaction “is a major factor in students’ decision to complete or drop” online courses (p. 198). Therefore, given the importance of student satisfaction, the following section highlights a few of the main studies on social presence and student satisfaction. In the 1980s and early 1990s, a number of researchers began investigating social presence and computer-mediated communication (CMC) (e.g., Walther, 2002, 2004). However, Gunawardena (1995; Gunawardena & Zittle, 1997) is perhaps the earliest, most frequently cited, and foundational researcher of social presence and learning environments using CMC. Gunawardena conducted two studies with Globaled conference participants (Gunawardena, 1995; Gunawardena & Zittle, 1997). The studies consisted of graduate students from different universities who attended the Spring 1992 and Fall 1993 Globaled computer conferences via a listserv.2 The participants in the studies filled out questionnaires after they completed the conferences. Gunawardena (1995) reported that, contrary to popular opinion, CMC could be perceived as a social medium and that social presence could be cultivated. Further, she stated that, although CMC is described as a medium that is low in nonverbal cues and social context cues, participants in conferences create social presence by projecting their identities and building online communities. In order to encourage interaction and collaborative learning, it is important that moderators of computer conferences promote the creation of conducive learning environments. (p. 163) Gunawardena and Zittle (1997), working from data collected from participants in the Fall 1993 conference, later reported that social presence was a strong predictor of student 2
It is important to highlight that the majority of the students in these studies completed the online learning experience (i.e., the Globaled conference) as a component of a faceto-face course; further, they took part in the conference via a listserv rather than a course management system like Blackboard, WebCT, or eCollege. 41
satisfaction with computer conferences. They also found that students who felt a stronger sense of social presence enhanced their socio-emotional expression (e.g., through the use of emoticons) whereas those with a low sense of social presence did not. Gunawardena and Zittle concluded that social presence (and as a result student satisfaction) depends on what instructors and students do rather than simply the characteristic of a CMC medium. Despite shortcomings of their research (e.g., small sample size, sample selection, course format) as well as the fact that they caution readers not to generalize their results, the work of Gunawardena (1995) and Gunawardena and Zittle (1997) is regularly cited—and generalized—as foundational research on social presence and CMC. Research conducted by Richardson and Swan (2003) is arguably less foundational than the work of Gunawardena and Zittle but methodologically more sound. Richardson and Swan (2003) conducted a study to investigate the relationship between students’ perception of social presence, perceived learning, and satisfaction with their instruction. Their study consisted of 97 participants taking online courses at Empire State College, a site purposefully chosen because of its nontraditional online program. Almost half of the students in the sample stated that it was their first online course. Richardson and Swan developed a survey based on Gunawardena and Zittle’s (1997) survey and used a multiple regression to analyze the data collected from the survey. Richardson and Swan (2003) found three things from their study. First, they found that students with higher perceived social presence scores perceived they learned more than students with lower scores, thus indicating that there is “a relationship between students’ perceived social presence and students’ perceived learning” (p. 77). Second, they found a link between student satisfaction with their instructor and perceived
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learning—which researchers have been finding in face-to-face settings for years. Third, they found that students with high social presence scores “were highly satisfied with their instructor” (p. 73). However, it is important to note that they did not find a relationship between age or amount of college experience and social presence. Further, they concluded that online learners found the social presence of faculty and students to be an integral aspect of an online course. Other researchers (Hostetter & Busch, 2006; Russo & Benson, 2005; So & Brush, 2008) have found a relationship between social presence and student satisfaction in online learning environments as well. In fact, student satisfaction is the most consistent finding across all studies of social presence and CMC. However, like most findings on social presence, there always seems to be at least one study that contradicts the findings of others. For instance, Joo, Lim, & Kim (2011) recently sought to investigate the structural relationships between perceived level of presence, perceived usefulness and ease of online tools, and learner satisfaction and persistence at a South Korean online university (p. 1654). They administered two different surveys resulting in 709 responses. While they found teaching presence had a significant effect on both social presence and cognitive presence (which suggests how a course is designed and facilitated effects social presence), they also found that contrary to previous studies, social presence was not a significant predictor of satisfaction. Further research though is needed to see if this study is an outlier or if perhaps students’ perceptions of social presence and its relationship to satisfaction is changing. While student satisfaction does not equal student learning, it is a necessary component of a successful learning environment. Further, online learning has a history of
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having a higher dropout rate than face-to-face courses (Levy, 2007) as well as being characterized as involving more work than traditional face-to-face courses. Thus, it is imperative for online instructors to recognize the important role student satisfaction can play in online learning environments. If students are not satisfied, they will presumably not log-on to their online course and therefore will not successfully complete their online course or learn the required material. Another important component to student learning online is interaction. The following section will address the relationship between interaction and social presence. Social Presence and Interaction Interaction is a key component of any learning environment (Dunlap, Sobel, & Sands, 2007). Interaction and online learning has specifically received a great deal of attention over the years (Anderson, 2006; Anderson & Garrison, 1998; McIsaac, Blocher, Mahes, & Vrasidas, 1999; Moore, 1989; Moore & Kearsely, 2005; Vrasidas & Glass, 2002; Wagner, 1994). Interaction has been defined in a number of ways. According to Wagner (1994), interaction is simply “reciprocal events that require at least two objects and two actions. Interactions occur when these objects and events mutually influence one another” (p. 8). Interaction—that is, reciprocal events—can occur in many different forms in an online environment. Moore (1989) was the first to identify three main types of interaction in distance education: (a) learner-to-content interaction, (b) learner-to-instructor interaction, (c) and learner-to-learner interaction. Later researchers identified additional types of interaction found in online learning environments: (a) teacher-to-teacher, (b) teacher-to-content, (c) content-to-content, (d) learner-to-technology, and (e) teacher-to-technology (Anderson,
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2003, 2006; Anderson & Kuskis, 2007; Shank, 2004). Each of these is an important component of any online learning environment. Furthermore, each of these types of interaction can influence social presence. However, learner-to-instructor and learner-tolearner interaction are the most germane; of the two, learner-to-learner interaction has received the most attention. Researchers have shown that learner-to-learner interaction is a critical component in online learning (Richardson & Swan, 2003). Learner-to-learner interaction is motivating and stimulating for students (Moore & Kearsley, 2005). Further, social presence is directly related to learner-to-learner interaction (Tu, 2000). Students are perceived as being there as a result of their online interactions with their peers; if they do not interact with their peers and instructors, they are not perceived as being there or connecting with their peers or instructors. Therefore, in this section, I will summarize a few key studies about social presence and interaction. Tu and McIsaac (2002) conducted a mixed methods study with 43 graduate students in an online course. They found that social presence influences online interaction. More specifically, they found that social presence is necessary for social interaction. However, they also found that the quantity or frequency of participation online did not directly relate to social presence. That is, interacting more did not necessarily increase one’s social presence. Finally, they found that group size in synchronous discussions influenced how much students interacted with others online. As a result of their study, Tu and McIsaac (2002) argued that students need to establish trust “before attaining a higher level of social presence” (p. 142). They also found that informality helped increase social presence. But most importantly, they
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concluded that it is not the quantity but the quality of interactions online that make the difference. Like Tu and McIsaac, Swan and Shih (2005) also discovered some interesting relationships between social presence and interaction. The participants in their study came from four online graduate educational technology courses; 51 students completed an online questionnaire [based on Richardson and Swan’s (2003) previous survey that was based on the instrument developed by Gunawardena and Zittle]. After the survey was completed, the 5 students with the highest and the 5 students with the lowest social presence scores were identified, their postings were analyzed, and then they were interviewed. Content analysis was used to explore the discussion postings using the indicators developed by Rourke et al. (2001a). Like Tu and McIsaac (2002), Swan and Shih found that students who interacted more in the discussion forums were not necessarily perceived as having the most social presence; rather, students who were more socially orientated, even if they interacted less than others, were perceived as having greater social presence. Swan and Shih argued that this supports the idea that perceived presence is not directly linked to how much one participates online. Further, they found that students perceiving the most social presence of others were also the ones who successfully projected their own presence into the discussions. Swan and Shih concluded that students projected their presence online “by sharing something of themselves with their classmates, by viewing their class as a community, and by acknowledging and building on the responses of others” (p. 124), rather than simply posting more than others. Therefore, this research suggests that the quality of online postings matters more than the quantity when it comes to social
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presence. Finally, unlike earlier research (e.g., Richardson & Swan, 2003), Swan and Shih found that the age of participants did matter. More specifically, they found that younger students were more comfortable with online discussions than older students and that students over the age of 45 did not bond well with other (younger) students (p. 123). Even so, these differences could be due to the different samples; further, findings such as these are likely to diminish over time, as more and more people of all ages spend time online. It is very possible that the occurrence of contradictory findings, like these about age and social presence, arise because researchers have studied social presence in very different contexts, with very different course formats, and very different groups of students and instructors. Tu and McIsaac (2002) have already shown the important role social context plays in social presence. Therefore, while age might diminish as a significant variable over time, course format (e.g., hybrid vs. predominantly asynchronous vs. predominantly synchronous), length of term, subject of study, and students’ experience with online courses might continue to influence how social presence is perceived, maintained, and enhanced in online learning environments. Perhaps the most important research conducted on social presence has focused on student learning. But just like previous research, researchers studying social presence and student learning have found mixed and contradictory results. Social Presence and Student Learning Very few researchers have investigated the relationship of social presence and student learning. That is, of the over 100 studies conducted on social presence, less than a handful of studies have focused on student learning (Picciano, 2002; Wise et al., 2004)—
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and the majority that have only focused on perceived learning (e.g., Richardson & Swan, 2003). This is not, though, simply a trend restricted to research on social presence and online learning. Tallent-Runnels et al. (2006) have shown that generally speaking, “few studies actually focus on instruction and learning online” (p. 116). This is most likely due to the difficulty of measuring student learning (Fryshman, 2008). Because students are complex creatures with vastly different backgrounds and experiences, it is often difficult to determine what was learned specifically as the result of what happened in a given course. As a result, most researchers who do focus on student learning actually operationalize it as student performance on course assessments. This is true of Picciano (2002) and Wise et al. (2004), the two researchers who have studied social presence and student learning. Picciano (2002) was one of the first to investigate social presence and student learning. He was interested specifically in the relationship between social presence, student interaction and performance, and student perceptions of social presence and actual participation. Participants in Picciano’s study came from one completely online asynchronous graduate education course. The 23 participants in the study were teachers seeking a school administrator certification for the state of New York; they all had at least five years teaching experience and a MA (Picciano, 2002). Only eight of the 23 students had taken an online course before. It is also important to note that the World Trade Center was attacked during week two of this course; the attack on the World Trade Center had a great impact on people across the world—but especially in New York. Therefore, it is likely that the emotional distress felt by many Americans during this time
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could have impacted the results of this study and the social presence of the participants online. Picciano (2002) collected three different types of data. First, he calculated how often students participated in the course discussions. However, interestingly, he chose not to count “one line ‘me too’ postings and social messages” (p. 29); instead he wanted to focus on “substantive comments.” Given the importance “me too” postings and “social comments” can play in social presence, this decision likely skewed the results. He also administered a student satisfaction survey—questions coming from both the Inventory of Presence Questionnaire developed by the Presence Research Working Group and Tu’s Social Presence and Privacy Questionnaire (SPPQ). Then, finally, he collected scores from an exam and a written assignment. The exam was a multiple-choice exam designed to explore 13 issues the course focused on. The written assignment was a case study. Picciano created three groups—low, moderate, and high—of student interaction, and then three groups of social presence (based on the survey). He then calculated correlations of student interaction and the scores on the exam and the written assignment as well as social presence and the performance on the exam and the written assignment. Due to sample size, Picciano only used basic descriptive statistics (i.e., means and correlations) to analyze his data. Regarding student perceptions of interaction and learning, Picciano (2002) found that “there is a strong, positive relationship between student perceptions of their interaction in the course and their perceptions of the quality and quantity of their learning” (p. 28). Further, there was a positive relationship between student perceptions of interaction, social presence, and their performance. However, he found that perceived
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performance and actual performance differed. To investigate actual student interaction and performance, he found that actual student interaction had no relationship to the performance on the exam but did have a relationship to the written assignment for the highly interactive group. Finally, regarding social presence and performance, he found a positive statistical relationship between social presence and the written assignment (.5467) but not a positive statistically significant relationship between social presence and the performance on the exam (-.3570). Wise et al. (2004) also investigated student learning and social presence. Unlike Picciano (2002), Wise et al. used an experimental research design that looked at how social presence is related to learning in self-paced, one-to-one mentoring-supported, online courses. That is, rather than using one online course that relies heavily on student-to-student discussions, Wise et al. focused on self-paced online courses designed for teacher professional development. These were self-paced courses typically completed in a 12 week time period. However, participants in this study had to complete them in 6 weeks because it was an assignment for another course they were taking. Twenty students taking a graduate course called Elementary and Secondary School Curriculum took part in the study; half of the participants had teaching experience and half did not. The students with teaching experience were randomly assigned to either a high or low social presence condition; the students without teaching experience were evenly distributed among the conditions (Wise et al.). For each condition, two instructors were randomly assigned to five students (p. 255). The instructors had been trained on social presence cues—which included the indicators developed by Rourke et al. (2001);
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they varied the social presence cues they used based on the condition they were assigned to. The researchers physically went to students’ courses to solicit their participation. Students then completed a pre-assessment survey which focused on demographics and learning intentions. Then after the course was over, they had students complete a survey. They did not include the survey in their article, and they never explicitly said how the survey was constructed. They calculated message length as well as level of student social presence by analyzing student messages with a type of content analysis. Then the final assignment of the course—which was a lesson plan on integrating technology—was assessed by two raters using a rubric. They found that students in the high social presence condition replied with messages twice as long as those of students in the low social presence condition. Further, students in the high social presence condition tended to show a higher degree of social presence in the content of their messages to the instructors. However, Wise et al. did not find a statistically significant relationship between how students performed on the final assignment of the course and the social presence condition. Further, unlike previous studies, they did not find a significant effect between the condition and student satisfaction or the condition and perceived learning. These findings led Wise et al. (2004) to conclude the following: Social presence impacts the atmosphere of the course as indexed by the perceptions of the instructor and the nature of the interaction, but there is no identifiable effect on the overall impact of the course as indexed by learning or perceived learning, engagement, or satisfaction. (p. 262)
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While Wise et al. try to make sense of their results, they never acknowledge how certain issues—such as unique course format, limited time frame, lack of other students (to name just a few)—might have skewed their results. While Picciano (2002) and Wise et al. (2004) directly investigated social presence and student learning (which they operationalize as student performance on specific assignments), other researchers have investigated social presence and student perceived learning. For instance, as mentioned earlier, Richardson and Swan (2003) conducted a study in which they found that students who were identified with higher social presence perceived they learned more than those with lower social presence. They also found a relationship between student satisfaction with their instructor and perceived learning. Russo and Benson (2005) also found a statistically significant relationship between student perceptions of their own presence and the points they earned in a class. However, Hostetter and Busch (2006) did not find a relationship between students’ perception of presence and learning outcomes. Inconsistencies such as these, as well as those between Picciano and Wise et al., suggest that the findings on social presence and student learning are inconclusive. Despite previous researchers’ efforts like those just described, researchers such as Rourke and Kanuka (2009) have been critical of research on social presence and the CoI as a whole for not spending enough time showing whether or not teaching presence and social presence actually influence student learning. But despite some of the inconsistences reported so far, research suggests social presence plays an important role in online courses.
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Establishing and Maintaining Social Presence Despite some mixed results, social presence appears to be related to student satisfaction, student interaction online, students’ sense of community, as well as possibly student learning. Therefore, as the number of students taking courses online increases each year (Allen & Seaman, 2010), it is critical to better understand how social presence is established and maintained in online learning environments. The categories and indicators developed by Rourke et al. (2001a) and later expanded upon by Swan (2003) can be seen as guidelines for establishing social presence. For instance, if the expression of emotions, the use of humor, or self-disclosure are indicators of social presence, then it is reasonable to expect that if one expresses his or her emotions more, uses humor, and self-discloses information then he or she will be able to establish social presence. Further, research suggests (e.g., Wise et al., 2004) that social presence behaviors engender more social presence. Thus, indicators like those listed in Table 2.4 should then be seen as guidelines for establishing social presence. Table 2.4 Strategies to establish and develop social presence Categories
Indicators
Strategies
Affective
Emotions
Express emotions
Humor
Use humor
Self-disclosure
Self-disclose personal information
Value
Express personal values
Paralanguage
Use features of text, like emoticons to express emotion
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Table 2.4 (con’t.) Cohesive
Interactive
Greetings & salutations
Greet other students
Vocatives
Address students by name
Group reference
Use inclusive pronouns like “we,” and “us”
Social sharing
Share personal information
Self-reflection
Reflect on the course openly
Acknowledgement
Refer directly to others’ postings
Disagreement
Agree or disagree with others’ postings
Approval
Express approval
Invitation
Ask questions
Personal advice
Offer advice to peers
Note. From “Developing Social Presence in Online Course Discussions,” by K. Swan, 2003, in S. Naidu (Ed.), Learning and Teaching with Technology: Principles and Practices (pp. 147-164). London: Kogan Page. Synthesizing past literature (which included the work of Rourke et al.), Aragon (2003) identified a similar list of strategies on how to establish social presence. Aragon identified three components to establishing social presence online: (a) the role of course design, (b) the role of the instructor, and (c) the role of the participants (see Table 2.5). Aragon’s three components to establishing social presence are similar to the three types of presence—social presence, teaching presence, and cognitive presence—of the CoI framework developed by Garrison et al. (2000). Aragon’s strategies for instructors though are not simply what Garrison et al. would call “teaching presence” strategies in the CoI framework.
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Table 2.5 Strategies to Establish and Maintain Social Presence Course Design
Instructors
Participants
Develop welcome messages
Contribute to discussion boards
Contribute to discussion boards
Include student profiles
Promptly answer email
Promptly answer email
Incorporate audio
Provide frequent feedback
Strike up a conversation
Limit class size
Strike up a conversation
Share personal stories and experiences
Structure collaborative learning activities
Share personal stories & experiences
Use humor
Use humor
Use emoticons
Use emoticons
Use appropriate titles
Address students by name Allow students options for addressing the instructor Note. From “Creating Social Presence in Online Environments,” by S. R. Aragon, 2003, in, New Directions for Adult and Continuing Education, 100, (pp. 57-68). Certain strategies such as “sharing personal experiences and stories” are more of a type of social presence strategy used by instructors. This is important because the CoI traditionally does not differentiate between how a student and how an instructor establishes his or her social presence. Swan and Shih (2005) though pointed out that there are some differences between the two. And Nippard and Murphy (2007), who sought to investigate how teachers and students manifest social presence in synchronous web-based secondary classrooms, found that in their study students and instructors did in fact engage in different social presence behaviors.
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Some question whether there may be an optimal level of social presence (Garrison & Anderson, 2003; Wise et al., 2004). For instance, Garrison and Anderson posit that too little social presence can prevent a learning community from forming but too much social presence may reduce student learning by discouraging critical discourse (Garrison & Anderson, 2003). Conjectures such as these might suggest that while it might be important to focus on establishing social presence early in a course, it might be less important later on in the course. Dunlap and Lowenthal (2010), though, have argued based on their experience that it is important to continue to maintain social presence throughout the duration of an online course. Mixed results arise, though, on how social presence is maintained throughout the duration of a course. For instance, the research of Rourke et al. (2001a) suggests that purely social communication decreases over time. However, Stacey (2002) later found in her study that purely social communication did not decrease but actually increased over time; as a result, she concluded “that social relationships require continuation of social presence factors through a much longer period, as one semester is only the beginning of group formation online” (p. 150). But then to confuse matters even more, Swan (2003) later found that “although the use of affective indicators mirrored the general flow of the course discussions as the course progressed, cohesive indicators declined in importance, while the importance of interactive indicators increased” (pp. 161-162). This possibly suggests that different types of social presence behaviors serve different functions and vary across time. For instance, Lomicka and Lord (2007)—who studied how foreign language graduate students established and maintained social presence through weekly
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journal activities—found that the type of task influenced the type of presence used by students. Some Gaps in the Literature Despite the popularity of social presence research, a number of gaps in the literature remain. As researchers and practitioners continue to rely on theories and research on social presence to influence their practice, it is imperative to address some of these gaps. In the following section, I will briefly describe a few of these gaps that future research needs to address. First, as indicated throughout this chapter, previous researchers have found mixed and contradictory results. For instance, some studies have found a strong relationship between student satisfaction and social presence (Gunawardena, 1995; Gunawardena & Zittle, 1997; Richardson & Swan, 2003), but other studies have not (Joo, Lim, & Kim, 2011; Wise et al., 2004). Some studies have found a relationship between social presence and student performance (whether perceived or actual) (Picciano, 2002; Richardson & Swan, 2003; Russon & Benson, 2004) while others have not (Hostetter & Busch, 2006; Wise et al., 2004). Finally, some studies have found that social presence changes over time (Rourke et al., 2001a; Swan, 2003) while others have not (Lomicka & Lord, 2007; Stacey, 2002). Recently, Akyol, Vaughan, and Garrison (2011) sought to investigate how time effects the development of a CoI. They studied the CoI in a 6 week and a 13 week online course. They reported that an “independent samples t-test revealed statistically significant differences between the short and long-term courses on affective communication . . . and group cohesion” (Akyol et al., p. 235). More specifically and to their surprise—because conventional wisdom suggests that more time is needed to
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develop group cohesion—they found that students’ messages in the 6 week course included more group cohesion indicators than the students’ messages in the 13 week course. At the same time, there were more affective indicators in the 13 week course than the 6 week course. Second, conclusions are drawn and assumptions made about the nature of social presence from research conducted on vastly different types of online courses. For instance, researchers have failed to recognize how the socio-cultural context and course format effects social presence. For instance, researchers (e.g., Tu, 2001; Wise et al., 2004) have conducted a number of studies on social presence in which the teacher had face-to-face meetings with students; meetings like these will have likely impacted the development and perception of social presence. This is not to suggest that meeting faceto-face with online students is a poor decision, but rather that it can influence students’ perceptions and therefore should only be compared to other instances where faculty meet face-to-face with their students. In other cases, researchers have studied social presence in non-traditional courses. For instance, Gunawardena (1995; Gunawardena & Zittle, 1997) studied social presence in a computer conference administered through a listserv, Tu (2001; 2002a) studied social presence in face-to-face courses using CMC as well as televised courses, and Wise et al. (2004) studied social presence in six week self-paced courses. While it is important to understand how social presence is developed and maintained in these nontraditional types of online courses, it is even more important to recognize how social presence might change across a variety of different online learning formats and contexts. For instance, Lowenthal, Wilson, and Parrish (2009) have argued about the importance context plays in
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online learning. And both Arbaugh, Bangert, and Cleveland-Innes (2010) and Gorsky, Caspi, Antonovsky, Blau, and Mansur (2010) have recently found some interesting differences in students’ perceptions of the CoI across academic disciplines. Third, the only relationship found between social presence and actual student learning (as opposed to perceived student learning) comes from a study that was conducted in New York City during the attack on the World Trade Center (Picciano, 2002); there is reason to believe that a tragic event such as this could have skewed the results. Further, Picciano (2002) only found a statistical relationship with one of his measures of student learning and social presence. However, on the other hand—as already mentioned—a number of researchers (Picciano, 2002; Richardson & Swan, 2003; Russon & Benson, 2004) have found a relationship between social presence and perceived learning. Differences and issues like this illustrate that questions remain about the relationship of student learning—both actual and perceived—and social presence. Fourth, and finally, the majority of past research on social presence has heavily relied on survey data to study social presence. Studying students’ perceptions of social presence is important. However, relying only on self-report data can be problematic because students might be simply providing socially desirable answers (Hostetter & Busch, 2006, p. 9). Further, self-report data tend to be collected at one period during a semester and therefore cannot show change over time (Kramer, Oh, & Fussell, 2006). Unfortunately, though, compared to studies using only self-report data, few researchers (e.g., Delfino & Manca, 2007; Hughes et al., 2007; Rourke et al., 2001a; Swan, 2003) have actually analyzed online discussions when studying social presence. But if researchers want to understand better how social presence develops, is maintained, and
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changes over a course, they must begin to look at what is “said” and done in threaded discussions—the primary avenue for interaction. Chapter Summary Researchers and practitioners alike seem fascinated by the concept of social presence. I have found over a 100 articles on the subject. However, like most research on online learning (Bernard et al, 2004; Tallent-Runnels, 2006), research on social presence and online learning is of mixed quality. Even though initial research suggests that social presence is related to student satisfaction, student interaction, and student learning, many questions remain. In the next chapter, Chapter 3, I will outline the methods used for this study. Then in Chapter 4, I go over the results of the study and I conclude in Chapter 5 with a discussion of the results.
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CHAPTER 3 METHOD The purpose of this study is to explore the phenomena of social presence in an online graduate level education course at the University of Colorado Denver. To accomplish this, I utilized a mixed research methods approach that employed both quantitative and qualitative methods to understand better social presence. In the following chapter, I elaborate on the methods used for this study. Research Questions Research questions help narrow the focus of a study by providing a framework, setting boundaries, and giving rise to the type of data that will be collected (Cresswell & Plano Clark, 2007). The following research question guided this exploratory study: How does social presence manifest in an asynchronous, online graduate-education course? Research Design Mixed methods research has become popular over the past few years (Leech & Onwuegbuzie, 2006). Around the same time, researchers of CMC (e.g., Goldman, Crosby, Swan, & Shea, 2005; Gunawardena, Lowe, & Anderson, 1997; Hiltz & Arbaugh, 2003) began arguing about the importance of using multiple methods when studying the complexity of asynchronous learning environments. However, to date the majority of research on social presence has utilized either a quantitative or qualitative approach, which conceivably limits researchers interpretation of the data and understanding of the phenomenon. I utilized a mixed methods research design in this study. The purpose of using a mixed methods approach was to facilitate the richness of data and expand the
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interpretation of the findings (Collins, Onwuegbuzie, & Sutton, 2006; Onwuegbuzie & Leech, 2004), as well as to answer the research question that guided this study. Sample Researchers differentiate between sampling schemes and sampling designs (Onwuegbuzie & Collins, 2007; Onwuegbuzie & Leech, 2007b). Thus, I elaborate below on the sampling scheme and the sampling design used in this study. Sampling Scheme The goal of this study was to gain insights into a phenomenon (i.e., social presence) rather than to generalize findings to a population. In situations like these, Onwuegbuzie and Collins (2007) argue that a purposeful sample should be used. Therefore, a non-random (non-probability) criterion sampling scheme was used in this study. A section of EDLI 7210 Educational Policy Making for a Democratic Society— which was taught in the spring of 2007 at the University of Colorado Denver—was identified as an appropriate sample for this study. This course was selected for a number of reasons. First, this course was a fully online course. While it is helpful to study social presence in hybrid or televised courses, the focus of this study is on the nature of social presence in fully online courses. Second, this course was an asynchronous, instructorfacilitated, online course—the most popular type of online course in higher education. And third, this was an education course. Recognizing that CMC is always socially situated (Herring, 2004), the goal of this study was to study social presence in an education setting—like the majority of previous research on social presence (Lowenthal, Lowenthal, & White, 2009).
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Nineteen graduate students were enrolled in the course. The following course description describes the basic focus of the course: This course examines the role and impact of policy and policy processes in educational organizations. Models will be developed to analyze the nature of policy, how policy processes work, conceptualizations of and research on these, and their implications for improving educational practices to benefit student learning and other organizational behaviors and outcomes. The study of policy and policy processes will be facilitated by several activities that will familiarize you with various perspectives on, models of, and research about the initiation of policy issues, the processes of implementation and evaluation, and their outcomes and effects. Collaboration, group work, and research are emphasized. The learning objectives of the course are: 1. To read critically a variety of works on policy-making processes and outcomes 2. To develop skills as a policy analyst and advocate 3. To develop appreciation for and use of various policy models, policy research, and policy effects The following are the main assignments of the course (see Table 3.1 for a description of each assignment): •
Reading logs
•
A policy critique
•
An observation
•
A book review
•
A personal-professional task
•
A small-group project
•
Online interactivity and quality of work.
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Table 3.1 Assignment Descriptions Individual and Group Assignments Individual Assignments Policy Critique (8.47% 11.8% of course grade): Write a five page (or less) doublespaced paper assessing the goals (intended), trends, conditions, projections, alternatives relative to a local, regional, or state educational policy. Observation (8.47% 11.8% of course grade): First observe and analyze a policy process (school board meeting, city: council, state legislature, county commission). Then write a 2-3 page analysis of their observation. Book Review (8.47% 11.8% of course grade): Select a book related to policy studies and write a 3-5 page review. Online Interactivity and Quality of Work (16.95% of course grade): Login regularly, take part in threaded discussions, and produce quality work. Group Assignments Reading Logs (15.25% of course grade): Discuss readings in small groups Then write nine reading logs summarizing the readings and posing questions for the instructor. Personal-Professional Task (12.7% of course grade): In a group of two, take some risk and discuss deeply important individual personal-professional goals. Analyze trends that facilitate or impede each other’s goal achievement. Then write a 3-5 page paper summarizing his or her partner’s self analysis and plan. Small-Group Project (23.73% of course grade): Working in small groups of 4-5 students, study a policy at the local, state, or national level. Then write a 10-15 page double-spaced group paper employing a qualitative approach to collecting data that informs their critical analysis of the policy. In addition to the assignments, a number of different types of discussions were conducted in the course. The most active discussions were the “General Discussion Forum,” “Reading Groups,” “Reading Log Discussion Forum,” “Pairs,” and finally “Project Groups” (which everyone but the “General Discussion Forum” was directly tied to key assignments).
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Sampling Design Social presence researchers who study online course discussions historically only analyze a small sample of course discussions. For instance, Rourke et al. (2001a) only analyzed one week of discussions in two different courses in their foundational study, which consisted of 134 messages or 30,392 words. Swan (2003) analyzed 235 posts with an average number of words per posting at 82.4 (which she explained was 10% of the entire courses discussions). And then Hughes et al. (2007) analyzed three different groups of students with a total of 974 messages or 63,655 words. For this study, I chose to analyze every threaded discussion in the course using content analysis, which consisted of 1,822 posts or 160,091 words (see Table 3.2). Then based on the results of the content analysis, two specific threaded discussions (which span multiple weeks of the class) were identified—one with the highest social presence indicators (which was Pair 9) and one with the lowest social presence indicators (which was Reading Group E)—and analyzed using constant comparison analysis in an effort to explore better the phenomenon of social presence. It is important to note that for the purpose of this study, all discussion forums in the course are referred to as “threaded discussions”—regardless of their purpose, the level of dialogue, or the amount of interaction between the instructor and the students.
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Table 3.2 Threaded Discussions Raw Data* Discussion Name # of Participants # of Posts # of Words Virtual Office 7 44 2560 General—Syllabus 14 48 3294 General—Groups 6 14 639 General—Independent Work 3 3 155 General—Individual Work 2 2 84 Adult Learning Discussion Forum— 7 12 456 Your Learning Adult Learning Discussion Forum— 3 3 221 Questionnaire #1 A: Reading Group A 4 125 7828 B: Reading Group B 5 132 11677 C: Reading Group C 4 95 8452 D: Reading Group D 4 109 12562 E: Reading Group E 5 40 5235 F: Reading Group F 4 106 10916 G: Reading Group G 5 103 8116 Pair 1 3 32 2028 Pair 2 3 40 6222 Pair 3 3 45 3000 Pair 4+ 4 6 248 Pair 5 3 30 2232 Pair 6 3 28 1453 Pair 7 3 26 2687 Pair 8 3 21 3658 Pair 9 3 15 2909 Pair 10 2 22 2129 Plus Delta Week2 8 13 866 Plus Delta Week 3 8 22 2375 Plus Delta Week 4 2 2 299 Plus Delta Week 5 2 2 109 Plus Delta Week 6 3 3 234 Project Group 1 5 109 12673 Project Group 2 5 180 15322 Project Group 3 5 138 8404 Project Group 4 5 113 6791 Project Group 5 4 126 12380 Reading Log 1 5 12 1364 Reading Log 3 1 1 513 Total 156 1822 160,091 *Note. The discussion names were copied exactly as they were worded in the online course. If a discussion did not have any posts (e.g., Reading Log 2), it was not listed.
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Data Collection The data for this study were collected from the asynchronous threaded discussions from an online course taught in eCollege—a learning management system used at the University of Colorado Denver. While the course was taught in 2007, an archived copy of the course is stored in eCollege. Archived copies of course discussions, like these, “provide readily accessible records of the evolution of social relationships in online classes” (Goldman, Crosby, Swan, & Shea, 2005, p. 109). The course discussions were copied from eCollege to Microsoft Word; each discussion was saved as its own file. Student names were replaced with pseudonyms, and the files were imported into NVivo 8. Data Analysis Initially when researchers began studying online discussions, they focused on the frequency of participation (Henri, 1992). In fact, researchers have only relatively recently begun to move beyond the basics (e.g., frequency of student participation, the level of interaction, and message length) to focus instead on studying the content of messages online (Pena-Shaff & Nicholls, 2004). When researchers began focusing on analyzing the content of messages, they turned to content analysis (De Wever, Schellens, Valcke, & Keer, 2006). In this study, though, I used three types of analysis to analyze the data: (a) word count, (b) content analysis, and (c) constant comparison analysis (Leech & Onwuegbuzie, 2007; see Table 3.3).
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Table 3.3 Overview of Data Analysis Research Question: How does social presence manifest in a graduate education asynchronous online course? Data Analysis
Type of Data
Purpose of Results
•
Word Count (Quantitative)
•
All course discussions
•
Explore the frequency of top words used
•
Content Analysis (Quantitative)
•
All course discussions
•
Explore the presence and frequency of categories and indicators of social presence.
•
Constant Comparative Analysis (Qualitative)
•
One discussion thread with high social presence & one with low social presence
•
Identify codes, groups, and themes in the data missed by content analysis.
DD DDD Word Count Traditionally, word count involves identifying deductively a word or words from the literature on a subject or inductively identifying from the data specific words that seem out of place or hold special meaning and then counting the frequency of these words. For the purpose of this study, word count was used solely as a way to initially explore the data primarily by looking for the frequency of and more importantly the type of words used in the online discussions. NVivo 8 can quickly and efficiently calculate word counts. Word count is an effective initial way to analyze data by exploring the occurrence of words in a data set. The assumption with word counts, according to Leech and Onwuegbuzie (2007), “is that more important and significant words for the person will be used more often” (p. 568). However, it is important to acknowledge that word count has some limitations (e.g., it can decontextualize a word and its meaning) (Leech &
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Onwuegbuzie). Therefore, word count should not be used as the only method to analyze data. And for this study, it was used solely as an initial method to identify if certain types of words (e.g., student names or greetings and salutations which are indicators of social presence) were used more than others. Content Analysis In the social sciences, content analysis has been the leading method used by researchers to analyze text (Carley, 1993). Content analysis is understood and defined in a number of different ways. For instance, Berelson (1952) defined it as “a research technique for the objective, systematic, quantitative description of the manifest content of communication” (p. 519). But then Holsti (1969) defined it as “any technique for making inferences by objectively and systematically identifying specified characteristics of messages” (p. 14). Finally, Carley (1993) explains that “content analysis focuses on the frequency with which words or concepts occur in texts or across texts” (p. 81). Regardless of how one defines it, the purpose of content analysis “is to reveal information that is not situated at the surface of the transcripts” (De Wever, Schellens, Valcke, & Van Keer, 2006, p. 7). For this study, I followed the following five steps identified by Herring (2004): 1. The researcher formulates a research question and/or hypotheses 2. The researcher selects a sample 3. Categories are defined for coding 4. Coders are trained, code the content, and the reliability of their coding is checked 5. The data collected during the coding process are analyzed and interpreted.
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I turned to the literature at step number three to identify categories for coding. I first looked at the broad categories of the CoI framework developed by Garrison et al. (2000). Garrison et al. identified three categories of social presence—namely, emotional expression, open communication, and group cohesion. At that time, they only identified some possible examples of indicators for each category (see Table 3.4). I then referred to the work of Rourke et al. (2001a)3 in which Garrison and his colleagues more fully developed the categories and indicators of social presence. Table 3.4 Original Social Presence Categories and Example Indicators Element
Category
Examples of Indicators
Social Presence
Emotional Expression
Emotions
Open Communication
Risk-free expression
Group Cohesion
Encouraging collaboration
Rourke et al. changed the names of the categories from Emotional Expression to Affective Responses, Open Communication to Interactive Responses, and Group Cohesion to Cohesive Responses. They also identified specific indicators for each category of social presence as well as definitions of each indicator (see Table 3.5).
3
Please note that some uncertainty exists regarding the original date of Rourke et al.’s article entitled “Assessing Social Presence in Asynchronous Text-based Computer Conferencing.” I personally have a hard copy in which the publication is listed as 1999 and another as 2001. Researchers tend to cite it both ways. I contacted Liam Rourke to get some clarification but he simply replied that he was not sure but that he thought 2001 might be correct. I reference it as 2001 for the purpose of this study. 70
Table 3.5 Rourke et al.’s Categories and Indicators of Social Presence Category
Indicators
Definition of Indicators
Affective Responses
Expression of emotions
Conventional expressions of emotion, or unconventional expressions of emotion, includes repetitious punctuation, conspicuous capitalization, emoticons
Use of Humor
Teasing, cajoling, irony, understatements, sarcasm
Self-Disclosure
Presents details of life outside of class, or expresses vulnerability
Continuing a Thread
Using reply feature of software, rather than starting a new thread
Quoting from Other Messages
Using software features to quote others entire message or cutting and pasting sections of others’ messages
Referring explicitly to other messages
Direct references to contents of others’ posts
Asking questions
Students ask questions of other students or the moderator
Complimenting, expressing appreciation
Complimenting others or contents of others’ messages
Expressing agreement
Expressing agreement with others or content of others’ messages
Vocatives
Addressing or referring to participants by name
Addresses or refers to the group using inclusive pronouns
Addresses the group as we, us, our, group
Phatics/Salutations
Communication that serves a purely social function; greetings, closures
(originally “Emotional Expression”)
Interactive Responses (originally “Open Communication”)
Cohesive Responses (originally “Group Cohesion”)
Note. From “Assessing Social Presence in Asynchronous Text-based Computer Conferencing,” by L. Rourke, D. R. Garrison, and W. Archer, 2001a, in Journal of Distance Education, 14. Swan (2003), however, later made some changes to the list of indicators—namely Swan simplified the interactive indicators but elaborated on the affective indicators (see 71
Table 3.6). Finally, Hughes et al. (2007) replicated Rourke et al.’s (2001a) work but apparently were unaware of Swan’s previous study. They too made some changes to the indicators of social presence originally developed by Rourke et al. but some that were different than Swan. Faced with this evolution of social presence indicators (see Table 3.6), I decided to integrate the changes both Swan and Hughes et al. made to the social presence indicators (see Table 3.7). I used this initial combined list of indicators during the first training session with one of two coders. During the training sessions, it became apparent that the list of indicators needed to be amended. Table 3.6 Evolution of the Indicators of Social Presence Rourke et al. (2001a)
Swan (2003) Categories & Indicators
Hughes et al. (2007)
Affective Responses Expression of emotions Use of Humor Self-Disclosure
Affective Responses Paralanguage Emotion Value Humor Self-Disclosure
Affective Expression of emotion Use of Humor Self-Disclosure
Interactive Responses Continuing a Thread Quoting from Other Messages Referring explicitly to other messages Asking questions Complimenting, expressing appreciation Expressing agreement
Interactive Responses Acknowledgement Disagreement Approval Invitation Personal Advice
Interactive Referring to other’s messages Asking Questions Complimenting, expressing appreciation Expressing Agreement
Cohesive Responses Vocatives Addresses or refers to the group using inclusive pronouns Phatics / Salutations
Cohesive Responses Greetings & Salutations Vocatives Group Reference Social Sharing Self-reflection
Cohesive Vocatives Expresses group inclusivity Phatics / Salutations Embracing the Group
Categories & Indicators
Categories & Indicators
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Table 3.7 Swan & Hughes et al. Combined List of Categories and Indicators of Social Presence Category & Indicator Affective Responses Paralanguage
Emotion
Value Humor
Self-Disclosure
Interactive Responses Acknowledgement
Agreement / Disagreement Approval Invitation
Personal Advice Complimenting, expressing appreciation
Definition (Swan) Features of text outside formal syntax used to convey emotion (i.e., emoticons, exaggerated punctuation or spelling) Use of descriptive words that indicate feelings (i.e., love, sad, hate, silly); conventional or unconventional expression of emotions Expressing personal values, beliefs, and attitudes Use of humor—joking, teasing, cajoling, irony, sarcasm, understatement
Criteria (Hughes)
Refers directly to an emotion or an emoticon. Use of capitalization only if obviously intended
Only code if a clear indication that this is meant to be funny, e.g., extra punctuation or an emoticon
Sharing personal information, expressing vulnerability or feelings
An expression that may indicate an emotional state but does not directly refer to it. Uncertainty, non comprehension
Referring directly to the contents of others’ messages; quoting from others’ messages agreement Expressing agreement or disagreement with other’s messages Expressing approval, offering praise, encouragement Asking questions or otherwise inviting response. Students ask questions of each other or moderator Offering specific advice to classmates Complimenting, expressing appreciation
Explicit or implicit recognition that another message has been the motivation for this message Expressing agreement with each other or contents of messages
Complimenting or showing appreciation of each other or contents of messages
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Table 3.7 (con’t.) Cohesive Responses Greetings & Salutations / Phatics Vocatives Group Reference / inclusivity
Social Sharing
Self-reflection
Embracing the Group
Greetings, closures. Communication that serves a purely social function Addressing or referring to classmates by name Referring to the group as “we,” “us,” “our.” Addresses the group as a possessed or as a whole Sharing information unrelated to the course Reflection on the course itself, a kind of self-awareness of the group Revealing life outside the group
Any reference to the group with a possessive pronoun Not really about yourself but more of a social response
Any expression that lets the group know about the circumstance of the author but does not make author vulnerable
For instance, under the affective category, the indicator of value was eliminated because it was nearly impossible for two coders to reliably identify value. Further, given the content of the course, nearly every other discussion posting appeared to have a “I think” or “I feel. . . ” statement (which were the examples originally provided by Swan). Under the interactive responses, the indicators of approval and personal advice were eliminated. Approval was eliminated because of its overlap with complimenting/ expression appreciation and personal advice was difficult to identify thus complicating reliability. Finally, under the category of cohesive responses, social sharing and selfreflection were eliminated. Social sharing and embracing the group overlapped and self-
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reflection was difficult to identify. The following coding sheet in Table 3.8 was used for the content analysis. Table 3.8 Coding Sheet Used for Content Analysis Category & Indicator
Definition (Swan)
Criteria
Affective Responses Paralanguage Features of text (PL) outside formal syntax used to convey emotion (i.e., emoticons, exaggerated punctuation or spelling)
Examples
Someday……; How awful for you L; Mathcad is definitely NOT stand along software; Absolutely!!!!!
Emotion (EM)
Use of descriptive words that indicate feelings (i.e., love, sad, hate, silly); conventional or unconventional expression of emotions
Refers directly to an emotion or an emoticon. Use of capitalization only if obviously intended
When I make a spelling mistake, I look and feel stupid; I get chills when I think of . . . I am scared; This is fun; Sorry this is such a lame email; Hope you are OK; I am pleased that
Humor (H)
Use of humor— joking, teasing, cajoling, irony, sarcasm, understatement
Only code if a clear indication that this is meant to be funny, e.g., extra punctuation or an emoticon
God forbid leaving your house to go to the library I’m useless at computers but will this make me a bad nurse??? Ha Ha ; LOL
SelfDisclosure (SD)
Sharing personal information, expressing vulnerability or feelings
An expression that may indicate an emotional state but does not directly refer to it; Uncertainty, noncomprehension
I sound like an old lady; I am a closet writer; We had a similar problem. I’m not quite sure how to . . .; This is strange; I don’t understand how; I don’t’ know what that means; As usual I am uncertain; It’s all too much . . .; Website??? Help!!!!
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Table 3.8 (con’t.) Interactive Responses Acknowledgement Referring directly (AK) to the contents of others’ messages; quoting from others’ messages agreement; Reference to others’ posts Agreement / Disagreement (AG)
Expressing agreement or disagreement with others’ messages
Invitation (I)
Asking questions or otherwise inviting response. Students ask questions of each other or moderator
Expressing Appreciation (EA)
Showing appreciation of each other
Cohesive Responses Greetings & Salutations / Phatics (GS)
Vocatives (V)
Explicit or implicit recognition that another message has been the motivation for this message
Those ‘old machines’ sure were something; we won by a landslide – ‘landslide’ (next response)So what you’re saying is . . .; I thought that too . . . For me the question meant . . .;
Expressing agreement with each other or contents of messages
I’m with you on that; I agree; I think what you are saying is right. I think that would be a good plan; I think your suggestion is good Any suggestions?; Would you describe that for me, I am unfamiliar with the term. Does anybody know . . .?
Showing appreciation or approval of each other or contents of messages or complimenting
You make a good point; Right on; Good luck as you continue to learn I like your briefing paper . . .; It was really good;
Greetings, closures. Communication that serves a purely social function
Hi Mary; That’s it for now, Tom Hi; Hey; Bye for now;
Addressing or referring to classmates by name
You know, Tamara, . . .; I totally agree with you Katherine Sally said that . . .
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Table 3.8 (con’t.) Cohesive Responses (con’t.) Group Referring to the Reference / group as ‘we’, inclusivity ‘us’, ‘our’. (GR) Addresses the group as a possessed or as a whole Embracing the Group (EG)
Revealing life outside the group that is not emotional or expressing vulnerability or feelings. Also that isn’t related to the course
Any reference to the group with a possessive pronoun
We need to be educated; Our use of the Internet may not be free. We need some ground rules; The task asks us to . . .
Any expression that lets the group know about the circumstance of the author
The kids are asleep now; I’m a physiotherapist; It’s raining again; It’s 4am—I’m off to bed;
Constant Comparison Analysis Constant comparison analysis was the final type of analysis conducted on the threaded discussions. Constant comparison analysis—a specific type of comparative analysis—is a general method used in social science research that traces back to the work of Glaser and Strauss and their development of grounded theory (1967). While researchers like Krathwohl (2004) and Creswell (1998, 2008) approach constant comparison analysis from only a grounded theory perspective, it is not restricted to a grounded theory or inductive approach (Leech & Onwuegbuzie, 2007). Leech and Onwuegbuzie (2007) explain that constant comparison analysis can be conducted inductively, deductively, or abductively. Constant comparison analysis is useful when trying to explore and understand the big picture of a phenomenon (e.g., social presence). In fact, it is one of the most commonly used types of qualitative analysis (Leech & Onwuegbuzie, 2007). However, 77
researchers of CMC rarely use it to analyze online course discussions, most likely due to the time involved to conduct this type of analysis. It was used in this study to dig more deeply into the threaded discussions to understand better the nature of social presence. To conduct constant comparison analysis, I read the entire threaded discussion and partitioned each meaningful unit into small chunks. I then labeled each chunk with a code while constantly comparing new codes with previous ones. I then grouped the codes together. Once I grouped the codes together, I identified themes that emerged from the data. Figure 3.1 outlines the steps I took with examples from a previous study I conducted. Step 1. Read the discussion post Hello everyone! I love the educational environments you have created this week. Educators and students should always be the ones who create our schools. It is inspirational to see so many of you create from the schools you have been in or are currently in. Thanks for your creativity! Dr. Deb C.
Step 2. Chunk the discussion post into meaningful units [Hello everyone!] [I love the educational environments you have created this week.] [Educators and students should always be the ones who create our schools.] [It is inspirational to see so many of you create from the schools you have been in or are currently in.] [Thanks for your creativity!] [Dr. Deb C]
Step 3. Code each meaningful unit while constantly comparing new codes with previous codes [Hello everyone!] GREETING [I love the educational environments you have created this week.] POSITIVE FEEDBACK [Educators and students should always be the ones who create our schools.] ELABORATION / CLARIFICATION [It is inspirational to see so many of you create from the schools you have been in or are currently in.] POSITIVE FEEDBACK [Thanks for your creativity!] POSITIVE FEEDBACK [Dr. Deb C] CLOSING REMARK
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Step 4. Make a list of the codes and group the codes Codes Closing remark Directions Positive feedback Greeting Questioning Answering question Elaboration / clarification Writing style Resource Number of students Inclusive language Teacher request Colorado law Faculty seeking feedback Empathy Welcoming Negotiation Accommodation Contact information
Grouping of codes Course logistics Directions Writing style Number of students Teacher request Colorado law Greetings and Salutations Welcoming Greeting Closing remark Teaching / Facilitation Questioning Answering questions Elaboration / clarification Positive feedback Resource
Step 5. Identify themes that emerge from the data (include specific language from the groups, codes, or data when appropriate) While RTEOF have to deal with day to day course logistics, such as directions on how to complete assignments and course expectations, they play more of a role of as a facilitator through the use of questioning, elaborating/clarifying, and giving positive feedback than as a instructor or giver of knowledge.
Figure 3.1. Steps followed to complete constant comparison analysis of online discussions Reliability and Validity Reliability and validity are key considerations for any researcher. These two concepts are intricately connected (Cresswell, 2008). Issues of reliability and validity are addressed in the following pages. Reliability Reliability is essentially the consistency of scores researchers obtain from a measure (Goodwin, 2001). More specifically, according to Goodwin, “interrater agreement and reliability is the extent to which scores obtained from two or more raters
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(scorers, judges, observers) are consistent” (p. 15). The most common method used to calculate interrater reliability is a percent agreement statistic (Rourke et al., 2001b). I selected ten percent of the discussions to assess interrater reliability. Two coders (i.e., me and another researcher) chunked and coded the discussions using content analysis. One challenge though with interrater reliability is that there is not a consistent agreed upon level of what must be achieved (Rourke, Anderson, Garrison, & Archer, 2001b). Past research on social presence (e.g., Rourke et al., 2001a; Swan, 2003) was used as a guide of where interrater reliability should lie. Following Rourke et al. and Swan, the entire discussion posting was used as the unit of analysis. As a result, 100% agreement was found between the two coders when identifying the chunks to code because the learning management system clearly identified an entire post. After some initial training, the two raters then coded 10% of the discussions to establish reliability of coding. A percent agreement statistic was calculated using Holsti’s (1969) coefficient of reliability for each of the threaded discussions: •
Reading Group G: 80%
•
Pair 6: 78%
•
Project Group 3: 77%
The overall percent agreement for all of the discussion was 78%, which is an acceptable level of agreement given past research (Garrison, Anderson, & Archer, 2001; Hughes et al., 2007). Validity Validity is a complex concept. Validity has been defined as the “trustworthiness of inferences drawn from data” (Eisenhart & Howe, 1992, p. 644). However, over the
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years, researchers’ understanding of validity—and therefore definitions and standards— has evolved (Dellinger & Leech, 2007; Goodwin & Leech, 2003). Further, quantitative and qualitative researchers tend to understand and deal with validity differently (Cresswell & Plano Clark, 2007; Dellinger & Leech, 2007). Historically, quantitative researchers separate validity into content, criterionrelated, and construct validity. Qualitative researchers, on the other hand, historically describe validity as trustworthiness. A large component of establishing trustworthiness is developing a sound theoretical framework (Garrison, Cleveland-Innes, Koole, & Kappelman, 2006, p. 2), as I have tried to do throughout this study. Further, the coding schemes that were used for this study are based directly in the literature. Chapter Summary Researchers have studied social presence in online learning environments for a number of years now. However, to date, research on social presence suffers from a host of problems—ranging from inconsistent and contradictory findings to strange sampling decisions. Further, researchers have not been able to demonstrate a consistent relationship between student learning and social presence. Part of the problem might be the methodological decisions that researchers have made. Rather than employ a monomethod approach like the majority of past research, this study employed a mixed methods approach to studying social presence—utilizing both quantitative and qualitative methods to understand the complex nature of social presence. In addition, in this study I specifically focused on how students establish and maintain social presence in a textbased environment by focusing on what is “said” in the threaded discussions.
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CHAPTER 4 RESULTS As described in Chapter 3, I used a mixed methods research approach to explore how social presence manifests in an online graduate level education course at the University of Colorado Denver. More specifically, I was interested in finding out how users established their social presence through text alone in asynchronous threaded discussions. In this chapter, I share the results from the word count, content analysis, and constant comparison analysis I conducted to explore how online learners establish and maintain their presence in one specific fully online course. Word Count I conducted a word count of the threaded discussions to initially explore the data. I was curious whether certain types of words appeared more frequently than others across all of the threaded discussions as well as within certain types of threaded discussions as opposed to others. For example, did certain words appear more in threaded discussions with a pair of students vs. threaded discussions with small groups of students? Using Nvivo 8, I specified the parameters for a word count frequency report. I first looked at the top 50 words used across all of the threaded discussions (see Appendix B for a complete list of word count frequency’s for each word count conducted). While I set forth to investigate the top 50 words used across all threaded discussions, I found that the top 20 words were sufficient to get a basic understanding of the data. Thus, I only report on the top 20 words in this section (though I have included the top 50 results in Appendix B).
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Table 4.1 lists the top 20 words used across all of the threaded discussions (see Figure 4.1 for a visual representation). The word “I” was used most frequently (4,858 times which represents 4.13% of all the words used) followed next by the word “you” (2,186 times; 1.86% of all the words used). The frequency of these words is not that surprising but the fact that “we” (which is often used as a sign of group reference and therefore an indicator of social presence) was used 1,367 times (or 1.16% of all words used) and ranks fourth overall in all words used is noteworthy. Some other things of interest are the fact that “your” which can often be an example of “acknowledgement” (i.e., another indicator of social presence) was used 810 times or eighth overall. And finally, the word “policy”—which is the focus of the course—was used 600 times (or 10th overall) whereas the instructor’s pseudonym, “Bob,” was used 566 times (or 14th overall). Table 4.1 Top 20 Words Used Across All Threaded Discussions Rank 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20
Word I you have we my what do your can policy me all about bob so Instructor Think Our Work Would
Count 4858 2186 1428 1367 1001 948 814 810 730 600 595 592 574 566 565 564 553 538 494 482
Percentage (%) 4.13 1.86 1.21 1.16 0.85 0.81 0.69 0.69 0.62 0.51 0.51 0.50 0.49 0.48 0.48 0.48 0.47 0.46 0.42 0.41 83
Figure 4.1. Word cloud of word count results without the discussion headings. After looking at the frequency of the top 50 words used across all threaded discussions, I then ran a word count report for each of the main threaded discussions: Project Groups (see Table 4.2), Pairs (see Table 4.3), and Reading Groups (see Table 4.4). While “I” and “you” were still the first and second most used words in each of the main threaded discussions, Figure 4.1 illustrates that “we” and “your” (two possible social presence indicators) show up in the top 20 across all three of these threaded discussions and “our” (which is also a possible social presence indicator) shows up across two of the threaded discussions—namely, the Project Groups and the Pairs threaded discussions. Each of these words according to the coding sheet (which was discussed in Chapter 3) and the literature in general (see Chapter 2) are possible indicators of group reference and acknowledgement and therefore considered to be indicators of social presence. I mention “possible” because in this case word count does not take into consideration the context in which a given word is used; for instance, “we” could be referring to “we Americans” or “we the class.” 84
However, I found it interesting, though not necessarily surprising, that the word “we” and to a smaller degree “our” (i.e., group reference) show up more in specific types of small-group discussions where the purpose of the discussion is on collaborating on a class project together as compared to reading groups (which are also small-group threaded discussions but one with a different purpose). This suggests that the purpose of a threaded discussion might influence the degree to which its participants employ certain types of behaviors (i.e., the things referred to later in this chapter as indicators of social presence) to establish and maintain their social presence. Once I had a basic feel for the data, I then conducted a content analysis, which I elaborate on in the next section.
Project Groups
Pairs
Reading Groups
Rank
Word
Count
%
Word
Count
Word
Count
%
1
I
1674
4.08
I
960
4.87
%
I
1784
3.79
2
you
729
1.78
you
438
2.22
you
802
1.70
3
we
678
1.65
my
339
1.72
have
532
1.13
4
have
497
1.21
have
291
1.48
we
416
0.88
5
what
387
0.94
we
209
1.06
what
358
0.76
6
do
267
0.65
your
189
0.96
do
348
0.74
7
can
261
0.64
me
148
0.75
policy
344
0.73
8
your
258
0.63
what
145
0.74
my
328
0.70
9
our
251
0.61
do
130
0.66
can
297
0.63
10
all
241
0.59
work
123
0.62
reading
293
0.62
11
think
221
0.54
about
119
0.60
your
283
0.60
12
my
215
0.52
goals
116
0.59
one
255
0.54
13
so
214
0.52
can
110
0.56
about
242
0.51
14
data
202
0.49
our
102
0.52
all
231
0.49
15
policy
193
0.47
how
100
0.51
think
227
0.48
16
would
184
0.45
school
97
0.49
me
226
0.48
17
some
181
0.44
teachers
85
0.43
so
225
0.48
18 19 20
need me about
176 173 171
0.43 0.42 0.42
goal some would
84 82 82
0.43 0.42 0.42
instructor bob summary
222 221 196
0.47 0.47 0.42
Figure 4.2. Frequency of possible social presence indicators across the three major and most frequented threaded discussions.
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Table 4.2 Top 20 Words across Project Groups Rank 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20
Word I you we have what do can your our all think my so data policy would some need me about
Count 1674 729 678 497 387 267 261 258 251 241 221 215 214 202 193 184 181 176 173 171
Percentage (%) 4.08 1.78 1.65 1.21 0.94 0.65 0.64 0.63 0.61 0.59 0.54 0.52 0.52 0.49 0.47 0.45 0.44 0.43 0.42 0.42
Table 4.3 Top 20 Words across Pairs Rank 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20
Word I you my have we your me what do work about goals can our how school teachers goal some would
Count 960 438 339 291 209 189 148 145 130 123 119 116 110 102 100 97 85 84 82 82
Percentage (%) 4.87 2.22 1.72 1.48 1.06 0.96 0.75 0.74 0.66 0.62 0.60 0.59 0.56 0.52 0.51 0.49 0.43 0.43 0.42 0.42 86
Table 4.4 Top 20 Words across Reading Groups Rank 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20
Word I you have we what do policy my can reading your one about all think me so instructor bob summary
Count 1784 802 532 416 358 348 344 328 297 293 283 255 242 231 227 226 225 222 221 196
Percentage (%) 3.79 1.70 1.13 0.88 0.76 0.74 0.73 0.70 0.63 0.62 0.60 0.54 0.51 0.49 0.48 0.48 0.48 0.47 0.47 0.42
Content Analysis After conducting word count, I used an amended version (see Chapter 3) of the social presence indicators developed by Rourke et al. (2001a) to conduct content analysis on all of the threaded discussions in the course in order to identify what types of social presence indicators were present in each threaded discussion. As an exploratory study, I was interested in exploring the data to see how the students and the instructor in this given sample established and maintained their social presence. More specifically, though, I was curious about the overall occurrence of all of the social presence indicators (taken as a whole) across all of the threaded discussions, as well as the degree to which each category (i.e., groups of specific types of social presence indicators) and specifically each
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individual indicator were used in this sample. But at the same time, based on the CoI framework coupled with the word count results, I was also interested in the degree to which all of the social presence indicators, categories of social presence indicators, and specifically each individual social presence indicator occurred in specific types of threaded discussion. Finally, and based in part on the results of my own research (Lowenthal & Dunlap, 2011), I was curious how individual students might employ certain types of social presence behaviors differently than others. In summary, in order to explore how social presence manifests in threaded discussions (i.e., the research question guiding this study), I was interested in the occurrence and the frequency of the social presence indicators across all of the threaded discussions, as well as their occurrence and frequency within specific threaded discussions, and finally their relationship to each student (i.e., how often each student used specific social presence indicators). Figure 4.2 visually illustrates the stages of disaggregation I went through and report on in the following sections.
Figure 4.3. Stages of disaggregation of content analysis used to explore use of social presence indicators in a fully online asynchronous online course.
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Stage One: Social Presence Categories and Indicators across All Threaded Discussions Past research on social presence, or at least research focused on identifying indicators of social presence in online discussions, has focused primarily on reporting the results in terms of the three categories or types of social presence indicators. Thus, I was first interested in identifying which category of social presence indicators (i.e., Affective, Interactive, and Cohesive) was identified the most and which was identified the least across all of the threaded discussions. In other words, as a class, were “Affective,” “Cohesive,” or “Interactive” indicators used the most? Content analysis revealed that of the three different categories (or types) of social presence, “Interactive” indicators were present the most with 2,581 instances, “Cohesive” indicators were present the second most with 2,454 instances, and “Affective” indicators were present the least with 1,373 instances (see Figure 4.4 and Table 4.5). The differences between “Interactive” indicators and “Cohesive” indicators across all of the threaded discussions are minor. But there is an observable difference between these two categories and the “Affective” category of social presence indicators (see Figure 4.4). In other words, in this sample, students used “Affective” indicators the least. This is interesting in part because while Hughes et al. (2007) found a similar result in their sample, Swan (2003) found that “Affective” indicators were actually used the most in her sample.
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Figure 4.4. A visual depiction of the frequency of each of the three social presence categories. After examining the category level, I drilled down further to identify the frequency at which participants in this sample used each of the individual social presence indicators across all of the threaded discussions. The top three indicators used across all of the threaded discussions were “acknowledgement” (i.e., recognizing and openly acknowledging a previous post by a person) which was used the most at 1,137 instances, followed next by “invitation” (e.g., asking a question) which was used 747 times, and then by “vocatives” (i.e., addressing someone directly by the first name) which was used 748 times (see Table 4.5 and Figure 4.5). It is difficult to compare these results to other researchers because as mentioned earlier, the majority of those who do analyze online discussions focusing on social presence indicators do not report their results at the indicator level. Swan (2003), however, is one exception. But Swan only reports her findings at the indicator level through a series of bar graphs that lack exact numerical values (but still enable a reader to compare the frequency of each indicator). Acknowledgement was the only top-three 90
indicator shared with my sample and Swan’s sample; paralanguage which was used infrequently in this sample was actually the most frequently occurring social presence indicator in Swan’s study. Table 4.5 Social Presence Frequency across All Forums Category & Indicator
Frequency
Total Affective Responses Paralanguage (PL) Emotion (EM) Humor (H) Self-Disclosure (SD)
1373 270 526 53 524
Total Interactive Responses Acknowledgement (AK) Agreement / Disagreement (AG) Invitation (I) Expressing Appreciation (EA)
2581 1137 192 747 505
Total Cohesive Responses Greetings & Salutations / Phatics (GS) Vocatives (V) Group Reference / inclusivity (GR) Embracing the Group (EG)
2454 714 748 638 354
Total
6408 The least frequently used indicators of social presence were “humor” which was
used the least at 53 instances (which was also the least used indicator in Swan’s sample), followed next by “Agreement/Disagreement” which was used 192 times, and then by “paralanguage” which was used 270 times (see Table 4.6 for a complete ranking of each of the social presence indicators across all of the threaded discussions).
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1137
1200 1000 600
526
524
505
638 354
400 270 200
714 748
747
800
192
Affective
53
Interactive
0
Cohesion
Figure 4.5. Frequency of social presence indicators across all threaded discussions Table 4.6 Social Presence Indicators Ranking from Highest to Lowest Frequency Social Presence Indicators Acknowledgement Vocatives Invitation Greetings & Salutations / Phatics Group Reference / Inclusivity Emotion Self-Disclosure Expressing Appreciation Embracing the Group Paralanguage Agreement / Disagreement Humor
Frequency 1173 748 747 714 638 526 524 505 354 270 192 53
While it is useful to compare how the individual social presence indicators manifest across all three categories of social presence, it is also helpful to drill down to see how they compare to other indicators within their same category. The reason for this is because it is possible that within a given category that certain indicators of social presence are used more frequently than others. For instance, in the “Affective” category
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“emotion” and “self-disclosure” appeared the most frequently and almost in the same frequency (see Figure 4.6). In the “Interactive” category however, signs of “acknowledgement” were by far the most frequently used social presence indicator (see Figure 4.6). Finally, in the “Cohesion” category, “greetings / salutations / phatics,” “vocatives,” and then “group reference” all appeared in about the same frequency but “embracing the group” was used the least (see Figure 4.6).
Figure 4.6. Social presence indicators separated by category
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Stage Two: Social Presence Categories and Indicators By Discussion Forum As helpful as it is to look at the frequency of social presence indicators across all of the threaded discussions and treating all of the threaded discussions essentially as one case, it is perhaps more insightful and helpful to drill down and look at the occurrence of social presence indicators across and within types of threaded discussions. At this stage, I first looked at the occurrence of social presence indicators across specific types of threaded discussions. For the ease of reporting, I separated full-class threaded discussions (i.e., discussions that are “open” to the entire class) from small-group threaded discussions (i.e., discussions that are “closed” to a small select group of students assigned with a specific task like discussing the reading or collaborating on a course project). See Table 4.7 for the list of “open” vs. “closed” threaded discussions. But because each threaded discussion differs in total number of posts and words, I needed a way to calculate the social presence density of each discussion. Following the lead of Rourke et al. (2001a), I calculated the social presence density for each indicator in each threaded discussion. But because the unit of analysis for this study was the entire post, I calculated the social presence density by taking the average social presence indicator per post (as opposed to per word like Rourke et al., 2001a) to facilitate comparison across open and closed threaded discussions.
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Table 4.7 Open vs. Closed Threaded Discussions Open to Entire Class
Small Group (limited to 2-5)
Virtual Office --Virtual Office
Reading Groups --Reading Group A --Reading Group B --Reading Group C --Reading Group D --Reading Group E --Reading Group F --Reading Group G
General Discussions --General Syllabus --General Groups --General Independent Work --General Individual Work Adult Learning Discussions --Adult Learning Discussion Forum: Your Learning --Adult Learning Discussion Forum: Questionnaire #1 Plus Delta Discussions --Plus Delta Week 2 --Plus Delta Week 3 --Plus Delta Week 4 --Plus Delta Week 5 --Plus Delta Week 6 Reading Log Discussions --Reading Log1 --Reading Log 3
Pairs --Pair 1 --Pair 2 --Pair 3 --Pair 4 --Pair 5 --Pair 6 --Pair 7 --Pair 8 --Pair 9 --Pair 10 Project Groups --Project Group 1 --Project Group 2 --Project Group 3 --Project Group 4 --Project Group 5
I found when comparing the average social presence indicators per post between open threaded discussions and closed threaded discussions that a higher density of social presence occurred in closed threaded discussions than in open threaded discussions (see Table 4.8). For instance, the average per post “Affective” indicator is 0.78 in closed discussions (meaning there is an average .78 affective indicators per post) compared to 0.56 for open discussions; the average “Cohesive” indicators is 1.37 in closed discussions
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as compared to 1.17 in open discussions; and the average “Interactive” indicators is 1.45 in closed discussions vs. 1.09 in open discussions. Table 4.8 Average Social Presence Indicators Per Post across Open and Closed Threaded Discussions Open Discussions
Closed Discussions
Affective Cohesive Interactive
Total 101 211 197
Average 0.56 1.17 1.09
Total 1272 2243 2382
Average 0.78 1.37 1.45
Total
509
2.81
5897
3.59
I then decided to look deeper within the closed discussions to explore any observable differences between the different types of closed discussions used because while all three were “closed” discussions, each one had a distinct purpose which could have influenced how students posted in each threaded discussion. When comparing all three of the different types of “closed” discussions (see Table 4.9 and Figure 4.7), “Pairs” had the highest total social presence average per post with 4.20 social presence indicators per post. “Project Groups” was next with an average of 3.76 social presence indicators per post. And then “Reading” groups had the lowest average of social presence indicators per post. These differences could likely be due to a combination of the group size and the purpose of each of these threaded discussions. For instance, the “Pairs” and the “Project Groups” had very specific tasks that required interaction, cohesion, and collaboration whereas the “Reading Groups” (while also a small group) had less prescriptive tasks (see Table 3.1 in Chapter 3).
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Table 4.9 Average Social Presence Indicators across Closed Threaded Discussions Reading Groups
Pairs
Project Groups
Total
Average
Total
Average
Total
Average
Affective
549
0.77
253
0.95
470
0.71
Cohesive
776
1.09
467
1.76
1000
1.50
Interactive
956
1.35
394
1.49
1032
1.55
Total
2281
3.21
1114
4.20
2502
3.76
Figure 4.7. Visual depiction of the average social presence indicators grouped by category in closed threaded discussions. But when I began to compare each category and later each indicator, the results began to change. For instance, the “Pairs” threaded discussions have the highest average of all of the social presence indicators per post across all the categories and indicators. 97
But when I disaggregated these results, I found that the “Pairs” threaded discussions did not have the highest social presence density across all three categories of social presence. For the interactive category of indicators, the “Pairs” group actually had a lower per post average than the “Project Groups.” At the same time, while the “Reading Groups” had the lowest total social presence average per post overall, these threaded discussions actually had a higher average of affective indicators than “Project Groups” (see Table 4.10). This could suggest that certain types of tasks in certain group sizes could elicit more social presence behaviors per participant than others. At the same time, the differences are minor and more research would likely need to be conducted to support this theory. Table 4.10 Ranking of Average Social Presence Indicators Across Closed Threaded Discussions Social Presence Category & Closed Threaded Discussion
Average Per Post
Affective Indicators Pairs Reading Groups Project Groups
0.95 0.77 0.71
Cohesive Indicators Pairs Project Groups Reading Groups
1.76 1.50 1.09
Interactive Indicators Project Groups Pairs Reading Groups
1.55 1.49 1.35
Each threaded discussion—specifically the closed threaded discussions—consists of different students and therefore even though the tasks might be the same, it is possible that individual students and their natural or learned communication skills influence the
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frequency and therefore overall social presence density in a given threaded discussion (which is in part why I looked at each student’s social presence behaviors during Stage 3 of the content analysis). Therefore, I dug deeper to look at the social presence density across all closed threaded discussions (see Table 4.11). One of the Pairs threaded discussions—specifically Pair 9—had the highest overall average of social presence indicators per post per discussion as well as the highest per post average of each of the three categories of social presence indicators. Reading Group E and Reading Group G ended up with the lowest social presence per post average per individual threaded discussions. These results follow the general trend identified earlier (see Figure 4.6) with the Pairs threaded discussions having the overall highest density of social presence per post and the Reading Groups threaded discussions having the lowest overall density of social presence per post. This could suggest that the overall size and purpose of a specific discussion highly influences the amount of social presence indicators used by students in any given discussions: For instance, the Pairs discussions involved two students taking part in personal discussions versus the Reading Groups which involved small groups of 4-5 students talking about the weekly readings in the course. As one might imagine, two students discussing personal matters might engender more affective, cohesive, and interactive indicators than a larger group discussing course readings.
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Table 4.11 Average Social Presence Indicator per Threaded Discussion Discussion Forum
Open Discussions Virtual Office General: Syllabus General: Groups General: Independent Work General: Individual Work Adult Learning Discussion Forum –Your Learning Adult Learning Discussion Forum –Questionnaire #1 Plus Delta Week2 Plus Delta Week 3 Plus Delta Week 4 Plus Delta Week 5 Plus Delta Week 6 Reading Log 1 Reading Log 3 Closed Discussions Reading Group A Reading Group B Reading Group C Reading Group D Reading Group E Reading Group F Reading Group G Pair 1 Pair 2 Pair 3 Pair 4+ Pair 5 Pair 6 Pair 7 Pair 8 Pair 9 Pair 10
Total Posts
Affective/ Avg. Per Post
Cohesive/ Avg. Per Post
Interactive /Avg. Per Post
Social Presence/ Avg. Per Post
44 48 14 3
16 (0.36) 12 (0.25) 8 (0.57) 3 (1.00)
59 (1.34) 44 (0.92) 12 (0.86) 5 (1.67)
44 (1.00) 34 (0.71) 16 (1.14) 3 (1.00)
119 (2.7) 90 (1.88) 36 (2.57) 11 (3.67)
2
0 (0.00)
3 (1.50)
2 (1.00)
5 (2.5)
12
4 (0.33)
13 (1.08)
12 (1.00)
29 (2.42)
3
4 (1.33)
2 (0.67)
5 (1.67)
11 (3.67)
13 22 2 2 3 12 1
15 (1.15) 19 (0.86) 3 (1.50) 3 (1.50) 7 (2.33) 7 (0.58) 0 (0.00)
24 (1.85) 30 (1.36) 0 (0.00) 5 (2.50) 4 (1.33) 10 (0.83) 0 (0.00)
15 (1.15) 36 (1.64) 3 (1.50) 2 (1.00) 4 (1.33) 20 (1.67) 1 (1.00)
54 (4.15) 85 (3.86) 6 (3.00) 10 (5.00) 15 (5.00) 37 (3.08) 1 (1.00)
125 132 95 109 40 106 103 32 40 45 6 30 28 26 21 15 22
110 (0.88) 88 (0.67) 104 (1.09) 120 (1.10) 23 (0.58) 59 (0.56) 45 (0.44) 18 (0.56) 41 (1.03) 41 (0.91) 5 (0.83) 38 (1.27) 14 (0.50) 23 (0.88) 33 (1.57) 25 (1.67) 15 (0.68)
128 (1.02) 124 (0.94) 129 (1.36) 153 (1.40) 29 (0.73) 84 (0.79) 129 (1.25) 46 (1.44) 71 (1.78) 84 (1.87) 5 (0.83) 65 (2.17) 38 (1.36) 41 (1.58) 48 (2.29) 38 (2.53) 31 (1.41)
192 (1.54) 203 (1.54) 95 (1.00) 186 (1.71) 41 (1.03) 126 (1.19) 113 (1.10) 51 (1.59) 59 (1.48) 78 (1.73) 5 (0.83) 38 (1.27) 30 (1.07) 40 (1.54) 33 (1.57) 30 (2.00) 30 (1.36)
430 (3.44) 415 (3.14) 328 (3.45) 459 (4.21) 93 (2.33) 269 (2.54) 287 (2.79) 115 (3.59) 171 (4.28) 203 (4.51) 15 (2.50) 141 (4.70) 82 (2.93) 104 (4.00) 114 (5.43) 93 (6.20) 76 (3.45)
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Table 4.11 (con’t.) Closed Discussions (con’t.) Project Group 1 Project Group 2 Project Group 3 Project Group 4 Project Group 5
109 180 138 113 126
72 (0.66) 96 (0.53) 111 (0.80) 79 (0.70) 112 (0.89)
160 (1.47) 276 (1.53) 168 (1.22) 136 (1.20) 260 (2.06)
167 (1.53) 292 (1.62) 189 (1.37) 141 (1.25) 243 (1.93)
399 (3.66) 664 (3.69) 468 (3.39) 356 (3.15) 615 (4.88)
Stage Three: Social Presence Categories and Indicators By Students While conducting the content analysis, I began to get a sense that certain students used certain social presence indicators (e.g., paralanguage and vocatives) more than others. Therefore, I decided to investigate the frequency at which each student used social presence indicators. I reasoned that it could be that, even though a certain threaded discussion (which consisted of a group of students) might have a high social presence density, it could be the result of one group member who was extremely active and proficient with employing affective, interactive, and cohesive means of communication in threaded discussions. Henceforth, I first looked at each participant’s use of all three of these categories of social presence as a whole; however, I excluded five students who failed to post more than ten overall posts throughout the semester. Of those who posted more than ten times, Cathy had the highest average with 5.43 instances of social presence per post, followed next by Diana with 4.87 per post, and Mary with 4.64 per post. This becomes more striking when these results are compared to participants with the lowest use of social presence indicators per post. The three participants with the lowest number of social presence indicators per post were Instructor Bob who had the lowest average at 2.24 instances per post, followed by Sam with 2.42 per post, and then Monica at 2.89 per post.
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But when I dug a little deeper I found that a high or low social presence rating (i.e., the average social presence indicators used per post) does not necessarily mean that the participant in question scores the same on all three categories of indicators or even on a given set of indicators within a category. In other words, one could feel competent and comfortable with interactive types of communication but not with affective or cohesive. For instance, while Cathy had a high overall social presence average per post (when taking into consideration all three categories of social presence), she had one of the three lowest interactive averages per post. In other words, while her use of affective and cohesive indicators was high compared to her peers, her use of interactive indicators was low compared to her peers. Similarly, while Instructor Bob had an overall low total social presence score, he in fact had the highest interactive score (see Table 4.12) thus suggesting that he may be more proficient at interactive types of communication than cohesive or affective. Table 4.12 Student’s Use of Social Presence Categories Total Posts
Adam Cathy Christine Daphne Dawn Denise Diana Erica Gabriela Instructor Bob
76 77 107 73 121 103 94 66 55 328
Social Presence Total Posts (Avg. Per Post) 254 (3.34) 418 (5.43) 362 (3.38) 253 (3.47) 360 (2.98) 393 (3.82) 458 (4.87) 221 (3.35) 173 (3.15) 736 (2.24)
Affective Total Posts (Avg. Per Post)
Cohesive Total Posts (Avg. Per Posts)
Interactive Total Posts (Avg. Per Posts)
56 (0.22) 122 (0.29) 86 (0.24) 42 (0.17) 69 (0.19) 61 (0.16) 156 (0.34) 53 (0.24) 34 (0.20) 115 (0.16)
109 (0.43) 175 (0.42) 115 (0.32) 112 (0.44) 123 (0.34) 178 (0.45) 151 (0.33) 101 (0.46) 66 (0.38) 204 (0.28)
89 (0.35) 121 (0.29) 161 (0.44) 99 (0.39) 168 (0.47) 154 (0.39) 151 (0.33) 67 (0.30) 73 (0.42) 417 (0.57)
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Table 4.12 (con’t.) Kate Kyleigh Laura Mary Micky Monica Richard Sam Sara Vicky
99 85 39 117 93 53 31 78 50 64
354 (3.58) 274 (3.22) 172 (4.41) 543 (4.64) 423 (4.55) 153 (2.89) 130 (4.19) 189 (2.42) 229 (4.58) 234 (3.66)
52 (0.15) 75 (0.27) 44 (0.26) 91 (0.17) 96 (0.23) 32 (0.21) 23 (0.18) 50 (0.26) 54 (0.24) 47 (0.20)
157 (0.44) 99 (0.36) 73 (0.42) 231 (0.43) 174 (0.41) 61(0.40) 61 (0.47) 55 (0.29) 88 (0.38) 82 (0.35)
145 (0.41) 100 (0.36) 55 (0.32) 221 (0.41) 153 (0.36) 60 (0.39) 46 (0.35) 84 (0.44) 87 (0.38) 105 (0.45)
But even treating each social presence indicator within a given category equally could perhaps be hiding certain trends. For instance, it could be that certain people are strong with certain indicators in a given category but not others (for instance, someone might have a high Affective category but simply because he or she is really proficient at disclosing personal information and sharing emotion, but not at using paralanguage and humor). So, I decided to take a look at the students with the highest overall social presence average per post (see Figure 4.8 and Figure 4.9). While Cathy had the highest social presence per post average at 5.43 instances per post, Cathy’s (like Mary’s) strength appears to be “greetings and salutations.” Diana on the other hand uses “paralanguage” more frequently than “greetings and salutations.” Diana though was one of the students in the Pairs 9 threaded discussion which had the highest per post average of social presence indicators; it is important to note that she was paired with Sara who was fourth on the overall list with the highest average of social presence indicators.
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These results likely suggest two things. First, that just because someone may be proficient at employing a certain type or category of social presence behaviors (i.e., affective, interactive, and / or cohesive) does not mean that this same person is proficient at or comfortable with each indicator related to the category of social presence communication. In other words, while someone might use a lot of affective types of communication, he or she might never use paralanguage and vocatives, opting instead for the use of greetings and salutations, acknowledgement of others, and the use of emotion. Second, these findings might point to the fact that people—especially in small groups— might begin to mirror the communication behaviors of their peers. For example, if a peer (in a small group) has strong social presence behaviors and heavily uses paralanguage then other students in the group might begin to use paralanguage more frequently than before simply from mimicking their peer. Cathy Greetings & salutations Emotion Acknowledgement Vocatives Paralanguage Group Reference
0.84
Diana Paralanguage
0.64
0.6 0.6 0.56 0.52 0.51
Acknowledgement Group Reference Invitation Emotion Self Disclosure
0.63 0.62 0.59 0.5 0.49
Invitation
0.45
0.43
Expressing Appreciation Embracing the Group Self Disclosure
0.42
Greetings & salutations Vocatives
Mary Greetings & salutations Acknowledgement Invitation Group Reference Vocatives Expressing Appreciation Emotion
0.31
Self Disclosure
0.31
0.31
0.18
0.26
Embracing the Group Agreement
Humor Agreement
0.12 0.1
Expressing Appreciation Embracing the Group Agreement Humor
0.09 0.03
Paralanguage Humor
0.1 0
0.36 0.35
0.85 0.79 0.5 0.5 0.44 0.44 0.37
0.17
Figure 4.8. Ranking of social presence indicators used by the three students with the highest overall social presence per post average.
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Mary’s Individual Use of Social Presence Indicators 0.44
0.1
0.37
0.17
Paralanguage
0
EmoSon
0.31
Humor
0.5
Self Disclosure GreeSngs & salutaSons 0.85
VocaSves Group Reference
0.79
Embracing the Group Acknowledgement
0.44
0.18
InvitaSon
0.5
Diana’s Individual Use of Social Presence Indicators 0.09
0.31
0.64
Paralanguage EmoSon
0.59 0.5
Humor Self Disclosure
0.03
GreeSngs & salutaSons VocaSves
0.63 0.49
Group Reference Embracing the Group
0.26 0.43 0.62
0.31
Acknowledgement InvitaSon
Cathy’s Individual Use of Social Presence Indicators
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0.1
0.42
0.52
0.45
Paralanguage EmoSon
0.6
Humor 0.12
0.6
0.35
Self Disclosure GreeSngs & salutaSons VocaSves Group Reference
0.36
Embracing the Group 0.84 0.51
Acknowledgement InvitaSon
0.56
Figure 4.9. Disaggregation of three students with highest social presence per post average. Constant Comparison Analysis While social science has a long tradition of using content analysis alone to analyze the content of online discussions, I decided at the beginning of this study to use multiple types of analysis in an effort to better explore how social presence manifests in threaded discussions in a completely online course. I turned to constant comparison analysis in hopes that it would reveal things that were missed by content analysis. At the beginning of this study, I decided to analyze the threaded discussion with the highest average social presence density per discussion post and the threaded discussion with the lowest in hopes of identifying different ways that social presence manifests in threaded discussions. After conducting content analysis, I selected the Pair 9 threaded discussion as having the highest social presence density at 6.20 per post and the Reading Group E as having the lowest social presence density at 2.33 per post. I then used constant comparison analysis to code these two threaded discussions in an effort to
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see if themes might emerge that tell a similar or different story than the content analysis results. Due to the different nature of each threaded discussion, I conducted constant comparison analysis on each discussion separately. I first analyzed Reading Group E (which had the lowest social presence density). As touched on in Chapter 3, the Reading Group discussions consisted of small groups of 4-5 students that were tasked with discussing the course readings and jointly writing nine different reading logs about the course readings. The readings logs were supposed to not only summarize the readings but also bring up any questions the group members had so that the instructor could then answer them in the Reading Group threaded discussions. Students had two incentives to take part in the Reading Group threaded discussions: First, students were graded on each of the nine reading logs, which consisted of 15.25% of the course grade; second, students were graded for their online interactivity and quality of work, which consisted of 16.95% of the course grade. As mentioned in Chapter 3, the first step of conducting constant comparison analysis involved reading the entire threaded discussion. After reading all of the posts in the threaded discussion, I then chunked the text into meaningful units. I then coded each meaningful unit while constantly comparing new codes with previous codes. During the coding process, I focused on the way people were communicating while still trying not to limit myself or be confined in any way to the social presence indicators used for content analysis. After coding all of the meaningful units, I then listed the codes and grouped similar codes.
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The analysis resulted in 89 unique codes (see Appendix C). Those codes were gathered into eight separate groups (see Table 4.13). Table 4.13 Groups of Codes Resulting from the Constant Comparison Analysis Reading Group E Grouping of Codes Course logistics & facilitation Emotion Greetings and Salutations Sharing Life Details Gracious/Gratitude Self Disclosing Personal Matters Playing Nice with Others Policy Related Class Discussions
In the fifth and final step, I identified themes from the data—while including specific language from the groups, codes, or data when appropriate. The following two themes emerged from the data from Reading Group E. (I have italicized any text that came straight from the threaded discussions.) •
Policy is complex and multifaceted; it is something that many students and teachers have no idea about; while the readings varied in complexity and required a little more time than texts in past classes, with the help of the instructor the students came to find the study of policy interesting and relevant.
•
Students began the threaded discussion (which spanned two months) with chit chatting and telling personal stories but quickly changed their focus to the task at hand of discussing public policy in general and the readings in particular;
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overtime the focus of the discussion was solely on the reading and public policy—by this point the discussion largely consisted of students posting questions and the instructor answering the questions. After analyzing the Reading Group E threaded discussion, I analyzed the Pair 9 threaded discussion (which had the highest social presence density) following the same steps as above. The Pair 9 threaded discussion had a different purpose than the reading group. According to the course syllabus, the Pairs group is a place where group members work on a personal-professional development activity that requires each student to take a bit of risk and develop some trust with each other while discussing individual personalprofessional goals that are deeply important to one another. Similar to the Reading Group threaded discussions, students had two incentives to take part in the Pair’s threaded discussions: First, students were graded on the 3-5 page paper that resulted from their work in their pairs group they were assigned to, which consisted of 12.7% of the course grade; second, students were graded for their online interactivity and quality of work, which consisted of 16.95% of the course grade. Likely due in part to the different purpose, the Pairs threaded discussions had a higher social presence density than other threaded discussions but specifically the Pairs 9 group had the highest among all of the Pairs and all of the threaded discussions in general. Analysis of the Pairs 9 group resulted in 63 codes (see Appendix C), which I then grouped into nine groups (see Table 4.14).
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Table 4.14 Groups of Codes Resulting from the Constant Comparison Analysis Reading Pair 9 Grouping of Codes Course logistics & facilitation Collaboration Emotion Sharing Life Details Playing Nice with Others Policy Related Class Discussions Greetings and Salutations Self Disclosing Personal Matters Gracious/Gratitude
Three themes emerged from this data as well. Like before, I have italicized any text that came straight from the threaded discussions. •
Students who have a past relationship and spend time with each other either professionally (e.g., we are fortunate enough to work together) or personally outside of class can have an easier time collaborating with each other because of their past relationship, shared experiences, and geographic closeness which others might not have. These benefits can help them NOT to be alone, give them opportunities to chat a lot, provide a strong and safe foundation to openly share how they are struggling personally and professionally, and to regularly meet faceto-face.
•
Instructors can only react to what they see in a threaded discussion. It is difficult to assess and to support students when they collaborate offline.
•
When asked to take a risk, trust a peer, and self-disclose personal details, it helps when two people already know each other, have some trust already built, have shared experiences, and finally have the ability to talk and meet offline. 110
While the results of the constant comparison analysis did not necessarily contradict any of the findings from the word count or content analysis, they did begin to fill in some details about what students were talking about in each threaded discussion and how the type and purpose of a threaded discussion could influence how people communicate with one another. Chapter Summary I utilized word count, content analysis, and constant comparison analysis to explore how social presence manifests in a fully online discussion. Results illustrate that participants’ use of social presence behaviors (e.g., indicators of social presence) vary across the course. The results also reveal that looking at the total social presence indicators or even simply the frequency at which each category of social presence is used (e.g., affective, cohesive, and interactive) might be misleading and miss important details about how and when people use certain social presence behaviors. These results will be discussed at greater length in Chapter 5.
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CHAPTER 5 DISCUSSION I set out to explore how social presence manifests in a fully online asynchronous course. In Chapter 1, I laid out an argument for why additional research needs to be conducted on social presence. Then in Chapter 2, I reviewed the literature on social presence and the community of inquiry (CoI). After reviewing the literature, I then explained in Chapter 3 the methods that were used for this study. Finally in Chapter 4, I reported on the results of the study. Now in Chapter 5, I will discuss the significance of these results, the limitations of this study, and the practical implications for the results— specifically for course designers and faculty. Key Findings A deep and meaningful educational experience involves teaching presence, social presence, and cognitive presence (Garrison et al., 2000). The CoI framework posits that social presence is developed as the result of teaching presence. More specifically, educators develop social presence through instructional design and organization, facilitating discourse, and direct instruction (the three components of teaching presence) (Anderson, Rourke, Garrison, & Archer, 2001). This does not mean that social presence cannot naturally occur. Walther (1992) argued almost 20 years ago that people are social creatures and that given enough time people will find ways to use any communication medium for social purposes. Online educators however typically do not want to wait and hope that their student’s natural social tendencies kick-in. Instead they often strive to find ways to help encourage the development of social presence in online courses (which is what the CoI refers to as teaching presence).
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The CoI framework (as well as the CoI literature as whole), though, does not provide much guidance on how to design courses, facilitate discourse, and provide direct instruction to facilitate the development of social presence (Garrison & Arbaugh, 2007). For instance, how many threaded discussions should be in a course? Should the threaded discussions be full class discussions or small groups? Should they have specific instructional tasks? Educators can make some inferences from the indicators of teaching presence developed by Anderson et al. (2001) (see Table 5.1), but even these indicators lack sufficient detail. Table 5.1 Teaching Presence Categories and Indicators Teaching Presence Categories and Indicators Instructional Design and Organization Setting Curriculum Designing Methods Establishing Time Parameters Utilizing Medium Effectively Establishing Netiquette Facilitating discourse Identifying areas of agreement/disagreement Seeking to reach consensus/understanding Encouraging, acknowledging, or reinforcing student contributions Setting climate for learning Drawing in participants, prompting discussion Assess the efficacy of the process Direct Instruction Present content/questions Focus the discussion on specific issues Summarize the discussion Confirm understanding through assessment and explanatory feedback Diagnose misconceptions Inject knowledge from diverse sources e.g., textbook, articles, internet, personal experiences (includes pointers to resources) Responding to technical concerns
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Some of the results presented in Chapter 4 might begin filling this void. That is, the results provide a couple of possible guidelines for how educators can design and develop online courses to increase social presence. However, as an exploratory study using a small sample, the findings from this study should not be generalized to all populations. In fact, any and all findings should be confirmed with additional research. With that in mind, I will address some key findings in the following paragraphs. Group Size One of the first things that stood out initially with the word count results and then with the content analysis results was that the social presence density—that is, the average social presence indicator per discussion post—differed across types of threaded discussions, specifically open vs. closed discussions. In other words, a higher social presence density existed for small-group discussions than for large-group discussions. This suggests that students projected themselves as “real” and “there” in the threaded discussions through specific social presence behaviors (e.g., self disclosing information, addressing people by first name, using emoticons) more frequently in small discussions than in large discussions. While very little research has been conducted on group size and social presence, Tu and McIsaac (2002) claimed that “appropriate communication group size” can influence social interaction and thus social presence. They concluded based on the qualitative data in their study that “the size of the discussion group exerted a major impact on students’ interaction, particularly in real-time discussions” (p. 145). And while they recommend that two to three participants are an ideal group size for real-time
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discussions, they unfortunately do not offer any suggestions for an ideal group size for asynchronous discussions. Rourke and Anderson (2002a) conducted a study on using peer teams to lead discussions. They found that students preferred small-group peer-led threaded discussions more than full class instructor-led discussions. They concluded that this preference was possibly due to the fact the small-group discussions consisted of four students and were led by their peers rather than the instructor. But the students’ preference for small-group discussions could have been due to a combination of the group size, the instructional task, and the instructor’s reduced role rather than simply the fact that the discussions were peer led. This finding about large- and small-group discussions, however, does not suggest that social presence cannot develop in large group discussions. In fact, Nagel and Kotze (2009) found high levels of social presence in a “super-sized” course of 100+ students. This finding about group size might simply confirm what Kreijns, Kirschner, and Jochems (2003) argued about group size—namely, that anonymity and non-participation increases as groups get larger (p. 340). In other words, as the group size (or class size) increases, it is easier for students to hide and sit back and lurk (or not participate at all). Lurking is not necessarily a bad thing (see Dennen, 2008). However, students need to actually interact with their peers in order to project themselves as “real” and “there” in threaded discussions. And this type of interaction might simply be easier for students in smaller groups—especially those who might have a tendency to lurk in large threaded discussions.
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My personal experience teaching in face-to-face environments has shown me that as the class size gets larger, fewer and fewer students ask questions on their own. In my experience, small groups can force even the shiest and reluctant student to talk to her or his peers. Given this, it might make sense for faculty to utilize small-group threaded discussions more at the beginning of a course to help students begin to establish their social presence early on in a given course or program of study. Small groups likely place an additional amount of peer pressure on individual students. Individual students are no longer simply held accountable for their actions by their instructor but also by their peers. In my experience, peers are much more likely to send other peers an email for nonparticipation in small groups—especially those that involve group work—than they would in large group discussions. Further, these results could support the need for the development of a number of small learning communities rather than the typical approach, which too often focuses on developing one all-encompassing learning community with every student in the course. More research though needs to be conducted across other samples to confirm that group size can in fact influence the development of social presence. Instructional Task In this study, though, group size alone did not guarantee a high level of social presence. For instance, project groups and pairs had a higher social presence density than reading groups even though reading groups were also small groups. This difference in the social presence density likely could be due to the instructional task of each threaded discussion. In my experience, students quickly identify what discussions they need to take part in and which one’s they do not—both in terms of the relevance of the threaded
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discussions toward the course and the student’s personal and professional goals as well as any points the discussion is worth toward the final grade. Students’ participation in both of these threaded discussions was graded and both of these threaded discussions were tied to specific assignments that were graded as well. However, as mentioned in Chapter 4, the reading groups involved identifying questions that resulted from the course readings and then having the instructor answer the questions. As a result, the dynamic of the discussions appeared to be less goal specific (or at least less clearly defined) as the other two types of small threaded discussions. Reading Groups had less peer accountability at least in comparison to the Pairs threaded discussion. Also, more student-to-instructor and instructor-to-student rather than studentto-student interaction occurred in these threaded discussions. In fact, when looking at the number of posts and the number of words in each post in these threaded discussions, the instructor’s role in the reading groups is more prominent than in the Pairs or Project groups (see Table 5.2). This does not necessarily mean that instructors should say less or avoid direct instruction. In fact, the CoI argues for the use of direct instruction as one way to establish social presence. Rather it might simply suggest that the purpose of a discussion likely influences how and what a student posts—and therefore the amount of social presence behaviors used by both faculty and students. Table 5.2 Instructor vs. Student Postings in Small Discussions Reading Groups Posts Student
Words
Pairs Posts
Words
Project Groups Posts
Words
543 (77%) 42,176 (71%) 219 (83%) 22,087 (89%) 630 (94%) 47,758 (91%)
Instructor 165 (23%) 16,860 (29%) 46 (17%) 2,629 (11%)
42 (6%)
4,992 (9%)
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The pairs discussion groups had the highest overall density of social presence. While this is likely due in part to the fact that the pairs groups consisted of only two students, it is perhaps equally due to the fact that the pairs groups were tasked with sharing personal things with one another. In fact, the pairs had the highest frequency of affective indicators per post, which is likely largely due to the instructional task. To date though, no research specifically examines how specific instructional tasks in threaded discussions affect social-presence behaviors used in the threaded discussions. Researchers for years have questioned how best to structure threaded discussions (Gilbert & Dabbagh, 2005). And they have shown that the structure of a threaded discussion as well as how an instructor posts—thus modeling and setting the tone—can influence how students post (see Dennen, 2005). While Lowenthal and Dunlap (2011) investigated students’ perceptions of how specific instructional tasks influence students’ perceptions of social presence, to date there is a lack of research on how small working groups (working on specific assignments—whether group assignments or not) can help build social presence. The reason the pairs group had a higher social presence density though could also be due in part to the instructors role in these discussions. An, Shin, and Lim (2009) found that “when the instructor’s intervention was minimal, students tended to more freely express their thoughts and opinions, with a large number of cues for social presence” (p. 749). Thus, while course designers like myself as well as faculty in general seem to prefer clear-cut guidelines, it is possible that there are not any clear-cut guidelines. These results seem to suggest that it could be a combination of small group size, instructional tasks that engender interpersonal dialogue, and low instructor involvement that helps
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build social presence. But at this point, while this is reasonable, it is simply speculation. Additional variables such as one’s personal communication style, how discussions are graded, and the relevance of the instructional tasks to name a few, need to be investigated to see how they too influence how social presence manifests. Further research needs to be conducted to verify how instructional tasks (including not only what students are asked to do but also how they are graded as well as the personal and professional relevance of the assignments), group size, and instructor involvement can impact the development of social presence. Past Relationships Constant comparison analysis of the threaded discussions with the highest and the lowest density of social presence revealed that the pairs with the highest social presence density worked together and even carpooled together. Practitioners have argued for years that online courses—whenever possible—should start with face-to-face meetings to establish social presence. This finding, though, might suggest something more. It could suggest that people who have a strong relationship outside of class might have an easier time with interactive, cohesive, and affective types of communication than people who do not have a relationship outside of class. This finding is supported by the work of Lowenthal and Dunlap (2011). Lowenthal and Dunlap found that having a positive group project experience with a student helps increase a student’s perceptions of social presence between the students in question and helps them maintain future relationships with one another—even in the absence of ever meeting face-to-face. Both of these findings suggest that having a past relationship with someone is helpful when establishing social presence in online courses. It could be that a cohort
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model that enables students multiple opportunities to build relationships with other students semester after semester is more valuable (at least when it comes to building social presence) than beginning a course or a program with face-to-face meetings. Walther (1994) argued years ago that the possibility of future interaction can influence the degree to which people socially interact online thus further giving support for cohort models or other types of models that enable students to take multiple courses with the same students and/or with the same instructor. Further research though is needed to confirm this because while the students’ past relationship emerged in the data in this one group, it was difficult to ascertain whether or not other students had past relationships with their peers and if so to what degree. One Size Doesn’t Fit All But perhaps the number one finding of this study from a design perspective, as disheartening as it is, is that one size does not fit all. In other words, the results show that while there are trends (e.g., that closed threaded discussions had a higher social presence density than open threaded discussions), there is not always a clear reason as to why some students use specific social presence behaviors (e.g., paralanguage) and others do not. While some students might use (or some threaded discussions might elicit) high levels of social presence overall, each of the indicators or at least the categories (i.e., types of social presence) differed across students and types of threaded discussions. This finding supports what Lowenthal and Dunlap (2011) found. They found that each student appears to have her or his own threshold for social presence. In other words, different people have their own social presence needs. What works for one student might not work for another and what is comfortable or ideal for one student might not be
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comfortable or ideal for another. Along these lines, it is possible that each person— perhaps based in part on his or her own social presence needs—has developed their own level of proficiency at utilizing social presence behaviors in threaded discussions. That is, each person has developed different levels of literacy at computer-mediated discourse. However, a stylistic element appears to affect how people communicate in online learning environments as well. For instance, some students appear to almost habitually use emoticons (like Diana) whereas others do not appear to use them at all (like Kate, Denise, Dawn, or Laura). It is possible that just as people have different communication styles in face-to-face environments, that they also have different communication styles in online environments. Further research though is needed to find out why some people use certain types of communication behaviors (e.g., the use of vocatives or paralanguage) and others do not. Limitations of Studying Social Presence Every research study has some limitations. I address the limitations of this study later in this chapter. For now, though, I want to address some insights that resulted from studying social presence behaviors in threaded discussions in this study. These insights are possible limitations of social presence theory in general (or at least how social presence is conceptualized within the CoI) as well as possible limitations with identifying and quantifying social presence behaviors in particular. While practitioners will likely find little use of these insights, researchers of social presence on the other hand might find this section the most useful contribution of this study.
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Situational Variables of CMC As mentioned earlier, social presence theory dates back to the work of Short et al. (1976). Short et al. developed their theory of social presence based on their research on how telecommunications effects the way two people communicate. In other words, Short et al. and their theory of social presence originally focused on one-to-one communication. While instances of one-to-one CMC (e.g., email) occur, more often than not CMC in online courses takes place in threaded discussions that involve three or more communicators. Instances of one-to-one communication are found in threaded discussions. But this one-to-one communication is often done “in front” of others. The “publicness” of CMC in threaded discussions is likely to influence what, when, and how a person communicates in online courses—which is perhaps why Tu focused so much on privacy in his early work (see Chapter 2 and Tu 2000, 2001, 2002a, 2002b) and perhaps why students feel more comfortable or more pressured to present themselves as “real” and “there” in small personal groups as opposed to larger impersonal groups. More often than not, though, communication in threaded discussions is a one-tomany model—thus changing the dynamic and making it more like public speaking. Or when it is one-to-one, it is like talking to another person on the phone but while on a speakerphone (where others are listening). I contend that these changes in the social context in which one communicates—more than any limitation of the technology—likely changes how people communicate and establish themselves as “there” and “real.” This becomes important when one starts to think about the indicators of social presence developed by Rourke et al. (2001a).
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Rourke et al. (2001a) claim that they developed these categories and indicators based on their previous work (Garrison, Anderson, & Archer, 2000), other literature in the field, and finally their experience reading online transcripts. However, I posit that we have reason to believe that, as the technology of online threaded discussion forums has improved over the years, as bandwidth has increased, as people’s experience using CMC has improved (e.g., the increase in email use and the fact that Facebook has millions of users alone are great examples of how people’s use or at least comfort and ability with CMC has improved), and finally as the pedagogies used in online courses have matured, the study of online transcripts has or at least should have changed over the years. In other words, many of these indicators of social presence might no longer be relevant, might lack enough specificity, or simply might be based too much on old assumptions of socalled “proper” ways to communicate with CMC (which were likely influenced by the older one-to-one model of CMC). For instance, while addressing someone by his or her first name might help build a sense of closeness and presence, the genre of CMC that takes place in online courses— especially in large threaded discussions—often makes it difficult to use certain types of social presence behaviors like addressing someone by her or his first name. For instance, when an instructor is addressing the class as a whole, it does not make sense to begin a post by mentioning everyone’s name. Further, while it might make sense to begin an initial reply to someone’s post by stating her or his first name (to build cohesion), as a thread continues and the posts go back and forth, an insistence on beginning each post with someone’s first name could influence the ebb and flow of a conversation and possibly hurt cohesion by making the conversation feel overly formal. Another example
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of the issues that arise when beginning a post with someone’s first name is that times occur when an instructor is responding to one student but wants to invite the entire class into the discussion. If an instructor begins the reply with the student’s name, then it may send a message to the other students that the post is only for that person and not the rest of the class. Another situational variable that is given very little attention in social presence theory in general and specifically in the CoI framework (see Garrison et al., 2000) is how one’s role or status can influence not only how but what one communicates and how one is perceived as being “there” or being “real.” For instance, it is reasonable to assume that students in an online course—even in a so called “learner centered” course—are more interested in what their instructor has to say than their peers (if only because the instructor will be assigning their grade at the end of the semester). In fact, eCollege—a Learning Management System used at the University of Colorado Denver—recently started highlighting instructors’ posts with a different color to differentiate them from the rest—thus suggesting that instructors’ posts are different than students’ posts. While the CoI framework has an element called “teaching presence,” as mentioned earlier, it focuses on how instructors design and organize a course, facilitate discourse, and provide direct instruction. Teaching presence, though, does not specifically address how an instructor establishes his or her own social presence, especially given the added task of direct instruction and facilitating discourse. I have argued elsewhere (Lowenthal & Lowenthal, 2010), in part building on the work of Swan and Shih (2005) and their differentiation between students’ and instructors’ social presence, that one problem with the CoI framework is that it does not differentiate
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(or really even acknowledge) how an instructor might establish his or her social presence differently than students. In my experience, instructors often talk differently than their students—this happens both in face-to-face classrooms and online. Further, each instructor has her or his own style and level of comfort in the classroom. While some instructors share parts of their personality and will engage in affective types of communication, others will not. Further, while instructors might build opportunities to establish social presence in their own online courses—in my experience, they often will not engage in these activities with students. The bottom line is that when instructors talk (i.e., post), students tend to listen (i.e., read). This is not always the case when other students talk. Students are not always as interested in what their peers say as in what their instructor says. I often think about what instructors do to establish their own social presence and how the little things they do (because of their status) can carry even more weight than if a fellow student did the exact same thing. For instance, I posit that, when an instructor engages in affective communication (e.g., sharing emotion or self-disclosing), it carries more weight than when a student does the same thing. Further, and because of the difference in roles and status, students tend to talk to an instructor differently than to their peers (i.e., code switch; see White & Lowenthal, 2011). But none of these dynamics are considered when researchers study social presence. Further, as the result of this study, I have begun thinking about ways that instructors and students can actually thwart social presence. For instance, what happens when a student posts a question that nobody acknowledges or responds to? While this likely happens in most courses at least once a semester—if only because some students
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post at the last minute in a given week—as a result of this study, I have begun thinking about how detrimental it can be if a student self-discloses personal information or shares emotional things and nobody responds or acknowledges it. Occurrences like this could possibly result in students feeling alienated and not acknowledged as being “there” and “real.” But so much of the literature on social presence focuses on what people do to establish social presence rather than on things people can do to thwart social presence. Short et al. (1976) originally studied types of communication that were not only one-to-one but also ongoing in the given moment. I contend that asynchronous threaded discussions in online courses that take place over time, involve a many-to-many model, likely involve students who have past relationships with each other (e.g., from past courses) and likely future relationships (e.g., future courses), and consist of individuals who are most likely paying money to be involved in the threaded discussions (and therefore have some extra motivation to effectively communicate with one another and their instructor) are a bit more complicated than Short et al. and possibly even Rourke et al. (2001a) could have originally imagined. I also contend that situational variables like these need to be considered when studying social presence. For instance, while content analysis is a useful technique to study online discussions, quantitative measures or counts of social presence behaviors might have limited value—especially when they do not take into consideration the context in which social behaviors are used. Unit of Analysis Among other things, the unit of analysis one uses when conducting content analysis influences the frequency of social presence indicators. For instance, following past researchers’ lead (e.g., Rourke et al., 2001a and Swan, 2003), for this study I used
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the entire discussion post as the unit of analysis. While I do not regret this decision, I now recognize that the unit of analysis one chooses can largely determine what one sees and what one does not see in her or his findings. I assert that when researchers approach analyzing online threaded discussions from a purely quantitative content-analysis perspective—frequency counts are everything. If researchers only count a specific indicator of social presence (e.g., use of emotion) once in a post because the post is the unit of analysis, he or she is likely to miss some details. For instance, you can imagine how many times students might use the word “we” as a group reference within a single post in small-group discussions focused on a group project. But if the unit of analysis is simply the entire post, the high frequency of the use of the word “we” may be lost in the totality of the words. I posit that the frequency of this group reference—the word “we”—would be captured more accurately if the unit of analysis was smaller than the entire post (e.g., each meaningful unit). For example, if a discussion post has the group reference “we” five times in the post, this indicator of social presence would only be counted once if the unit of analysis is the entire post but might be counted up to five times if the unit of analysis was a meaningful unit (which is not always but often the sentence level). Researchers have written much about the ideal unit of analysis when using content analysis to code online discussions (De Wever, Schellens, Valcke, & Van Keer, 2006; Rourke & Anderson, 2004; Rourke, Anderson, Garrison, & Archer, 2001b). Unfortunately, very little consensus exists on which is the best approach to take because while one might gain granularity with using a smaller unit of analysis, interrater reliability decreases and workload increases. I finally decided to stick with using the
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entire discussion post as my unit of analysis after hearing Wise (Wise & Chiu, 2011) justify her decision for using the entire post as her unit of analysis at AERA. She argued that students read and therefore interact with and make meaning from each post in threaded discussions not with each paragraph or word. Future research must investigate how the unit of analysis influences content analysis results of threaded discussions. Problems with the Social Presence Indicators and Treating Them Equally To truly understand social presence, researchers ideally should look at both students’ attitudes of social presence as well as students’ behaviors online. In other words, researchers need to get a better idea of what specific behaviors elicit perceptions of “closeness” and “realness” in others. The indicators of social presence are a great start but they have limitations (as touched on earlier). For instance, when using them to conduct content analysis, a researcher is supposed to identify when they find an instance of each indicator. Let’s take greetings and salutations as an example. The problem with this is that greetings and salutations, while similar, are two different things. For instance, one could argue that someone who continually uses a salutation more than a greeting is focusing more on themselves than on acknowledging others in a given threaded discussion. Further, a greeting with a vocative (e.g., “Hi John”) is arguably better at developing a sense of presence and projecting oneself as “real” and “there” than either “Hi” or ending a post with one’s first name. Similarly, the current coding sheet lists paralanguage as a type of affective communication that establishes social presence. The problem, though, with using paralanguage as an indicator of social presence is two fold: First, all uses of paralanguage are not necessarily equal; second, students use paralanguage differently. Regarding the
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first point, some students appear to be chronic users of ellipses and seem to almost use them as a period or a pause rather than in an emotive sense. This use of paralanguage is different than intentional uses of emoticons and should arguably be treated as being different. Secondly, paralanguage—especially the use of anything more than emoticons—seems to be a learned behavior that only certain types of students use. In other words, if a student is likely to express her or himself in ALL CAPS or with !!!!, then he or she is likely to do it again, whereas other students never seem to use this type of communication in threaded discussions. Treating all uses of emotion equally raises other issues. For instance, students may use the word “hope” but do not appear to be using it in an emotional sense. Similarly, other students use the word “thanks” as a habitual salutation rather than as a sign of appreciation. Given this, it might be more useful for researchers to identify levels of each indicator. For instance, researchers can identify instances of emotive text but then they must identify whether it’s a strong, medium, or soft use. One way to address some of this is to be able to interact with the participants as one codes the threaded discussions. In other words, member checking might be an essential component when identifying social presence behaviors because reading the text alone might not be enough. Or even better, a researcher should be able to check both the original poster (about intent) as well as all faculty and students about how they perceived the so-called social presence behavior because analyzing online discussion behaviors without intent and how the communication behaviors (i.e., the language used in the postings) are perceived is limiting from both a design and a research perspective.
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Another problem—which I mentioned in Chapter 1—focuses on researchers’ tendency to treat all three categories and subsequent indicators of social presence equally. As I mentioned in Chapter 2, some researchers tend to define social presence as not only presenting oneself as “real” and “there” but also establishing a positive emotional connection with others. In this case, it makes sense that while interactive and cohesive types of communication are important and possibly necessary building blocks for affective communication, affective communication is the best way to build an emotional connection with others. In other words, simply ending a discussion posting with a salutation is not near as powerful as disclosing personal information. Further research though is needed to test this theory. Problems with Measuring the Community of Inquiry One final observation involves a conflict between the Community of Inquiry Questionnaire—which was developed relatively recently by a team of CoI researchers (Arbaugh et al., 2008; Swan et al., 2008)—and the indicators of social presence developed by Rourke et al. (2001a). To illustrate my point, Table 5.3 lists the Community of Inquiry Questionnaire questions for social presence next to Rourke et al.’s original indicators.
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Table 5.3 Measuring Social Presence in a Community of Inquiry Community of Inquiry Questionnaire Affective expression 14. Getting to know other course participants gave me a sense of belonging in the course. 15. I was able to form distinct impressions of some course participants.
Indicators of Social Presence --Paralanguage --Emotion --Humor --Self Disclosure
16. Online or web-based communication is an excellent medium for social interaction. Open communication 17. I felt comfortable conversing through the online medium. 18. I felt comfortable participating in the course discussions.
--Acknowledgement --Agreement / Disagreement --Invitation --Expressing Appreciation
19. I felt comfortable interacting with other course participants. Group cohesion 20. I felt comfortable disagreeing with other course participants while still maintaining a sense of trust. 21. I felt that my point of view was acknowledged by other course participants.
--Greetings & Salutations / Phatics --Vocatives --Group Reference / Inclusivity --Embracing the Group
22. Online discussions help me to develop a sense of collaboration. While keeping in mind that the Community of Inquiry Questionnaire is meant to measure student's attitudes and perceptions and the indicators of social presence are meant to identify what students do and say, one would still expect to see more overlap between the two instruments. But when I look at the questions for affective expression and then the indicators for affective expression, I see very little overlap. First, the
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Community of Inquiry Questionnaire has some strange questions that seem to focus more on the medium than on what a participant does. For instance, question 16 states “online or web-based communication is an excellent medium for social interaction.” Students are asked the degree to which they agree with this statement. But is it not possible that students might agree that CMC can be an excellent medium for social interaction but disagree that CMC has been well used in a specific course? Then question 14 appears to be inquiring about a student's sense of belonging but the social indicators do not address that. In fact, group cohesion and specifically group reference seem like better indicators of students’ feeling a sense of belonging to a group. The problems continue when one looks at open communication and group cohesion. My point or rather my insight is that researchers who use the Community of Inquiry Questionnaire to study social presence appear to be studying different things than those who use indicators of social presence. Limitations of the Study As I mentioned earlier and in Chapter 1, every study suffers from some type of limitation. Perhaps the first limitation of this study is the small sample size. While I intentionally chose this small sample as a starting point for my line of research, I recognize that multiple samples might have provided a nice point of comparison. Threaded discussions are rich and full of data for researchers to mine. But I have come to the conclusion that relying only on threaded discussions is limiting. A researcher misses the things that might be said in emails, over the phone, or even in assignments turned in to a drop-box. Recently, researchers (Archer, 2010; Shea et al., 2010; Shea et al., 2009; Shea, Vickers, et al., 2009; Shea & Vickers, 2010) have argued about the need to look at an entire course—rather than just threaded discussions or survey data—when
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studying the CoI. Like these researchers, I have found that another limitation of this study is that it only focused on what was posted in the threaded discussions. Last but not least, conducting content analysis without being able to check with students about the meaning behind their postings as well as how other students interpret their postings is also problematic and perhaps the biggest limitation of studies like this. Concluding Thoughts and Implications Despite the aforementioned limitations, the results of this study can be useful for researchers and practitioners alike. From a research perspective, the study suggests that social presence is much more complicated than previously conceptualized. While it is helpful to investigate how students establish and maintain social presence in online courses—which in this study was restricted to investigating postings in threaded discussions—the list of indicators of social presence originally developed by Rourke et al. (2001a) need to be revised. Further, multiple and mixed methods should be employed whenever possible to investigate not only what students do and say but also how these behaviors are perceived by others. Finally, and perhaps most importantly, researchers need to spend more time focusing on how situational variables, such as the size of the group, the instructional task, and the instructor’s role, in combination with personal preferences influence how social presence is established and maintained. Research, though, should inform practice. The results of this study, despite limitations, have a number of pedagogical implications that instructional designers and faculty alike can apply. For instance, the results of this study point to the importance of the intentional use of different types of group activities and threaded discussions. Much like in large lecture classrooms, students taking part in large threaded discussions might
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feel that their voice is lost, that it is simply too hard to reach out and be heard, and that it is too difficult to project one’s personality. Further, rather than having several small weekly threaded discussions, it might make more sense—at least from a social presence perspective—to include some longer project-based discussions with smaller groups that take place over multiple weeks. The results also argue for the importance of “positive” past relationships with students. Developing a traditional cohort model where students complete their entire program of study with the same group of students is one way to help leverage the power of past relationships to build social presence. This research, though, simply suggests that it might be advantageous in terms of social presence to have students take a few back-toback courses that build upon one another together, and involve the students in well orchestrated group work. This research also seems to suggest that having the same instructor teach more than one course (and possibly back to back) could be powerful in terms of leveraging past relationships between instructors and students—this though assumes the past relationships are positive. However, when it is not possible to have students complete their program of study in a cohort or take back-to-back courses, designers and faculty could focus on having both getting-to-know-you activities upfront as well as reconnecting activities throughout a given course (see Dunlap & Lowenthal, 2011, in press, for more on “getting to know you” strategies that can be used in the beginning of a course as well as throughout a course). Finally, it is likely that a magic social presence formula does not exist. Each student might have her or his own sensitivity to and proficiency at projecting her- or
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himself as “real” and being “there” and specifically establishing connections with others. Therefore, instructors and designers must try to find multiple and continual ways for students and instructors to present themselves as “real” and “there” in threaded discussions as well as other parts of online courses. For instance, some of the strategies I have used and written about with colleagues to establish and maintain social presence involve using digital stories (see Lowenthal & Dunlap, 2007, 2010), using social media (see Dunlap & Lowenthal, 2009a, 2009b), using digital music (see Dunlap & Lowenthal, 2010b), giving feedback publicly (see Lowenthal & Thomas, 2010), and making one-onone phone calls to students (see Dunlap & Lowenthal, 2010a). Given all of this, and in conclusion, designers and faculty should consider the following elements the next time that they design or teach a course: •
Set up a variety of small-group discussion groups;
•
Provide well structured small-group assignments that take time and collaboration to complete;
•
Balance instructor involvement;
•
Establish incentives for students to take part in threaded discussions;
•
Use a variety of instructional tasks and discussion prompts—some of which ask for students to share personal and emotional details (when appropriate).
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APPENDIX A Social Presence Measures Table A1 Feelings about CMC 1. Stimulating-dull 2. Personal-impersonal 3. Sociable -unsociable 4. Sensitive-insensitive 5. Warm-cold 6. Colorful-colorless 7. Interesting-boring 8. Appealing-not appealing 9. Interactive-noninteractive 10. Active-passive 11. Reliable-unreliable 12. Humanizing-dehumanizing 13. Immediate-non-immediate 14. Easy-difficult 15. Efficient-inefficient 16. Unthreatening-threatening 17. Helpful-hindering Note. From “Social Presence Theory and Implications for Interaction and Collaborative Learning in Computer Conferences,” by C. N. Gunawardena, 1995, in International Journal of Educational Telecommunications, 1(2/3), 147-166.
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Table A2 Social Presence Scale 1. 2. 3. 4. 5. 6. 7. 8. 9.
Messages in GlobalEd were impersonal. CMC is an excellent medium for social interaction. I felt comfortable conversing through this text-based medium. I felt comfortable introducing myself on GlobalEd. The introduction enabled me to form a sense of online community. I felt comfortable participating in GlobalEd discussions. The moderators created a feeling of online community. The moderators facilitated discussions in the GlobalEd conference. Discussions using the medium of CMC tend to be more impersonal than faceto-face discussion. 10. CMC discussions are more impersonal than audio conference discussions. 11. CMC discussions are more impersonal than video teleconference discussions. 12. I felt comfortable interacting with other participants in the conference. 13. I felt that my point of view was acknowledged by other participants in GlobalEd. 14. I was able to form distinct individual impressions of some GlobalEd participants even though we communicated only via a text-based medium. Note. From “Social Presence as a Predictor of Satisfaction Within a Computer-mediated Conferencing Environment,” by C. N. Gunawardena and F. J. Zittle, 1997, in The American Journal of Distance Education, 11(3), 8-26.
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Table A3 Model and Template for Assessment of Social Presence Category Affective Responses
Indicators Expression of emotions Use of Humor Self-Disclosure
Interactive Responses
Continuing a Thread Quoting from Other Messages Referring explicitly to other messages Asking questions
Cohesive Responses
Complimenting, expressing appreciation Expressing agreement Vocatives
Definition of Indicators Conventional expressions of emotion, or unconventional expressions of emotion, includes repetitious punctuation, conspicuous capitalization, emoticons Teasing, cajoling, irony, understatements, sarcasm Presents details of life outside of class, or expresses vulnerability Using reply feature of software, rather than starting a new thread Using software features to quote others entire message or cutting and pasting sections of others’ messages Direct references to contents of others’ posts Students ask questions of other students or the moderator Complimenting others or contents of others’ messages
Expressing agreement with others or content of others’ messages Addressing or referring to participants by name Addresses or refers to Addresses the group as we, us, our, group the group using inclusive pronouns Phatics / Salutations Communication that serves a purely social function; greetings, closures
Note. From “Assessing Social Presence in Asynchronous Text-based Computer Conferencing,” by L. Rourke, D. R. Garrison, and W. Archer, 2001a, in Journal of Distance Education, 14.
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Table A4 Additional Social Presence Variables Dimensions I. Social Context
II. Online Communication
III. Interactivity
IV. Privacy
Familiarity with recipients
Keyboarding and accuracy skills
Timely Response
Formats of CMC
Assertive / acquiescent
Use of emoticons and paralanguage
Communication Styles
Access and Location
Informal/formal relationship
Characteristics of real-time discussion
Length of Messages
Patterns of CMC
Trust relationships
Characteristics of discussion boards
Formal/Informal
Social relationships (love and information)
Language skills (reading, writing)
Type of tasks (planning, creativity, social tasks)
Psychological attitude toward technology
Size of Groups
Access and location
Communication strategies
User’s characteristics Note. From “The Relationship of Social Presence and Interaction in Online Classes,” by C.-H. Tu and M. McIsaac, 2002, in The American Journal of Distance Education, 16(3), 131-150.
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Table A5 Community of Inquiry Survey Instrument 5 point Likert scale 1=strongly disagree, 2=disagree, 3=neutral, 4=agree, 5=strongly agree Teaching Presence Design & Organization 1. The instructor clearly communicated important course topics. 2. The instructor clearly communicated important course goals. 3. The instructor provided clear instructions on how to participate in course learning activities. 4. The instructor clearly communicated important due dates/time frames for learning activities.
Facilitation 5. The instructor was helpful in identifying areas of agreement and disagreement on course topics that helped me to learn. 6. The instructor was helpful in guiding the class towards understanding course topics in a way that helped me clarify my thinking. 7. The instructor helped to keep course participants engaged and participating in productive dialogue. 8. The instructor helped keep the course participants on task in a way that helped me to learn. 9. The instructor encouraged course participants to explore new concepts in this course. 10. Instructor actions reinforced the development of a sense of community among course participants.
Direct Instruction 11. The instructor helped to focus discussion on relevant issues in a way that helped me to learn. 12. The instructor provided feedback that helped me understand my strengths and weaknesses. 13. The instructor provided feedback in a timely fashion.
Social Presence Affective expression 14. Getting to know other course participants gave me a sense of belonging in the course. 15. I was able to form distinct impressions of some course participants. 16. Online or web-based communication is an excellent medium for social interaction.
Open communication 17. I felt comfortable conversing through the online medium. 18. I felt comfortable participating in the course discussions. 19. I felt comfortable interacting with other course participants.
Group cohesion 20. I felt comfortable disagreeing with other course participants while still maintaining a sense of trust. 21. I felt that my point of view was acknowledged by other course participants. 22. Online discussions help me to develop a sense of collaboration.
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Table A5 (con’t.) Cognitive Presence Triggering event 23. Problems posed increased my interest in course issues. 24. Course activities piqued my curiosity. 25. I felt motivated to explore content related questions.
Exploration 26. I utilized a variety of information sources to explore problems posed in this course. 27. Brainstorming and finding relevant information helped me resolve content related questions. 28. Online discussions were valuable in helping me appreciate different perspectives.
Integration 29. Combining new information helped me answer questions raised in course activities. 30. Learning activities helped me construct explanations/solutions. 31. Reflection on course content and discussions helped me understand fundamental concepts in this class.
Resolution 32. I can describe ways to test and apply the knowledge created in this course. 33. I have developed solutions to course problems that can be applied in practice. 34. I can apply the knowledge created in this course to my work or other non-class related activities.
Note. From “Validating a Measurement Tool of Presence in Online Communities of Inquiry,” by K. Swan, P. Shea, J. Richardson, P. Ice, D. R. Garrison, M. Cleveland-Innes, and J. B. Arbaugh, 2008, in E-Mentor, 2(24), 1-12.
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APPENDIX B Word Count Results Table B1 Word Count Results across All Forums Rank 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50
Word I you have we my what do your can policy me all about bob so instructor think our work would one how reading week from some more just know need get group doc also an well out school like good thanks here which other should data i’m paper could research
Count 4858 2186 1428 1367 1001 948 814 810 730 600 595 592 574 566 565 564 553 538 494 482 456 454 428 421 414 414 407 392 390 383 381 348 346 345 341 334 328 324 320 318 313 302 288 281 275 264 264 261 254 251
Percentage (%) 4.13 1.86 1.21 1.16 0.85 0.81 0.69 0.69 0.62 0.51 0.51 0.50 0.49 0.48 0.48 0.48 0.47 0.46 0.42 0.41 0.39 0.39 0.36 0.36 0.35 0.35 0.35 0.33 0.33 0.33 0.32 0.30 0.29 0.29 0.29 0.28 0.28 0.28 0.27 0.27 0.27 0.26 0.24 0.24 0.23 0.22 0.22 0.22 0.22 0.21
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Table B2 Word Count Results across Project Groups Rank 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50
Word I you we have what do can your may our all think my so data policy would some need me about from paper work how draft just know also bob instructor more out should thanks get schools mary here good doc like could group make project week school programs well
Count 1674 729 678 497 387 267 261 258 255 251 241 221 215 214 202 193 184 181 176 173 171 169 169 166 161 155 150 150 144 142 142 139 136 133 132 130 127 125 122 120 118 114 112 112 111 111 111 109 108 107
Percentage (%) 4.08 1.78 1.65 1.21 0.94 0.65 0.64 0.63 0.62 0.61 0.59 0.54 0.52 0.52 0.49 0.47 0.45 0.44 0.43 0.42 0.42 0.41 0.41 0.40 0.39 0.38 0.37 0.37 0.35 0.35 0.35 0.34 0.33 0.32 0.32 0.32 0.31 0.30 0.30 0.29 0.29 0.28 0.27 0.27 0.27 0.27 0.27 0.27 0.26 0.26
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Table B3 Word Count Results across Pairs Rank 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50
Word I you my have we your me what do work about goals can our how school time teachers goal some would think bob instructor need know so an week well all out been like more one also from just get see good when where i’m each help students other plan
Count 960 438 339 291 209 189 148 145 130 123 119 116 110 102 100 97 88 85 84 82 82 79 76 76 75 73 72 71 66 65 63 62 61 61 60 60 59 58 57 55 55 54 54 54 53 52 52 52 51 50
Percentage (%) 4.87 2.22 1.72 1.48 1.06 0.96 0.75 0.74 0.66 0.62 0.60 0.59 0.56 0.52 0.51 0.49 0.45 0.43 0.43 0.42 0.42 0.40 0.39 0.39 0.38 0.37 0.37 0.36 0.34 0.33 0.32 0.31 0.31 0.31 0.30 0.30 0.30 0.29 0.29 0.28 0.28 0.27 0.27 0.27 0.27 0.26 0.26 0.26 0.26 0.25
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Table B4 Word Count Results across Reading Groups Rank 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50
Word I you have we what do policy my can reading your one about all think me so instructor bob week summary doc would more how our get from questions work just log group which an know research some well democratic good Lasswell also chapter here has like thanks heck any
Count 1784 802 532 416 358 348 344 328 297 293 283 255 242 231 227 226 225 222 221 202 196 190 185 175 171 165 164 162 161 156 155 151 141 141 139 138 138 138 131 130 128 128 126 122 122 117 115 114 113 112
Percentage (%) 3.79 1.70 1.13 0.88 0.76 0.74 0.73 0.70 0.63 0.62 0.60 0.54 0.51 0.49 0.48 0.48 0.48 0.47 0.47 0.43 0.42 0.40 0.39 0.37 0.36 0.35 0.35 0.34 0.34 0.33 0.33 0.32 0.30 0.30 0.29 0.29 0.29 0.29 0.28 0.28 0.27 0.27 0.27 0.26 0.26 0.25 0.24 0.24 0.24 0.24
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APPENDIX C Constant Comparison Analysis Results Table C.1 Reading Group E Codes Acknowledging lack of knowledge Addressing question
Codes Generated Greeting Happiness
Advice Agreement Answer Answering questions Anticipation Apology Appreciation Assignment discussion
Heading Hope Hoping for help Humor Justification of example Likes course reading Note Opinion
Belief Bias Clarification Commitment to more discussion Complimenting texts Contextualizing Point Critique Critique of writing Discussing Reading Discussing policy Doubt Empathy Enjoyment Example Example of criticism Excitement Explaining struggles Explanation General Policy Discussion Grade details
Paralanguage Personal course interests Personal example Personal interest in course stuff Personal interest in reading Personal Life Details Personal story Personal study details Personalization of Material Philosophical Discussion Plan Plea Policy answer Positive feedback Positive thinking Question Quotation Reading discussion Recommendation Recommending other sources
Reflection Reflection about course material Relating Relating to Others Research discussion Resource Resource recommendation Response Reveal life outside of class Reveal life outside of class as relates to class Reveal problems Reveal struggling Reveals lack of knowledge Salutation Shares thinking about thinking Shares thoughts about reading Sharing thoughts Sharing values Showing relevance Story example Thinking about reading Thinking about the course Thinking about thinking Thought Thoughts about policy Thoughts about reading Vocative Wonder Worth mentioning
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Table C.2 Reading Group E Groups Grouping of Codes Course logistics & facilitation Addressing question Answering questions Critique Critique of writing Grade details Heading Question Advice Recommendation Recommending other sources Emotion Anticipation Paralanguage Apology Doubt Empathy Enjoyment Excitement Happiness Hope Hoping for help Plea Humor Greetings and Salutations Greeting Salutation Vocative Sharing Life Details Personal example Personal story Story example Reveal life outside of class Reveal life outside of class as relates to class Personal Life Details Personal study details Gracious / Gratitude Appreciation Positive feedback Positive thinking Self Disclosing Personal Matters Explaining struggles Acknowledging lack of knowledge Reveal problems Reveal struggling Reveals lack of knowledge Sharing values
Policy Related Class Discussions Reflection Reflection about course material Thinking about reading Thinking about the course Thinking about thinking General Policy Discussion Discussing reading Discussing policy Thoughts about policy Thoughts about reading Policy answer Shares thinking about thinking Shares thoughts about reading Sharing thoughts Research discussion Showing relevance Belief Bias Thought Wonder Worth mentioning Response Resource Resource recommendation Personal interest in course stuff Personal interest in reading Plan Personalization of Material Philosophical Discussion Complimenting texts Contextualizing Point Justification of example Likes course reading Note Opinion Assignment discussion Quotation Reading discussion Example Example of criticism Clarification Commitment to more discussion Personal course interests Answer Explanation Playing Nice with Others Agreement Relating Relating to Others
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Table C.3 Pair9 Codes
Acknowledgement Agreement Answer to question Anticipation Appreciation Assignment details Assignment discussion Best wishes Brainstorming Commitment Concern Confidence in peers Course planning Doubt Emotion Enjoyment
Codes Generated Positive feedback Positive self assessment Question Question about meeting Reassurance Recommendation Reference education literature Reflection Relating Relating to others Request Reveal uncertainty Revealing concerns Revealing life in other courses Revealing struggles Revealing thinking
Explanation
Revealing unawareness
Explanation for struggles Feeling overwhelmed Greeting Happiness Heading Hope Inquiring about life outside of course Introspection invitation Likes idea Paralanguage Personal sharing Plan to collaborate Plans Plans to meet
Salutation Self assessment Self disclosure Sharing course plans Sharing plans Sharing successes Thanks Thinking about policy Thinking out loud Thoughts on assignments Thoughts on instructor Thoughts on leadership Understanding task Vocative
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Table C.4 Pair9 Groups Course logistics & facilitation Recommendation Question Request invitation Understanding task Assignment details Assignment discussion Heading
Collaboration Question about meeting Course planning Plan to collaborate Plans Plans to meet Sharing course plans Sharing plans
Emotion Concern Anticipation Happiness Doubt Emotion Enjoyment Feeling overwhelmed Hope Paralanguage
Sharing Life Details Introspection Personal sharing Reflection Self assessment Revealing life in other courses Positive self assessment Sharing successes Inquiring about life outside of course
Playing Nice with Others Relating Relating to others Acknowledgement Agreement Answer to question Likes idea Confidence in peers Commitment Reassurance
Policy Related Class Discussions Reference education literature Brainstorming Thinking about policy Thinking out loud Thoughts on assignments Thoughts on instructor Thoughts on leadership Revealing thinking Explanation
Self Disclosing Personal Matters Revealing unawareness Revealing struggles Self disclosure Reveal uncertainty Revealing concerns Explanation for struggles
Gracious / Gratitude Positive feedback Best wishes Appreciation Thanks Greetings and Salutations Greeting Vocative Salutation
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