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2012 thesis correlation between undergraduate college students facebook use and co curicular involvement
 

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    2012 thesis correlation between undergraduate college students facebook use and co curicular involvement 2012 thesis correlation between undergraduate college students facebook use and co curicular involvement Document Transcript

    • CORRELATION BETWEEN UNDERGRADUATE COLLEGE STUDENTS‟ FACEBOOK USE AND CO-CURRICULAR INVOLVEMENT A Thesis Submitted to the School of Graduate Studies and Research in Partial Fulfillment of the Requirements for the Degree Master of Arts Christopher Steven Weiss Indiana University of Pennsylvania May 2012
    • ii Indiana University of Pennsylvania School of Graduate Studies and Research Department of Student Affairs in Higher Education We hereby approve the thesis of Christopher Steven Weiss Candidate for the degree of Master of Arts _____________ _________________________________________________ John W. Lowery, Ph.D. Associate Professor of Student Affairs in Higher Education, Advisor _____________ _________________________________________________ Holley A. Belch, Ph.D. Professor of Student Affairs in Higher Education _____________ _________________________________________________ John A. Mueller, Ed.D. Professor of Student Affairs in Higher Education ACCEPTED ____________________________________________ _____________________ Timothy P. Mack, Ph.D. Dean School of Graduate Studies and Research
    • iii Title: Correlation between Undergraduate College Students‟ Facebook Use and Co-Curricular Involvement Author: Christopher Steven Weiss Thesis Chair: Dr. John Wesley Lowery Thesis Committee Members: Dr. John Mueller Dr. Holley A. Belch This study determined if a correlation existed between college students‟ Facebook use and co-curricular involvement. While Facebook use has exploded in the past decade, research on how this phenomenon affects college students and student affairs professionals is limited. For the purpose of this study, Facebook use was quantified in terms of minutes of use, frequency of logging in, and services utilized; and involvement was measured by how much time and in what way students participated in co-curricular activities and utilized campus resources. A statistically significant, but weak, positive correlation was found between the amount of time participants‟ spent on Facebook the previous day and the number of hours per week they participated in activities outside of the classroom (r = .137, p < .05). Student affairs professionals should understand the results of this study in order to effectively promote student involvement in an environment dominated by Facebook use.
    • iv ACKNOWLEDGMENTS I am so thankful for those who have played a role in my work on this thesis over the last 15 months. This has been an extremely meaningful experience and journey, and my ability to complete this project would not have been possible without their support. As my thesis advisor, Dr. John Wesley Lowery has played an immense role in my work on this thesis. His countless hours of reading and revising, and ability to cut through my manuscripts to get me to explain what I really meant, have been invaluable to the work I have presented and my growth as a scholar. He has been an amazing teacher, support system, and role model in my academic growth, which has instilled in me the confidence and passion to continue to pursue my role as a scholar and researcher. I would like to thank the rest of my faculty committee, Dr. Holley Belch and Dr. John Mueller. They consistently pushed me to write clearer and more professionally. Dr. Mueller played an integral role in the selection and narrowing of my research topic. Dr. Belch provided her excellent detailed eye and high standards for implementing the style guide used in this work. I would also like to thank Dr. Reynol Junco for his support throughout my research. Dr. Junco was very gracious in letting me use his latest instrument. I highly valued his assistance with several questions that I had through my research process, and his positive feedback and genuine interest in my work were very motivational. I also must recognize the support of my friends and family, who have understood and supported me in every way. While I certainly did not give them enough of my time and energy while working on this thesis, I could not be more grateful to them for welcoming me back after this work was complete.
    • v I am delighted to thank Hannah, the most wonderful partner any researcher could ask for. Hannah has been so incredibly supportive, even though I usually chose to spend time on this thesis rather than with her. She never made me feel guilty for the work I was doing, and always showed that she valued it as much as I did. While she claims I would have been able to complete this thesis without her support, I can say with absolute certainty that without her I would have been miserable the entire time. For all the batches of cookies and cups of tea she made during long nights of writing and researching, I truly thank her for always standing by my side. I greatly anticipate our next adventure together, and every day I am inspired by what the future holds for us. Last, and perhaps most importantly, I would like to thank my supervisor, mentor, and friend Julene Pinto-Dyczewski, who in so many ways has been the most influential person to me over the last two years. Jules is by far the best student affairs professional and supervisor I have ever met, and exemplifies the perfect model of integrating theory into practice. Jules truly embodies the power of positive reinforcement and the critical role it plays in human development, interpersonal relationships, and educating students, and this thesis is an example of her success in encouraging me to complete this work. Jules has affected my overall growth and development as a professional and a person more than any other individual over the last two years. I am so grateful for her support in being flexible with my assistantship around the needs of this thesis, and all around for how much she has taught me these past two years, which I hope is reflected in this thesis. From the bottom of my heart, I truly thank all of these individuals. Not a moment goes by that I am not aware of how fortunate I am to have been surrounded by such amazing people who have helped me to accomplish so much.
    • vi TABLE OF CONTENTS Chapter Page One THE PROBLEM………………………………………………………..1 Statement of the Problem……………………………………………… 1 Facebook………………………………………………………………. 2 Involvement…………………………………………………………….3 The Relationship between Involvement and Facebook Use……………4 Negative correlation…. .....………………………………………4 Positive correlation ………………………………………………5 Research Questions ...………………………………………………...7 Significance…………………………………………………………….9 Summary………………………………………………………………11 Two LITERATURE REVIEW.……………………………………………..12 College Students……………….……………….……………………..12 Characteristics of the College Student Population……………….12 Millennial generation……………….………..………………13 Digital natives……………….……………….……………....13 Proliferation of Technology on Campus……………….………...16 Mobile use……………….……………….……………….….16 Campus support for technology……………….……………..17 Summary……………….……………….……………….……….18 College Student Involvement…............................…........................…19 Involvement Theory….….….….….….….….….….….….….…..20 Involvement vs. Engagement….….….….….….….….….….…...22 Benefits of Involvement….….….….….….….….….….….….….26 Satisfaction….….….….….….….….….….….….….….….…26 Student development….….….….….….….….….….….….…28 Persistence….….….….….….….….….….….….….….….….32 Measures of Involvement….….….….….….….….….….….……34 Hours of involvement….….….….….….….….….….….…... 35 National Study of Student Engagement (NSSE) scales….…..36 Extracurricular Involvement Inventory (EII) ….….….….…..37 College Student Experiences Questionnaire (CSEQ) ….……37 For the current study….….….….….….….….….….….….…39 Summary….….….….….….….….….….….….….….….….……39 Facebook Use Among College Students….….….….….….….….…...40 Definitions and Contextualization….….….….….….….….….… 40 Services offered by Facebook….….….….….….….….….….41 College students‟ use of Facebook….….….….….….….…... 42 Mobile Facebook use….….….….….….….….….….….……44 Negative Outcomes Associated with Facebook Use….…….…... 45 Facebook depression….….….….….….….….….….….…….46 Narcissism….….….….….….….….….….….….….….….….47 Stress….….….….….….….….….….….….….….….….……49
    • vii Chapter Page Drinking and partying.…......….….….….….…........….….....49 Distraction................................................................................50 Positive Outcomes Associated with Facebook Use.......................50 Sharing information and opportunities.................................... 51 Transition to college................................................................ 52 Diversity...................................................................................53 Facebook therapy.....................................................................54 Social capital............................................................................55 Offline social life..................................................................... 57 Measures of Facebook Use............................................................58 Facebook Intensity Scale......................................................... 58 Net.Generation survey............................................................. 58 Junco‟s (2012) Facebook instrument.......................................59 For the current study................................................................60 Summary........................................................................................60 Facebook and Involvement....................................................................61 Negative Relationship....................................................................62 No Relationship............................................................................. 64 Foregger‟s (2008) study...........................................................64 Ericson‟s (2011) study.............................................................65 Positive Relationship..................................................................... 66 The Higher Education Research Institute‟s (HERI; 2007) analysis.....................................................................................66 Heiberger and Harper‟s (2008) study...................................... 67 Junco‟s (2012) study................................................................67 Summary........................................................................................68 Summary of Literature.......................................................................... 69 Conclusion.............................................................................................71 Three METHOD..............................................................................................72 Methodology..........................................................................................72 Sample...................................................................................................72 Descriptive Statistics......................................................................73 Instrumentation......................................................................................76 Facebook Instrument......................................................................76 College Student Experiences Questionnaire..................................77 Demographics................................................................................ 80 Procedures............................................................................................. 80 Data Analysis.........................................................................................81 Conclusion.............................................................................................82 Four RESULTS..............................................................................................83 Preliminary Analysis............................................................................. 83 Facebook Usage.............................................................................83 Involvement................................................................................... 88
    • viii Chapter Page Primary Analysis................................................................................... 90 Correlations between Facebook Use and Involvement..................90 Factor analysis......................................................................... 94 Controlling for Demographics.......................................................96 Conclusion.............................................................................................97 Five DISCUSSION AND IMPLICATIONS.................................................98 Discussion of the Findings.................................................................... 99 Preliminary Findings......................................................................99 Facebook use............................................................................99 Co-curricular involvement.....................................................102 Primary Analysis..........................................................................104 Limitations...........................................................................................109 Implications.........................................................................................110 Implications for Theory ...............................................................110 Implications for Research ............................................................111 Implications for Practice .............................................................114 Summary and Conclusion ...................................................................118 REFERENCES................................................................................................................120 APPENDICES.................................................................................................................133 Appendix A - Junco‟s (2012) Facebook Instrument....................................................133 Appendix B - College Student Experiences Questionnaire (CSEQ) ...........................138 Appendix C - Demographic Data ................................................................................141 Appendix D - INFORMED CONSENT FORM ..........................................................144 Appendix E - Email Inviting Students to Participate ...................................................145 Appendix F - Institution Review Board Approval .......................................................146 Appendix G - CSEQ Item Usage Agreement ..............................................................147 Appendix H - Spearman‟s rho Correlations between Facebook Items ( N = 207) ......149
    • ix LIST OF TABLES Table Page 1 Descriptive Statistics for Participants.....................................................................75 2 Time Spent on Facebook among Participants.........................................................84 3 Number of Times Facebook was Checked among Participants..............................85 4 Frequency of Performing Facebook Activities among Participants.......................86 5 Involvement in Activities Outside of the Classroom among Participants..............89 6 Involvement Response among Participants............................................................90 7 Pearson‟s r Correlations between Level of Facebook Use and Involvement Measures..................................................................................................................90 8 Spearman‟s rho Correlations between Facebook Activities and Involvement Measures..................................................................................................................91 9 Rotated Component Matrix.....................................................................................91 10 Correlations between Facebook Activity Scales and Involvement Measures........96
    • 1 CHAPTER ONE THE PROBLEM This thesis describes a study to determine if a correlation exists between the level and nature of undergraduate college students‟ Facebook use and co-curricular involvement within the campus community. This chapter will provide an introduction of the role that Facebook and co-curricular involvement play in the lives of undergraduate college students, and will establish the key constructs and significance of the study for stakeholders. The second chapter will discuss a review of the literature, and describe previous research conducted on both variables. The third chapter will then discuss the methodology used to conduct the study, including the instrumentation used, procedures of determining the sample and administering the survey, and statistical analysis techniques. That will be followed by a presentation of the results from the data collection of the study in the fourth chapter. Finally, the fifth chapter will present a discussion of the results, including potential meanings, limitations of the study, and implications for future theory, research, and practice. Statement of the Problem College students have always found ways to connect with each other (Horowitz, 1988). For the past two decades, technology has provided some of the most popular new ways for students to connect (Junco & Mastrodicasa, 2007). From the seemingly limitless opportunities of what it allows students to do, to the appeal of experimenting with new advanced devices, college students have always spent large amounts of time using technology (Junco & Mastrodicasa, 2007; Strange & Banning, 2001). Throughout this time, many professionals have worked to capitalize on this appeal and make these
    • 2 technologies educationally and developmentally purposeful; most often, these attempts have not been as successful as desired (Strange & Banning, 2001). The most recent evolution in technology that students have widely adopted is social media. Social media refers to websites and applications that individuals can use for social networking, where online communities of users develop interpersonal relationships and share user-generated content through a technological medium (Ericson, 2011; Junco & Chickering, 2010; Junco, Heiberger, & Loken, 2010). The three most common examples of social media services on college campuses are Facebook, Twitter, and YouTube. Studies have found that as many as 90% of college students are frequent users of social media (Junco, 2012; S. Smith & Caruso, 2010); this usage may play a role in the ways in which students relate to and communicate with each other (Junco & Mastrodicasa, 2007; Upcraft, 2007). Facebook Facebook is a large social media service created in 2004, where users generate profiles to connect and stay in touch with their friends and acquaintances. It began as a small service limited to students at Harvard University, and shortly thereafter expanded to Stanford, Columbia, and Yale, with nearly 1 million active users by the end of its first year. As access expanded to all college and high school students by the end of 2005, there were over 6 million active users. Facebook allowed anyone to join in 2006, and reached more than 12 million active users (“Statistics,” 2012). In 2011, there were over 845 million users, 50% of which logged in to the service daily (“Statistics,” 2012). Facebook is by far the social media service of choice for most college students: several studies have reported that over 85% of college students have an
    • 3 active Facebook account (Junco, 2012; S. Smith & Caruso, 2010; A. Smith, Rainie, & Zickuhr, 2011). In one study, college students on average used Facebook over 11.8 hours per week (Junco, 2012). Involvement Involvement is “the physical and psychological time and energy that students spend devoted to their college experience” (Astin, 1984, p. 235). When college students spend their time in educationally or developmentally purposeful activities on campus, they are spending their time productively involved. This definition focuses particularly on factors that facilitate development rather than the developmental process itself. Involvement theory is concerned solely with the behavior of involvement, and intentionally excludes the impact of involvement or students‟ perception of how it makes them feel (Astin, 1984; Evans, Forney, Guido, Patton, & Renn, 2010). A high intensity of co-curricular involvement is evident when students are markedly committed enough to a group or organization that they invest considerable time, psychic energy, and physical activity, for the pursuit of furthering the group‟s purposes (Davis & Murrell, 1993; Winston & Massaro, 1987). Many studies have shown significant positive relationships between students‟ level of involvement and their overall personal development and persistence to graduation (Astin, 1984, 1993; Kuh, 2009; Pascarella & Terenzini, 2005). The time and energy of students is by far the most valuable resource within an institution of higher education, even when compared to money, so it is important to understand the ways in which students are using this resource (M. Wilson, 2004). Student affairs professionals‟ primary responsibility on campus is to increase student involvement in developmentally
    • 4 purposeful activities (Evans et al., 2010). The Relationship between Involvement and Facebook Use Research has shown that students spend a significant amount of their time using Facebook (Junco, 2012; Manago, Taylor, & Greenfield, 2012). Involvement theory has stated that it is important for students to spend their time in educationally and developmentally purposeful activities (Astin, 1984). With that in mind, evidence will soon be presented to demonstrate the importance of determining if there is a correlation between undergraduate college students‟ level and nature of Facebook use and co- curricular involvement in these positive activities, and if a correlation exists, what its direction is. Consensus does not currently exist on this question, though the following studies have focused on similar constructs and offered insights into this specific relationship. Negative correlation. One common perception is that Facebook – like other forms of technology that preceded it – isolates students (Barkhuus & Tashiro, 2010). Althought it is in the very nature of Facebook to connect people online, technology usually does keep students physically separated from each other, and has the potential to limit face-to-face interaction (Coomes, 2004; Lowery, 2004). This could lead to a serious degeneration in an entire population of adults‟ ability to develop effective interpersonal skills, understand social cues, and confront interpersonal conflicts (Junco & Chickering, 2010). One study (Junco, 2012) found an overall negative correlation between the quantity of Facebook use, and student engagement and involvement in co-curricular activities. Specific Facebook behaviors linked to this negative correlation were playing
    • 5 games and checking up on friends. There was also a negative correlation between time spent on Facebook Chat and time spent preparing for class. These results suggested that Facebook use does require time and psychological energy, but overall that time and energy does not translate positively to co-curricular involvement (Junco, 2012). Positive correlation. On the other hand, authors (Heiberger & Harper, 2008; Higher Education Research Institute [HERI], 2007; Manago et al., 2012) have noted that students‟ use of Facebook can have a positive connection to involvement. One study (Manago, et al., 2012) found results that imply that students who spend more time involved in co-curricular activities come into contact with more individuals, who then have the potential to become Facebook friends. If the size of one‟s social network is linked to positive outcomes, and co-curricular activities increase the size of one‟s social network, then Facebook use and co-curricular involvement may be positively correlated (Manago et al., 2012). There is evidence that online interactions through Facebook do not remove users from the offline world, but indeed support and enhance offline relationships and social capital, which therefore increases users‟ participation in offline settings (Ellison, Steinfield, & Lampe, 2007; Manago et al., 2012). Students‟ involvement in this online community connects them to far more people than could be provided within a physical campus community. While earlier studies have stressed the importance of face-to-face communication in personal development (Astin, 1993; Pascarella & Terenzini, 2005), few have attempted to study the same developmental impact within the virtual landscape. Additionally, the intentional nature of editing one‟s profile could mean that students have the opportunity to self-select into various communities and migrate with ease, rather than
    • 6 being confined to their physical location or past placement (Martinez Aleman & Wartman, 2009). This idea of technology providing an intentional and socially reinforcing environment has existed before the invention of Facebook (Putnam, Feldstein, & Cohen, as cited in Lowery, 2004), and studies on social capital have supported Facebook‟s success in achieving this vision (Ellison et al., 2007; Manago et al., 2012). It has also been suggested that Facebook is the new student union, and that progressive leaders in higher education should shift their emphasis and resources from the physical building where students used to be, to the community on Facebook where the students of the 21st century spend their time (Heiberger & Harper, 2008). If Facebook use is linked to increased participation in developmental activities, it would be difficult to find the developmental difference between opportunities to participate in these activities on campus compared to on Facebook (Martinez Aleman & Wartman, 2009). Along those lines, some (Heiberger & Harper, 2008; Martinez Aleman & Wartman, 2009) have suggested that Facebook is not intrinsically devoid of the capability to provide developmental opportunities. Professionals should take advantage of opportunities to turn virtual spaces into developmentally beneficial environments – as they already have with physical spaces – in which students would want to participate (Heiberger & Harper, 2008; Junco, 2012; Martinez Aleman & Wartman, 2009). Since students communicate frequently through Facebook (Junco, 2012; Junco & Mastrodicasa, 2007), it is common for those who are already involved in campus activities to utilize this online space to attract other students to join them in their pursuits (Martinez Aleman & Wartman, 2009). Using Facebook as a campus bulletin board might change the role of the service from being its own distinct activity, to becoming merely a
    • 7 medium for others to share their activities happening on the physical campus. Within this online community, all student Facebook users have equal access to the information that others share, unlike posters that students hang in residence halls that preclude outsiders from ever becoming aware of certain opportunities, for example. In this way, Facebook could serve as a vehicle for the democratization of opportunities for campus involvement. Through increasing awareness of opportunities to participate in developmental activities, Facebook has the potential to increase productive behaviors of involvement regardless of how much time students spend on the service itself (Junco & Chickering, 2010; Martinez Aleman & Wartman, 2009). While these perspectives are enticing, existing research has not yet fully examined these issues. The debate on the relationship between Facebook use and productive and developmental levels of increased involvement continues (Junco & Chickering, 2010). For the most part, the argument is highly polarized with a wide array of opinionated speculations, with many positions lacking substantial supporting research (Junco, 2012). Some professionals have recognized how much time students spend on Facebook, and have therefore decided that they must incorporate it into their work of promoting students to become involved in campus activities (Olson & Martin, 2010). This rationale is weak, since the justification for using Facebook is unsubstantiated when the actual correlation between college students‟ level and nature of Facebook use and co-curricular involvement has not been fully established (Junco & Chickering, 2010). Research Questions Students‟ time is an invaluable resource (Astin, 1984). Many disagree about whether Facebook is a productive use of this time and how it relates to involvement
    • 8 (Cotton, 2008; Junco, 2012; Junco & Chickering, 2010). With that in mind, there is a need for specific research on the relationship between student use of Facebook and their co-curricular involvement. There are two research questions for this study: Is there a correlation between the level of undergraduate college students‟ Facebook use and their co-curricular involvement within the campus community? And is there a correlation between the nature of undergraduate college students‟ Facebook use and their co- curricular involvement within the campus community? This study examined the extent and manner of Facebook use among college students, their level and type of co-curricular involvement within the campus community, and determined if there was a relationship between the two constructs. The researcher accomplished this by measuring the level and specific activities of Facebook use and co- curricular involvement. The instrument for this study measured Facebook use through the number of minutes each day that students actively spent using the service, as well as the number of times per day that they logged in to the service. To measure specific Facebook behaviors, the survey asked 14 questions measuring the frequency with which participants engaged in common Facebook activities. The researcher measured involvement quantitatively by determining the average amount of hours per week participants spent in co-curricular activities and organizations. This was achieved by modifying a question on the College Student Experiences Questionnaire (CSEQ) to ask how many hours per week participants typically spent involved in activities outside of the classroom. The researcher then measured the behavioral extent of that involvement by administering two scales of the CSEQ. The first was the Campus Facilities scale, which measured the frequency and extent to which
    • 9 students utilized spaces on campus such as the student union and recreational facilities. The second was the Clubs and Organizations scale, which measured the behavior and level of involvement in student clubs and organizations. Based on previous research that measured social media use and campus involvement to some extent (Heiberger & Harper, 2008; HERI, 2007; Junco, 2012; Junco, Heiberger & Loken, 2010; Martinez Aleman & Wartman, 2009), this research study began with the hypothesis that there would be a positive correlation between college students‟ level and nature of Facebook use and co- curricular involvement on campus. Significance A greater understanding of the correlation between college students‟ level and nature of Facebook use and co-curricular involvement will benefit many stakeholders. First, college administrators would benefit from this study. Everything from creating policy to campus design has an impact on student involvement (Astin, 1984; Braxton, 2003; Pascarella & Terenzini, 2005). In an environment where student time and energy is the most valuable resource an institution has, it is essential to have a thorough understanding of any phenomenon‟s impact on involvement (M. Wilson, 2004). This is especially important given the significance of the relationship between involvement and retention of students (Pascarella & Terenzini, 2005). Administrators would be able to use this information in developing policies and making decisions, including the allocation of resources to utilize or deter the usage of Facebook. Second, students would benefit from this research. Professionals would be able to create environments more suitable to increasing involvement among students, characterized in part by heavy use of social media (Junco, 2012; S. Smith & Caruso,
    • 10 2010). Students will exhibit increased levels of learning and personal development, since students‟ level of involvement is responsible for the most substantial amount of growth from precollege characteristics (Astin, 1984; Davis & Murrell, 1993; Pace, 1982; Pascarella & Terenzini, 2005). Therefore, this research could benefit students because professionals would be able to better educate them about what Facebook does and does not do, and help identify the most educationally and developmentally beneficial ways for it to be used. Third, student affairs professionals need to understand if a relationship exists between Facebook use and student involvement. This understanding will help to inform better practices for increasing involvement within campus communities, which is one of the primary functions of student affairs professionals (Baird, 2003; Braxton, 2003; Evans et al., 2010; Strange & Banning, 2001). As student affairs professionals continue to educate students about how to have a safe and productive college experience, it is becoming essential to include training about effective uses of Facebook, specifically with the goal of promoting co-curricular involvement. Thus, in a continued effort to increase involvement and therefore promote student learning and development, it is the responsibility of student affairs professionals to gather empirical evidence to help guide future interventions (Creamer, Winston, & Miller, as cited in Pope, Reynolds, & Mueller, 2004). In an environment where Facebook is as ubiquitous as mobile phones (S. Smith & Caruso, 2010), it is essential to understand the impacts that this technology has on student involvement. By understanding if there is a correlation between college students‟ level and nature of Facebook use and co-curricular involvement, higher education
    • 11 administrators, students, and student affairs professionals will gain information that could prove critical to making college environments supportive of current students. Summary Co-curricular involvement plays a crucial role in student learning and development (Astin, 1984, 1993; Evans et al., 2010; Pascarella & Terenzini, 2005). Social media, particularly Facebook, has become widely and frequently used on college campuses (Junco, 2012; S. Smith & Caruso, 2010; Smith et al., 2011). In one single- institution study (Junco, 2012), students spent over 11.8 hours per week using Facebook. Given this amount of time students typically spend on Facebook – time that could be spent participating in other activities – it is important to understand if there is a correlation between undergraduate college students‟ Facebook use and co-curricular involvement. This chapter has introduced a research study that aims to determine if there is a correlation between college students‟ level and nature of Facebook use and co-curricular involvement within the campus community. This study is important to three main stakeholders. It will assist college administrators in making decisions regarding Facebook use on campus, it will be useful to students who are highly engaged in social media and expect to experience maximum personal growth associated with attending college, and it will help student affairs professionals in their goal of increasing co- curricular involvement and fostering student learning and development. This chapter has defined and clarified Facebook use and co-curricular involvement within the context of this study. The following chapter will explore relevant research on these topics in relation to the significance of this study.
    • 12 CHAPTER TWO LITERATURE REVIEW The previous chapter introduced college student Facebook use and co-curricular involvement, and the significance of a study on the relationship between the two. This section will provide more insight into these two variables, specifically as they relate to the proposed study. This chapter will begin with an introduction of the population of interest for the proposed study, and then discuss co-curricular involvement, college students‟ Facebook use, and studies that have measured the relationship between them to some degree. College Students Before examining the background of the specific constructs of this study, it is important to understand the population of interest. This section will provide a brief overview of college students, and the proliferation of technology among this population and on the college campus. Characteristics of the College Student Population As of 2010, there are over 17 million students enrolled in 4,291 institutions of higher education across the United States (U.S. Department of Education, as cited in “Profile of Undergraduate Students,” 2009). The demographics of these students vary greatly, especially when considering age. Student enrollments represent almost every age group of adults. This diversity contributes to the great richness in the higher education community, yet is also a source of tension between the various generations (Coomes & DeBard, 2004). For example, in the 2008-2009 academic year, 17.3% of students in higher education were between the ages of 24-29, and 23% were 30 years old or older.
    • 13 The largest group of students was in the 15-23 age group, which made up over 59% of enrolled college students (U.S. Department of Education, as cited in “Profile of Undergraduate Students,” 2009). Millennial generation. As demonstrated by the breakdown of the student population by age, the largest generation currently enrolled in higher education is the Millennial generation, which includes individuals born between 1982 and 2002 (Coomes & DeBard, 2004). There are important characteristics of this generation of students that relate directly to higher education. They are larger than any previous generation, and are estimated them to grow to over 33% larger than the Baby Boomer generation (Coomes & DeBard, 2004). The Millennial generation is also more racially and ethnically diverse than any previous generation. Over 39% of the generation belongs to a minority racial or ethnic group, some of whom are first-generation Americans (Broido, 2004). Millennial students are also typically more comfortable with technology, and have been referred to as the Net generation (Junco & Mastrodicasa, 2007) and digital natives (Palfrey & Gasser, 2008; Prensky, 2001; S. Smith & Caruso, 2010). Digital natives. Prensky (2001) coined the term “digital native” (p. 1). According to his definition, those born in 1980 or later fall within this category. Prensky (2001) described these individuals as native speakers of the language of computers and the Internet, where the development of digital technologies has created a dramatic paradigm shift that makes them distinctively different from previous generations. This generation of digital natives “think and process information fundamentally differently than their predecessors” (Prensky, 2001, p. 1). Palfrey and Gasser (2008) expanded on this definition, stating that the
    • 14 distinguishing factor of digital natives is their high level of computer skill and knowledge. The authors affirmed that a significant problem that directly results from this is a lack of attention to protecting personal privacy. Digital natives publish a greater amount of personal information in public spaces. This is particularly disturbing when looking at how that published information could be detrimental years or decades later (Palfrey & Gasser, 2008). Scholars (boyd, 2007; Farquhar, 2009) have conducted studies that support these characteristics of digital natives. In one case, at a large public Midwest institution, Farquhar (2009) interviewed undergraduate students who then used Facebook while being observed by the researcher. One of the conclusions of the study was that digital natives had substantially different usages of technology and social media than older generations. There were four specific findings: digital natives were successful at creating an intricate and accurate representation of their personal identity online, reciprocity was a key value in technologically mediated interpersonal relationships, differentiation between online and offline identities did not exist, and digital natives appeared to have less- developed offline social skills (Farquhar, 2009). In seeking to understand college students‟ use of technology, Junco and Mastrodicasa (2007) conducted a multi-institutional study to collect data on this generation‟s use of technology and how it related to the college environment. The authors said that the primary characteristic to take into account with digital natives – or the Net generation, as the authors referred to them – is that students rely on technology to communicate with each other. These college students have more interactions in a technologically mediated space compared to previous generations, and will increasingly
    • 15 expect their communications to occur online (Junco & Mastrodicasa, 2007). Junco and Mastrodicasa (2007) asserted this is why it is important to consider this generation of college students differently than previous generations. On the other hand, some researchers have questioned the validity in making such broad generalizations of the skills and characteristics of a single generation (Hargittai, 2009; Morgan & Bullen, 2011). Hargittai (2009) conducted a study of the online skills and abilities of a diverse group of first-year college students at a private institution in the Midwest. The study found a substantial degree of variance between the levels of skill within the group of digital natives, with participants‟ abilities ranging from meeting the expectation of digital natives, to a lower level of competency than expected of older individuals. Overall, while digital natives are comfortable with technology, that comfort does not translate to a high level of skill (Hargittai, 2009; Morgan & Bullen, 2011). Additionally, Hargittai (2009) found statistically significant relationships between technological skill level and socioeconomic standing, race, ethnicity, and gender. Participants that displayed the lowest level of technological skill were predominantly female, African American, Hispanic, and/or of low socioeconomic standing. Keeping in mind the fact that the Millennial generation, or digital natives, are more racially and ethnically diverse than any previous group (Broido, 2004), Hargittai‟s (2009) findings suggest a modification to the differentiation between digital natives and other generations to include recognition of the role of privilege in participation in the modern technological society.
    • 16 Proliferation of Technology on Campus The EDUCAUSE Core Data Service report (Arroway, Davenport, Xu, & Updegrove, 2010) provided results from a study on the information technology environments and practices at over 875 institutions throughout the nation. These results indicated that students are using technology more than ever, and administrators have responded by making campuses more conducive to this evolution. Based on the awareness that college students expect a larger integration of technology into every aspect of their lives, and on the substantial advances in educational technology in the past decade, technology has become present in almost every aspect of college campuses (Arroway et al., 2010). S. Smith and Caruso (2010) conducted the EDUCAUSE Center for Applied Research (ECAR) Study of Undergraduate Students and Information Technology. The participants were a nationally representative sample of almost 37,000 students. One series of questions in the ECAR study sought to determine students‟ use of the Internet. On average, students reported spending 21.2 hours per week online (S. Smith & Caruso, 2010). An analysis of this time compared to students‟ GPA showed no statistically significant correlation. S. Smith and Caruso (2010) also reported that 98.6% of students owned a computer, and that 33% of those students owned more than one computer. Over 89% of respondents said that they owned a netbook or laptop, while only half owned a desktop computer. Mobile use. A continuing theme among the ECAR (S. Smith & Caruso, 2010) report was that students‟ technology use is becoming more mobile than ever before. Almost all participants reported owning a mobile phone, and two-thirds of them said they
    • 17 could access the Internet from their phone. Of those with internet access from their phone, over 90% of respondents said they primarily use their mobile devices for text messaging and accessing social networking sites, including Facebook, and that they engage in these activities daily. Respondents also listed using their mobile phones to check the news and weather, get sports updates and statistics, and send and receive email. While studies (boyd, 2007; Farquhar, 2009; Junco & Mastrodicasa, 2007) have reported that Millennial generation students are heavy users of technology, they are not the only college students immersed in adapting it for educational purposes. Among the ECAR (S. Smith & Caruso, 2010) study‟s participants, only about 78% belonged to the Millennial generation. S. Smith and Caruso (2010) did not find a statistically significant difference between the responses of Millennial students compared to older students, which may suggest that the generations are not as different as previous definitions (Palfrey & Gasser, 2008; Prensky, 2001) proposed. Therefore, even though higher education is not composed only of Millennial students, this data suggests that most college students share similar levels of technological skill and comfort as the digital natives. Campus support for technology. According to Arroway, Davenport, Xu, and Updergrove‟s (2010) data, college and university administrators are expanding support for students‟ use of technology, from smart classrooms to online web portals. The latest trend is finding ways to support mobile devices on campus. One particular service that is becoming standard is providing campus-wide wireless Internet access, or Wi-Fi. Arroway et al. (2010) reported that most classrooms at institutions within the study were equipped with Wi-Fi, and noted a similar trend within residence halls. Furthermore, the
    • 18 authors stated that student unions provided Wi-Fi in over 95% of the participating institutions (Arroway et al., 2010). Student perceptions (S. Smith & Caruso, 2010) and institutional data (Arroway et al., 2010) linked the integration of technology to increased levels of learning. Students reported an overall acceptance and willingness to use technology for academic pursuits both in and outside of the classroom. S. Smith and Caruso (2010) noted that over one- third of students reported using technology in the classroom in some way, and most of those students said that it was educationally beneficial. Over 66% of students who said their professors posted class materials online reported that they did not use technology as an excuse to skip class; some even reported that it helped improve their class experience by easing the pressures of note-taking. Almost a quarter of the students surveyed said they had used social networking sites as part of an assigned class responsibility or to collaborate with peers on class work. Among those who did not, over one-third said that they would appreciate the opportunity to do so (S. Smith & Caruso, 2010). Summary Prensky (2001), and Palfrey and Gasser (2008), described individuals within the Millennial generation as digital natives. Hargittai (2009), on the other hand, found that members of the Millennial generation were not a homogenous group who all possessed the same level of technological skill. S. Smith and Caruso (2010) found that older students answered questions regarding technology use in higher education similarly to those of the Millennial generation. This distinction is relevant because it would encourage higher education professionals to apply the same assumptions of students‟ use of technology to all college students, regardless of age, and that technological comfort is
    • 19 not equivalent to a high level of skill. Faculty, staff, and administrators have already begun responding to this by increasing the technological integration of campus in many ways (Arroway et al., 2010; S. Smith & Caruso, 2010). This section provided an overview of the characteristics of college students, examined how these students use technology, and discussed how most campuses support the behavior. The student population is very diverse (Broido, 2004; “Profile of Undergraduate Students,” 2009) and typically represented by high-users of technology (Arroway et al., 2010; S. Smith & Caruso, 2010). This background information should help to inform an understanding of college students‟ use of technology and social media, and the substantial amount of time they dedicate to using it. The next section will look more deeply at the importance of spending that time invested within the physical campus community, specifically regarding co-curricular involvement. College Student Involvement According to Evans, Forney, Guido, Patton, and Renn (2010), one of the primary goals of student affairs professionals is to increase involvement in order to expose students to developmental activities and learning experiences outside of the classroom. Astin (1984) defined student involvement as the “quantity and quality of the physical and psychological energy that students invest in the college experience” (p. 235). Specifically, this study will focus on students‟ level of involvement in co-curricular activities, where the term co-curricular refers to activities which happen outside of the classroom.
    • 20 Involvement Theory The theory of involvement originated from Pace‟s (1982) work (Astin, 1984; Davis & Murrell, 1993; Kuh, 2009). Pace (1982) identified the two most important features of student learning and development to be the frequency of time and quality of effort students invest in the college environment. The college environment corresponds to the facilities and opportunities that foster educative experiences within behavioral settings, or places on campus that intentionally promote learning and development, such as the student union or library. Pace (1982) verified this theory through a study of over 12,000 undergraduate students at 40 different institutions nationwide using the College Student Experiences Questionnaire (CSEQ). The fundamental aspect of Pace‟s (1982) theory was that the most substantial determining factor of student success in higher education was the quality of effort students invested in the college experience, which was far more predictive than precollege characteristics or the college environment. In other words, Pace (1982) argued “what counts most is not who they are or where they are but what they do” (p. 18). In defining college student involvement, Astin (1984) identified five key postulates of involvement theory: involvement requires physical and psychological energy, involvement occurs along a continuum, involvement has both quantitative and qualitative features, development is proportional to the quantity and quality of involvement, and educational effectiveness is related to the capacity to increase involvement. As Astin (1984) introduced, M. Wilson (2004) elaborated that students‟ finite time and energy is the single most significant resource an institution has. Competing for this precious resource, the activities in which students spend their time are
    • 21 in direct opposition with each other. The greatest benefits of involvement will only be attained if students select the most educationally and developmentally purposeful activities in which to participate (Davis & Murrell, 1993; Roberts, 2003). Davis and Murrell (1993) warned that students might choose to become more involved in activities that isolate them or take them away from their studies, and that professionals should intervene to prevent these behaviors from commonly occurring. Braxton (2003) echoed Astin‟s (1984) statement that everything an institution does, from creation of policies to design and layout of campuses, significantly affects how students spend their time and energy. Since the goal of higher education is student learning and development, professionals should evaluate decisions and policies based on their ability to increase involvement. Indeed, it has been repeatedly stated that institutions could improve the overall quality of higher education simply by working to increase student involvement on campus, both in and outside of the classroom (Astin, 1984; Braxton, 2003; Pascarella & Terenzini, 2005; Winston & Massaro, 1987). Promoting involvement is the most effective way to make the most use of, and build on, the strengths each student initially brings to the campus (Astin, 1984; Davis & Murrell, 1993). One way of going about this would be creating communities that effectively produce a culture of involvement, such as learning communities comprised of highly engaged students. Baird (2003) suggested that a strategy for accomplishing this would be for student affairs professionals to serve as negotiators between students and their institutions, by creating the conditions for these communities to exist, and to encourage students to become co-creators of the community. Braxton (2003) suggested another perspective, that student affairs professionals should intentionally construct
    • 22 opportunities for social interactions among students and with professionals, with a specific emphasis on facilitating face-to-face discussions. One of the main challenges facing student affairs professionals is finding ways to make opportunities for involvement appealing to students (Astin, 1984; Baird, 2003; Braxton, 2003; Evans et al., 2010). This is an even more challenging issue for large institutions, where the likelihood of social involvement is significantly less than at smaller institutions (Pascarella & Terenzini, 2005). While it is difficult to identify what the most meaningful opportunities for involvement are (Winston & Massaro, 1987), they include participating in diverse residential environments, joining student organizations, taking responsibility within new leadership positions, participating in varsity or intramural sports, and finding new peer groups. Finding ways to create more opportunities for involvement, or determining what barriers might prevent students from taking advantage of such opportunities, is a critical task for student affairs professionals (Astin 1984, 1993; Chickering & Reisser, 1993; Pascarella & Terenzini, 2005; Strange & Banning, 2001). Involvement vs. Engagement If Astin‟s (1984) definition of student involvement was an evolution of previous research (Pace, 1982) on how students spend their time and energy on campus, student engagement is the most recent embodiment of that idea. It is important then to clarify why the current study will utilize the theory of involvement, which is less commonly used than the current construct of engagement. This section will define engagement in order to explain why the theory of involvement best meets the needs of this study. Kuh (2009) defined engagement as “the time and effort students devote to
    • 23 activities that are empirically linked to desired outcomes of college and what institutions do to induce students to participate in these activities” (p. 683). This definition evolved from Astin‟s (1984) theory of involvement, and Pace‟s (1982) earlier notion of the quality of student effort and time on task (Kuh, 2009). It is important to note the difference of Kuh‟s (2009) definition to these previous ideas, and contrast the relationship to its evolution. To start, there are obvious similarities that continue the tradition of involvement in Kuh‟s (2009) definition of engagement. The emphasis remains on the time and effort that students spend in activities believed to promote learning and development. Both theory‟s core philosophy was introduced in the second “Student Personnel Point of View” (American Council on Education, 1949/1994) which said that there is value in understanding what activities students decide to invest their time and energy, and that students are ultimately responsible for their own growth (Davis & Murrell, 1993). The main tenets of engagement originated from Chickering and Gamson‟s (1987) seven good practices in undergraduate education (Kuh, 2009). These principles are student-faculty contact, active learning, prompt feedback, time on task, high expectations, respect for diverse learning styles, and cooperation among students. This serves as the foundation for the benchmarks of the National Survey of Student Engagement (NSSE), which quantifies the student experience and measures engagement. The scope and reach of these seven principles are indicators of the breadth of the definition of engagement (Kuh, 2009). A few key components of engagement differ from the definition of involvement. Whereas Astin (1984) focused specifically on the behavior of involvement and not its
    • 24 outcome, Kuh (2009) conceived of engagement as a broad construct that incorporates most aspects of the collegiate experience and defined it by its impact on empirical educational outcomes. This breadth of scope helps make NSSE data vital to most stakeholders in higher education, and provides useful information for any party whose goal is student learning and development. One of the most focal aspects of the definition of engagement is the way in which students invest time and energy in their academic pursuits. This is directly aligned with the goal of persistence and graduation, where involvement in activities outside of the classroom is measured in terms of its ability to impact academic and class-related outcomes (Kuh, 2009). Kuh‟s (2009) definition of engagement provides another difference from Astin‟s (1984) definition of involvement. Within engagement, there is an emphasis on how strongly students feel connected to their institution because of what professionals within the institution do to create environments conducive to engagement. It is logical that such an evaluation would be necessary, based on the good practices introduced by Chickering and Gamson (1987), specifically including student-faculty contact, prompt feedback, high expectations, and respect for diverse learning styles. However, this approach to engagement differs greatly from Astin‟s (1984) definition of involvement, which intentionally does not include this feeling of connectedness. The definition of engagement is highly concerned with developmental outcomes and student response to their level of engagement. Due primarily to its substantial reach, engagement is viewed partly as a behavior, and more significantly as an influence of student learning and development. This is why one of the key aspects of measuring engagement is to determine the likelihood of development resulting from satisfaction and
    • 25 participation in a supportive campus environment (Kuh, 2009). On the other hand, the definition of involvement – and therefore any of its measurements – focuses strictly on the behavior of involvement. Astin (1984) stated that involvement does not focus on how students feel resulting from their behavior, but simply the amount of time and energy students devoted to intentionally educational and developmental activities. While this behavior has become an important component of engagement, the definition of involvement is highly focused in comparison. Involvement theory explicitly attempts to understand students‟ behavior in regards to how they devote their time and energy in the college experience. Scholars (Baird, 2003; Ericson, 2011; Heiberger & Harper, 2008; Junco, 2012; Kuh, 2009) have noted the similarities and differences between the definitions of involvement and engagement. In some cases (Baird, 2003; Ericson, 2011), researchers conflated the definitions to create an understanding of a specific interest in time and effort, without sacrificing the broad developmental impacts of engagement. In other studies, researchers (Heiberger & Harper, 2008; Junco, 2012) outlined the evolution of involvement to engagement in order to show the significance of engagement in the current understanding of student development, while highlighting the specific focus on time on task. To be sure, there are differences between the definitions of involvement and engagement, which matches the perceptions of scholars and practitioners. Engagement is the most recent evolution of the understanding of the impact of how students spend their time and energy and its impact on their learning and development (Kuh, 2009). This definition is much broader than Astin‟s (1984) definition of involvement. Involvement
    • 26 theory is useful in providing specific focus, since it is conceptualized only as a student behavior in how time and energy are spent, with a greater emphasis on experiences outside of the classroom. It is also more clearly defined and articulated than Pace‟s (1982) theory, from where involvement theory came. For that reason, involvement is more directly relevant to this study, rather than the definition of engagement and its emphasis on academic behavior, developmental outcomes, and feelings of connection to institutional environments. Benefits of Involvement Roberts (2003) and Baird (2003) affirmed that students‟ overall satisfaction with their college experience positively relates to the total time on task spent interacting with one‟s peers and educational materials. Astin (1984) proposed that the amount of time and energy students devote to developmental activities directly and positively affects their ability to achieve desired developmental outcomes. Tinto (1975) and Kuh (1995, 2009) stated that involvement, satisfaction, and psychosocial development all relate to student persistence. A brief discussion of studies on the benefits of student involvement follows. Satisfaction. Many studies have found a direct correlation between level of involvement in co-curricular activities and degree of satisfaction with the overall college experience. Since the theory of involvement originated from data on student satisfaction and persistence, Astin (1984) specifically described the correlation between involvement and satisfaction. First, Astin (1984) reported that residential students, who are considered highly involved based solely on the fact that they spend most, if not all, of their time on the
    • 27 campus, reported higher levels of satisfaction than commuters. These students reported the highest levels of satisfaction with the areas of student friendships, faculty-student relationships, institutional reputation, and social life. Second, students involved with athletic programs reported high levels of satisfaction compared to less-involved students. The areas of satisfaction reported were with the institution‟s academic reputation, intellectual environment, student friendships, and institutional administration. Third, students involved with student government associations reported very high levels of satisfaction with their college experience, specifically in greater than average satisfaction with student friendships (Astin, 1984). In addition to Astin‟s (1984) work, Kuh (1995) conducted a study of the value of co-curricular experiences. In an attempt to measure the significant impact of experiences outside of the classroom on student learning, Kuh (1995) carried out a multi-institutional qualitative research study, where the overall goal was to determine the outcomes of out- of-class experiences. In the end, the author compiled a 14-item taxonomy of significant outcomes. This taxonomy included sense of purpose, social competence, confidence, and application of knowledge. Kuh (1995) stated that the combination of these 14 items was highly correlated with student satisfaction. Therefore, in addition to the specific beneficial outcomes, Kuh (1995) concluded that student satisfaction in general increased as a product of increased involvement. Various institutional settings have reflected the relationship between involvement and satisfaction. J. D. Wilson (1999) conducted a study of students involved in recognized campus organizations at a mid-sized southern institution. The researcher found a positive relationship between level of involvement and satisfaction with the
    • 28 institution, which showed that students who belonged to an organization reported the most satisfaction with their college experience. Elliott (2009) reported similar results when focusing on community college students. When the researcher compared a group of involved students to a similar group of their un-involved peers, students involved in formal co-curricular activities reported significantly higher levels of satisfaction with their college experience. Overall, Astin (1993), and Pascarella and Terenzini (2005), reported similar findings. In Astin‟s (1993) analysis of the Cooperative Institutional Research Program (CIRP) data, the results showed that a perception of a strong student community had the strongest direct effects on student satisfaction when compared to any other environmental measure. Since involvement is a crucial component of community (Strange & Banning, 2001), Astin‟s (1993) analysis seems to show that involvement played a key role in student satisfaction. Pascarella and Terenzini (2005) summarized the literature on the impact that college has on students. They analyzed a remarkable number of studies, and effectively summarized the overall impact that participation in higher education has on college students. Pascarella and Terenzini (2005) echoed Astin‟s (1993) finding, where students who perceived membership in an organized group of students who had similar values and attitudes to their own showed higher levels of satisfaction with their college experience. Student development. A substantial number of studies have measured the relationship and impact of involvement on student development. As stated explicitly in Astin‟s (1984) theory of involvement, “The extent to which students can achieve particular developmental goals is a direct function of the time and effort they devote to
    • 29 activities designed to produce these gains” (p. 222). Involvement in co-curricular activities has a direct impact on positive student development (Astin, 1984, 1993; Chickering & Reisser, 1993; Elliott, 2009; Kuh, 1995; Pace, 1982; Pascarella & Terenzini, 2005; Winston & Massaro, 1987). The small, single-institution studies that determined links between specific aspects of involvement and development, and the large and broad multi-institutional studies, have provided a thorough understanding of this effect. Referring back to Kuh‟s (1995) study, the qualitative analysis displayed overwhelming benefits of involvement on student development, which supported the theory of involvement. Of the 14 taxonomy items, 9 that were reported by Kuh (1995) to be caused by high levels of involvement are also directly related to psychosocial and cognitive development as identified by Chickering and Reisser (1993), and Love and Guthrie (1999). Examples of these items include autonomy and self-directedness, social competence, reflective thought, and application of knowledge. Several scholars (Guardia & Evans, 2008; Guiffrida, 2003; Harper & Quaye, 2007; Renn & Bilodeau, 2005) have noted the impact that co-curricular involvement has in the social identity development process. In their qualitative analysis, Harper and Quaye (2007) found that Black students attending a predominantly White institution reflected on their experiences involved with Black student organizations as being beneficial to their sense of belonging and development of their racial identity. The researchers placed specific emphasis on the fact that most students reported joining such organizations while displaying characteristics symbolic of Cross‟ (1995) Immersion- Emersion stage. Harper and Quaye (2007) noted that the more involved students they
    • 30 interviewed showed signs of Cross‟ (1995) Internalization stage, the final stage after Immersion-Emersion, and that the students directly related their development to their involvement in these groups. Harper and Quaye (2007) concluded that co-curricular involvement and participants‟ social identity development were directly related. Guiffrida (2003) found similar results among African American students at another predominantly White institution; Guardia and Evans (2008) reported similar findings among Latino/a students at a Hispanic Serving Institution; and Renn and Bilodeau (2005) identified a similar correlation among Lesbian, Bisexual, Gay, and Transgendered (LBGT) students involved in a regional LGBT conference. To study the relationship between involvement in clubs and organizations, and overall student development, Foubert and Grainger (2006) administered the Student Development Task and Lifestyle Inventory (SDTLI) and a simple measure of involvement and leadership to a random sample of traditionally aged students at a mid- sized southeast public institution, over the course of four years. The researchers found a substantial positive statistically significant correlation between levels of involvement and development, where the more intensely participants were involved, the higher they scored on the SDTLI. Many researchers (Cooper, Healy, & Simpson, 1994; Elliott, 2009; Martin, 2000; J. D. Wilson, 1999) have found results consistent with Foubert and Grainger (2006). Additional studies have examined the relationship between co-curricular involvement, and critical thinking and cognitive development (Gellin, 2003; Terenzini, Pascarella & Blimling, 1996; Whitt, Edison, Pascarella, Nora, & Terenzini, 1999). Gellin (2003) conducted a meta-analysis of research presented between 1991 and 2000 on this
    • 31 relationship, which showed an overall gain in critical thinking. The author stated that the positive nature of involvement in multiple activities, which would provide various perspectives and encourage reevaluation of preexisting attitudes and values, could help these gains in critical thinking. Similar findings were reported by Terenzini, Pascarella, and Blimling‟s (1996) review of previous literature on the relationship of involvement and cognitive development, as well as Whitt, Edison, Pascarella, Nora, and Terenzini (1999), whose results were measured with their Nonclassroom Peer Interaction Scale. Moving to large multi-institutional studies on the impact of involvement on student development, Astin‟s (1993) analysis of the CIRP data provided insights into the effect of involvement on cognitive and affective outcomes of student learning and development. Astin (1993) reported that there was statistically significant evidence that greater time spent involved in both academic, and co-curricular activities had substantial positive effects on learning and development. This significance was stronger than almost every other measure of environmental aspects or precollege characteristics. Moreover, Astin (1993) found the opposite to display similar significant results: strong negative outcomes resulted from behaviors of un-involvement, including activities that isolated students or removed them from the campus. Dugan, Garland, Jacoby, and Gasiorski (2008) studied involvement among commuter students, who are traditionally underrepresented in the literature. The perception that commuter students are automatically less involved has led to negative, generalized statements, such as commuter students being deficient in their involvement and development, which is not accurate or supported by research studies (B. Jacoby, personal communication, October 10, 2011). Using nationally representative data from
    • 32 the Multi-Institutional Study on Leadership, Dugan et al. (2008) found that involvement in specific peer interactions, leadership training, and employer relations had equal impacts on self-efficacy and leadership development for commuter students as residential students. This is relevant because it indicates that commuter students – which represent over 85% of college students (Dugan, Garland, Jacoby, & Gasiorski, 2008) – who participate in intentionally developmental activities receive similar benefits as residential students. Overall, one of Pascarella and Terenzini‟s (2005) conclusions was that interpersonal involvement with peers and faculty directly increases psychosocial development, and more specifically interpersonal development. Supporting Astin‟s (1993) findings, Pascarella and Terenzini (2005) reported that overall, level of involvement within the campus community is by far the single most predictive factor in student development, especially when academic, co-curricular, and social involvement are mutually reinforcing. Pascarella and Terenzini (2005) concluded “Students derive the greatest developmental benefits from engagement in peer networks that expose them to individuals different from themselves” (p. 615). Persistence. One area of study that is of particular interest to a variety of groups within higher education is student persistence, or the rate at which students successfully continue enrollment at an institution through degree completion. Tinto‟s (1975) theory of student persistence stated that precollege characteristics and social and academic integration within the institution directly affect students‟ rate of commencement. Braxton, Hirschy, and McClendon (2004) provided a summary and critique of this model. The authors argued that a single theory could not explain a problem as complex as
    • 33 student persistence across institutional types. However, the authors noted that social integration, and therefore involvement, played an important role in understanding student persistence and departure. One of Braxton, Hirschy, and McClendon‟s (2004) primary conclusions was that “The greater the level of psychological energy a student invests in various social interactions at his or her college or university, the greater the student‟s degree of social integration” (p. 26). Several researchers (Astin, 1984, 1993; Berger & Milem, 1999; Pascarella, 1982; Tinto, 1975) have sought to understand the relationship between level of co-curricular involvement and persistence. This is a logical connection when considering Tinto‟s (1975) emphasis on social integration as one of the primary determining factors in persistence, and since Astin‟s (1984) theory of involvement originated from research on college student persistence. Pascarella (1982) conducted a multi-institutional study to determine the predictive validity of theoretical models of student departure. The most important result was the significant correlation between social and academic integration from Tinto‟s (1975) model and departure decisions, even when taking into account a wide variety in student precollege characteristics (Pascarella, 1982). A similar finding was reported by Berger and Milem (1999) in their multi-institutional study, who stated that involvement in co-curricular activities increased levels of social integration and the perception that the institution was supportive to student needs and desires, which lead to the decision to persist. Elliott (2009) found a direct increase in persistence related to a student‟s level of satisfaction and psychosocial development. In their summary of research within the previous decade, Pascarella and Terenzini (2005) stated that the single most influential
    • 34 factor of student persistence was level of involvement, specifically as it related to face-to- face interaction among peers. Since involvement increases satisfaction with the college experience, and increases the level of psychosocial development that occurs during college, it becomes undeniable that involvement indeed affects persistence. According to Pascarella and Terenzini (2005), “Interaction with peers is probably the most pervasive and powerful force in student persistence and degree completion,” (p. 615). Additionally, “extracurricular involvement had modest, positive effects on institutional persistence and educational attainment” (Pascarella & Terenzini, 2005, p. 616). Astin (1993) and Pascarella and Terenzini (2005), found that face-to-face interaction with peers and faculty directly increased satisfaction, psychosocial and interpersonal development, and likelihood of persistence. The emphasis is that student satisfaction, learning and development, and persistence increases by providing access to environments and opportunities for involvement; but caution must be taken to remember that these benefits can only be realized if students are held individually responsible for taking advantage of these opportunities (Davis & Murrell, 1993; Pascarella & Terenzini, 2005). Measures of Involvement The definition of involvement focuses particularly on factors that facilitate development, rather than the developmental process itself. It is concerned solely with the behavior of involvement, and intentionally excludes the impact of involvement or students‟ perception of how it makes them feel (Astin, 1984; Davis & Murrell, 1993; Evans et al., 2010). A high intensity of involvement is evident when students are markedly committed enough to a group or organization that they invest considerable
    • 35 time, psychic energy, and physical activity, for the pursuit of furthering the group‟s purposes (Davis & Murrell, 1993; Winston & Massaro, 1987). This section will examine four different measures of involvement, including a general understanding of an average level of hours of involvement, select scales from NSSE, the Extracurricular Involvement Inventory (EII), and the College Student Experiences Questionnaire (CSEQ). Hours of involvement. The first measure of involvement is intentionally simplistic. It is not limited to a specific instrument or scale, and often does not exist as more than a single question. Quite simply, researchers ask participants to report how many hours they spent involved in co-curricular activities in a given timeframe. This type of measurement can range from one single number in which participants summarize their total time of involvement, to a series of questions on the number of hours spent participating in a list of activities. For example, in Junco‟s (2012) study of the relationship between Facebook use and level of engagement, to measure students‟ level of co-curricular involvement, one question was asked directing students to list the number of hours per week that they spent involved in activities outside the classroom. On the other hand, Pascarella (1982) created an instrument called the Student Involvement Questionnaire, for a study that sought to measure level of involvement as it related to social integration and persistence. The instrument was comprised of many questions that asked participants to list how many hours each week they spent involved in specific activities, such as intramural athletics, fraternity/sorority activities, and hobbies or social clubs. While this is a simplistic means of measuring involvement, it is useful when trying to show that another activity does or does not inhibit the amount of hours that
    • 36 participants can spend involved in co-curricular activities. In this way, this form of measurement is the most common when used in combination with another measurement to determine a relationship between involvement and another construct. Unfortunately, this approach fails to measure the rich and complex definition of involvement as summarized by Astin‟s (1984) five postulates. It does not provide the researcher with enough information to draw conclusions of the actual relationship between a behavior and actual level of involvement, since involvement is more complicated than simply the number of hours students spend performing a behavior (Astin, 1984; Davis & Murrell, 1993). National Study of Student Engagement (NSSE) scales. A second measure of involvement utilized in multiple studies (Ericson, 2011; Junco, 2012; Junco, Heiberger, & Loken, 2010) relied on scales from the NSSE instrument. Since involvement is one component of engagement (Kuh, 2009), it is logical that part of the instrument used to measure engagement must include a measurement of involvement. Ericson (2011) created one instrument from selections of NSSE to measure involvement by extracting the following scales: diversity within college activities, personal-social growth, non- classroom experience, and miscellaneous student activities. Ericson (2011) scored this instrument following the instructions from NSSE, and created an involvement score. However, the original purpose for creating these scales was not to measure involvement, and the researcher of this study broadened the definition of involvement to include the items measured by these scales. The individual items in this instrument do not fall within the scope of Astin‟s (1984) definition of involvement, since most seek to measure the degree of students‟ development exhibited in their behaviors, rather than focusing
    • 37 explicitly on the behavioral aspect of involvement. Extracurricular Involvement Inventory (EII). The third measure of involvement is the EII (Winston & Massaro, 1987). This instrument was derived by expanding on Pace‟s (1983) Clubs and Organizations scale from the second edition of the CSEQ, and added further detail implied by Astin‟s (1984) definition of involvement. Winston and Massaro (1987) found that the EII was indeed more successful at measuring high levels of involvement among students when compared to Pace‟s (1983) Clubs and Organizations scale. Most frequently, researchers have used this instrument to study the level of involvement among student leaders and to separate the moderately involved from the highly involved, e.g. J. D. Wilson (1999) and Elliott (2009). However, the EII is not as effective at measuring students who are less involved in co-curricular activities (Winston & Massaro, 1987). Researchers have typically used the EII where the sample was a specifically targeted group of student leaders. College Student Experiences Questionnaire (CSEQ). The final measure of involvement is the CSEQ, which various authors have continually updated since its creation by Pace (1982) in 1978. The original function of the CSEQ was to measure the quality of effort that students invest in their college experience, and understand its impact on the level of achievement of college students (Davis & Murrell, 1993; Pace, 1982). There have been four editions of the CSEQ, and this study will discuss and utilize the most recent edition updated in by Pace and Kuh (1998). The main components of the CSEQ are the scales that measure the frequency and quality of effort students invest in their college experience. There are 14 scales in all. The first seven scales focus on the use of campus resources, and the other seven focus on the extent to which participants
    • 38 take advantage of personal and social opportunities. These scales measure topics including campus facilities, clubs and organizations, residence hall involvement, athletic and recreational facilities, and cultural activities (Pace, 1982). The Campus Facilities and Clubs and Organizations scales, which remain unchanged since the second edition, provide measures of involvement very closely aligned to Astin‟s (1984) definition (Davis & Murrell, 1993). These scales from the CSEQ ask how frequently students participate in activities such as using campus facilities and participating in leadership activities within organizations, using a four-point Likert scale. The response options are never, occasionally, often, and very often, where a response of never scores one point and a score of very often scores four points. These scales measure optional activities, that can be thought of as student initiative, since they are not mandatory for college credit, and rank participation along a spectrum. This means that the score goes beyond simple frequency of participation and is representative of the quality of effort students exert in their behaviors (Pace, 1982), which is a fundamental aspect of Astin‟s (1984) theory of involvement. One specific study recently utilized the CSEQ, conducted by Pike, Kuh, and Gonyea (2003). The authors sought to empirically link the influence of institutional characteristics to student learning and intellectual development. Using the CSEQ, the researchers were able to determine that student learning and development did in fact occur in meaningful ways at a variety of nation-wide institutions, but that Carnegie classification and institutional mission were not significantly correlated to the gains and experiences of students enrolled at different institutions (Pike, Kuh, & Gonyea, 2003). Pascarella and Terenzini (2005) recognized the importance of the CSEQ in the increase
    • 39 in research conducted on involvement and the quality of student effort. Researchers continue to use the CSEQ to measure the relationship between student involvement and other constructs, with studies published as recently as 2010 (Murphy, 2010; J. R. Wilson, 2010). An item missing from the CSEQ is a measure of how many hours in a given time period students spend involved in co-curricular activities, though the instrument does ask a similar question about academic involvement. A version of this question for co- curricular involvement would be useful in providing a direct quantitative correlation between hours of involvement and other constructs. For the current study. It is important to consider these measures of involvement, each with varying levels of detail and consistency with Astin‟s (1984) original definition. For the purposes of this study, the CSEQ is the most appropriate instrument. It effectively measures students‟ behavior of involvement, and their level of involvement within those behaviors. This meets Astin‟s (1984) qualification of the behavioral, or qualitative, aspect of involvement. The only addition to the CSEQ that becomes necessary is a question asking for hours of co-curricular involvement within a given timeframe, or the quantitative aspect of involvement. With this addition, the CSEQ is by far the best choice to measure involvement as operationalized by this study, when compared to the alternatives. Summary Involvement, as defined as the amount of physical and psychological time and energy that students invest on campus (Astin, 1984), is a crucial element of the college experience. Involvement directly influences student satisfaction, psychosocial and
    • 40 cognitive development, and persistence to graduation. Student affairs professionals are responsible for increasing student involvement on campus, and Astin (1984) suggested evaluating the efforts of higher education administrators based on their ability to increase such involvement. When looking at the programs, services, and facilities provided within institutions of higher education it is essential to study their impact on student involvement (Astin, 1984; Braxton, 2003; Evans et al., 2010). Likewise, it is essential to understand new phenomena on campus in relation to this involvement, to determine whether they are contributors or threats to student learning and development. This holds particularly true for phenomena that could affect students‟ individual initiative in taking advantage of these opportunities, since students are ultimately responsible for their own participation (Davis & Murrell, 1993). The following section will discuss studies conducted on one such phenomenon, Facebook and how it is used by college students. Facebook Use Among College Students As the social media service of choice, college students spend a great deal of their time using Facebook (Junco, 2012; S. Smith & Caruso, 2010). In order to understand if a relationship exists between campus involvement and Facebook use, it is important to begin with a thorough definition of Facebook, the services it provides, and how it is used. From there, a review of research studies will introduce the various negative and positive outcomes linked to college students use of Facebook. Finally, this section will end with measures of Facebook use, including the instrument that this study will employ. Definitions and Contextualization To define Facebook, first it is important to define its overarching category of technology, social media. Social media refers to websites and applications that
    • 41 individuals can use for social networking, where online communities of users develop interpersonal relationships and share user-generated content through a technological medium (Ericson, 2011; Junco & Chickering, 2010; Junco, Heiberger, & Loken, 2010). Some examples of social media platforms are Facebook, Twitter, YouTube, and LinkedIn. Facebook allows users to generate profiles to connect and stay in touch with their friends and acquaintances, while facilitating the creation and maintenance of large social networks (Junco & Chickering, 2010; Manago et al., 2012). With over 845 million users, Facebook is by far the largest social media service (“Statistics,” 2012). Services offered by Facebook. There are many services that Facebook provides to its users; Smock, Ellison, Lampe, and Wohn (2011) went as far as to call Facebook a “toolkit” (p. 2326), composed of varying tools and services to meet diverse needs. In this way, Facebook is not a single entity, but rather an umbrella service or suite of social media tools. As demonstrated by its history, Facebook is very dynamic, and therefore the list of these tools frequently changes based on the needs of its users – and more commonly, based on the pressures of online competition. In the fall of 2011, the tools that existed within this social media platform could be grouped into three primary categories: staying connected, interacting with peers, and gaming. The first category is staying connected with a Facebook user‟s friends, by browsing the profiles and recent activities of peers whom they connect with through a mutual approval process. Ways of doing this are through viewing others‟ status updates answering the question of “What‟s on your mind,” creating and RSVPing to events, and viewing photos and videos (Junco, 2012; Papacharissi & Mendelson, 2011; S. Smith & Caruso, 2010; Smock, Ellison, Lampe, & Wohn, 2011).
    • 42 For the second category of interacting with peers, Facebook users can conduct another group of activities according to Smock et al. (2011). The primary form of interaction is broadcasting status updates to all users connected within one‟s social network. Users can share links with their friends, most frequently to news stories or various other websites. They can send private messages to each other, which are not displayed publicly and typically represent a means of personal communication (Manago et al., 2012). Users can comment on user-generated content, such as pictures, status updates, and recent activities. Facebook has an instant messaging service, called Facebook Chat. Facebook users can also post and tag photos and videos of themselves and their friends (Junco, 2012; Papacharissi & Mendelson, 2011; S. Smith & Caruso, 2010; Smock et al., 2011). For the last group of activities, Facebook users can play games created by third- party application developers hosted within Facebook. Though this list is not exhaustive, it does comprise the majority of Facebook activities in which college students most frequently participate (Junco, 2012; Papacharissi & Mendelson, 2011; S. Smith & Caruso, 2010; Smock et al., 2011). College students’ use of Facebook. In the nationally representative ECAR Study of Undergraduate Students and Information Technology, S. Smith and Caruso (2010) reported that 90% of college students use social media services, and 97% of those students use Facebook. Over 90% of students who use social media responded that they logged in to Facebook daily. Similarly, in a nationally-representative study, A. Smith, Rainie, and Zickuhr (2011) found that 86% of college students use Facebook. The popularity of Facebook is also evident in the average number of minutes that students
    • 43 report spending on the service every day. In a study conducted by Junco (2012) at a mid- sized public northeastern institution, students who had active Facebook accounts reported using the service an average of 101.9 minutes per day. Furthermore, according to the nationally-representative 2011 CIRP Freshmen Survey (Pryor, DeAngelo, Blake, Hurtado, & Tran, 2011), including responses from 203,967 incoming first-year students, only 5.2% of high school students reported not spending any time on social networking sites. Of these incoming students, 51.3% reported spending more than three hours per week using such services. This represents an 11.5% increase over similar responses from 2007 (Pryor et al., 2011). Thus, it appears that incoming students will continue to increase the currently observed levels of Facebook use on campus. Based on another single-institution study, the average number of Facebook friends that existed within one‟s social network was 440 (Manago et al., 2012). These networks were found to comprise several different types of relationships: close connections, activity connections, acquaintances, maintained connections from previous social groups, and strangers or online-only connections. The percentage of close friends within one‟s network was 39%, compared to loose, or superficial, connections, which was 61%. Moreover, the more Facebook friends an individual had, the higher the percentage of loose connections that existed within their network. Manago, Taylor, and Greenfield (2012) believed that these findings suggest that social networks expand primarily through the addition of distant relationships, where increased participation in activities led to a larger social network of loose connections. There are many reasons that students use the tools offered by Facebook.
    • 44 Papacharissi and Mendelson (2011) conducted a study at an urban institution of students‟ motivations for using Facebook. The survey was administered online and promoted through Facebook; the initial sample was snowballed, resulting in 15% of the population not being current college students. Through a series of questions, the researchers asked participants what they did when they logged on to Facebook. Nine distinct significant motives of using Facebook were identified through a factor analysis: expressive information sharing, habit, relaxing entertainment, passing time, cool and new trend, companionship, professional advancement, escape, social interaction, and new friendships (Papacharissi & Mendelson, 2011). In a study conducted at a large Midwestern institution, Smock et al. (2011) expanded on these nine motives (Papacharissi & Mendelson, 2011) to determine which of these were reasons to use Facebook in general, in comparison to those that motivated use of specific services within Facebook. They found a relation between general use and the three motives of relaxing entertainment, expressive information sharing, and social interaction. A more significant relationship existed between the other six (habit, passing time, cool and new trend, companionship, professional advancement, escape, and new friendships), and usage of specific Facebook features (Smock et al., 2011). Mobile Facebook use. The newest trend with Facebook is accessing the service on mobile devices, such as smartphones and Internet-enabled cell phones. Of the 62.7% of students that reported owning such a mobile device in the ECAR study, 76.9% said that they accessed Facebook from this device (S. Smith & Caruso, 2010). In Barkuus and Tashiro‟s (2010) qualitative analysis of student Facebook use at a large public institution, one main component of research examined mobile usage. Students who were able to
    • 45 access Facebook on their mobile device reported an overall increase in usage of the service, though they recognized a distinct change in the manner in which they used Facebook. On a cell phone, students said they were more likely to perform the following activities: respond to messages, briefly check to see if anything new was happening with their friends, or browse recently uploaded photos. Students reported that these behaviors happened much more frequently than before using a mobile device, but they also said they spent much less time on Facebook when using their phone compared to their computer. The authors explained this evolution as students now using Facebook in “short „bursts‟…remaining constantly „in touch‟ with a large set of friends and acquaintances” (Barkhuus & Tashiro, 2010, p. 137). Students indeed reported that this communication pattern was essential to maintaining their social life, particularly for scheduling ad-hoc meetings in clubs or organizations, as well as study groups or class-related exchanges. Negative Outcomes Associated with Facebook Use When Facebook first gained notoriety, the popular media coverage seemed to focus on the various negative outcomes of using Facebook, including privacy concerns, potential harm from the existence of a sometimes-incongruent online persona, and users‟ misconception of their online audience (Ellison et al., 2007). There have been a number of studies conducted to support claims of the relationship of negative outcomes to Facebook use. Interestingly, students in one single-institution study were aware of a majority of the detrimental outcomes associated with using Facebook, as demonstrated by asking them to list these outcomes (Silverman, 2007). This section will highlight some of these studies, including negative linkages to psychosocial, behavioral, and academic
    • 46 issues. Facebook depression. One concept that has appeared frequently is “Facebook depression” (O‟Keeffe, Clarke-Pearson, & Council on Communications and Media, 2011, p. 800). This term has been discussed in clinical journals, primarily written about adolescents, but can affect anyone ranging from pre-teen children to adults. There are many components to Facebook depression, but the main idea is that using Facebook causes symptoms identical to clinical depression – which should be treated similarly – but has a tangible, solvable cause (Aboujaoude, 2011). One aspect of Facebook depression was contextualized in a study of college students at a medium-sized West Coast university by Jordan, Monin, Dweck, Lovett, John, and Gross (2011), where sadness was found to be caused by false perceptions about friends‟ level of happiness. The authors found that this came from the fact that most users publish the best, or even over-glorified, version of themselves and their lives. This results in a misconception when students view others‟ profiles and perceive how happy they must be. When compared to their own lives, students‟ friends seem to be doing much better than they are. Due to this error in perception, users reported feeling depressed (Jordan et al., 2011). Another contributor to Facebook depression is when a Facebook user receives negative or no feedback on content that she or he shares. In this way, attention seeking leads to Facebook depression. The trigger for this depression usually occurs when a user spends a great deal of time and energy creating content that they believe is particularly outstanding. If the post does not receive the desired feedback, students have reported feelings of depression, caused by thinking that people do not care about their posts or that
    • 47 their contributions are not significant (Aboujaoude, 2011). Narcissism. The previously mentioned behaviors can result in users who are more interested in their outward image and persona than the relationships they have with others, which is part of the definition of narcissistic behavior. A Facebook profile is a user‟s online persona, according to Aboujaoude (2011), a psychiatrist who discussed case studies from college students and members of the local community that were treated at the Stanford University Impulse Control Disorders Clinic. One‟s offline persona is different from this online persona, which individuals use to connect and interact with other users through a technological medium. This causes a great opportunity to present the best side of oneself, but also a challenge to ensure that the profile properly reflects the individual. Moreover, students may now be establishing their social identity through this public performance on Facebook. Many students spend a great deal of time grooming their online persona to ensure the presentation of their absolute best image, regardless of accuracy (Aboujaoude, 2011; Manago et al., 2012). Users interact through commenting and liking the content shared by their peers. This means that many students will share content, with the primary motivation of seeking the approval and acceptance of their friends through comments and likes. The intentional effort to create content that maximizes attention from peers is very narcissistic, especially when coupled with the desire to consistently edit, or groom, one‟s profile and public image (Aboujaoude, 2011; Bergman, Fearrington, Davenport, & Bergman, 2010; Manago et al., 2012). Buffardi and Campbell (2008) conducted a single-institution study that sought to understand how Facebook manifests narcissism in users. The authors stated that
    • 48 narcissism is more likely, and perhaps even caused, by social networking sites like Facebook. This is due to the a heightened level of control over almost every aspect of the environment, and the emphasis on shallow relationships with a great number of peers. Their most significant finding was that students were surprisingly effective at recognizing narcissistic students simply by viewing their Facebook profile, as confirmed through scores of the Narcissistic Personality Inventory (NPI). Buffardi and Campbell (2008) asserted that this is problematic for college students, because when users perceive an individual to be narcissistic they do not pay attention to the content of the individual‟s profile, which in turn decreases the individual‟s social capital and offline social life. Since Facebook could increase the likelihood of narcissistic behavior, to which other users would respond negatively, simply using this social media service could be damaging to an individual‟s online persona and ability to remain involved in offline social activities on campus (Buffardi & Campbell, 2008). Further research from a Southeastern university has supported this hypothesis (Saculla & Derryberry, 2011). The authors stated that students in their sample who reported higher levels of Facebook use also scored higher on measures of narcissism. The instrument used to measures narcissism was the Facebook as a Vehicle for Popularity scale, which measured the extent to which participants used Facebook to portray themselves as being popular. The results of this research are relevant because they showed that an increased usage of Facebook could lead to increased levels of narcissism, which the authors observed could be linked to decreased likelihood of moral judgment development. Therefore, students should be educated in ways to use Facebook that do not lead to narcissistic behaviors, or eliminate the need for face-to-face
    • 49 communication, which would also decrease opportunities for moral judgment development (Saculla & Derryberry, 2011). Stress. Long before the current prominence of Facebook, scholars (Lowery, 2004; Roberts, 2003) noted that socially interactive technologies have the potential to increase stress in the lives of college students. A study conducted at a mid-Atlantic university by Gemmill and Peterson (2006) showed that keeping up with online requests through Facebook can be a daunting task, and it caused a great deal of additional stress for a quarter of their participants. The authors noted that a significant amount of participants reported using Facebook to receive social support from friends and family during stressful times, which S. Smith and Caruso‟s (2010) data supported. Gemmill and Peterson (2006) found that some students had reported using Facebook as an effective way to escape from the academic stresses of college life. However, Gemmill and Peterson (2006) clarified that this is a bi-directional form of stress relief, and while Facebook could provide a medium to receive support, it therefore becomes a way that one‟s peers might seek social support. In this way, Facebook use could lead to increased stress levels for students through their friends seeking more social support then they are able to provide, or at a time when they were already experiencing high levels of stress (Gemmill & Peterson, 2006). Drinking and partying. In an analysis of CIRP‟s Your First College Year (YFCY) survey data, conducted by the Higher Education Research Institute (HERI, 2007), high usage of Facebook (defined as spending more than six hours per week on the service) was highly correlated to partying and drinking alcohol. All users of Facebook reported an overall greater degree of social interactions to some degree. The specific data
    • 50 regarding alcohol consumption showed a significant increase in the behavior by any participants who spent greater than one hour per week using the service. Distraction. It is easy to associate the distraction reported from technology use throughout the last two decades with Facebook (Barkhuus & Tashiro, 2010). In a quantitative and qualitative study including multiple focus groups, Silverman (2007) found a consistent theme that Facebook was perceived as a waste of time and served as a large distraction. The ECAR study (S. Smith & Caruso, 2010) reinforced this emphasis on distraction. Not only did respondents report concerns that Facebook was distracting them from academic and social endeavors, but some students even stated that Facebook served as a distraction during class through its use on mobile phones. Junco and Cotten (2011) linked this information with data supporting educationally damaging effects of Facebook as a distraction, in a study conducted at a small public Northeastern institution. Their data showed a negative relationship between Facebook use, particularly when studying, and overall GPA. The authors took into account previous literature which provided a framework for understanding that multitasking in any way could negatively affect the learning process. When compared to the relationship between general distractions and GPA, Junco and Cotten‟s (2011) data demonstrated that paying attention specifically to Facebook while studying had a markedly more significant relationship to poorer academic outcomes. Positive Outcomes Associated with Facebook Use Despite the list of negative outcomes associated with Facebook use, there are also positives. While the students in Silverman‟s (2007) study reported that they were aware of many of the drawbacks to Facebook use, a majority stated that the overall benefits
    • 51 outweighed these risks. Results from the ECAR (S. Smith & Caruso, 2010) study echoed this finding. The research that follows will show the linkages between Facebook use and positive outcomes. This section will introduce research studies that have shown communicational, psychosocial, and offline benefits connected to Facebook use. Sharing information and opportunities. One of the most commonly cited reasons that Facebook is beneficial on college campuses is that it dramatically increases exposure to opportunities. As has already been established, most college students use this service. It is logical that providing information through Facebook gives the greatest number of students the greatest opportunity to receive that information (Martinez Aleman & Wartman, 2009; Silverman, 2007). Through the qualitative data analysis of the ECAR study, S. Smith and Caruso (2010) found that many students reported being able to organize or discover study sessions through Facebook. Between scheduled Facebook events and informal status updates, students reported the ability to create study groups, organize meeting times and locations, and invite other students, regardless of how strong preexisting social connections were. Silverman (2007) found through qualitative and quantitative data that students discovered many opportunities for involvement through Facebook. S. Smith and Caruso (2010) also reported that students utilized the various aspects of the service to find out about and join on-campus organizations, and that the online context of signing up greatly reduced the social anxiety and barriers to entry that are typically associated with the fear of joining a new organization. The ease of sharing opportunities for co-curricular involvement, access to faculty and staff members, and awareness of events happening within the community are
    • 52 valuable services that Facebook provides (Martinez Aleman & Wartman, 2009). This creates a possible opportunity to accomplish the primary goal of student affairs professionals, in reaching out and encouraging the greatest number of students to become involved in purposefully developmental activities (Heiberger & Harper, 2008). Since such a substantial number of college students use Facebook (S. Smith & Caruso, 2010), a single social media service connects the majority of them. Access to this group of individuals can be useful in mobilizing students for a cause, spreading awareness of an issue, or sharing an opportunity to get involved in an opportunity larger than any single campus (Silverman, 2007). Even more significantly, within Facebook, students are the ultimate authority when promoting their ideas. Therefore, students can start campus initiatives, make the information available to a significant number of users across the world, and receive more respect than if an administrator were to encourage a group of students to act on the topic (Martinez Aleman & Wartman, 2009; Silverman, 2007). Transition to college. Facebook can contribute to easing first-year students‟ transition to the college environment (Ellison et al., 2007; Heiberger & Harper, 2008; Martinez Aleman & Wartman; Silverman, 2007). New students are able to connect with their college network before they arrive on campus. This allows them sufficient time to create online relationships with their new peers, and establish a group of friends to support each other when they arrive on campus. Many orientation staffs and student leaders attempt to reach out to new students during the summer before their arrival. The focus is often to promote joining their clubs or organizations, but the overall goal is to promote positive involvement and make new students feel comfortable about their
    • 53 transition before they officially begin their first year (Heiberger & Harper, 2008; Martinez Aleman & Wartman; Silverman, 2007). The difficult process of leaving a social circle, such as a high school, and starting to form a new one from the ground up can also be stressful, and there is evidence that first-year students utilize Facebook to maintain their old ties as a support system to decrease the stress in creating a new network (Ellison et al., 2007; Manago et al., 2012). Diversity. A core aspect of students‟ development in college is exposure to and acceptance of diversity (Pope, Reynolds, & Mueller, 2004). When students come from less diverse environments, they are less likely to participate in multicultural activities in a new college environment (Pascarella & Terenzini, 2005). Fortunately, studies (Ericson, 2011; Silverman, 2007) have found that Facebook helps facilitate students‟ participation in diverse peer groups and organizations, and promote opportunities for involvement in multicultural activities. On a private campus with very little visible diversity, Ericson (2011) found that traditionally underrepresented students were among the highest users of Facebook, and that they were effectively able to promote involvement in their activities to members of their racial or ethnic group as well as the general community. On a highly diverse campus, Silverman (2007) found that Facebook use increased exposure to opportunities for involvement with groups of traditionally underrepresented students. Overall, research has shown that Facebook is a useful platform to equalize opportunities for involvement in a variety of multicultural activities (Ellison et al., 2007; Martinez Aleman & Wartman, 2009; Silverman, 2007).
    • 54 Facebook therapy. Facebook therapy is when individuals who experience emotional instability seek social support by posting self-relevant information online through Facebook, in search for fulfillment of psychological and social needs (Buechel & Berger, 2011; Ferrell, 2011). A study conducted at a Midwestern university by Ferrell (2011) found that one function of Facebook use was to maintain a balanced lifestyle between students‟ psychological needs, social needs, and social interactions. The author described Facebook as serving a homeostatic function, where use of the service reduced social pain for those who might have felt excluded, and assisted them in their return to a state of equilibrium. Ferrell‟s (2011) results suggested that Facebook helped students deal with perceptions of social exclusion through the finding that participants who reported feeling left out spent more time using the service. In their study at a mid-Atlantic university, Buechel and Berger (2011) found that social sharing of emotions on Facebook was related to an increase in psychological well- being. The researchers stated that sharing self-relevant content through Facebook acted as a therapeutic source of assistance for students in need. Specifically, Buechel and Berger (2011) found that students‟ perception that close friends and family would read the content that they published boosted their well-being through increasing their perception of social support. Since Buechel and Berger‟s (2011) data showed that emotionally unstable individuals were more likely to share content about negative experiences, students who were in the greatest need of social support were also the ones to receive the most positive outcomes from sharing personal information through Facebook. Manago, Taylor, and Greenfield (2012) found a significant positive relationship between the overall size of one‟s social network and their perception of the
    • 55 level of social support it provided, regardless of how close the relationships within that network were. The results were consistent with previous findings, in that larger social network sizes were correlated with higher self-reports of self-esteem (Manago et al., 2012). Social capital. Ellison, Steinfield, and Lampe (2007) conducted a study to measure the relationship between Facebook use and the bonding, bridging, and maintaining of social capital at a large Midwestern university. Social capital refers to the resources acquired from relationships with people, which allow individuals to draw on resources from members of their network. This is relevant because social capital relates to increased levels of commitment, community, and collective actions. Bridging social capital is utilizing weak ties within individuals to expand and connect new individuals; bonding social capital is the deeper relationship of a close group of friends and family; and maintained social capital is the ability to stay in touch with a social network after physically disconnecting from it (Ellison et al., 2007). The researchers found that Facebook use alone was not a significant predictor of social capital, but that intensity of Facebook use was a highly positive and statistically significant predictor. Overall, there was a correlation between Facebook use and the maintenance and creation of social capital. Ellison et al. (2007) found that Facebook played a role in the process of forming bonding and bridging social capital, as well as maintaining it. The authors noted that Facebook use seemed to lower the barriers to participation in social activities and relationships, and made it easier to initiate and maintain communication, especially among shy students who might be reluctant to do so in person. Bridging social capital, and the establishment of weak ties, was found to be assisted by Facebook use,
    • 56 which resulted in wide and expanding social groups, willingness to support the campus community, and an increased sense of wanting to get involved on campus (Ellison et al., 2007). Moreover, Ellison et al. (2007) found that Facebook use helped students to maintain their social capital, particularly in regards to social networks from participants‟ high schools. The authors argued that this maintained social network is responsible for eliminating the difficulties of losing connection with old friends, and therefore eases the transition into the college social network. Facebook use made it easier for participants to convert latent ties – or social connections that were technically possible but did not yet exist – into actual relationships (Ellison et al., 2007). According to the researchers, Facebook use also assisted students with low satisfaction and low self-esteem. Bridging capital assisted students by providing increased opportunities and information, which allowed them to get more out of their college experience without needing to be highly satisfied, engaged, outgoing, or assertive as prerequisite conditions. Facebook acts as a useful tool in crystallizing relationships that may have started weak, where the individuals did not have access to the time or location to develop them further, and allowed them to build and expand the relationships online (Ellison et al., 2007). Manago et al.‟s (2012) results, when controlled for self-esteem, suggested that those with larger social networks reported that they were overall happier with their lives, implying that the social capital gained through Facebook use has direct applications beyond the realm of the social media service. One of Ellison et al.‟s (2007) closing remarks summarized their findings, “Online interactions do not necessarily remove
    • 57 people from their offline world but may indeed be used to support relationships and keep people in contact, even when life changes move them away from each other” (p. 1165). This explanation of Facebook‟s role in increasing social capital summarized how Facebook use could translate to increased social and co-curricular involvement. Offline social life. Several studies (Barkhuus & Tashiro, 2010; Ellison et al., 2007; HERI, 2007; Martinez Aleman & Wartman, 2009; Silverman, 2007) have found that increased levels of Facebook use relate to greater levels of offline social interactions. Silverman (2007) found that students reported using Facebook to establish ways to get together with friends offline, and then to stay in touch with their peers during periods where these meetings were not possible. The results of the HERI (2007) analysis showed that students who reported using Facebook more often also reported spending more time socializing with peers. This finding was later supported by Manago et al. (2012) in that students‟ social networks primarily contained friends gained from participation in co- curricular activities. This finding was potentially explained by the idea that increased time spent offline in various activities introduced students to more potential Facebook friends, which then resulted in a larger amount of time spent using the service (Manago et al., 2012). In Barkhuus and Tashiro‟s (2010) study, participants reported that using Facebook increased their offline social lives because it was so easy to connect online to create and maintain their relationships. Ellison et al. (2007) found evidence to suggest that participation in an online Facebook community did not preclude students‟ from involvement in the offline world, but in fact was useful in promoting that involvement both within the campus community, as well as with relationships to individuals in
    • 58 previously inhabited communities. Measures of Facebook Use Researchers have developed multiple measures of Facebook use. Understanding how people use Facebook is relevant for marketers, psychologists, and educators alike. The type of measurement a researcher chooses to use is a direct result of the primary goals for which they intend to use the information, and therefore the types of measurements vary greatly. The most prominent measures of Facebook use are the Facebook Intensity Scale, the Net.Generation survey, and Junco‟s (2012) Facebook instrument. Facebook Intensity Scale. In the field of marketing and communications media, the most prominent measurement of Facebook use is the Facebook Intensity Scale (Ellison et al., 2007). It focused on the motivations and gratifications of users of Facebook, and included specific scales for each of Facebook‟s various services. It is composed of a list of activities in which participants indicate how frequently they use the service, and then determines the benefits and social results of that participation. It is a thorough and long instrument, and has been proven to be effective in gauging how and why participants use the service (Ellison et al., 2007). Net.Generation survey. Junco and Mastrodicasa (2007) created an instrument for their study of how Millennials, or in their words the Net generation, use modern social technologies. This instrument focused on what services students use, how they interact with them, and how much time they spent using them. It broadly measured how students used online instant messaging, cell phones, Internet websites, and social media. The instrument has not been updated since the researchers created it, and most of the
    • 59 technologies that it measures are no longer indicative of what students use, though it was very effective in laying a foundation for researchers to measure this type of technology use. Junco’s (2012) Facebook instrument. Most recently, Junco (2012) studied college students‟ use of Facebook and their overall educational engagement. He sought to measure both the quantity of Facebook use, but also the way in which participants used the service. This instrument measures the quantity of Facebook use in two ways. It asks how many minutes participants spend using the service in an average day, and then how many minutes they spent yesterday. Next, it asks how many times the participant checks Facebook in an average day, and how many times they checked yesterday. In order to measure the behaviors in which students participate while using Facebook, Junco (2012) created a 14-item questionnaire measuring specific Facebook behaviors. The author created the instrument by asking for recommendations from current students, Facebook friends, and a network of expert professionals, on how students currently use Facebook. Junco (2012) then compiled the list and presented it to two classes of undergraduate students. After making suggested modifications, colleagues and students made final recommendations through Facebook in regards to wording and content structure. Current students who use Facebook, and a group of expert professionals knowledgeable on the topic verified the questions of the final instrument (Junco, 2012), and the behaviors that the instrument measures reflect the findings of previous research (Papacharissi & Mendelson, 2011; Smock et al., 2011) on the ways in which individuals use Facebook. This 14-item questionnaire seeks to measure what percentage of time users spend participating in these specific Facebook activities.
    • 60 For the current study. While the Facebook Intensity Scale is highly regarded within the field that has produced the most literature on Facebook, it is very long and detailed, specifically in regards to the motivations and outcomes of Facebook use. Therefore, it is beyond the scope of the purposes of this study. As for the Net.Generation survey, only Facebook use is of interest for this study, which makes this survey is too broad to meet the needs of this research, and it has not been updated to reflect recent changes in technology. Junco‟s (2012) instrument measures the quantity of Facebook use, through minutes of use per day and number of times checked per day, and behavior of Facebook use, by measuring how frequently students participate in specific Facebook activities. This instrument meets the specific needs of the current study in that it succinctly provides detailed information about Facebook activities, as well as level of use. Junco‟s (2012) instrument is designed to measure the information that this study is seeking to collect, and does so better than other previously mentioned instruments. Summary Facebook is by far the preferred social media service of choice for college students; many students report spending a great deal of time utilizing the service (Junco, 2012; S. Smith & Caruso, 2010). The research has simultaneously identified positive and negative outcomes associated with this use. However, based on the different activities that can be performed through Facebook, and viewing it as a collection of unique tools rather than a single entity, it is more likely that the service itself has no intrinsically positive or negative influence (Junco, 2012). Having looked at the issues of Facebook use among college students, and with an effective tool to measure specific Facebook activities in relation to the level to which students use the service, data will be provided
    • 61 that will help answer the research questions for this study. The next section will look more specifically at the psychosocial development of college students, with an emphasis on co-curricular involvement in relation to Facebook use. Facebook and Involvement The definitions of Facebook use and co-curricular involvement have now been presented. It is necessary to understand Facebook use since college students use the service so heavily (Junco, 2012; S. Smith & Caruso, 2010); it is equally essential to understand co-curricular involvement due to its impact on student development and persistence (Astin, 1984; Pascarella & Terenzini, 2005). Despite the importance of these concepts, the relationship between college students‟ level and nature of Facebook use and co-curricular involvement is still not well understood (Junco, 2012). Before the existence of Facebook, scholars have speculated that social technologies would have an impact on co-curricular involvement. Strange and Banning (2001) noted the dual potential of the introduction of computer-mediated communications on campus. Depending on the viewpoint, technology could potentially be either responsible for destroying vital aspects of the current definition of community on campus, or for assisting in creating an even more dynamic and accessible community. Lowery (2004) echoed that perspective by speculating that online social relationships could prove beneficial in strengthening offline connections, but that care must be taken to avoid the potential downside of eliminating the priority of face-to-face communication. In a study of a selection of data from the 2003 National Survey of Student Engagement (NSSE), Nelson Laird and Kuh (2005) found that students who were frequent users of technology also displayed higher levels of educational achievement and engagement.
    • 62 The studies (Heiberger & Harper, 2008; HERI, 2007; Junco, 2012) that researchers have conducted to date on Facebook use have helped illuminate potentially meaningful relationships with involvement. Most of these studies have focused on broader measurements of student engagement rather than the specific definition of involvement used for this study. Since interest in Facebook for its developmental and educational outcomes is a recent development on college campuses, relevant research is limited, and therefore this section will provide an overview of all of this literature. Negative Relationship Of the studies that have included objectives to test for a relationship between Facebook use and level of involvement, one found an overall negative correlation. Junco (2012) conducted a study to measure the relationship between level of engagement within the institution, and level and behavior of Facebook use. He sampled all students through a campus-wide email invitation at a mid-sized, Northeastern public institution, and received an overall response rate of 44%. The purpose of the study stemmed from a belief that a link existed between Facebook and real-world engagement in meaningful ways. The first construct that Junco (2012) based this study on was engagement, defined by Kuh (2009). The researcher measured engagement through an instrument written by Junco, Heiberger, and Loken (2010) for a similar study of Twitter use and engagement. The researchers created this instrument by adapting 19 items from NSSE, with permission, that specifically targeted the researchers‟ definition of engagement. As part of engagement, the instrument measured students‟ level of involvement through one item, which asked how many minutes per week students typically spent involved in activities
    • 63 outside of the classroom. This understanding of engagement is similar to the definition of involvement used for this study, but differs in a few ways. As stated earlier, involvement relates to behavioral decisions. While research has shown a direct link between involvement and personal development (Astin, 1984, 1993; Pascarella & Terenzini, 2005), the definition for this study did not seek to understand that outcome. Junco‟s (2012) definition of engagement, on the other hand, intentionally sought to understand the developmental outcomes of engagement. Moreover, engagement as used for Junco‟s (2012) study was primarily focused on academic outcomes. It included a limited emphasis on co-curricular involvement as a key aspect of overall engagement, but emphasized academic measures and outcomes of engagement. This was displayed by the fact that the researcher only measured involvement through a simple scale of minutes per week. To measure level and nature of Facebook use, Junco (2012) asked how many minutes each day participants spent using the service, how many times each day they checked the service, and how frequently they participated in specific activities within the service. Junco (2012) found a statistically significant correlation between overall Facebook use and decreased levels of student engagement. Specifically, time spent on Facebook in non-communicative behaviors were negative predictors of engagement, where these behaviors were defined as playing games, checking up on friends, and posting photos. The author concluded that there was a negative relationship between the investment of time in Facebook, and engagement and co-curricular involvement. It is also worth noting that Junco (2012) did find statistically significant positive correlations between specific behaviors of Facebook use, which will be discussed in the section on
    • 64 positive relationships. No Relationship In addition to Junco‟s (2012) study that found a negative relationship between degree of Facebook use and level of engagement, two studies found no statistically significant relationship between Facebook use and co-curricular involvement. The first study (Foregger, 2008) sought to measure students‟ intentions for using Facebook. The second (Ericson, 2011), measured the relationship between socially interactive technologies, including Facebook use, and campus involvement. Foregger’s (2008) study. One of Foregger‟s hypotheses was that students who spent more time involved in campus activities would spend proportionately less time on Facebook. Foregger (2008) administered a survey to students registered for a communication course at a large public Midwestern university, and received 340 responses that met the criteria for the study. First, participants completed a survey of potential uses of Facebook, including how much time they spent on the service. Second, Foregger (2008) asked participants to list the number of student organizations within which they were involved during the previous semester. With that data, Foregger (2008) split participants into two groups based upon level of involvement in campus activities. To qualify for the low activity group, participants reported involvement in no activities; for the high activity group, students were involved in greater than four activities. Foregger (2008) found that whether students reported high or low levels of involvement in campus activities, they reported similar amounts of time spent on Facebook. The author noted that this finding suggested that Facebook is potentially unrelated to campus involvement altogether, in that it neither hinders nor promotes
    • 65 involvement in campus activities. Ericson’s (2011) study. More recently, Ericson (2011) conducted a study to determine if a correlation existed between student use of socially interactive technologies and involvement on campus. Through the researcher‟s definition of socially interactive technologies, the study measured student use of cell phones, text messaging, email, instant messaging, and Facebook. For the construct of involvement, Ericson (2011) based the study‟s definition on a combination of Kuh (2009) and Astin‟s (1984) work, as explained in detail earlier. Ericson‟s (2011) survey combined selections from two instruments. The first instrument the researcher used was a compilation of four subscales of NSSE, which sought to measure student involvement as one specific aspect of engagement. These subscales were diversity within college activities, personal-social growth, non-classroom experience, and miscellaneous student activities. The second instrument was the Net.Generation Survey created by Junco and Mastrodicasa (2007). Ericson (2011) sampled a population of students at a small, private, Northeastern religiously affiliated institution. The response rate was 15.4%, totaling 154 students who were demographically representative of the student population. In the analysis of the social media piece, Ericson (2011) found no statistically significant correlation between Facebook use and measures of involvement in campus activities. Similar to Foregger (2008), Ericson‟s results showed that participants with varying levels of campus involvement reported equally high and low levels of social media use. Ericson (2011) concluded that these findings suggested that students were not disengaged on campus because they are using Facebook, nor were they using Facebook
    • 66 to find new ways to become involved. Rather, Ericson (2011) suggested that the participants had found ways to simultaneously use Facebook and continue to be involved in campus activities. Essentially, Ericson‟s (2011) point was that students who were more involved but who reported similarly high levels of Facebook use must have been multitasking in some way. Due do the high numbers of students using mobile phone to access Facebook, Ericson (2011) concluded that participants had not needed to sacrifice participation in order to achieve high levels of involvement and Facebook use. Positive Relationship On the other hand, three studies have found a positive relationship between use of Facebook, and level of engagement and campus involvement. One was an analysis of data of a nationally representative sample of college students conducted by HERI (2007), while the other two studies (Heiberger & Harper, 2008; Junco, 2012) were single- institution studies. All three discuss the positive relationship between Facebook use and co-curricular involvement. The Higher Education Research Institute’s (HERI; 2007) analysis. HERI (2007) analyzed results of CIRP‟s YFCY survey. The analysis found several statistically significant results that students who spent time on Facebook also spent more time involved socially, and in campus activities, which were measured separately. The HERI (2007) analysis indicated that students who spent more time on Facebook did not consequently spend less time than their peers on academic activities such as homework and preparing for class. Moreover, “First-year students who spent more time on social networking sites were much more likely to report that they interacted daily with close friends at their institution and those not at their institution” (HERI, 2007, p. 2). The
    • 67 authors stated that their results seemed to suggest that students used social media as an extension of their social lives, where students who spent more time involved with their peers also spent more time interacting on social media. Heiberger and Harper’s (2008) study. Seeking to build upon the HERI (2007) analysis, Heiberger and Harper (2008) conducted a survey of 377 students at a medium- sized, public Midwestern university. The goal of the study was to measure students‟ level of engagement in relation to their level of Facebook use. The researchers used the same definitions of Facebook use and engagement as described by Junco and Cole-Avent (2008), which influenced Junco‟s (2012) definition that was discussed earlier in this chapter. Heiberger and Harper (2008) found that students who spent more than an hour a day on Facebook responded that they felt a stronger connection to their friends within their university, and spent more time involved in campus activities. Heiberger and Harper (2008) found that Facebook use did not interfere with campus involvement, and actually related to higher levels of engagement and involvement. In fact, participants who reported spending greater than one hour per day on Facebook were almost 20% more likely to be involved in one or more student organizations. The students were almost twice as likely to spend six or more hours involved in a student organization, compared to students who spent less than one hour per day on Facebook (Heiberger & Harper, 2008). Junco’s (2012) study. Finally, although Junco (2012) found an overall negative relationship between Facebook use and student engagement, the results showed different relationships between individual behaviors of Facebook use. By breaking down individual Facebook behaviors for Junco‟s (2012) Facebook instrument, it became more
    • 68 clear that a positive correlation existed between some activities, and engagement and involvement. First, there was a positive relationship between time spent on Facebook and time spent participating in co-curricular activities. Second, Junco (2012) found that communicative activities, defined as commenting on content, creating or RSVP‟ing to events, and viewing pictures, were statistically significant and strongly positively related to level of engagement. Junco (2012) stated that there was a direct link between these communicative behaviors and real-world experiences, and therefore is logically related to increased levels of engagement. These results indicated that while certain Facebook activities were potentially negative predictors of engagement, others were positive predictors (Junco, 2012). Summary These conflicting results illuminate the fact that there is still a limited understanding of the relationship between college student Facebook use and co-curricular involvement, despite observing that Facebook use and involvement independently have a large impact on students. There has not yet been a study specifically conducted to measure the constructs of Facebook use and co-curricular involvement as defined by Astin (1984). In addition to conflicting results, previous studies have had varying structures, primarily in regards to instrumentation. The results of these studies have shown limited measurement of one or more of the constructs of interest in the current study. Some studies (Ericson, 2011; Foregger, 2008; Heiberger & Harper, 2008; HERI, 2007) have not focused on or measured Facebook use to as nuanced a degree as Junco (2012), where the instrument measured behavior and level of use. Some (Ericson, 2011;
    • 69 Foregger, 2008; Junco, 2012) have also differed in their measurement of involvement. In one case (Foregger, 2008), a minimal measure of involvement in campus activities existed, where the only data collected was the number of organizations in which participants reported being previously involved. Alternatively, the tool to measure co- curricular involvement in another case (Ericson, 2011) was extracted from a larger instrument intended to measure engagement, which is a much broader construct. This lack of understanding restrains student affairs professionals‟ work with students, particularly in promoting their co-curricular involvement and development. Therefore, it is essential to specifically measure, with as much detail as possible, the relationship between level and behavior of Facebook use and involvement on campus. Summary of Literature College students overall are heavy users of technology (Junco, 2012; S. Smith & Caruso, 2010). This has created an expectation that every aspect of the college environment should support this behavior (Arroway et al., 2010). Moreover, the way in which college students connect with their world, information, and peers has changed to fit within this technological environment (Ellison et al., 2007; Junco & Mastrodicasa, 2007; Manago et al., 2012; S. Smith & Caruso, 2010). Regardless of age or generation, the majority of college students prefer to interact through technological mediums, and the modern college campus has grown a great deal to support this trend (Arroway et al., 2010; S. Smith & Caruso, 2010). This is relevant because many aspects of the college experience are impacted by this communication evolution (Junco & Mastrodicasa, 2007), including the understanding of student learning and development that has always guided the work of higher education professionals (Junco, 2012).
    • 70 Students‟ co-curricular involvement is an important aspect of the college experience (Astin, 1984; Evans et al., 2010). How students decide to spend their time and energy is a critical component in understanding the success of institutions of higher education in achieving their educational mission and goals (Davis & Murrell, 1993; Pace, 1982). As the most valuable resource an institution has at its disposal, it is important to determine where students are investing their time and energy to ensure that they are participating in educationally and developmentally beneficial activities (M. Wilson, 2004). Since time and energy are finite resources, it is the role of every member of the institution to verify that positive student behaviors are promoted, because every activity that does not fall within these guidelines is in direct competition with positive levels of involvement (Braxton, 2003). Indeed, Astin (1984) and Baird (2003) called for an evaluation of everything that professionals do within an institution based on their ability to increase involvement. The positive outcomes associated with increasing this involvement are substantial: student satisfaction, psychosocial development, and persistence to graduation (Astin, 1993; Kuh, 1995; Pascarella & Terenzini, 2005; Winston & Massaro, 1987), which scholars stated are essential in a high quality college experience (Astin, 1984; Baird, 2003; Braxton, 2003; Evans et al., 2010; Kuh, 2009; Roberts, 2003; Tinto, 1975; M. Wilson, 2004). More than 85% of college students use Facebook (S. Smith & Caruso, 2010; Smith et al., 2011), and one recent study reported that students spend over 101.9 minutes each day on the social media platform (Junco, 2012). There are many negative and positive outcomes linked with this usage. The negatives include decreased focus on educationally purposeful tasks (Junco & Cotten, 2011), increased stress (Gemmill &
    • 71 Peterson, 2006), and psychological detriments including narcissism (Buffardi & Campbell, 2008; Manago et al., 2012; Saculla & Derryberry, 2011) and depression (Jordan et al., 2011). Positives include increased levels of engagement (Heiberger & Harper, 2008), social capital (Ellison et al., 2007; Manago et al., 2012), and offline social activities (Manago et al., 2012; Martinez Aleman & Wartman, 2009). Students have reported an awareness of most of these negatives and positives, but may not be effective decision-makers in choosing the most beneficial ways of using Facebook (Silverman, 2007). Most importantly, studies determining concrete outcomes of Facebook use are still limited (Junco, 2012). This means that a firm understanding of the ways in which Facebook affects college students is still lacking, especially in regards to its role in the vital task of increasing co-curricular involvement. Conclusion This chapter described characteristics of college students and their technologically connected lives; the importance of co-curricular involvement in student satisfaction, development, and persistence; and college students‟ use of Facebook and the relationship to positive and negative developmental outcomes. It has described many research studies that sought to understand each of these ideas in detail. This chapter ended with a summary and synthesis of these studies, and connected them to highlight the importance of this research study. The following chapter will discuss the proposed methods of conducting this research study.
    • 72 CHAPTER THREE METHOD The purpose of this research study was to determine whether a relationship existed between college students‟ level and nature of Facebook use and co-curricular involvement within the campus community. With the understanding of the significance of this study and relevant literature on these constructs in mind, this chapter will describe the means by which the researcher conducted this study, including the methodology, sample, instrumentation, procedures, and data analysis. Methodology The quantitative research approach for this study employed a correlational design. It aimed to determine if a correlation existed between both the level and nature of college students‟ Facebook use and their co-curricular involvement. This type of study involves determining if a relationship exists between two or more variables, and to what degree, with an attempt to discover a connection (Gay, Mills, & Airasian, 2009). This approach was appropriate because the variables of Facebook use and campus involvement are scale variables, and the study seeks to understand the relationship between the two. Sample The subjects of interest for this study were undergraduate college students who use Facebook and have an active account with the service. Graduate students were not of interest to the researcher because the definition of involvement used for this study pertains particularly to undergraduate students (Astin, 1984). This study was conducted at a mid-sized public doctoral-granting institution in the mid-Atlantic region, which enrolls a fairly diverse population of over 15,000 students. Those invited to participate in
    • 73 this study were selected through a random sample of all current undergraduate students at the institution, with a sample size of 1,000 students. Staff from the research assistance center generated the random sample and provided a list of email addresses to the researcher. Invited study participants were asked to complete an online survey that measured their level and nature of Facebook use and co-curricular involvement, and then collected their demographic data. Descriptive Statistics Of the 1,000 undergraduate students in the random sample, 225 participants responded for an overall response rate of 22.5%. Upon initial analysis, there were eight students who did not report having an active Facebook account, and were removed from further analyses. Ten participants did not complete the entire survey and were also removed from analysis. Therefore, all analyses are based on the 207 respondents with active Facebook accounts who completed the survey. Table 1 provides the responses to the demographic section of the survey. Women represented 73.3% of the sample, and 26.7% were men. The mean age of the sample was 20.7 years of age and the standard deviation was 4.2 years. The age of participants ranged from 18 to 57, although over 89% were between the ages of 18 and 22. First-year students represented the largest group when broken down by years of attendance, at 36.8%. In terms of race and ethnicity, the sample was predominantly Caucasian, with 85.7% of respondents identifying as White. Most categories used in the demographic section of the questionnaire reflected the admission data collected for the institution, to be used in establishing generalizability to the overall campus population. These demographic responses were closely related to the overall undergraduate student
    • 74 population, except for a slight over-representation of women and Caucasians within the response group. Additional demographic data collected from the sample included place of residence, major, GPA, and device used to complete the survey. Among respondents, the largest group of students lived off campus within a five-mile radius of the university, at 43.9%, followed closely by those who lived on campus at 42.9%. A wide range of academic majors were represented in the sample, with the highest percentage of students majoring in the College of Health and Human Services at 38.2%, followed by the College of Natural Sciences and Mathematics at 19.8%. Reported GPA from the Fall 2011 semester ranged from 1.0 or lower to 3.6 of higher, with 3.35 being the mean GPA of participants. The largest group of participants reporting 3.6 or higher at 40%, with only 12.9% reporting lower than a 2.6 GPA. Participants by far used a laptop computer to complete the survey, at 65.7% of responses. The remainder of the respondents used either a desktop computer, or mobile device (defined by the survey as „smart phone, iPod touch, etc.‟), and no respondents reported using a tablet computer.
    • 75 Table 1 Descriptive Statistics for Participants Variable n % Gender Identity ( N = 206) Male 55 26.7 Female 151 73.3 Age ( N = 205) 18 40 19.5 19 43 20.9 20 40 19.5 21 46 22.4 22 15 7.3 23 7 3.4 24 2 0.9 25 2 0.9 26 – 30 5 2.4 31 – 40 3 1.4 41 – 50 1 0.4 50 and older 1 0.4 Race or Ethnicity ( N = 204) American Indian 0 0.0 Asian 6 2.9 Black 12 5.8 Hispanic 3 1.4 International 3 1.4 Multiracial 5 2.4 Pacific Islander 0 0.0 White 175 85.7 Years Enrolled ( N = 206) 1 or less 76 36.8 2 48 23.3 3 40 19.4 4 36 17.4 5 or more 6 2.9 Current Residence ( N = 205) On Campus, Residence Hall 88 42.9 Off Campus, < 5 miles away 90 43.9 Off Campus, > 5 miles away 27 13.1
    • 76 Variable n % GPA, as of Fall 2011 ( N = 205) 1.0 or lower 1 0.4 1.1 – 1.5 1 0.4 1.6 – 2.0 9 4.3 2.1 – 2.5 16 7.8 2.6 – 3.0 29 14.1 3.1 – 3.5 67 32.6 3.6 or higher 82 40.0 College of Enrollment ( N = 207) Business 21 10.1 Education and Educational Technology 24 11.6 Fine Arts 10 4.8 Health and Human Services 79 38.2 Humanities and Social Sciences 31 15.0 Natural Sciences and Mathematics 47 19.8 Device Used for Survey ( N = 207) Laptop Computer 136 65.7 Desktop Computer 36 17.4 Mobile Device (Smart Phone, iPod Touch, etc.) 34 16.4 Tablet Computer (iPad, Kindle Fire, etc.) 0 0.0 Note. Totals of percentages are not 100 for every characteristic because of rounding. Instrumentation The survey for this study was composed of two previously created instruments, and a researcher-created section that collected basic demographic data. The purpose of these individual instruments, their construction, and psychometric properties will be reported. Facebook Instrument Junco (2012) created an instrument to measure participants‟ level and nature of Facebook use. This instrument assesses the participants‟ level of use by asking, on average, how many minutes per day they spend on Facebook. Level of use is also assessed in a question that asks how many minutes participants spent on Facebook yesterday, which refers to the day before the participant completed the survey. It also
    • 77 measures the frequency with which participants log in to Facebook, by asking on average how many times per day the participant logs in, as well as how many times the participant logged in the previous day. Finally, the instrument measures the nature of Facebook use by asking 14 questions related to how likely participants are to engage in specific Facebook behaviors when they log in to the service, along a five-point scale ranging from „very frequently (nearly 100% of the time)‟ to „never‟ (Junco, 2012; see Appendix A). To score the results, the researcher first determined the quantity of Facebook use through the results of the hours of use and the frequency of checking Facebook, and compared the individual scores to the distribution of all participants. Second, the researcher coded the results of the 14 items that measured quality of use, where a response of „very frequently‟ received a score of five and „never‟ received a score of one. Each response generated an individual score, and the researcher analyzed each score independently. The instrument‟s author stated that the process of creating the questionnaire discussed in Chapter two established content validity, by including the most current feedback from the target population of Facebook users and relevant authorities in the field (R. Junco, personal communication, June 20, 2011). Reliability was not reported by the author. College Student Experiences Questionnaire Pace (1982) created the CSEQ in 1978, in order to measure the quality of student effort in the college experience and its impact on achievement. Since its original creation, the CSEQ has been updated three times. The fourth edition, updated by Pace and Kuh in 1998, was used for this study. In measuring the quality of student effort, the
    • 78 CSEQ utilizes 14 scales, seven of which ask students about their use of various campus resources, and seven which ask about the social and academic opportunities in which they have participated. These scales report the quality of effort students invest in their college experience, or their level of initiative, which relates directly to the behavioral component of Astin‟s (1984) definition of involvement. The two scales that were used for this study are the Campus Facilities scale, which measured the extent to which students took advantage of the physical campus, and the Clubs and Organizations scale, which measured the extent to which students participated in campus events and organizations. Some questions from the Campus Facilities scale include “How often have you met other students at some campus location (campus center, etc.) for a discussion,” “How often have you played a team sport (intramural, club, intercollegiate),” and “How often have you attended a lecture or panel discussion.” Questions from the Clubs and Organizations scale include “How often have you attended a meeting of a campus club, organization, or student government club,” “How often have you managed or provided leadership for a club or organization,” and “How often have you met with a faculty member or staff advisor to discuss the activities of a group or organization” (see Appendix B). Responses were measured along a four-point Likert scale, with options ranging from „very often‟ to „never‟. Each choice received a score, with „very often‟ receiving four points, and „never‟ receiving one point. The researcher averaged the score of all items of the questionnaire, where the mean was the quality of effort, or the students‟ behavioral level of co-curricular involvement. Scores were analyzed by individual scale and collectively as a total CSEQ score.
    • 79 To measure the quantity of involvement, the researcher modified a preexisting question on the CSEQ related to academic involvement. The original question asked for hours of academic involvement outside of the classroom each week. The modification for this study simply changed the academic portion to ask about co-curricular involvement. The modified question reads “During the time school is in session, about how many hours a week do you usually spend outside of class on activities related to co- curricular involvement, such as using campus recreational facilities, participating in organizations, campus publications, student government, fraternity or sorority, intercollegiate or intramural sports, attending a lecture or panel discussion, etc.?” The response options were a checklist of the number of hours at five-hour intervals, ranging from zero to more than 30, which were the response options from the original question. Reliability and validity for the CSEQ were estimated through procedures conducted by the Indiana University Center for Postsecondary Research and Planning, based on a nationally representative sample of undergraduate students. A high level of reliability was established, with Cronbach‟s Alpha scores ranging from .74 to .92 among the different scales. Each scale correlated with one another, and the items of the scales were significantly correlated based on their scores. Specifically for the current study, the Cronbach‟s Alpha score for the Clubs and Organizations scale was .83, and the Cronbach‟s Alpha score for the Campus Facilities scale was .74 (Gonyea, Kish, Kuh, Muthiah & Thomas, 2003). Validity for the CSEQ was calculated in several ways. Construct validity was shown through correlations among the activity scales, supported by a factor analysis, which resulted in personal-social and intellectual-academic factors. Content validity was
    • 80 established through inter- and intra-scale cluster correlations, where alpha factors for the Clubs and Organizations scale and Campus Facilities scale were .47-.82, and .74, respectively. Overall, the Buros Mental Measurements stated that the items on the CSEQ are clear, well-defined, and have face validity (Gonyea, Kish, Kuh, Muthiah & Thomas, 2003). Demographics In addition to these two instruments, the survey obtained basic demographic information. Participants were asked to identify their place of residence (on-campus, off- campus residing within five miles of campus, and off-campus residing greater than five miles away from campus), years of attending the institution, gender, age, race and ethnicity, GPA, and academic major (see Appendix C). These demographic characteristics have been shown to directly relate to co-curricular involvement (Astin, 1984; Winston, Miller, & Cooper, 1999) or Facebook use (Ericson, 2011; Hargittai, 2009; HERI, 2007; Junco, 2012), and could affect the results of the correlation between the two. By administering the two previously discussed instruments, the survey for this study measured the behavior and quantity of co-curricular involvement through the CSEQ and the level and nature of Facebook use through Junco‟s (2012) instrument. Procedures R. Junco (personal communication, June 20, 2011) granted approval to use the Facebook instrument. The Indiana University Center for Postsecondary Research and Planning approved the usage of the CSEQ items through a licensing contract. The researcher submitted a proposal to the human subjects review board of the host institution and received permission to conduct a study of live participants. With the aid of the staff
    • 81 in the research assistance center, the researcher established the random sample. The researcher administered the instrument as an online questionnaire through Qualtrics. Qualtrics is an online survey research suite that allowed the researcher to host, distribute, and administer the survey, and from where the results were downloaded at the end of the study. The survey included Junco‟s (2012) Facebook instrument, the two CSEQ scales and question about the number of hours spent in activities outside of the classroom, and demographic questions. The researcher sent an email to the sample inviting them to participate, which described the research study and provided a link to the Qualtrics survey (See Appendix D). The first question of the survey asked participants if they had a Facebook account, and if they had logged in within the last 30 days, based on Facebook‟s definition of an active user. Those who did not meet the criteria for participating were forwarded to the end of the survey, thanked for their participation, and offered the opportunity to enter into a raffle. As an incentive to participate in the study, students were informed that upon completion of the survey they had the option of entering into a raffle drawing to receive one of 10 iTunes gift cards valued at $10 each. Through Qualtrics, the researcher sent two reminder emails to those who had not responded. The researcher then sent a thank you email to all participants after the survey closed. Data Analysis The data of this survey were used to determine if a correlation existed between Facebook use and co-curricular involvement on campus. The researcher downloaded the results of the survey from Qualtrics into the Statistical Package for the Social Sciences (SPSS), and scored them. In the preliminary analysis, the means, standard deviations,
    • 82 and reliabilities were reported for each scale and subscale. Then a correlation was run between the quantity of Facebook use responses and hours per week of involvement, Campus Facilities CSEQ responses, Clubs and Organizations CSEQ responses, and total CSEQ score. Next, a correlation matrix through SPSS was run to identify co-variates among the construct variables and demographic variables. Conclusion This chapter has described the methodology of a research study on the correlation between college students‟ level and nature of Facebook use and co-curricular involvement within the campus community, and explained how Facebook use and involvement were quantified. It has also described the process of analyzing the data collected by the researcher. The following chapter will describe the analysis of the results of this data collection.
    • 83 CHAPTER FOUR RESULTS The research study for this thesis sought to determine whether a relationship existed between undergraduate college student Facebook use and co-curricular involvement on campus. The researcher collected data through an online survey, which administered Junco‟s (2012) Facebook instrument, items from the CSEQ (Pace & Kuh, 1998), and a series of demographic questions. Following the previously introduced methodology, this chapter will report the responses of the data collection of 207 participants in the preliminary analysis, and the correlational findings in the primary analysis. Preliminary Analysis The following sections will report the responses of the 207 participants who had an active Facebook account at the time of taking the survey and completed the survey in its entirety. The first section will describe the reported quantity and level of Facebook usage, followed by a description of the participants‟ level and type of co-curricular involvement. Facebook Usage To determine average levels for Facebook use, the researcher assigned the mean of the range as the score of each nominal response option. Based on the mean of the range, the mean amount of time respondents reported spending on Facebook on average was 61.26 minutes per day, where the most common response was an average of 31 to 40 minutes per day, as reported in Table 2. As for the amount of time participants reported spending on Facebook yesterday, using the same method, the mean time spent on
    • 84 Facebook yesterday was 50.27 minutes, with the largest group of respondents reporting spending 10 or less minutes on Facebook yesterday. There was a strong positive correlation (r = .809, p < .01) between responses to the time spent using Facebook on average and yesterday questions. Table 2 Time Spent on Facebook among Participants Average Facebook Use ( N = 207) Facebook Use Yesterday ( N = 206) Minutes n % n % 10 or less 21 10.1 36 17.4 11 to 20 19 9.2 27 13.0 21 to 30 19 9.2 29 14.0 31 to 40 30 14.5 23 11.1 41 to 50 14 6.8 14 6.8 51 to 60 21 10.1 19 9.2 61 to 70 13 6.3 8 3.9 71 to 80 6 2.9 6 2.9 81 to 90 18 8.7 10 4.8 91 to 100 5 2.4 6 2.9 101 to 110 8 3.9 4 1.9 111 to 120 10 4.8 3 1.4 121 to 130 7 3.4 8 3.9 131 to 140 3 1.4 2 1.0 141 to 150 2 1.0 0 0.0 151 to 160 2 1.0 0 0.0 161 to 170 1 0.5 1 0.5 171 to 180 4 1.9 3 1.4 More than 180 4 1.9 7 3.4 Note. Totals of percentages are not 100 for every characteristic because of rounding. For number of times Facebook was checked on average, based on the mean of the range, participants reported checking Facebook an average of 8.59 times per day, and the highest number of respondents reported checking Facebook between three and four times per day. As reported in Table 3, the mean of participants reported checking Facebook 7.48 times yesterday, with the largest group of respondents reporting checking Facebook
    • 85 three to four times yesterday. There was a strong positive correlation between responses of number of times participants checked Facebook on average and yesterday (r = .841, p < .01). There was a moderate correlation between the average amount of time respondents spent on Facebook and the average number of times they checked Facebook (r = .483, p < .01). A moderate positive correlation existed between amount of time participants spent on Facebook yesterday and number of times they checked Facebook yesterday (r = .571, p < .01). Table 3 Number of Times Facebook was Checked among Participants ( N = 207) Average Facebook Checks Facebook Checks Yesterday Times n % n % Less than 1 5 2.4 14 6.8 1 to 2 30 14.5 36 17.4 3 to 4 38 18.4 42 20.3 5 to 6 31 15.0 34 16.4 7 to 8 25 12.1 16 7.7 9 to 10 23 11.2 17 8.2 11 to 12 12 5.8 10 4.8 13 to 14 5 2.4 10 4.8 15 to 16 10 4.9 4 1.9 17 to 18 2 1.0 3 1.4 19 to 20 9 4.4 9 4.3 21 to 22 3 1.5 2 1.0 23 to 24 2 1.0 0 0.0 25 to 26 4 1.9 2 1.0 27 to 28 2 1.0 1 0.5 29 to 30 0 0.0 2 1.0 More than 30 6 2.9 5 2.4 Note. Totals of percentages are not 100 for every characteristic because of rounding. For the behavioral measurement of Facebook use, the online survey included 14 questions regarding the frequency of conducting different individual activities. Responses ranged from „very frequently,‟ or 100% of the time the participant logged in to Facebook, which received a score of five, to „never,‟ which received a score of one. This
    • 86 section reports the participants‟ responses to these questions, to describe the individual behavior of Facebook use among respondents. The most common activities that participants conducted were: commenting on content, checking to see what their friends were up to, and viewing photos. Nearly half of the respondents reported that they performed these activities somewhat or very frequently when they logged in to Facebook. The least common Facebook activities among participants were creating or RSVPing to events, playing games, posting videos, and tagging videos. More than 77% of respondents reported rarely or never performing these activities. Table 4 reports the responses to all Facebook activities. Table 4 Frequency of Performing Facebook Activities among Participants Variable M SD n % Posting Status Updates ( N = 207) 2.62 0.93 Very Frequently (100% of the time) 6 2.9 Somewhat Frequently (75% of the time) 27 13.0 Sometimes (50% of the time) 78 37.7 Rarely (25% of the time) 75 36.2 Never 21 10.1 Sharing Links ( N = 206) 2.33 1.01 Very Frequently (100% of the time) 4 1.9 Somewhat Frequently (75% of the time) 24 11.6 Sometimes (50% of the time) 54 26.1 Rarely (25% of the time) 79 38.2 Never 45 21.7 Sending Private Messages ( N = 206) 2.70 1.02 Very Frequently (100% of the time) 13 6.3 Somewhat Frequently (75% of the time) 31 15.0 Sometimes (50% of the time) 58 28.0 Rarely (25% of the time) 89 43.0 Never 15 7.2 Commenting on Content ( N = 207) 3.35 1.03 Very Frequently (100% of the time) 29 14.0 Somewhat Frequently (75% of the time) 62 30.0 Sometimes (50% of the time) 78 37.7
    • 87 Variable M SD n % Commenting on Content ( N = 207) 3.35 1.03 Rarely (25% of the time) 29 14.0 Never 9 4.3 Chatting on Facebook Chat ( N = 203) 2.67 1.12 Very Frequently (100% of the time) 10 4.8 Somewhat Frequently (75% of the time) 43 20.8 Sometimes (50% of the time) 52 25.1 Rarely (25% of the time) 67 32.4 Never 31 15.0 Checking to See What Somebody is Up To ( N = 205) 3.51 1.17 Very Frequently (100% of the time) 50 24.2 Somewhat Frequently (75% of the time) 59 28.5 Sometimes (50% of the time) 53 25.6 Rarely (25% of the time) 32 15.5 Never 11 5.3 Creating or RSVPing to Events ( N = 205) 2.02 0.91 Very Frequently (100% of the time) 3 1.4 Somewhat Frequently (75% of the time) 12 5.8 Sometimes (50% of the time) 32 15.5 Rarely (25% of the time) 97 46.9 Never 61 29.5 Playing Games ( N = 205) 1.57 1.03 Very Frequently (100% of the time) 7 3.4 Somewhat Frequently (75% of the time) 10 4.8 Sometimes (50% of the time) 12 5.8 Rarely (25% of the time) 35 16.9 Never 141 68.1 Posting Photos ( N = 206) 2.79 1.07 Very Frequently (100% of the time) 15 7.2 Somewhat Frequently (75% of the time) 36 17.4 Sometimes (50% of the time) 64 30.9 Rarely (25% of the time) 72 34.8 Never 19 9.2 Tagging Photos ( N = 205) 2.51 1.12 Very Frequently (100% of the time) 14 6.8 Somewhat Frequently (75% of the time) 25 12.1 Sometimes (50% of the time) 49 23.7 Rarely (25% of the time) 81 39.1 Never 36 17.4
    • 88 Variable M SD n % Viewing Photos ( N = 205) 3.58 1.06 Very Frequently (100% of the time) 39 18.8 Somewhat Frequently (75% of the time) 82 39.6 Sometimes (50% of the time) 51 24.6 Rarely (25% of the time) 24 11.6 Never 9 4.3 Posting Videos ( N = 204) 1.80 0.92 Very Frequently (100% of the time) 4 1.9 Somewhat Frequently (75% of the time) 5 2.4 Sometimes (50% of the time) 30 14.5 Rarely (25% of the time) 73 35.3 Never 92 44.4 Tagging Videos ( N = 204) 1.63 0.88 Very Frequently (100% of the time) 4 1.9 Somewhat Frequently (75% of the time) 4 1.9 Sometimes (50% of the time) 19 9.2 Rarely (25% of the time) 63 30.4 Never 114 55.1 Viewing Videos ( N = 205) 2.34 1.04 Very Frequently (100% of the time) 7 3.4 Somewhat Frequently (75% of the time) 19 9.2 Sometimes (50% of the time) 58 28.0 Rarely (25% of the time) 73 35.3 Never 48 23.2 Note. Totals of percentages are not 100 for every characteristic because of rounding. Involvement For the first measure of co-curricular involvement, the researcher asked respondents to report how many hours per week they typically spent involved in activities outside of the classroom. This section reports the participants‟ responses to demonstrate the overall amount of time reported participating in co-curricular activities. Table 5 reports that almost half of participants reported spending between 1-5 hours per week involved in co-curricular activities, with zero hours per week being the second-highest ranking response. Based on the mean of the range of response options, the average
    • 89 amount of time that participants spent involved in co-curricular activities was 6.27 hours per week. Table 5 Involvement in Activities Outside of the Classroom among Participants ( N = 207) Variable n % 0 Hours per week 33 15.9 1 – 5 Hours per week 96 46.4 6 – 10 Hours per week 31 15.0 11 – 15 Hours per week 27 13.0 16 – 20 Hours per week 12 5.8 21 – 25 Hours per week 6 2.9 26 – 30 Hours per week 1 0.5 More than 30 Hours per week 1 0.5 Note. Totals of percentages are not 100 for every characteristic because of rounding. Participants answered questions from two scales of the CSEQ to report their behavior of co-curricular involvement. All CSEQ response options ranged from „very often,‟ which received four points, to „never,‟ which received one point. To determine the total CSEQ score and scores on each of the two subscales, the researcher averaged the total CSEQ scores, and the presented score represents the mean of the responses. Therefore, possible scores for the CSEQ scales and total score could range from one to four. Scores on the Campus Facilities scale ranged from one to 3.5, the Clubs and Organizations scale scores ranged from one to four, and the total CSEQ scores ranged from one to 3.54. Overall, the average response to CSEQ items was 1.99, which is equivalent to a response of „occasionally,‟ or that the mean of respondents occasionally used campus resources and participated in campus activities. The correlation between hours per week involved in co-curricular activities and total CSEQ score was r = .536 (p < .01), the Campus Facilities scale was r = .454 (p < .01), and the Clubs and Organizations scale was r = .458 (p < .01). The Campus Facilities and Clubs and Organizations scales were also moderately correlated at r = .444
    • 90 (p < .01). Additionally, there was a strong internal correlation within each of the scales and among all items, demonstrated by Cronbach‟s Alpha scores of .73 to .84, showing a strong consistency within the measures of the behavior of involvement. The most common CSEQ behaviors that participants reported performing were meeting students at a campus location, using campus recreational facilities, and attending a meeting of a campus club or organization. Over 40% of the participants reported that they performed these activities often or very often. Table 6 reports means, standard deviations, and alpha coefficients of the CSEQ measures. Table 6 Involvement Response among Participants ( N = 207) Alpha Coefficient Mean Response Standard Deviation Campus Facilities 0.73 2.07 0.57 Clubs & Organizations 0.84 1.88 0.77 CSEQ 0.82 1.99 0.55 Primary Analysis The primary analyses for this study employed various correlations. The researcher conducted analyses starting from the broadest constructs of the correlation between the quantity of involvement and Facebook use. Then correlations were calculated between more specific items, such as Facebook behaviors and the CSEQ scores. This section will report these findings, and highlight the statistically significant and noteworthy relationships. Correlations between Facebook Use and Involvement The first correlations that the researcher calculated answered the first research question of the relationship between the level of Facebook use and co-curricular involvement. Level of Facebook use variables included the amount of time spent using
    • 91 Facebook on average and yesterday, and the number of times participants checked Facebook on average and yesterday. Involvement variables included hours per week spent involved in co-curricular activities, Campus Facilities scale score, Clubs and Organizations scale score, and total CSEQ score. Table 7 reports this correlation matrix. The most noteworthy correlation this analysis found was a relationship between hours per week of co-curricular involvement and amount of time spent on Facebook yesterday, which had a weak, but statistically significant correlation of r = .137 (p < .05). Table 7 Pearson’s r Correlations between Level of Facebook Use and Involvement Measures ( N = 207) Variables 1 2 3 4 1. Hours of Involvement – 2. CSEQ Total Score 0.536** – 3. CF Score 0.454** 0.876** – 4. C&O Score 0.458** 0.821** 0.444** – 5. FBAvg 0.097 -0.007 -0.016 0.005 6. FBYest 0.137* -0.010 -0.061 0.053 7. FBCheckAvg 0.006 -0.011 -0.016 -0.002 8. FBCheckYest 0.055 0.014 -0.023 0.053 Note. CF = Campus Facilities Scale; C&O = Clubs and Organizations Scale; FBAvg = amount of time spent on Facebook on average; FBYest = amount of time spent on Facebook yesterday; FBCheckAvg = number of times Facebook was checked on average; FBChecYest = number of times Facebook was checked yesterday. * p < .05. ** p < .01. The next set of correlations answered the second research question of the relationship between the nature of Facebook use and co-curricular involvement. Since the Facebook activity scales are non-intervallic and the responses were not normally distributed, a Spearman‟s rho correlation was calculated between the four involvement scores and each of the Facebook activities, reported in Table 8. There were several statistically significant, but weak correlations. The activities that did not have a statistically significant correlation with an involvement score were posting status updates,
    • 92 sharing links, commenting on content, checking to see what someone was up to, playing Facebook games, and posting videos. The only negative correlation was between viewing videos and the Clubs and Organizations scale score. There was a positive correlation between creating or RSVPing to events and all measures of involvement: hours per week of involvement (rs = .232, p < .01), total CSEQ score (rs = .242, p < .01), Campus Facilities scale (rs = .164, p < .05), and Clubs and Organizations scale (rs = .223, p < .01). A correlation also existed between sending private messages and the total CSEQ score (rs = .148, p < .05). There was a relationship between chatting on Facebook Chat and hours per week of involvement (rs = .182, p < .01), total CSEQ score (rs = .217, p < .01), and the Campus Facilities scale (rs = .214, p < .01). The correlation between posting photos and the Campus Facilities scale was rs = .141 (p < .05). Tagging photos was correlated to the total CSEQ score (rs = .195, p < .01) and the Campus Facilities scale (rs = .188, p < .01). There was a correlation between tagging videos and the total CSEQ score (rs = .170, p < .05) and the Campus Facilities scale (rs = .157, p < .05). Finally, viewing videos was positively correlated with the Campus Facilities scale (rs = .186, p < .01).
    • 93 Table 8 Spearman’s rho Correlations between Facebook Activities and Involvement Measures (N = 207) Hours CSEQ CF C&O 1. FB Status 0.016 0.083 0.064 0.106 2. FB Share 0.087 0.101 0.062 0.131 3. FB Message 0.127 0.148* 0.124 0.129 4. FB Comment 0.111 0.112 0.128 0.069 5. FB Chat 0.182** 0.217** 0.214** 0.118 6. FB Checking Up 0.051 0.068 0.046 0.050 7. FB Event 0.232** 0.242** 0.164* 0.223** 8. FB Game 0.060 0.072 0.037 0.110 9. FB Photo-Post 0.019 0.128 0.141* 0.025 10. FB Photo-Tag 0.104 0.195** 0.188** 0.114 11. FB Photo-View 0.120 0.114 0.119 0.048 12. FB Video-Post 0.090 0.140 0.137 0.114 13. FB Video-Tag 0.100 0.170* 0.157* 0.140* 14. FB Video-View 0.060 0.120 0.186** -0.005 Note. Hours = hours of involvement; CSEQ = total CSEQ score; CF = Campus Facilities Scale; C&O = Clubs and Organizations Scale; Status = posting status updates; Share = sharing links; Message = sending private messages; Comment = commenting (on statuses, wall posts, pictures, etc.); Chat = chatting on Facebook Chat; Checking Up = checking to see what someone is up to; Event = creating or RSVPing to events; Game = playing games (FarmVille, MafiaWars, etc.); Photo-Post = posting photos; Photo-Tag = tagging photos; Photo-View = viewing photos; Video-Post = posting videos; Video-Tag = tagging videos; Video-View = viewing videos. In an attempt to meaningfully group the Facebook activity items and identify relationships, the researcher used factor analysis to create groupings of items. This grouping was suggested by Junco‟s (2012) study, where two different sets of activities were found to have opposite effects on the dependent variable. Junco‟s (2012) groupings were not created statistically through factor analysis, but separated by the author based on whether the activity was positively or negatively related to the dependent variable. The groupings separated some activities into either the communicative or non-communicative category. The specific approach of conducting factor analysis for the current study was suggested by R. Junco (personal communication, March 2, 2012) to determine appropriate groupings for the results of this sample, since no prior scales had been
    • 94 established statistically by Junco (2012). The following section will report the procedure of conducting factor analysis to create scales for this study. Factor analysis. The 14 Facebook items were subjected to principal component analysis (PCA) using SPSS version 19. Prior to performing PCA, the suitability of data for factor analysis was assessed. Inspection of the correlation matrix revealed the presence of many coefficients of .3 and above (see Appendix H for correlation matrix). The Kaiser-Meyer-Olkin value was .788, exceeding the recommended value of .6 and Bartlett‟s Test of Sphericity reached statistical significance, supporting the factorability of the correlation matrix. Principal component analysis revealed the presence of four components with eigenvalues exceeding 1, explaining 36.14%, 11.69%, 9.6%, and 8.15% of the variance respectively. An inspection of the screeplot revealed a clear break after the third component. Using Catell‟s scree test, it was decided to retain three components for further investigation. This was further supported by the results of Parallel Analysis, which showed only three components with eigenvalues exceeding the corresponding criterion values for a randomly generated data matrix of the same size. Additionally, based on the items grouped in each component, the three groupings were the most conceptually meaningful to the researcher. The three-component solution explained a total of 57.45% of the variance, with Component 1 contributing 36.14%, Component 2 contributing 11.69%, and Component 3 contributing 9.6%. To aid in the interpretation of these three components, oblimin rotation was performed. The rotated solution revealed the presence of simple structure, with all three components showing a number of strong loadings and all variables loading
    • 95 substantially on only one component, as displayed in Table 9. There were moderate positive correlations between the three factors. The correlations for Factors 1 and 2 was r = .444 (p < .01), Factors 1 and 3 was r = .469 (p < .01), and Factors 2 and 3 was r = .476 (p < .01). The results of this analysis support the use of the three factors as separate scales. Table 9 Rotated Component Matrix Component Variable 1 2 3 Posting status updated .216 .652* .106 Sharing links .026 .583* .341 Sending private messages .007 .743* .151 Commenting on content .571* .554 -.069 Chatting on Facebook Chat .213 .680* .120 Checking to see what someone is up to .646* .036 .124 Creating or RSVPing to events .204 .508* .128 Playing games -.221 .323 .266 Posting photos .810* .138 .217 Tagging photos .774* .171 .267 Viewing photos .786* .181 .147 Posting videos .223 .163 .878* Tagging videos .209 .258 .843* Viewing videos .311 .196 .718* Note. * = Item grouped in this component The first scale, named by the researcher as the Facebook Interactive Scale, contained the following items: posting status updates, sharing links, sending private messages, chatting of Facebook Chat, and creating or RSVPing to events, and had a reliability of α = .68. The second scale, named the Facebook Passive Scale, contained commenting on content, checking to see what someone was up to, posting photos, tagging photos, and viewing photos, and had a reliability of α = .82. The third scale, named the Facebook Video Scale, contained posting videos, tagging videos, and
    • 96 watching videos, and had a reliability of α = .86. After creating these three scales, the researcher analyzed them using a similar method to the individual Facebook activities. Since intervallic scale scores were produced, Pearson‟s r was used to correlate each scale to the four measures of involvement. There were positive correlations between all scales and measures of involvement, and most correlations were statistically significant, as reported in Table 10. Table 10 Correlations between Facebook Activity Scales and Involvement Measures ( N = 207) Hours CSEQ CF C&O FB Interactive Scale 0.199** 0.214** 0.173** 0.190** FB Passive Scale 0.095 0.161* 0.162* 0.107 FB Video Scale 0.106 0.155* 0.184** 0.065 Note. Hours = hours of involvement; CSEQ = total CSEQ score; CF = Campus Facilities Scale; C&O = Clubs and Organizations Scale. * p < .05. ** p < .01. Controlling for Demographics The researcher sought to determine if any demographic variables were influential to the correlations described in the primary analysis. This was done by calculating the correlations between the demographic variables, each of the four measures of involvement, time spent on Facebook yesterday and on average, number of times Facebook was checked yesterday and on average, and each of the three Facebook scales. The strongest correlation found in this analysis was r = .292 (p < .01) between gender identity and the Facebook Passive scale. Due to this correlation, a partial correlation was run between the Facebook Passive scale and each of the four measures of involvement, controlling for gender. No meaningful differences in the correlations were found, so there was no evidence to suggest a need to control for gender. As a result, it was determined that it was not necessary to control for any demographic variables in the
    • 97 primary analysis. Conclusion This chapter presented the findings of a quantitative research study on the correlation between undergraduate college student Facebook use and co-curricular involvement. Data from 207 participants who had active Facebook accounts and completed an online survey were analyzed. The online survey contained a Facebook instrument created by Junco (2012), items from the CSEQ (Pace & Kuh, 1998), and a series of demographic questions. This chapter presented descriptive responses of the participants, as well as the correlation between the constructs of Facebook use and co- curricular involvement. In the next chapter, a discussion of these findings will be presented, as well as limitations of the study and implications for theory, practice, and future research.
    • 98 CHAPTER FIVE DISCUSSION AND IMPLICATIONS The past four chapters of this thesis have described a study of the correlation between undergraduate college student Facebook use and co-curricular involvement within the campus community. Facebook is the largest social media service, and is an online tool where users generate profiles to connect and stay in touch with friends and acquaintances, among other things. A vast majority of college students use Facebook (Junco, 2012; S. Smith & Caruso, 2010; Smith et al., 2011), and they spend a great deal of time using the service (Junco, 2012). Astin (1984) argued that student affairs professionals should work to increase the amount of physical and psychological time and energy that students invest in intentionally educational and developmental activities. Within the context of involvement theory, the amount of time and energy that students spend using Facebook may be negatively correlated to the developmental outcomes associated with involvement. Previous research has identified many negative (Gemmill & Peterson, 2006; Jodan et al., 2011; Saculla & Derryberry, 2011) and positive (Ellison et al., 2007; Manago et al., 2012; Martinez Aleman & Wartman, 2009) outcomes directly associated with Facebook use among college students. This chapter will begin with a discussion of the findings, including an answer to the research questions of this study. The first research question of this study was: Is there a correlation between the level of undergraduate college students‟ Facebook use and their co-curricular involvement within the campus community? And the second research question was: Is there a correlation between the nature of undergraduate college students‟
    • 99 Facebook use and their co-curricular involvement within the campus community? Then, this chapter will provide an interpretation of the findings described in the previous chapter, limitations of the study, and implications for theory, research, and practice. Discussion of the Findings This section will discuss the findings and important relationships in response to the research questions for this study. It will begin with an introduction and interpretation of the preliminary and descriptive findings, including the level and nature of Facebook use and co-curricular involvement among participants. The primary analysis will discuss the statistically significant relationships between Facebook use and co-curricular involvement, as well as potential meanings for the results. Preliminary Findings The initial descriptive analysis of the study revealed insights about the nature and level of Facebook use and co-curricular involvement within the participants of this study. This section will examine the noteworthy findings from both instruments. The researcher will analyze the scores and responses of the participants, and provide a summary of potential behaviors of respondents. Facebook use. As Chapter Three introduced, the participants completed Junco‟s (2012) Facebook instrument as part of the study. This instrument is composed of two sections. The first measured overall level of Facebook use, and the second measured the frequency of conducting specific Facebook behaviors. To score the first half, the researcher used the mean of the range of each option to create the mean score for each response, and represented participants through the mean of all responses. Since each of the Facebook activities listed in the second half of the instrument represent individual
    • 100 behaviors, this section reports responses individually based on option response rate to demonstrate the types of behaviors exhibited among respondents. Starting with average amount of time spent on Facebook, the mean response that participants spent an average of 61.26 minutes per day is notably lower than the most recent reporting of another single-institution study, which found an average usage of 101.9 minutes per day (Junco, 2012). As for time spent on Facebook yesterday, the mean of the responses was 50.27 minutes. For the number of times that participants checked Facebook each day on average, the mean of the responses was 8.59, compared with 7.48 times Facebook was checked yesterday. When considering these responses, one possible pattern that emerges is that on average students spent approximately six to seven minutes using the service each time they logged on to Facebook. Another possible pattern is that participants used Facebook in great depth only once or twice each day, and then checked in for updates for a few moments at a time throughout the rest of the day. These possibilities are especially likely if participants used Facebook from a mobile device during these shorter periods, which is supported by Barkhuus and Tashiro‟s (2010) finding that students used Facebook in short bursts when on a mobile device. There were three Facebook activities that most participants reported engaging in often or very often: commenting on content, checking to see what friends were up to, and viewing photos. In light of how Facebook works, this is not surprising since these three activities can all be conducted from the Facebook News Feed, which is the home page that users arrive on when logging in to the service. This page is a constantly updating feed where users can see all of their friends‟ most current activities, including embedded
    • 101 photos, while having the ability to comment on information without leaving the feed. By simply logging in to Facebook, users are automatically checking to see what their friends are up to and viewing their photos, and do not have to take additional steps to comment on the content they are viewing. These three activities are also easily accessed from most mobile platforms, including cell phones. While this study did not distinguish between the device on which Facebook was used, the high response rate to these three activities could result from the fact that respondents can perform these activities very quickly from any location, and are therefore the most common ways they use Facebook. Among participants of this study, 21.3% and 25.6% reported sending private messages or chatting on Facebook Chat somewhat to very frequently, respectively. Manago et al. (2012) proposed that students who spend more time sending private messages and chatting on Facebook Chat – activities with statistically significant positive correlations among respondents of the current study (rs = .515, p < .01) – have a social network composed of closer, more intimate friends. Fifteen percent of the respondents of the study reported posting status updates somewhat to very frequently. Manago et al. (2012) reported that students who post status updates more frequently believe that they have a large committed audience who read and follow their updates. In their study, there was a link between this perception and higher levels of narcissism, but also increased levels of life satisfaction, perceived social support, and self-esteem. Among respondents in the current study, over 76% reported that they rarely or never created or RSVPed to events. According to Martinez Aleman and Wartman (2009), one of the most effective ways to increase likelihood of student involvement in co-curricular activities through Facebook use is by encouraging them to create and RSVP
    • 102 to events. Of participants, 85% reported rarely or never playing Facebook games, an activity that Junco (2012) stated was one of the most physically and socially isolating Facebook behaviors. Thus, of the activities that previous researchers identified as having the most substantial positive or negative impact on involvement, most participants of the current study did not report performing these activities. Co-curricular involvement. As introduced in Chapter Three, two scales and one modified question from the CSEQ were used to measure co-curricular involvement in this study. The two scales used in the survey were the Campus Facilities scale and the Clubs and Organizations scale. To score the scales, the average of all responses were taken, where a response of „very often‟ received four points, and a response of „never‟ received one point. The modified question from the original CSEQ measured the overall hours per week of co-curricular involvement. The responses to this question were reported to demonstrate participants‟ amount of time spent involved in co-curricular activities each week. The moderate positive correlations between measures of involvement reinforce the tools utilized to quantify the construct of involvement for this study. These correlations suggest that those who spent more time involved in activities outside of the classroom were equally more likely to spend more time taking advantage of the physical campus as well as opportunities to participate in campus activities. It should be noted that over 86% of participants lived on campus or within 5 miles of campus. There were three behaviors on the CSEQ that 40% or more of the participants reported performing often or very often: meeting students at a campus location, using campus recreational facilities, and attending a meeting of a campus club or organization. These three most
    • 103 common activities represent physically spending time on campus, but do not represent higher levels of involvement such as holding a leadership role, meeting with a faculty or staff advisor, or maintaining a regular workout routine. Among the participants of this study, 7.7% received a total CSEQ score which reflected being involved on campus often or very often, and 15.5% of participants of the current study reported playing a team sport often or very often. Over 27% of respondents reported working on a campus committee, student organization, or project often or very often; and 21.4% reported providing leadership for a campus organization often or very often. Other noteworthy activities of co-curricular involvement, including the percentage of students who reported performing them often or very often, are: meeting another student at a campus location, 44.9%; attending a cultural or social event, 22.2%; going to a lecture or panel discussion, 12.1%; and all activities from the Clubs and Organization scale, 13%. Many studies have described important positive developmental outcomes including direct links with student satisfaction, psychosocial and cognitive development, and persistence to graduation (Astin, 1993; Kuh, 1995; Pascarella & Terenzini, 2005), associated with co-curricular involvement, which is measured by these CSEQ items. The representation of this population‟s co-curricular involvement is skewed toward the lower end of the involvement spectrum. Moreover, these scores represent a lower level of involvement than the norms determined by a multi-institutional study of the fourth edition of the CSEQ (Gonyea et al., 2003). The national norm for the Campus Facilities scale is an average response of 2.65, compared to 2.07 in the current study; for the Clubs and Organization scale is a 2.42, compared to 1.88 in the current study; and the overall average score for the two scales is 2.54, compared to 1.99 in the current study.
    • 104 However, based on the amount of hours per week that participants reported being involved in activities outside of the classroom, respondents of this study reported spending more time involved than students in the campus population as indicated by the 2011 NSSE results at the host institution. In response to a very similar question on the NSSE survey with the exact same response options, 71% of first year participants and 70% of senior participants of the 2011 study reported spending 0-5 hours per week involved in activities outside of the classroom, compared to only 62.3% of participants in the current study (Indiana University of Pennsylvania Institutional Research, Planning, and Assessment, 2011). The participants of this study reported being less involved in co- curricular activities than the national norm for the two CSEQ scales used in this study, but reported spending more time involved in co-curricular activities each week than the general student population at the institution. Primary Analysis This section will discuss the correlations between the constructs of Facebook use and co-curricular involvement and attempt to provide an answer to the research questions of this thesis. The researcher will answer the first research question through a discussion of the correlations between the level of Facebook use and co-curricular involvement, followed by answering the second research question through a discussion of the relationship between the nature of Facebook use, or scores of the Facebook activity scales, and co-curricular involvement. Statistically significant findings will be highlighted, and potential sources of the relationships will be offered. In response to the first research question for this study, weak correlations were found between the level of Facebook use and co-curricular involvement among
    • 105 respondents. The results showed a statistically significant, but weak, positive correlation between time spent on Facebook yesterday and hours per week involved in co-curricular activities (r = .137, p < .01). There were no other statistically significant relationships between the level of Facebook use and co-curricular involvement. There are several potential meanings for this relationship, which are evident from the descriptive analysis of the findings as well as the environment of the host institution of the study. The first explanation of the statistically significant, weak positive correlation between time spent on Facebook yesterday and hours per week of co- curricular involvement is that the two constructs are not correlated in any meaningful way. These results could indicate that Facebook use and co-curricular involvement are unrelated, with neither construct having an effect on the other. This low correlation could also be due to the nature of time spent on Facebook among respondents, primarily two of the patterns that emerged when considering the relationship between time spent on Facebook and number of times Facebook was checked. If participants spent no more than several minutes at a time using the service multiple times throughout the day, or for one large period of time followed by many small periods of time, the low correlation could be a result of students using Facebook as a way to fill spare windows of time. Participants could have been using Facebook from a mobile device in these ways, perhaps as a way to pass time in short bursts, as described by Barkhuus and Tashiro (2010). Examples of these types of time periods are the several minutes waiting before a meeting begins, between classes, or immediately before or after a meal. In this way, neither Facebook nor involvement would act as mutually exclusive or influencing activities, they would simply occur in different blocks of available time.
    • 106 While up to one hour each day dedicated to using Facebook is a considerable time commitment, these potential patterns of Facebook use could be less perilous within the context of involvement theory. Another explanation could come from the low variance in the level of involvement among participants, with most grouped around the lower levels of involvement. If overall responses represented a broader range of involvement, then the findings might have potentially revealed a stronger correlation between the constructs. Since the involvement instrument measured a variety of behaviors, from using a study lab to serving on a committee, opportunities for participation are not limited since these activities are simultaneously equally available to all students within the campus. Another important aspect of the correlation between Facebook use and co- curricular involvement is the environment of the host institution of the study. At the time of the study, there was no formal intentional approach to using Facebook within most levels of the institution. This lack of intentionality could have some responsibility for the weak correlations of this study. Despite the fact that most students who participated in this study were generally uninvolved, most used Facebook for a considerable amount of time. Since Facebook does not have a negative or positive role in student involvement, one way that Facebook could be playing a role in students‟ college experience is as a shared unifying experience and common area to discuss daily happenings with their peers. In other words, Facebook could be serving as the social backchannel of the college experience. A backchannel is a real-time online space where individuals can document, discuss, and add to something occurring in a physical space. In this way, Facebook may be acting as the online space
    • 107 for college students to keep track of and share their day-to-day lives. Facebook provides the means to connect and stay in touch with hundreds of individuals across the world, so college students may be using it as the platform for the social commentary of their college experience with their Facebook friends. For the purpose of this study, this conclusion would support the finding that Facebook use is not directly related to physical involvement within the campus, but rather that it is the online background where students go to discuss those things that happen within the physical campus. Another set of correlations were run to answer the second research question, or if there is a correlation between the nature of Facebook use and co-curricular involvement in campus activities. There were correlations found between the scores of each of the Facebook scales created by factor analysis described in Chapter Four, and co-curricular involvement. All relationships were positive, and most were statistically significant. The Interactive scale had the strongest statistically significant, though still relatively weak, relationship with measures of involvement, with its relationship to the total CSEQ score being the highest (r = .214, p < .01). The Interactive and Passive scales are similar to those identified by Junco (2012) in his communicative and non-communicative items, though Junco (2012) did not determine these groupings through factor analysis and there are some items from the current study that do not follow that grouping. Also, while Junco‟s (2012) items were either positively or negatively related to the measure of engagement, items in the Interactive or Passive scale of the current study varied only in the strength of their positive correlation. Items on the Passive scale include commenting on content, checking to see what friends are up to, and posting, tagging, and viewing photos. The first two, commenting
    • 108 on content and checking to see what friends are up to, are activities that can be conducted from the News Feed with no additional steps necessary (Junco, 2012). There is also no indication in previous research that there is a connection between these activities and social relationships or offline involvement. The last three items, posting, tagging, and viewing photos, are typically both physically and socially isolating behaviors. While the photos themselves may imply some social connections – being with people to take the pictures, including friends in them, and reminiscing about an event – the behavior of uploading and tagging photos typically occurs alone from a laptop or desktop computer (Junco, 2012). The items of the Interactive scale, on the other hand, are activities that typically involve more intentional effort and interaction with others (Junco, 2012). Items on this scale are posting status updates, sharing links, creating or RSVPing to events, sending private messages, and chatting on Facebook Chat. Previous research has indicated that Facebook Events is the most effective way to use Facebook to increase co-curricular involvement (Martinez Aleman & Wartman, 2009). In fact, in the current study creating or RSVPing to events was the only individual Facebook activity that had a statistically significant positive relationship with all four measures of involvement. These correlations were among the strongest throughout this study, with the correlation between creating or RSVPing to events and total CSEQ score (rs = .242, p < .01) representing this study‟s strongest relationship between Facebook use and co-curricular involvement. Additional research has identified that sending private messages and chatting on Facebook Chat can indicate intimate interpersonal relationships and increased offline social activities (Manago et al., 2012). Results of the current study are consistent with
    • 109 previous research, but suggest a weaker level of correlation, in that those who engage in these Facebook activities are also somewhat more likely to display a higher level of involvement within the campus community. Another approach to the correlation between the items of the Facebook Passive and Interactive scales to co-curricular involvement can be taken from the perspective of Strange and Banning‟s (2001) explanation of community. Facebook users who spend more time performing activities from the Interactive scale can use Facebook more effectively to invite others to interact with them, or use Facebook as a jumping off point to get involved within the campus community (Junco, 2012; Manago et al., 2012; Martinez Aleman & Wartman, 2009). Strange and Banning (2001) introduced the idea of technology serving as the front porch of the college experience. In this case, Facebook acts as the front porch, or the place where students connect around the college experience to reflect, process, and discuss their experiences. Individuals on the porch have the opportunity to invite others to join them or use the porch as the way in which to join the outside social world, similar to activities on the Interactive scale. The porch also allows individuals to choose behaviors more associated with „lurking‟ on the social world beyond (Strange & Banning, 2001), similar to those who spend more time conducting behaviors from the Passive scale (Junco, 2012). Limitations While this study provided results that revealed several statistically significant findings, when considering these results the reader should acknowledge a few limitations. By design, this was a single-institution study. Though each of the instruments has been used separately in other studies, the results of the participants in this study may not be
    • 110 representative of all college students. In some ways, the demographic breakdown of participants is not representative of the host institution‟s student population as a whole. While it is close, and representation can potentially be assumed, the group of respondents is overly representative of women and Caucasians. A limitation of the measure of involvement is that there are many factors that influence student involvement on campus. These factors include studying and having a job, among many others (Astin, 1984; Pace, 1982), though these potentially influential factors were not measured in the current study. Junco (2012) based part of the Facebook instrument on measuring individual Facebook activities, but each activity is its own scale item. This makes scoring difficult since a cumulative score is not generated. While factor analysis was used for this study to aid in scoring and interpretation of the results, it did not create the same groupings of activities as identified in Junco‟s (2012) original study. Additionally, Junco‟s (2012) Facebook instrument is new and lacks a formal verification of its psychometric properties. Implications Considering the findings of this study, as well as potential interpretations of their meaning, there are a number of implications for the future. From the weak but positive and statistically significant correlations that existed among respondents, to the different levels of correlation based on various Facebook activities, potential new directions emerge. This section will identify implications for future theory, research, and practice. Implications for Theory The primary theory that this study utilized was Astin‟s (1984) theory of involvement. Astin (1985) identified five postulates, and stated that involvement is the
    • 111 amount of physical and psychological time and energy that students invest in their college experience. One aspect of the theory noted that student time and energy are finite resources, so all of the options for how to spend this time and energy are in direct competition with each other. Therefore, it is the role of student affairs professionals to assist college students in choosing to participate in the most intentionally developmental and educational activities in order to maximize the positive outcomes associated with involvement (Astin, 1984; Braxton, 2003; Evans et al., 2010). The findings of the current study suggest that time spent on Facebook is unrelated to co-curricular involvement. Involvement theory should be re-examined in light of students‟ online presence through social media, which did not exist during the creation of the theory. Furthermore, there is the potential that students simultaneously engage in multiple activities while using Facebook, especially if they are accessing the service from a mobile device as speculated by Ericson (2011). If this is the case, the ways in which students spend their time would not necessarily be mutually exclusive, which would indicate a modification to involvement theory to account for the possibility of simultaneous activities or multi-tasking. With these findings in mind, it may also be appropriate to reconsider the characterization of Facebook as a negative use of time (Foregger, 2008; Gemmill & Peterson, 2006; Junco & Cotten, 2011; Silverman, 2007) within the context of involvement theory Implications for Research In order to determine more generalizable answers to the author‟s research questions, this study should be conducted at institutions with a more diverse student population, and among different types of institutions. It is important to measure the
    • 112 correlation between Facebook use and co-curricular involvement among diverse student populations, especially since the participants of this study are overly representative of Caucasians compared to the general student population, so the findings could vary if studies specifically target traditionally underrepresented groups of students. When exploring the effect of demographic variables, it will be useful to conduct a logistical hierarchical regression in order to gain an understanding of the predictive power of these variables on the constructs and their correlations. It is also important to measure this correlation within various institutional settings, since this relationship may be different based on institutional type as well as the environment of the institution in regards to how Facebook is utilized and how involved the student population is in co-curricular activities. As mentioned in the interpretations of the findings, one aspect that could potentially affect these relationships is the environment in which the study occurs, specifically how intentional different groups of the community are in using Facebook to increase involvement. In order to understand what impact the environment could have, if any, another approach would be to conduct an environmental assessment among institutions with different levels and types of intentional Facebook use in addition to administering the instrument used for this study. One way to increase the effectiveness of the measure of Facebook use could be to include a way to determine the differences between mobile use and desktop use. While it is clear that many students use Facebook on their mobile device (S. Smith & Caruso, 2010), only qualitative studies have sought to understand this use as it differs from traditional Facebook use (Barkhuus & Tashiro, 2010). Another way to improve the measure of Facebook use would be to create scales to understand how certain groups of
    • 113 Facebook activities are related, and create scoring methods for those scales. Moreover, future research could further examine the distinction between the nature of Facebook use into the Interactive and Passive scales, and examine the difference between the outcomes associated with use of items from these different scales. The strongest determining element of the correlation between Facebook use and co-curricular involvement in the current study was the way in which students chose to use Facebook. This is highlighted by the finding that the strongest positive correlation with measures of involvement was creating or RSVPing to events, followed by the Facebook Interactive scale, compared to lower positive correlations among items of the Passive and Video scales. This supports recommendations by Smock et al. (2011), and Junco (2012), that Facebook should be viewed as a collection of social media tools rather than a single entity. While Facebook as a whole was largely neutral in the current study, some of its services were associated with varying levels of positive outcomes. Moving forward, researchers could focus more on understanding how certain Facebook activities have varying effects on involvement and developmental outcomes, and how these positive outcomes could be enhanced. If Facebook use has a similar quantitative and qualitative definition as involvement, it would be beneficial to have an instrument that measures and scores Facebook use as comprehensively as the CSEQ measures involvement. Finally, typical of most social media platforms, Facebook is constantly changing in dynamic ways, so it is essential that measures of Facebook use continue to adapt. As more social media services become popular and intertwined, it will be important to move beyond measuring Facebook and find a way to comprehensively measure social media usage as a whole.
    • 114 In order to provide more rich and accurate results, it would be beneficial to add a qualitative component to the study. Ericson (2011) utilized this approach, and simply asked the research question for the study as an open-ended question at the end of the survey, which was useful in providing a comprehensive way to measure the relationship of these variables from the perspective of the participant. Finally, if the goal of co- curricular involvement is student development, then future research should attempt to measure the direct relationship between Facebook use and student development. This can be approached through a similar methodology to that of this study, but using a different instrument than the CSEQ, such as the Student Development Task and Lifestyle Assessment (Winston et al., 1999) or similar instruments. Implications for Practice The findings from this study indicate that there is no meaningful correlation between Facebook use and co-curricular involvement. This contradicts recent studies (Heiberger & Harper, 2008; HERI, 2007; Junco, 2012; Martinez Aleman & Wartman, 2009) in that involvement does not necessarily increase Facebook use, that Facebook does not decrease involvement, and that Facebook is not intrinsically responsible for an increase in involvement (Olson & Martin, 2010). This middle ground sends a message to professionals on both sides of the argument on whether to use Facebook in student affairs: Among these participants, Facebook use was unrelated to involvement in co- curricular activities. The findings from this study do not support the justification of using Facebook to meet students where they are to increase participation in intentionally developmental opportunities. Previous research (Heiberger & Harper, 2008; HERI, 2007; Junco, 2012;
    • 115 Martinez Aleman & Wartman, 2009) suggested that student affairs professionals could potentially look more carefully at the ways in which Facebook is used to interact with students, and the current study provides a recommendation that specific attention could be paid to using activities from the Interactive scale. If Facebook is to be used, intentional time and resources may be dedicated to identify the ways in which to create a developmentally positive environment within Facebook use, rather than simply using the service and expecting positive outcomes. There has been a call to dedicate more resources to professionals‟ use of Facebook (Junco, 2012; Junco & Chickering, 2010; Olson & Martin, 2010). The finding that Facebook activities from the Interactive scale are correlated with slightly higher levels of co-curricular involvement than other activities could be useful in meeting this call, in order to turn an inherently neutral service into one that promotes involvement, meeting the calls of Astin (1984), Strange and Banning (2001), and Evans et al. (2010). Since student affairs professionals have been responsible for increasing co-curricular involvement for decades (Astin, 1984; Evans et al., 2010) the remaining area for future improvement would be the ways in which they use Facebook. If there is a low level of intentional Facebook use, the weak correlation of this study could potentially indicate the baseline, or intrinsic level of Facebook‟s relationship to involvement. This idea of Facebook as intrinsically neutral in relation to developmental outcomes is supported by this author‟s summary of the literature. This summary suggested that many potential outcomes are primarily guided by the ways in which Facebook is used by individuals, and not a reflection of the innate qualities of Facebook itself. If the members of a community use Facebook intentionally and strategically to
    • 116 increase involvement, the relationship between the two might be stronger. When considering the possible conclusion that no correlation exists between Facebook use and involvement because of limited intentional use of Facebook to promote co-curricular involvement, the following perspective emerges as still being relevant. Strange and Banning (2001) suggested that it should be possible to use technology to promote and maintain involvement within the community, as well as “improve the effectiveness of college and university campus learning environments” (p. 198). Since so much time and energy is already dedicated to increasing involvement, it seems to make sense to match that level of dedication by using the most current and popular form of communication technology to do so. As those within institutions begin developing and implementing these intentional Facebook strategies to increase involvement, it will be essential to assess the results of their efforts. A similar approach to the methodology of this study should be used to evaluate the effect of new interventions of Facebook use. This evaluation is essential to determine whether Facebook played a role in any outcomes related to involvement, and can assist in decision-making about the continued allocation of personnel and resources to such interventions. Several steps of education have been suggested by previous literature (Junco, 2012; Junco & Chickering, 2010; Olson & Martin, 2010) and have not been discredited by the results of this study. College students should be educated on the potential positive and negative outcomes associated with Facebook use, and in ways to use Facebook that are relatively more productive at increasing involvement and developmental outcomes when compared to other types of activities. Educational programming can focus on
    • 117 emphasizing ways to engage in activities from the Interactive scale to achieve higher positive outcomes. As educators, student affairs professionals should potentially also be informed about these topics. It is not enough to simply understand what Facebook is. A more sophisticated understanding of Facebook‟s pieces could be beneficial, including how they function, and the ways in which they are related to involvement and potentially developmental outcomes in different ways. This will help them become more effective teachers and role models to their students, and will also assist them in using Facebook in slightly more effective ways to encourage co-curricular involvement. One way to begin this process of educating student affairs professionals could be for graduate preparation programs to include formal or informal training on Facebook use. This may achieve the previous goal of educating student affairs professionals, and could also help graduate students as they transition from their roles of using Facebook as their own social backchannel to finding ways to use it in a professional setting. It should not be assumed that graduate students would already know how to become positive role models and productive users of Facebook. This training is also supported by the ACPA/NASPA professional competency areas for student affairs practitioners (2010) that identified technology as an underlying thread across all professional competences, which would include Facebook-specific training to intentionally target graduate students as they undergo the transition to becoming emerging new professionals. Even those outside of student affairs could benefit from being educated on this neutral relationship between Facebook use and co-curricular involvement. Higher education administrators throughout the institutional community may be included. Astin (1984) and Braxton (2003) proposed everything that every professional within higher
    • 118 education does has an effect on involvement. These professionals should be trained on the importance of promoting co-curricular involvement, as well as ways to use Facebook that are relatively more likely than others to achieve this goal. This will help ensure that all individuals within the institution who may be responsible for coordinating Facebook use will understand that there is likely a neutral relationship between the two, with some activities that are comparatively more highly correlated to positive outcomes than others. Summary and Conclusion This chapter discussed the findings of a research study on the relationship between undergraduate college student Facebook use and co-curricular involvement. The results showed that there is a statistically significant, but weak, correlation between the two constructs. Therefore, Facebook use and co-curricular involvement are not strongly correlated, so neither construct is inherently positive or negative for the other. This chapter discussed the limitations of this study, as well as implications for theory, research, and practice based on these findings. This thesis has stated the problem and significance in understanding if there is a correlation between undergraduate college students‟ Facebook use and their level of co-curricular involvement within the campus community. A review of the literature provided a background on college students, the theory of involvement, and Facebook use among college students. The section that followed introduced the methodology of the research study used to understand this relationship. The researcher described and discussed findings from the study, and found an answer to the research questions among participants of the current study. These findings showed a neutral relationship between Facebook use and co- curricular involvement. Increasing co-curricular involvement has been a core aspect of
    • 119 effective higher education for decades (Astin, 1984; Evans et al., 2010), and Facebook use is highly debated within higher education (Junco & Chickering, 2010; Olson & Martin, 2010). Higher education administrators benefit from understanding the finding in the current study that there is no fixed relationship between Facebook use and co- curricular involvement. It is helpful to understand that the current study suggests that Facebook use is not a significant barrier to involvement. This will assist in making policies and decisions, as well as providing justification for ways to reallocate resources for using Facebook to involve students. Student affairs professionals benefit from these findings in several ways. As educators, they will be able to help students understand the importance of the difference between the ways in which they use Facebook, and highlight the activities that have been found to have a relatively higher level of positive impact on involvement compared to other types of activities. As practitioners guided by the goal to increase co-curricular involvement, this study provides specific activities that are slightly more likely to potentially increase this level of involvement. The findings from this study also can be useful in creating strategies grounded in research to justify the reallocation of resources for Facebook use with students, and assess the effect of those strategies after they have been implemented. Most importantly, these findings are significant because it is only when student affairs professionals can effectively utilize the modern forms of communication used by their students that they will achieve the goal originally provided by Astin (1984) of promoting student development by increasing co-curricular involvement.
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    • 133 APPENDICES Appendix A Junco’s (2012) Facebook Instrument
    • 134
    • 135
    • 136
    • 137
    • 138 Appendix B College Student Experiences Questionnaire (CSEQ)
    • 139
    • 140
    • 141 Appendix C Demographic Data
    • 142
    • 143
    • 144 Appendix D INFORMED CONSENT FORM Correlation Between Undergraduate College Students’ Facebook Use and Co-Curricular Involvement. The following information is provided in order to help you make an informed decision whether or not to participate in this research study. The purpose of this study is to gain a better understanding of the relationship between Facebook use and co-curricular involvement in campus activities. This research will be used to assist campus administrators in educating students about Facebook more effectively, and finding ways to increase opportunities for co-curricular involvement on campus. This online survey should take no longer than five (5) minutes to complete. The survey will focus on your level and behavior of Facebook use, as well as your quantity and nature of co-curricular involvement on campus. Your responses are important to us and we hope you will participate. However, your participation is completely voluntary, and you are under no obligation to participate. There are no known risks or discomforts associated with this research, and due to the nature of the online survey software it is impossible to link your responses to your actual identity. You may discontinue participation at any time by closing the browser window. Your responses will be considered only in combination with those from other participants. The information obtained in the study may be published in journals or presented at professional conferences but your identity will never be revealed. Due to the nature of this online survey software, it will be impossible for even the researcher to link your responses to your name or email address. All participants who complete the survey will be offered the opportunity to enter into a raffle to win 1 of 10 $10 iTunes gift cards. After completing the survey you will be redirected to an entry form, which is not linked in any way to your responses of this survey. If you have any questions regarding this study or would like a summary of the findings, please contact Christopher Weiss at C.Weiss@iup.edu. The faculty advisor for this research is Dr. John Wesley Lowery. This research has been approved by the Indiana University of Pennsylvania Institutional Review Board for the Protection of Human Subjects (724-357-7730). If you have questions about the research, research subjects‟ rights or research results, contact the following person: Christopher S. Weiss Graduate Student, Student Affairs in Higher Education G-37 Ruddock Hall c.weiss@iup.edu 724-357-5506
    • 145 Appendix E Email Inviting Students to Participate Hello ${m://FirstName}, I‟m Chris Weiss, a student in the Student Affairs in Higher Education graduate program here at IUP. I‟m hoping you can help me in a research study I‟m conducting for my Master‟s Thesis on the relationship between college student Facebook use and co- curricular involvement. You have been randomly selected to participate in this study. Your participation is completely voluntary, and if you decide to participate you have the opportunity to enter a raffle to win 1 of 10 $10 iTunes gift cards. The online survey should take approximately five (5) minutes of your time, and your responses and identity will be completely confidential. I sincerely hope you will take the time to let me know how you use Facebook and how involved you are on campus. More information on the study, including an informed consent form, can be found at the first page on the link below. If you would like to participate just follow the link below to the online survey. After completing the survey, you will be provided the opportunity to enter your email address to win one of the iTunes gift cards. Follow this link to the Survey:
 ${l://SurveyLink?d=Take the Survey} Or copy and paste the URL below into your internet browser: ${l://SurveyURL} If you have any questions, please email me at C.Weiss@iup.edu. Thank you so much for considering participating in my study, I hope your semester is off to a great start! Christopher Weiss Graduate Assistant for Training and Student Leadership Office of Housing, Residential Living, and Dining Indiana University of Pennsylvania 724-357-2628
    • 146 Appendix F Institution Review Board Approval
    • 147 Appendix G CSEQ Item Usage Agreement
    • 148
    • 149 Appendix H Spearman’s rho Correlations between Facebook Items ( N = 207) Variables FBAvg FBYest FBCheckAvg FBCheckYest 1. FB Status 0.347** 0.365** 0.355** 0.340** 2. FB Share 0.349** 0.292** 0.263** 0.246** 3. FB Message 0.176** 0.169** 0.167** 0.185** 4. FB Comment 0.364** 0.291** 0.350** 0.310** 5. FB Chat 0.297** 0.322** 0.295** 0.300** 6. FB Checking Up 0.247** 0.142* 0.361** 0.291** 7. FB Event 0.188** 0.164* 0.071 0.047 8. FB Game 0.107 0.116 0.028 -0.007 9. FB Photo-Post 0.244** 0.116 0.321** 0.182** 10. FB Photo-Tag 0.262** 0.118 0.294** 0.162* 11. FB Photo-View 0.324** 0.188** 0.331** 0.226** 12. FB Video-Post 0.222** 0.199** 0.107 0.143* 13. FB Video-Tag 0.238** 0.188** 0.124 0.147* 14. FB Video-View 0.262** 0.221** 0.218** 0.153* 1 2 3 4 1. FB Status – 2. FB Share 0.493** – 3. FB Message 0.237** 0.248** – 4. FB Comment 0.468** 0.282** 0.244** – 5. FB Chat 0.252** 0.216** 0.515** 0.384** 6. FB Checking Up 0.156* 0.046 -0.045 0.383** 7. FB Event 0.143* 0.100 0.259** 0.229** 1 2 3 4 8. FB Game 0.047 0.121 0.212** -0.032 9. FB Photo-Post 0.309** 0.172* 0.138* 0.389** 10. FB Photo-Tag 0.282** 0.206** 0.168* 0.416** 11. FB Photo-View 0.233** 0.128 0.116 0.452** 12. FB Video-Post 0.279** 0.349** 0.199** 0.201** 13. FB Video-Tag 0.318** 0.326** 0.339** 0.212** 14. FB Video-View 0.237** 0.324** 0.134 0.254** 5 6 7 8 6. FB Checking Up 0.181** – 7. FB Event 0.321** 0.070 – 8. FB Game 0.109 -0.009 0.183** – 9. FB Photo-Post 0.223** 0.311** 0.248** -0.084
    • 150 Variables 5 6 7 10. FB Photo-Tag 0.277** 0.312** 0.243** 11. FB Photo-View 0.206** 0.494** 0.139* 12. FB Video-Post 0.222** 0.172* 0.173* 13. FB Video-Tag 0.325** 0.168* 0.209** 14. FB Video-View 0.285** 0.242** 0.143* 9 10 11 10. FB Photo-Tag 0.827** – 11. FB Photo-View 0.593** 0.487** – 12. FB Video-Post 0.288** 0.305** 0.181** 13. FB Video-Tag 0.269** 0.345** 0.203** 14. FB Video-View 0.301** 0.297** 0.335** 13 14 14. FB Video-View 0.547** – Note. FBAvg = amount of time spent on Facebook on average; FBYest = amount of time spent on Facebook yesterday; FBCheckAvg = number of times Facebook was checked on average; FBChecYest = number of times Facebook was checked yesterday; Status = posting status updates; Share = sharing links; Message = sending private messages; Comment = commenting (on statuses, wall posts, pictures, etc.); Chat = chatting on Facebook Chat; Checking Up = checking to see what someone is up to; Event = creating or RSVPing to events; Game = playing games (FarmVille, MafiaWars, etc.); Photo-Post = posting photos; Photo-Tag = tagging photos; Photo-View = viewing photos; Video-Post = posting videos; Video-Tag = tagging videos; Video-View = viewing videos. * p < .05. ** p < .01.