Tsai, I.-C., Kim, B., Liu, P.-J., Goggins, S. P., Kumalasari, C., & Laffey, J. M. (2008). Building a Model Explaining the Social
Nature of Online Learning. Educational Technology & Society, 11(3), 198–215.
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Building a Model Explaining the Social Nature of Online Learning
I-Chun Tsai, Bosung Kim, Pei-Ju Liu, Sean P. Goggins, Christiana Kumalasari and James
M. Laffey
School of Information Science and Learning Technologies (SISLT), University of Missouri-Columbia, USA //
itch9@mizzou.edu // bkq22@mizzou.edu // pl6tf@mizzou.edu // outdoors@acm.org // ckef7@mizzou.edu //
laffeyj@missouri.edu
ABSTRACT
Based on a framework emphasizing the social nature of learning, this research examines a model of how social
constructs affect satisfaction within online learning using path analysis for students in higher education. The
social constructs evaluated in this study include sense of community (SOC), social ability (SA), perceived ease
of use (PEU) and usefulness (PU) of social awareness tools, and self-reported participation (SRP) in online
courses. Students’ social ability is predicted by perceived ease of use of social awareness tools and self-reported
participation. Satisfaction with online learning is explained by sense of community, social ability, and self-
reported participation. Sense of community is shown to be a mediator of the relationships between social ability
and satisfaction (SA S) and between perceived usefulness and satisfaction (PU S). Additionally, students’
social ability, perception of usefulness of social awareness tools, and self-reported participation serve as
predictors for students’ sense of community. The findings from the path analysis show the value of
simultaneously examining the relationships among the multiple social constructs, rather than simply examining
relationships of how one construct may predict another as has been shown in previous studies.
Keywords
Sense of community, Social ability, Technology Acceptance, Participation, Online learning satisfaction, Path
analysis
Introduction
Online learning has become a pervasive part of higher education. Online enrollment increased from 1.98 million in
2003 to 2.35 million in 2004, and approximately 74 percent of public institutions of higher education identified
online education as a critical long-term strategy in 2005 (Allen & Seaman, 2005). Many positive reports of online
learning success show its impact and potential, such as relative equivalence in test-result outcomes with face-to-face
courses (Talent-Runnels, et al., 2006), broad implementation and rapid growth across higher education, and
provision of access for many students who would otherwise have to forego higher education. Although students
appreciate the flexibility and convenience offered by online learning environments, online students do experience a
sense of isolation (Abrahamson, 1998; Bessar & Donahue, 1996; Rahm & Reed, 1998), and express being more
satisfied with face-to-face courses (Allen, Bourhis, Burrell, & Marbry, 2002; Simonsen, 1997; Klesius, Homan, &
Thompson, 1997). In her study, Carr (2000) found higher dropout rates for distance education (10-20%) over
traditional programs. Reasons given for the high dropout percentage of distance learners include limited support and
service of distance education, dissatisfaction with teaching methods, unfamiliarity with the technology used, and
student feelings of isolation. Hara and Kling (2000) also found that online students were frustrated by the
communication and technical difficulties that impeded interaction. Arbaugh (2000) argues that the lack of social
interaction was a factor that depressed student satisfaction in online learning. This dissatisfaction with online
learning can be seen in high rates of attrition for online students (Chyung, 2001). Ashar and Skenes (1993) found that
while adults were attracted to a higher education business program because of strong learning needs; those needs
were not strong enough to retain them. However, retention was positively impacted by establishing a social
environment within the program. Students need to feel involved and develop relationships with other students in an
online course (Rovai, 2002a). Following from an appreciation of the social nature of learning, learning and cognitive
development are recognized as substantially constituted through social participation and interaction (Vygotsky, 1978;
Wenger, 1996). In order to understand how students’ online learning satisfaction is affected by their social
participation and interaction with others, the present study seeks to build a model of the elements that contribute to
the social nature of online experience and influence satisfaction in online learning environments. We begin by
framing our research with key social constructs for understanding the social nature of online learning. Next, we
describe the use of path analysis, to examine the relationships among these constructs. Our results, present a model
for explaining how these social constructs influence satisfaction in online courses.