Is E-Learning for Everyone? An Internal-External Framework of E-Learning Initiatives
Pingying Zhang Department of Management Coggin College of Business University of North Florida Jacksonville FL 32224 USA Pingying.firstname.lastname@example.org
Lakshmi Goel Department of Management Coggin College of Business University of North Florida Jacksonville FL 32224 USAl.email@example.com
A framework called the Internal-External Model is proposed in an effort to explain individual e-learning success. This framework is derived from the strategic management technique of identifying strengths, weaknesses, opportunities and threats (SWOT). The framework is tested through data collected at a large southern university in the US, and the findings reported.
Results support a model where a favorable external environment for e-learning together with strong internal drives towards e-learning would in general lead to higher e-learning outcomes.
many higher education institutions have adopted e-learning in some form as part of their curriculum offering. Courses branded as online, distance, hybrid, or virtual, have some component which leverages electronic platforms for education
We rely on literature in strategy, specifically the strengths, weaknesses, opportunities, threats (SWOT) analysis, to guide the development of a framework that explains e-learning success. While the use of the SWOT framework in explaining e-learning is not new, prior research falls short in describing a model specific to the e-learning context, and providing empirical support for such a model.
One way to define success is through outcome factors such as enhanced learning, time savings, and academic success (Davies & Graff, 2005; Govindasamy, 2002; Garrison & Anderson, 2003)
. Another perspective on e-learning success considers system delivery factors such as the degree of use of the e-learning system and its adoption (Holsapple & Lee-Post, 2006).
User satisfaction has proved to be a reliable proxy for the success of an IT-based initiative (Bailey & Pearson, 1983).
Satisfaction itself can be multi-faceted and include elements such as perceptions of student achievement, attitudes and retention (Bernard et al., 2004), online interactions, thinking skills, information-processing skills (Hew & Cheung, 2003), and perceived quality of online courses (Rodriguez et al., 2008).
Prior research that predicts e-learning success outcomes has yielded inconclusive results.
For example, Rodriguez et al. (2008) failed to find a significant link between comfort with technology and number of online courses taken, while Gunawardena and Duphorne (2000) found that a learner well equipped with online skills is significantly associated with the satisfaction of online learning.
The SWOT framework is a strategic analysis tool used to identify and evaluate the strengths, weaknesses, opportunities and threats involved in a project or business venture.
A central idea in SWOT analysis is identifying a primary objective, or desired end state of the project.
Strengths and weaknesses are identified for the persons or practices within the organization that help or impede the achievement of the objective. Opportunities and threats relate to external environmental conditions that help or impede the achievement of the objective. Hence, strengths and weaknesses are considered factors internal to students participating e-learning; while opportunities and threats are factors external to the students. This framework is used as a guide to identify internal and external factors of interest in our context, i.e. e-learning initiatives.
SWOT analysis has been used to evaluate software tools for e-learning systems (Bilalis et al., 2002), distance learning opportunities (Tait & Mills, 1999), broad university strategies (Cardosa, Trigueriros & Narciso , 2005), student perceptions (Jackson & Helms, 2008), and digital library implementations (Wang, 2003).
The SWOT can be typically represented as a two-by-two matrix, such that combinations of strengths, weaknesses, opportunities and threats at different levels create different conditions that influence outcomes.
Individuals’ ability to use e-learning systems includes computer skills and comfort with the online mode of learning content delivery (Eastmond, 1994). This factor has received a strong empirical support in the context of the academic computer conference system (Harasim et al., 1995; Gunawardena & Duphorne, 2000), indicating the central role played by online skills and computer skills in the perceived satisfaction of e-learning.
Hypotheses one to four stress the effect of external construct—ease of use of technology—and four internal constructs—online skill, general attitudes towards IT, personal innovativeness in IT and online experience
Hypothesis 1 states that a high level of online skills with technology of high ease of use will generate better e-learning satisfaction than a low level of online skills with technology of low ease of use
In general, this hypothesis is supported
Hypothesis 2 describes that a strong attitude towards technology and high ease of use will generate better e-learning satisfaction than weak attitude towards technology and low ease of use.
Hypothesis 2 could be considered as supported
Hypothesis 3, we found significant differences for two outcomes, content satisfaction and efficiency & effectiveness, indicating strong personal innovativeness in IT and high ease of use will generate better e-learning satisfaction than low personal innovativeness towards IT and low ease of use. Hypothesis 3 is supported
Hypothesis 4 points out that previous online experience and high ease of use will generate better e-learning satisfaction than none-online experience and low ease of use.
Hypothesis 4 is supported
Hypothesis 5 states that a high level of online skills and a high level of institutional support will generate better e-learning satisfaction than a low level of online skills and low level of institutional support. We only find significant difference for one outcome, intention to take more e-learning courses. Hypothesis 5 is partially supported.
Hypothesis 6 is also partially supported as we only found significant difference for one outcome, intention to take more e-learning courses.
In testing hypothesis 7, a high level of institutional support and high personal innovativeness in IT leads to significantly higher medians for three of four outcome measures than a level low institutional support and low personal innovativeness in IT, indicating Hypothesis 7 is supported.
Hypothesis 8 tests whether previous online experience and a high level of institutional support will generate better e-learning satisfaction than none-online experience equipped and a low level of institutional support.
hypothesis 8 is partially supported.
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