Examining Learning Styles in an Interactive Asynchronous Online Course

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Conference Proceeding

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Research on learning styles for e-learning is relatively scanty. Our research examines learning styles of learners in an online course environment and their impact on learning strategies and preferences. “Learning style refers to how a learner perceives, interacts with, and responds to the learning environment; it is a measure of individual differences (Anderson and Elloumi, 2004, p. 14).” Existing research suggests that learners should have opportunities to learn from material consistent with as well as material different from their preferred learning styles. Hence, a good case can also be made that instructional design should be robust, that is, it should target multiple learning styles, which is a point of agreement by most researchers and educationists. This case is even stronger for e-learning where students are generally more diverse in terms of age, occupation, background, and geographic region.

The context of our study is an innovative asynchronous online learner-oriented course on Enterprise Resource Planning (ERP), which was designed from scratch using a structured design approach (Coppola, 2002).The ILS (Index of Learning Style) and ATLAS (Assessing the Learning Strategy of Adults) instruments were administered to 49 students enrolled in the course in Fall 2009. Students were also asked questions to assess their learning strategies and preferences for different components of the course. The following general hypotheses are tested: H1: There will be differences in learning styles of students. H2: Learners having different learning styles will display different learning strategies for course components. H3: Learners having different learning styles will display different learning preferences for course components.

The data analysis shows support for all the hypotheses. ANOVA tests performed on 49 observations showed that there was significant difference (p< 0.01) between each of the paired scales for each dimension measured by the ILS instrument. The dimensions are Active/Reflective, Visual/Verbal, Sensing/Intuition and Sequential/Global. Learners displayed different learning strategies and were classified as navigators, problem solvers and engagers. The distributions based on the sample were 38.78%, 42.86% and 18.37% respectively. Learners displayed differential preferences for course components that included case studies, individual assignments, instructor presentations, SAP software, and a project, among others.

Different learning styles were observed involving different learning strategies and preferences for different components of the course. The specific findings have implications for educators of online courses, educators of ERP, and researchers in online learning. Instructors can build more robust courses for e-learning and researchers will appreciate the complex links between learning styles and instructional design in an e-learning environment. Implications for future research are discussed.

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