CCE Theses and Dissertations

A Multiple Online Learning Platform Study of the Impact of Learning Style on Academic Performance

Date of Award


Document Type


Degree Name

Doctor of Philosophy (PhD)


Graduate School of Computer and Information Sciences


Maxine S. Cohen

Committee Member

Marlyn Kemper Littman

Committee Member

Steven R. Terrell


This research study investigated the relationship between learning style and academic achievement on multiple online learning platforms. The study was based upon data gathered from students enrolled in online courses at two community colleges in northeastern Pennsylvania. The study utilized the theoretical model of David Kolb's learning style theory, the Kolb Learning Style Instrument (LS13), and a researcher-developed survey. Students volunteering to participate in the study completed the survey and LSI. The learning styles, as identified by David Kolb include: accommodator, assimilator, converge, and diverge. These learning styles were compared to the students' academic performance in the courses. The students' academic achievement was measured by their final course grade. The learning styles and academic achievement of the students were statistically analyzed and correlated to the online learning style platform the colleges utilized. The online learning platforms in this study are the two most widely utilized (Blackboard (Bb) and WebCT).

Descriptive statistics and inferential statistical methods were utilized to test the hypotheses related to this research study. The ANOV A and t-test were two of the methods used to test the interval data. The results of the study suggest there were no statistically significant differences related to achievement based upon learning styles on the Bb platform and the WebCT platform. In addition, there were no statistically significant differences in achievement between the Bb platform and the WebCT platform.

There were also, no statistically significant differences in achievement between the learning styles on the Bb platform or on the WebCT platform. The research study also developed a learning style student profile for the Bb platform and the WebCT platform based upon the results of the statistical analysis and random sample population statistics. Data collected from the researcher-developed survey provided information related to age, gender, prior online course experience, prior computer experience, type of course enrolled in, major course of study, family income level, employment status, and the influence of use of multimedia on academic performance. Males and females were represented in all learning style categories with the exception of the diverger learning style category. There were no male divergers on either the Bb platform or the WebCT platform. Although these variables identified were not the major thrust of this research study, they provided insight into future research studies to be undertaken.

This study expected to find differences based upon course platform and/or learning style, however due to some limitations of the study, no significant differences were found. That is not to say differences are not there, just they were not uncovered by this particular piece of research. The results of the study may not be generalized to the entire learning community nationwide based upon the investigation being conducted only on two community colleges in the northeastern section of Pennsylvania and using only two online learning platforms. Additional studies are recommended to further test the hypotheses using different additional online learning platforms, larger sample sizes, and extend findings with other university populations.

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