[edit] Understanding Relationships between eLearning Website Feature Preferences and Learning Styles
Mukesh Srivastava (Computer Information Systems)
The primary purpose of this research was to investigate the relationship between perceived learning styles of the eLearners and their preference of eLearning website features. The secondary purposes of this study was to research various models of learning styles for examining learning styles and eLearning website Systems for studying eLearning website feature preferences of the eLearners. A broad research question was undertaken: What impact (if any) does an eLearner’s learning style have on their preferences for specific features in an eLearning website system? To follow an exploratory line of investigation three research questions were used to examine the broad question: 1) How can an eLearning website system be meaningfully selected to study eLearning website features preference? 2) How can an eLearner’s learning style be meaningfully categorized? 3) How do learning styles impact the eLearner’s preference of eLearning website features? Unlike Research Question 1 and 2 that were examined by mainly literature review, Research Question 3 was studied using a full-fledged empirical cycle involving setting up hypotheses, conducting a survey, and analysing data using statistical methods.
Mostly working undergraduate and graduate adult students, from CGPS at University of Mary Washington, were the participants in the survey study, and they completed three parts of the survey: background information, eLearning website feature preference and learning styles. Data analysis was carried out in four parts: descriptive statistics, relevant hypothesis testing, Cluster Analysis, and Kruskal-Wallis ANOVA.
The descriptive statistical analysis was carried out to provide statistical information about the study participants, eLearning Website Feature Preferences and Learning Styles. Correlation studies and hypotheses testing have been performed to study the direction and magnitude of relationship between learning styles and combinations of learning styles. Cluster analysis executed to investigate how learning styles can be clustered and if there is a possibility of correlation between clusters and website features. Kruskal-Wallis ANOVA of clusters and eLearning website features was done to examine the difference between clusters and eLearning website feature preference.
The results pertaining to correlation studies between learning styles and combinations of learning styles of the participants and eLearning website features preference indicated that largely there were non-significant correlations between the learning styles, combinations of learning styles and website feature preferences. There were few significant, but weak positive and negative correlations between the leaning styles and combinations of learning styles suggesting that a caution should be exercised by the eLearning website system designers and instructional designer in formulating eLearning website features using eLearning students’ learning styles as a consideration.
The association of learning style clusters and eLearning website feature preferences were examined and it revealed that Knowledge Seekers were the dominant group among all four clusters. The results indicated that at least two clusters (Knowledge Cultivator and Knowledge Seeker) have similar characteristics with small difference in the Pragmatist score. Kruskal-Wallis Test was conducted to compare the ranked mean scores on Clusters and eLearning website feature preferences. The results also showed that there is no difference in eLearning website feature preferences - among respondents in four Clusters – Knowledge Seeker, Thinker, Knowledge cultivator and Campaigner.
This research is one of the few studies conducted to provide suggestions for eLearning website system designers and online instructions designers about eLearning website feature preference based on learning styles. The results of this study suggest that there is no association between learning styles, combination of learning styles or clusters of learning styles and eLearning website features. Thus, future research should concentrate on exploring other factors that can be investigated in understanding relationships between learning styles and eLearning website features.
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