Profiling eLearning Website Feature Preferences: An Empirical Study

Learning in an eLearning presents different perspective in terms of preference of learning environment components. The patterns of eLearning website feature preferences were investigated in order to provide insights into learning strategies for learners. The focus of this investigation is to develop a classification of types of eLearning website feature preferences (clusters) and investigate their association with the learning of students as indicated via their performance. Based on an empirical study, researcher collected and analyzed students’ eLearning website feature preference in Blackboard. Nine measures were used to cluster the data set. The results revealed four clusters, viz.: Moderate eLearning Feature Preference Exhibitor, High eLearning Feature Preference Exhibitor, Heavy eLearning Feature Preference Sleeper and Moderate eLearning Feature Preference Sleeper, and demonstrated that learning as indicated by performance (grade point average range) different among the four clusters. The implications of eLearning feature preference are discussed from learning and teaching perspectives.