Application of the recommended learning path in the personalized adaptive e-learning system

Abstract

The study analyses how the topic sequences (teacher, learner, optimal) proposed in the personalized adaptive e-learning system influence the learning outcomes of the course. Three experiments were organised within the study. The first experiment showed that in most cases higher grades got those students who used the learner topic sequence. That lead to the need for improving the method for obtaining the optimal topic sequence. In the second experiment, the importance and complexity of the course topics was assessed. Next, weights for each topic were calculated based on the grade, importance and complexity of the topic. A recommended learning path development was proposed. The third experiment of the study evaluated the recommended learning path. The results showed that the recommended learning path gave better learning outcomes for two topics when compared to the optimal topic sequence. Future research will focus on the recommended learning path validation using larger sample group.