A Novel Adaptive Learning Path Method

Finding an appropriate learning path and content is an important issue to achieve learning goal especially in elearning systems. The main challenge of these systems is providing courses suitable to different learners with different knowledge background. Such systems should be efficient and adaptive. Furthermore, an optimal adaptive learning path can help the learners in reducing the cognitive overload and disorientation. In this paper, a novel two stages adaptive learning path algorithm, which is called ACO-Map is proposed. Discovering groups of learners according to their knowledge patterns is performed in first stage. Then in second stage ant colony optimization as a metaheuristic method is applied to find learning path based on Ausubel Meaningful Learning Theory. The output of this algorithm is a concept map for each group of learners according to their needs.