Adaptive learning path generation using colored Petri nets based on behavioral aspects

In E-Learning environment, generating a Learning Path for the learner provides a challenging work for researchers. Learning Path is a collection of different learning items that are combined to achieve a single objective. For adaptive learning path, learner's behavior should be considered for providing an adaptive environment based on learner characteristics. Providing adaptiveness to learners is achieved by using evolving dynamic user profiles. In this paper, User profile is evolved using Case Based Reasoning. The learner's behavior of the E-learning system is tracked dynamically using the Colored Petri Nets. The Adaptive Learning Path is generated using the learner's behavior patterns which are modeled as the learner's characteristics like learning styles, goals and performance. We compare our system with an adaptive e-learning system which considers static profiles for adaptiveness through our performance evaluating method. The measure for completing the course is used to classify the user. The evaluation shows that the user finds the E-learning system more adaptive and resulting in motivation to finish the course.