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Presenting feedback to learner is one of the essential elements needed for effective learning. Feedback can be given to learners during learning but also to authors during course development. But producing valuable feedback is often time consuming and makes delays. So with this reason and the others like incomplete and inaccurate feedback generating by human, we think that it’s important to generate feedback automatically for both learner and author in an intelligent tutoring system (ITS). In this research we used ontology to create a rich supply of feedback. We designed all components of the ITS like course materials and learner model based on ontology to share common understanding of the structure of information among other software agents and make it easier to analyze the domain knowledge. With ontologies in fact, we specify the knowledge to be learned and how the knowledge should be learned. In this paper we also show a mechanism to make reason from the resources and learner model that it made feedbacks based on learner.

AUTOMATIC FEEDBACK GENERATION - Using Ontology in an Intelligent Tutoring System for both Learner and Author Based on Student Model