Designing an intelligent tutoring system based on learners’ selfefficacy and learning style features

The purpose of this article is to design an intelligent tutoring system which exploiting selfefficacy attributes of students, can personalize the learning environment. The learner model of the proposed system includes features of academic selfefficacy and learning style. After identification of these features, proportional education strategies are presented and implemented in the tutoring system in a real environment. The effectiveness of the proposed approach is evaluated in terms of learners success and their satisfaction from the learning system. The results show that considering functional characteristics in learning model, and proportional recommendations to the characteristics, results in learners educational progress and their educational satisfaction.