Learner Model of Intelligent Tutoring System Based on Bayesian Network

Abstract

The main importance of the education system is the intelligent tutoring system (ITS). An ITS is a computer system that wants to give immediate and modified instructions or feedback to learners, usually without the intervention of a teacher. In the ITS, the terms of acquiring skills and knowledge use the technology of artificial intelligence to bring a lot of help to the learners. In this process, human instructors are not essential to contribute to the organization, to overcome this problem it has been used as Bayesian Network (BN). The beginner learner model is the heart of an ITS. The level of understanding of the ITS can be greatly improved by using a BN with high self-learning potential to build an ITS for the beginner concept. The fundamental theory of an ITS for the beginner concept will be mainly discussed. Then, at this stage, the elements of impact on the learning method of the learners are studied from the perception of the expertise in the teaching of the beginner, mutual with the state of learning and the characteristics of the beginner. Based on the BN the correct probability interval for learners to answer four classified stages like stage U are 0.8 ~ 1.0, stage V are 0. 7 ~ 0.8, stage W are 0.4–0.6, and stage X are 0.1–0.3. The results of the evaluation confirm that the system has a strong analytical capacity. Finally, an ITS for the beginner concept is developed based on the BN. This model can assess the psychological limit of the beginning learner impartially and can conclude the next activity of the beginning learner. Furthermore, the representation is also adapted for e-learning assessment and assessment outcomes are achieved to demonstrate the effectiveness of the modified model.KeywordsIntelligent Tutoring System (ITS)Learner ModelBayesian Network (BN)AssessmentLearner