Study on Intelligent Tutoring System for Learner Assessment Modeling Based on Bayesian Network

Abstract

The most crucial part of the educational system is the intelligent tutoring system. A computer system that intends to give learners quick and customised lessons or feedback, usually without the intervention of a professor, is known as an intelligent tutoring system. Artificial intelligence technology is employed in an intelligent tutoring system to provide a lot of help to learners in terms of acquiring skills and knowledge. Human professors are not required to contribute to the organisation in this process, and Bayesian Network has been employed to solve this problem. An intelligent tutoring system’s heart is the beginner learner model. Using a Bayesian network with high self-learning ability to build an intelligent tutoring system for the novice concept can considerably improve the level of comprehension of the intelligent tutoring system. The core philosophy of an intelligent tutoring system for the beginner concept will be the major focus. The rudiments of impact on the learners learning method are then studied at this level, starting with the perception of the beginner’s expertise in teaching, mutual with the state of learning, and the features of the beginner. Based on bayesian network, this work presented a study model for constructing an intelligent tutoring system for learner assessment. The tutoring system’s design model takes into account a client model and a learner model. The bayesian network was employed in an e-learning environment to assess the learner’s current level of knowledge so that the model may evolve and offer new knowledge to improve learner performance.