AI and Machine Learning Techniques in the Development of Intelligent Tutoring System: A Review
Fatema AlShaikh, Nabil M. Hewahi
Abstract
An Intelligent Tutoring System (ITS) is critical in education because it provides one to one personalized teaching assistance to learners as they educate how to solve problems through guidance and prompt feedback. ITS is one application of Artificial Intelligence (AI) in education. It provides a smart learning environment for students without intervention from the teacher. ITS's primary goal is to support and help learners obtain domain-specific intellectual knowledge in a practical and productive manner through the use of different computing technologies. This paper presents a comprehensive survey for previous research on ITS that utilize various techniques of AI and Machine Learning (ML). It gives an overview of ITS, its architecture, and some existing ITS examples. In addition, it highlights and summarizes the current research efforts and obstacles to ITS using AI, as well as some future opportunities. This study shows the importance of AI and ML in ITS development. It is noticed that researchers focus more on Reinforcement Learning (RL), Artificial Neural Networks (ANN), clustering, Bayesian Network (BN) and Fuzzy Logic (FL) approaches.