AI-Powered Personalised Learning Plans for Intelligent Tutoring Systems

Abstract

Abstract: Intelligent Tutoring Systems (ITS) are a promising way to personalize and adapt learning. They use educational theory and artificial intelligence to give students individualized instruction and support. This study examines the practical aspects of ITS implementation, emphasizing important factors, difficulties, and recommended procedures. The paper begins by outlining the design concepts that guide the deployment of ITS, highlighting the significance of personalized learning, proactive participation, prompt feedback, and flexibility. The first section of the article outlines the design principles that direct the implementation of ITS, emphasizing the value of proactive engagement, timely feedback, individualized learning, and adaptability. The paper also discusses how to include instructional methodologies and domain-specific expertise into the design of ITS, emphasizing the need of matching pedagogical approaches with educational goals.