Ai-Powered Personalized Learning System Design: Student Engagement And Performance Tracking System

Artificial Intelligence (AI) is penetrating all sectors of life, and education is not any different. This paper aims to discuss the use of AI in personalized learning environments, with particular concentration laid on the impact that AI has on the involvement and performance of students. This kind of “one-size-fits-all” model in education is usually a traditionally common approach, whereby students get the same type of teaching without considering their needs and preferences in learning. However, it does not meet the learning pace and style differences between students, which in turn lead them to disinterest and lower academic performance. Personalized learning systems powered by AI offer tailor-made educational experiences, using algorithms to sift through huge volumes of data on student performances, preferences, and learning patterns. The following are mechanisms through which AI facilitates personalized learning. First and foremost, the data has to be extracted and analyzed using AI algorithms from many sources; they may include, but are not limited to, student interaction with learning materials, assessment outcomes, and feedback. By processing such data for every student, AI systems will define his strengths and weaknesses, along with learning preferences, based on which separate educational content and delivery means can be created. In addition, AI-powered adaptive learning platforms dynamically adjust the pace and level of difficulty of learning materials to the individual student’s rate of progress.