Nauryzbayev B.A., Karipzhanova A INTELLIGENT PREDICTIVE SYSTEMS: HOW II HELPS TO IDENTIFY STUDENTS WITH POTENTIAL LEARNING DIFFICULTIES

Abstract

The amount of external data involved in education today makes it possible to find new approaches to the problem of predicting student performance and identifying which students are likely to have learning difficulties, using AI as a primary tool. This paper explores how feasible it is to apply AI models to extract useful insights from large amounts of data about students and their academic performance, behaviour and demographics. The direction in which machine learning methods are heading is predictive learning, based on quantisation of results, which in the coming period will allow educational institutions to identify at-risk student categories. Again, the possibility of applying these guessed factors to instructional planning is being considered, which contributes to better learning outcomes and enhances how important it is in student retention. The introduction of AI into the educational process undermines the traditional approach to student assessment and empowers faculty to work with student data to make decisions.