AI-POWERED LEARNING ANALYTICS: ENHANCING STUDENT PERFORMANCE THROUGH DATA-DRIVEN INSIGHTS

Abstract

The introduction of Artificial Intelligence (AI) into the education setting has truly transformed the process of measuring, interpreting, and streamlining learning outcomes. AI-based learning analytics uses vast amounts of data created by students on digital platforms, such as learning management systems (LMS), assessment and instructional apps, and records of interaction, to derive insights that are meaningful about student interactions, their trajectory, and their results. The classic educational analytics has generally concentrated on descriptive statistics, which provide post-hoc summaries of educational outcomes. Conversely, predictive and prescriptive analytics, supported by AI, can deliver actionable and real-time insights, allowing educators to recognize at-risk students and tailor interventions and improve the individualization of the learning experience.