AI-powered Predictive Analytics for Student Success

Ravi Samikannu, Sam Goundar, Jueying Li, S. Vinoth Kumar, Nyagong Santino David Ladu

Abstract


AI-powered predictive analytics are transforming the educational landscape by providing insights that enhance student success and retention. This paper examines the methodologies and technologies involved in developing predictive analytics systems, focusing on their applications in monitoring student performance and identifying at-risk students. Through case studies, the paper highlights the benefits of using AI-driven analytics in education, including improved academic outcomes, targeted interventions, and enhanced support services. Additionally, challenges related to data privacy, implementation, and reliance on technology are discussed.

Keywords


AI, predictive analytics, student success, education.

References


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