International Journal of Scientific Research and Engineering Development

The rapid expansion of remote education has reshaped modern learning systems, generating large volumes of digital learning data. This study investigates the impact of remote education on students’ academic performance using a machine learning–oriented analytical approach. The research examines key factors such as internet accessibility, learning mode, engagement level, satisfaction, and academic outcomes. Primary data was collected from students participating in online education through a structured survey. Machine learning techniques, including clustering analysis, were employed to identify hidden patterns among learners. The Elbow Method was used to determine the optimal number of clusters, followed by K-Means clustering to group students based on learning behavior and performance trends. The findings provide data-driven insights that can help educators and institutions optimize remote education strategies and improve learning outcomes. The rapid integration of Artificial Intelligence (AI) into remote education has significantly transformed teaching–learning processes. AI-enabled tools such as intelligent learning management systems, adaptive content delivery, automated assessments, and virtual interaction platforms have reshaped student engagement and academic performance. This study examines the impact of AI-enabled remote education on students’ academic performance by analyzing factors such as technological accessibility, AI-based learning support, student engagement, instructor–student interaction, and self-regulated learning skills. Primary data were collected from 60 undergraduate students using a structured questionnaire. Descriptive and analytical techniques, including percentage analysis, the Elbow Method, and K-Means clustering, were applied to classify students based on learning outcomes and satisfaction levels. The findings reveal that students with access to stable internet and AI-supported learning platforms demonstrate improved academic performance, while others face challenges related to technological barriers and reduced interaction.

Mrs.Deepa V, Ms.Deepika R,"Impact of AI-Enabled Remote Education on Students’ Academic Performance: A Descriptive and Analytical Study" International Journal of Scientific Research and Engineering Development, V9(1): Page(1754-1756) Jan-Feb 2026. ISSN: 2581-7175. www.ijsred.com. Published by Scientific and Academic Research Publishing.