Long-Term Effects Of AI-Personalized Learning On Engagement And Performance

Artificial Intelligence (AI) has significantly advanced personalized learning by customizing educational content to meet the unique needs of 306 students. This study explores the long-term impact of AI-driven personalized learning systems on student engagement and academic performance. Utilizing extensive datasets and advanced machine learning techniques—specifically J48 for classification and K-Means for clustering—the research offers valuable insights into optimizing education through AI. The methodology emphasizes ethical AI implementation, adherence to data privacy standards, and fairness. The results, validated using diverse student data, support the development of a scalable, inclusive AI framework for future educational environments.

Authors

Publication Details

Journal
International Journal of Environmental Sciences
Published
2025-08-04
DOI
https://doi.org/10.64252/85scy850
Citations
1
Primary Topic
Online Learning and Analytics
Type
article
Field-Weighted Citation Impact
1.69
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article

Long-Term Effects Of AI-Personalized Learning On Engagement And Performance

Krishnasamy Vijayakumar, A. Naveen
1 citations
International Journal of Environmental Sciences
Online Learning and Analytics
1.69
article

Long-Term Effects Of AI-Personalized Learning On Engagement And Performance

Krishnasamy Vijayakumar, A. Naveen
article en
1 citations

Abstract

Artificial Intelligence (AI) has significantly advanced personalized learning by customizing educational content to meet the unique needs of 306 students. This study explores the long-term impact of AI-driven personalized learning systems on student engagement and academic performance. Utilizing extensive datasets and advanced machine learning techniques—specifically J48 for classification and K-Means for clustering—the research offers valuable insights into optimizing education through AI. The methodology emphasizes ethical AI implementation, adherence to data privacy standards, and fairness. The results, validated using diverse student data, support the development of a scalable, inclusive AI framework for future educational environments.

International Journal of Environmental Sciences
Quality Education
Openalex Percentile: Top 11%
Online Learning and Analytics
1.69
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