Exploring Machine Learning in Education: Current Developments and Future Prospects

Author(s)	Ms. B KEERTHANA
Country	India
Abstract	This paper examines the transformative impact of machine learning (ML) on education, focusing on its potential to address long-standing challenges through innovative solutions. Key areas of emphasis include personalized learning, predictive analytics, content recommendation, and improved assessment methods. Drawing on contemporary literature and real-world applications, the study analyzes how ML algorithms are reshaping educational practices and enhancing learning outcomes. The discussion highlights both the benefits and limitations of integrating ML in the classroom, including ethical concerns and practical challenges. It also outlines future research directions, envisioning a data-driven educational ecosystem supported by intelligent systems tailored to individual learners. By offering insights for educators, policymakers, and researchers, this paper contributes to the ongoing discourse on creating a more adaptive, equitable, and effective educational landscape through machine learning technologies.
Keywords	Assessment Improvement, Educational Content Recommendation, Ethical Considerations, Machine Learning (ML) in Education, Personalized Learning, Predictive Analytics.
Published In	Volume 16, Issue 2, April-June 2025
Published On	2025-06-15

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International Journal on Science and Technology