AI-DRIVEN EDUCATIONAL INTERVENTIONS: AN EMPIRICAL STUDY ON THEIR EFFICACY IN IMPROVING ACADEMIC PERFORMANCE
Keywords:
Adaptive Learning Systems, Personalized Learning, Educational Data Analytics, AI Tutors, Learning AnalyticsAbstract
This article examines the transformative impact of Artificial Intelligence (AI) on education, focusing on its role in enhancing student learning and academic performance. Through a comprehensive analysis of current literature and empirical data, we investigate key applications of AI in educational settings, including personalized learning systems, administrative automation, intelligent content creation, and data analytics. Our findings reveal that AI-driven educational interventions significantly improve student engagement, knowledge retention, and overall academic achievement. Adaptive learning platforms and AI tutors demonstrate particular efficacy in tailoring educational experiences to individual student needs. However, the article also identifies critical challenges, such as data privacy concerns and potential algorithmic biases, that require careful consideration. By synthesizing quantitative performance metrics with qualitative assessments of student and educator experiences, this article provides a nuanced understanding of AI's potential to revolutionize education. The article concludes with a discussion of future directions for AI in education and offers recommendations for policymakers and educational institutions to effectively leverage AI technologies while addressing ethical considerations.
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