Enhancing Student Engagement with AI-Driven Personalized Learning Systems

This paper explores the impact of AI-driven personalized learning systems on enhancing student engagement in educational settings. With the increasing integration of artificial intelligence (AI) in various sectors, education is also experiencing a shift towards more adaptive and personalized learning environments. The study investigates how personalized learning paths, powered by AI algorithms, can address diverse learning needs and promote greater involvement from students. Through a comprehensive analysis of engagement metrics, pre-and post-implementation comparisons, and surveys from both students and educators, this research identifies key factors that contribute to improved student motivation, interaction, and academic performance. The findings suggest that AI-driven systems not only provide tailored learning experiences but also foster a deeper connection between students and their learning content. The paper concludes with recommendations for future research and practical applications in educational institutions to further optimize the use of AI for enhancing student engagement.

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Publication Details

Journal
International Transactions on Education Technology (ITEE)
Published
2024-10-14
DOI
https://doi.org/10.33050/itee.v3i1.662
Citations
17
Primary Topic
Online Learning and Analytics
Type
article
Field-Weighted Citation Impact
7.00
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article

Enhancing Student Engagement with AI-Driven Personalized Learning Systems

Gang Yao, Zaharuddin, Yu Chen
17 citations
International Transactions on Education Technology (ITEE)
Online Learning and Analytics
7.00
article

Enhancing Student Engagement with AI-Driven Personalized Learning Systems

Gang Yao, Zaharuddin, Yu Chen
article en
17 citations

Abstract

This paper explores the impact of AI-driven personalized learning systems on enhancing student engagement in educational settings. With the increasing integration of artificial intelligence (AI) in various sectors, education is also experiencing a shift towards more adaptive and personalized learning environments. The study investigates how personalized learning paths, powered by AI algorithms, can address diverse learning needs and promote greater involvement from students. Through a comprehensive analysis of engagement metrics, pre-and post-implementation comparisons, and surveys from both students and educators, this research identifies key factors that contribute to improved student motivation, interaction, and academic performance. The findings suggest that AI-driven systems not only provide tailored learning experiences but also foster a deeper connection between students and their learning content. The paper concludes with recommendations for future research and practical applications in educational institutions to further optimize the use of AI for enhancing student engagement.

International Transactions on Education Technology (ITEE)Vol. 3(1)
Universitas Nusa Bangsa (ID)
Openalex Percentile: Top 3%
Online Learning and Analytics
7.00
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Enhancing Student Engagement with AI-Driven Personalized Learning Systems — Gang Yao, Zaharuddin, et al. · International Transactions on Education Technology (ITEE) (2024) | TGRS Research Map | TGRS