AI-based tutoring systems in education: A systematic literature review on personalized learning, intelligent agents, and learning analytics
Document Type
Article
Source of Publication
Generators Bots and Tutors Creative Approaches to Human AI Synergy in Classroom Instruction
Publication Date
6-17-2025
Abstract
This systematic literature review examines the current state of AI-based tutoring systems in education, focusing on their roles in personalized learning, intelligent agent integration, and learning analytics within classroom instruction. A thorough analysis of 30 relevant studies reveals that AI-based tutoring systems significantly enhance educational outcomes by adapting learning experiences to individual needs through tailored feedback and customized learning trajectories, leading to improved student engagement and performance. Intelligent agents are central to these systems, providing social-emotional support, interactive feedback, and fostering motivation and deeper understanding. Learning analytics further support educators by enabling real-time monitoring of student progress, facilitating data-driven instructional adjustments, and ensuring timely, personalized support. Despite the progress, the study identifies ongoing challenges, particularly concerning ethical data use, scalability, and the need for integrating socio-emotional learning components.
DOI Link
ISBN
[9798337308470, 9798337308494]
ISSN
Publisher
IGI Global
First Page
185
Last Page
210
Disciplines
Computer Sciences | Education
Keywords
AI-based tutoring systems, personalized learning, intelligent agents, learning analytics, educational outcomes
Scopus ID
Recommended Citation
Almheiri, Abdulla Sultan Binhareb; Albastaki, Humaid; and Alrashdan, Hanadi, "AI-based tutoring systems in education: A systematic literature review on personalized learning, intelligent agents, and learning analytics" (2025). All Works. 7481.
https://zuscholars.zu.ac.ae/works/7481
Indexed in Scopus
yes
Open Access
no