A Comprehensive Review of AI-based Intelligent Tutoring Systems: Applications and Challenges

July 25, 2025 ยท The Cartographer ยท ๐Ÿ› arXiv.org

๐Ÿ“š THE CARTOGRAPHER: The Cartographer
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"Title-pattern auto-detect: A Comprehensive Review of AI-based Intelligent Tutoring Systems: Applications and Challenges"

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Authors Meriem Zerkouk, Miloud Mihoubi, Belkacem Chikhaoui arXiv ID 2507.18882 Category cs.IR: Information Retrieval Cross-listed cs.AI, cs.HC Citations 6 Venue arXiv.org Last Checked 3 days ago
Abstract
AI-based Intelligent Tutoring Systems (ITS) have significant potential to transform teaching and learning. As efforts continue to design, develop, and integrate ITS into educational contexts, mixed results about their effectiveness have emerged. This paper provides a comprehensive review to understand how ITS operate in real educational settings and to identify the associated challenges in their application and evaluation. We use a systematic literature review method to analyze numerous qualified studies published from 2010 to 2025, examining domains such as pedagogical strategies, NLP, adaptive learning, student modeling, and domain-specific applications of ITS. The results reveal a complex landscape regarding the effectiveness of ITS, highlighting both advancements and persistent challenges. The study also identifies a need for greater scientific rigor in experimental design and data analysis. Based on these findings, suggestions for future research and practical implications are proposed.
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