综述AI助学系统在教育中的应用与挑战，揭示其真实效果与改进方向。
A Comprehensive Review of AI-based Intelligent Tutoring Systems: Applications and Challenges
- 系统梳理2010–2025年研究，分析教学策略、自然语言处理等核心技术。
- 发现系统效果参差不齐，实验设计与数据分析需更强科学性。
- 适合教育科技研究者与智能教学系统开发者参考。
基于人工智能的智能辅导系统（ITS）在教育领域具有巨大潜力。尽管持续投入于系统设计与集成，但其实际效果仍呈现混合结果。本文通过系统性文献综述，分析2010至2025年间大量合格研究，涵盖教学策略、自然语言处理（NLP）、自适应学习、学生建模及特定领域应用。结果显示ITS在真实教育场景中表现复杂，虽有进展但仍面临显著挑战。研究强调需提升实验设计与数据评估的科学严谨性，并据此提出未来研究方向与实践建议。
原文摘要 · Abstract (English)
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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