Advancing Generative Intelligent Tutoring Systems with GPT-4: Design, Evaluation, and a Modular Framework for Future Learning Platforms

Generative Intelligent Tutoring Systems (ITS), powered by advanced language models like GPT-4, represent a transformative approach to personalized education by enabling real-time adaptability, dynamic content generation, and interactive learning. This study introduces a modular framework for designing and evaluating such systems, leveraging GPT-4's generative capabilities to facilitate Socratic-style interactions, personalized feedback, and adaptive learning support. A practical implementation, the Socratic Playground for Learning (SPL), was developed and evaluated in a pilot study with 30 undergraduate students, focusing on foundational English skills. The results demonstrated significant improvements in vocabulary, grammar, and sentence construction, along with high levels of engagement, adaptivity, and satisfaction. To ensure scalability and replicability, the framework employs lightweight JSON structures suitable for diverse educational settings. While the system shows promise, challenges such as computational costs and content validation highlight areas for further refinement. This research provides a foundation for the design and assessment of generative ITS, offering valuable insights into advancing personalized learning and exploring broader applications of generative AI in education.

生成式智能教学系统（Generative Intelligent Tutoring Systems，ITS）由GPT-4等先进语言模型驱动，代表了个性化教育的变革性路径，可实现实时自适应、动态内容生成与交互式学习。本研究提出了一套用于设计与评估此类系统的模块化框架，借助GPT-4的生成能力支撑苏格拉底式互动、个性化反馈及自适应学习支持。研究团队开发了一款实用落地系统——苏格拉底学习园地（Socratic Playground for Learning，简称SPL），并在一项针对30名本科生的试点研究中，以基础英语技能为核心目标对其进行了评估。结果显示，受试者在词汇、语法与句式构建能力上均取得显著提升，同时系统的参与度、自适应表现与用户满意度均处于较高水平。为保障系统的可扩展性与可复现性，该框架采用轻量化JSON结构，可适配多样化的教育场景。尽管该系统展现出良好的应用前景，但仍存在计算成本与内容验证等方面的挑战，有待进一步优化完善。本研究为生成式智能教学系统的设计与评估奠定了基础，为推进个性化教育、探索生成式AI在教育领域的更广泛应用提供了宝贵见解。