用AI打造可自适应的个性化学习系统，让教育更懂学生。
Generative AI in Education: From Foundational Insights to the Socratic Playground for Learning
- 基于大模型构建新型智能辅导系统，模拟苏格拉底式启发教学。
- 通过结构化提示追踪学生误解，实现动态反馈与个性化引导。
- 强调教育理念先行，技术服务于教学而非取代教师。
本文探讨了人类认知与大型语言模型（LLMs）之间的协同关系，指出生成式AI能够规模化推动个性化学习。文章对比了LLMs与人类认知的相似性，强调将AI融入教育的潜力与新视角。在分析技术与教学目标对齐的挑战后，回顾了早期智能辅导系统AutoTutor的成功、局限及其未竟之志。随后提出下一代系统——苏格拉底学习乐园（Socratic Playground），该系统采用先进的基于Transformer的模型，克服AutoTutor的限制，提供个性化、自适应的辅导体验。通过展示一个基于JSON的辅导提示框架，系统可有条不紊地引导学习者反思，并实时追踪常见误解。全文强调必须以教育理念为核心，确保技术赋能教学，而非替代教学。
原文摘要 · Abstract (English)
This paper explores the synergy between human cognition and Large Language Models (LLMs), highlighting how generative AI can drive personalized learning at scale. We discuss parallels between LLMs and human cognition, emphasizing both the promise and new perspectives on integrating AI systems into education. After examining challenges in aligning technology with pedagogy, we review AutoTutor-one of the earliest Intelligent Tutoring Systems (ITS)-and detail its successes, limitations, and unfulfilled aspirations. We then introduce the Socratic Playground, a next-generation ITS that uses advanced transformer-based models to overcome AutoTutor's constraints and provide personalized, adaptive tutoring. To illustrate its evolving capabilities, we present a JSON-based tutoring prompt that systematically guides learner reflection while tracking misconceptions. Throughout, we underscore the importance of placing pedagogy at the forefront, ensuring that technology's power is harnessed to enhance teaching and learning rather than overshadow it.
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