构建可模拟学习者渐进成长的智能学生模型
The Imperfect Learner: Incorporating Developmental Trajectories in Memory-based Student Simulation
- 用分层记忆结构模拟学生知识逐步构建过程
- 实验显示模型能准确反映学习中的渐进性与难点
- 适合教育AI开发与评估，尤其关注学习发展轨迹
用户模拟在人本AI研发与评估中至关重要，但现有教育应用中的学生模拟存在明显局限：仅关注单一学习经验，未能体现学生知识的渐进建构与技能演进。此外，大语言模型倾向于直接生成准确回答，难以刻画真实学习者不完整理解与发展阶段限制。本文提出一种基于记忆的新型学生模拟框架，通过分层记忆机制与结构化知识表示，融入学习者的发育轨迹。该框架还整合元认知过程与人格特质，动态融合认知发展与个人学习特征，实现更完整的个体画像。实际应用中，我们基于下一代科学标准（NGSS）构建了课程对齐的模拟器。实验结果表明，该方法能有效反映知识发展的渐进性及学生面临的典型困难，提供更真实的学习除程表征。
原文摘要 · Abstract (English)
User simulation is important for developing and evaluating human-centered AI, yet current student simulation in educational applications has significant limitations. Existing approaches focus on single learning experiences and do not account for students' gradual knowledge construction and evolving skill sets. Moreover, large language models are optimized to produce direct and accurate responses, making it challenging to represent the incomplete understanding and developmental constraints that characterize real learners. In this paper, we introduce a novel framework for memory-based student simulation that incorporates developmental trajectories through a hierarchical memory mechanism with structured knowledge representation. The framework also integrates metacognitive processes and personality traits to enrich the individual learner profiling, through dynamical consolidation of both cognitive development and personal learning characteristics. In practice, we implement a curriculum-aligned simulator grounded on the Next Generation Science Standards. Experimental results show that our approach can effectively reflect the gradual nature of knowledge development and the characteristic difficulties students face, providing a more accurate representation of learning processes.
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