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.

翻译：用户模拟对于开发和评估以人为中心的人工智能至关重要，然而当前教育应用中的学生模拟存在显著局限。现有方法侧重于单一学习体验，未能考虑学生逐步的知识建构和不断演变的技能组合。此外，大型语言模型被优化为生成直接且准确的响应，这使得表征真实学习者所具有的不完整理解与发展约束变得困难。本文提出一种新颖的基于记忆的学生模拟框架，该框架通过具有结构化知识表征的层次化记忆机制，融入了发展轨迹。该框架还整合了元认知过程与人格特质，通过对认知发展与个人学习特征的动态整合，丰富了学习者个体画像。在实践中，我们基于《下一代科学标准》实现了一个课程对齐的模拟器。实验结果表明，我们的方法能够有效反映知识发展的渐进性以及学生面临的典型困难，从而为学习过程提供了更准确的表征。