发表机构
Saarland University; Korea Advanced Institute of Science and Technology（萨尔兰大学; 韩国科学技术院）
机构由 AI 辅助整理，请以论文原文为准。AI 中文总结
本研究开发了结合LLM的智能辅导系统Math with Matt，在数学学习中同时提供认知与情感支持，经七年级学生课堂实验，其可降低数学焦虑、提升学习效率与体验。
AI 中文摘要
智能辅导系统（ITSs）传统上会将自适应支持聚焦于学习的认知方面，尽管这类系统效果显著，但目前人们对如何通过关注学生的情绪状态来增强这类系统的了解还很少。特别是，在自适应数学学习中，用于支持学生学习与体验的正念干预措施的作用仍未得到充分探索。我们开发了一款名为“Math with Matt”的智能辅导系统（ITS），该系统利用大型语言模型（LLMs）为代数学习提供认知与情感两方面的支持。该系统提供两项功能：1）基于LLM的正念聊天功能，通过教学智能体Matt提供情境感知的情感支持；2）正念反馈与提示信息（而非仅为评价性内容），以提升学习体验并减少数学焦虑。我们针对七年级学生开展了一项课堂研究，将正念版本与仅提供认知支持的版本进行对比。总体而言，该智能辅导系统降低了执行状态型数学焦虑并提升了学生的数学学习效果，不过两种条件之间未出现显著差异。然而，接受正念干预的学生展现出更高的学习效率与更均衡的问题解决行为，因为与认知版本组的学生相比，他们在更少的学习时间和更少的提示请求次数下就达到了相近的数学学习水平。此外，他们报告称，教学智能体比认知条件组的学生感受到更强烈的支持与关怀。我们的研究证明了通过基于LLM的交互将正念融入智能辅导系统的可行性与可扩展性，并将LLMs定位为认知数学辅导中一个自适应的社会情感层面。
英文摘要
Intelligent Tutoring Systems (ITSs) traditionally focus their adaptive support on cognitive aspects of learning. Although effective, little is known about how such systems can be enhanced by addressing students' emotional states. In particular, the role of mindful interventions for supporting student learning and experiences in adaptive math learning remains underexplored. We developed "Math with Matt", an ITS that leverages Large Language Models (LLMs) to provide both cognitive and emotional support in algebra learning. The system offers 1) an LLM-based mindful chat that delivers context-sensitive emotional support through a pedagogical agent Matt, and 2) mindful feedback and hint messages (not just evaluative) to enhance learning experiences and reduce math anxiety. We conducted a classroom study with 7th graders, comparing a Mindful version against a version with cognitive support only. Overall, the ITS reduced executive state-math anxiety and improved students' math learning, though no significant differences emerged between the conditions. However, students with the mindfulness interventions showed higher learning efficiency and well-balanced problem-solving behavior, since they achieve a similar level of math learning with less learning time and fewer requested hints compared to the Cognitive version. Additionally, they reported that the pedagogical agent felt more supportive and caring than students in the cognitive condition. Our study demonstrates the feasibility and scalability of integrating mindfulness into ITSs through LLM-based interactions and positions LLMs as an adaptive, socio-emotional layer within cognitive math tutoring.
