心理学学生与数学焦虑的关联认知结构，大模型无法复现。
Math anxiety and associative knowledge structure are entwined in psychology students but not in Large Language Models like GPT-3.5 and GPT-4o
- 用认知网络分析学生对数学和焦虑的概念关联
- 真实学生中焦虑情绪与数学负面评价可预测高焦虑水平
- GPT等大模型缺乏人类的情感认知结构，无法模拟此现象
数学焦虑对大学心理专业学生的职业选择和整体福祉构成重大挑战。本研究基于行为心智网络框架（即映射个体如何组织联想知识与概念情感感知的认知模型），探索个体与群体在数学与焦虑相关概念感知和关联上的差异。共开展4项实验，涉及两组心理学本科生（n1 = 70, n2 = 57），对比GPT模拟学生（GPT-3.5: n = 300；GPT-4o: n = 300）。实验1、2、3利用个体层面的网络特征，从数学焦虑量表预测数学焦虑总分及其子维度（观察性、社会性、评价性）。实验4聚焦于人类学生、GPT-3.5与GPT-4o的群体级感知。结果显示，在真实学生中，“焦虑”正向评分与更高网络度，加上“数学”的负向评分，可有效预测更高的总焦虑及评价性焦虑。而在大模型数据中，该模式不成立，因其模拟网络结构与心理测量得分与人类存在差异。此外，高焦虑学生集体将“焦虑”情感极化，低焦虑者无此特征；“科学”被正向评价，但与“数学”的负面感知形成对照。结果强调了理解概念感知与关联对管理学生数学焦虑的重要性。
原文摘要 · Abstract (English)
Math anxiety poses significant challenges for university psychology students, affecting their career choices and overall well-being. This study employs a framework based on behavioural forma mentis networks (i.e. cognitive models that map how individuals structure their associative knowledge and emotional perceptions of concepts) to explore individual and group differences in the perception and association of concepts related to math and anxiety. We conducted 4 experiments involving psychology undergraduates from 2 samples (n1 = 70, n2 = 57) compared against GPT-simulated students (GPT-3.5: n2 = 300; GPT-4o: n4 = 300). Experiments 1, 2, and 3 employ individual-level network features to predict psychometric scores for math anxiety and its facets (observational, social and evaluational) from the Math Anxiety Scale. Experiment 4 focuses on group-level perceptions extracted from human students, GPT-3.5 and GPT-4o's networks. Results indicate that, in students, positive valence ratings and higher network degree for "anxiety", together with negative ratings for "math", can predict higher total and evaluative math anxiety. In contrast, these models do not work on GPT-based data because of differences in simulated networks and psychometric scores compared to humans. These results were also reconciled with differences found in the ways that high/low subgroups of simulated and real students framed semantically and emotionally STEM concepts. High math-anxiety students collectively framed "anxiety" in an emotionally polarising way, absent in the negative perception of low math-anxiety students. "Science" was rated positively, but contrasted against the negative perception of "math". These findings underscore the importance of understanding concept perception and associations in managing students' math anxiety.
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