During reading, students construct mental models of what they read. Summaries can be used to evaluate the latent knowledge structure of these mental models. We used indices from Student Mental Model Analyzer for Research and Teaching (SMART) to explore the potential of a global index, Graph Centrality (GC), as a measure to describe mental model structure and its relation to the quality of student summaries (e.g., the amount of content-coverage). Students (n = 73) in an online graduate-level course wrote and revised summaries of their course readings. Data preview left the total count of 32 cases to evaluate how students’ mental representations changed from initial to final version. These summaries were analyzed using indices derived from the 3S model (surface, structure, semantic) as well as a measure of GC. The results of this initial investigation are promising, demonstrating that Graph Centrality captures important differences in students’ summaries, including revision behaviors to the wholistic structure of mental models, modification trajectories toward a cohesive and solid mental representation that is semantically similar to the expert model.

在阅读过程中，学生会构建自己所阅读内容的心理模型。总结可用于评估这些心理模型的潜在知识结构。我们使用了来自研究和教学的学生心理模型分析器（SMART）的索引来探索全球索引图中心性（GC）的潜力，以此来描述心理模型结构及其与学生摘要质量的关系（例如，内容覆盖率）。学生（n = 73）在在线研究生课程中撰写和修订了他们的课程阅读摘要。数据预览留下了32个案例的总数，以评估学生的心理表现从最初版本到最终版本的变化。使用从3S模型获得的索引（表面，结构，语义）以及GC度量对这些摘要进行了分析。这项初步调查的结果令人鼓舞，表明“图中心”捕获了学生摘要中的重要差异，包括对心理模型的整体结构的修正行为，对与专家模型在语义上相似的内聚性和坚实心理表示的修改轨迹。