Метрики центральности сетевого анализа как инструмент определения уровня абстракции понятий внутри понятийной структуры обучающихся

This study examines concepts as systemic elements within a conceptual structure, drawing on the theoretical framework of L.S. Vygotsky’s cultural-historical psychology. A key characteristic of concepts is their level of abstraction, which reflects their degree of generalization within a system. However, existing classification methods lack a unified approach, complicating empirical research. The current study aimed to explore network analysis metrics as a tool for distinguishing concepts of different levels within a concept structure. We analysed 242 concepts from conceptual maps created by experts and students in data analysis. First, a qualitative analysis was conducted using formal definitions and expert evaluations. Then, betweenness centrality and degree centrality metrics were applied to assess their effectiveness in distinguishing conceptual levels. The findings showed that betweenness centrality and normalized betweenness centrality significantly differed across levels: higher-level concepts had higher values compared to the basic and subordinate ones. Degree centrality varied depending on the classification method. When classified by definition, all group differences were shown to be significant. When classified by maps, differences were found only for the subordinate level. However, the number of incoming connections did not show distinguishing capability. Based on the results, it can be assumed that network analysis demonstrates potential not only in assessing the systemic characteristics of a conceptual structure but also in evaluating the role of individual concepts within it.