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Using Self-Organizing Neural Network Map Combined with Wards Clustering Algorithm for Visualization of Students Cognitive Structural Models about Aliveness Concept

机译:使用自组织神经网络地图结合Ward的聚类算法可视化学生关于活动概念的认知结构模型

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摘要

We propose an approach to clustering and visualization of students' cognitive structural models. We use the self-organizing map (SOM) combined with Ward's clustering to conduct cluster analysis. In the study carried out on 100 subjects, a conceptual understanding test consisting of open-ended questions was used as a data collection tool. The results of analyses indicated that students constructed the aliveness concept by associating it predominantly with human. Motion appeared as the most frequently associated term with the aliveness concept. The results suggest that the aliveness concept has been constructed using anthropocentric and animistic cognitive structures. In the next step, we used the data obtained from the conceptual understanding test for training the SOM. Consequently, we propose a visualization method about cognitive structure of the aliveness concept.
机译:我们提出了一种对学生的认知结构模型进行聚类和可视化的方法。我们使用自组织图(SOM)结合Ward的聚类进行聚类分析。在对100个主题进行的研究中,由开放式问题组成的概念理解测试被用作数据收集工具。分析结果表明,学生主要通过与人联系来构造活力概念。运动是与活力概念最频繁相关的术语。结果表明,以人类为中心和万物有灵的认知结构构造了活力概念。下一步,我们使用从概念理解测试中获得的数据来训练SOM。因此,我们提出了一种关于活力概念认知结构的可视化方法。

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