Modelling students’ knowledge organisation: Genealogical conceptual networks

• Published in: Physica A 2018-04, Vol.495, p.405-417
• Main Authors: Koponen, Ismo T., Nousiainen, Maija
• Format: Article
• Language: English
• Subjects: Concept networks; Directed networks; Modelling
• ISSN: 0378-4371; 1873-2119
• DOI: 10.1016/j.physa.2017.12.105

Learning scientific knowledge is largely based on understanding what are its key concepts and how they are related. The relational structure of concepts also affects how concepts are introduced in teaching scientific knowledge. We model here how students organise their knowledge when they represent their understanding of how physics concepts are related. The model is based on assumptions that students use simple basic linking-motifs in introducing new concepts and mostly relate them to concepts that were introduced a few steps earlier, i.e. following a genealogical ordering. The resulting genealogical networks have relatively high local clustering coefficients of nodes but otherwise resemble networks obtained with an identical degree distribution of nodes but with random linking between them (i.e. the configuration-model). However, a few key nodes having a special structural role emerge and these nodes have a higher than average communicability betweenness centralities. These features agree with the empirically found properties of students’ concept networks. •Computational model of students’ knowledge organisation is presented.•Genealogical networks are shown to describes students’ knowledge organisation.•Simple linking-motifs are enough to generate the genealogical networks.•The communicability betweenness centrality characterises the key concepts.