Modelling students' knowledge organisation : Genealogical conceptual networks

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http://hdl.handle.net/10138/308985

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Koponen , I T & Nousiainen , M 2018 , ' Modelling students' knowledge organisation : Genealogical conceptual networks ' , Physica A: Statistical Mechanics and its Applications , vol. 495 , pp. 405-417 . https://doi.org/10.1016/j.physa.2017.12.105

Title: Modelling students' knowledge organisation : Genealogical conceptual networks
Author: Koponen, Ismo T.; Nousiainen, Maija
Contributor: University of Helsinki, Department of Physics
University of Helsinki, Department of Physics
Date: 2018-04-01
Language: eng
Number of pages: 13
Belongs to series: Physica A: Statistical Mechanics and its Applications
ISSN: 0378-4371
URI: http://hdl.handle.net/10138/308985
Abstract: 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. (C) 2017 Elsevier B.V. All rights reserved.
Subject: Concept networks
Directed networks
Modelling
COMPLEX NETWORKS
PHYSICS
SCIENCES
PATTERNS
MAPS
114 Physical sciences
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