Knowledge Management & E-Learning: An International Journal (KM&EL), Vol 7, No 1 (2015)

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A standardised, holistic framework for concept-map analysis combining topological attributes and global morphologies

Stefan Yoshi Buhmann, Martyn Kingsbury

Abstract


Motivated by the diverse uses of concept maps in teaching and educational research, we have developed a systematic approach to their structural analysis. The basis for our method is a unique topological normalisation procedure whereby a concept map is first stripped of its content and subsequently geometrically re-arranged into a standardised layout as a maximally balanced tree following set rules. This enables a quantitative analysis of the normalised maps to read off basic structural parameters: numbers of concepts and links, diameter, in- and ex-radius and degree sequence and subsequently calculate higher parameters: cross-linkage, balance and dimension. Using these parameters, we define characteristic global morphologies: ‘Disconnected’, ‘Imbalanced’, ‘Broad’, ‘Deep’ and ‘Interconnected’ in the normalised map structure. Our proposed systematic approach to concept-map analysis combining topological normalisation, determination of structural parameters and global morphological classification is a standardised, easily applicable and reliable framework for making the inherent structure of a concept map tangible. It overcomes some of the subjectivity inherent in analysing and interpreting maps in their original form while also avoiding the pitfalls of an atomistic analysis often accompanying quantitative concept-map analysis schemes. Our framework can be combined and cross-compared with a content analysis to obtain a coherent view of the two key elements of a concept map: structure and content. The informed structural analysis may form the starting point for interpreting the underlying knowledge structures and pedagogical meanings.

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Knowledge Management & E-Learning: An International Journal (KM&EL)
ISSN 2073-7904

 

Maintained and Developed by:

Laboratory for Knowledge Management & E-Learning

Faculty of Education, The University of Hong Kong