Computational analysis and mapping of ijCSCL content

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Abstract

The purpose of this empirical study is to analyze and map the content of the International Journal of Computer-Supported Collaborative Learning since its inception in 2006. Co-word analysis is the general approach that is used. In this approach, patterns of co-occurrence of pairs of items (words or phrases) identify relationships among ideas. Distances based on co-occurrence frequencies measure the strength of these relationships. Hierarchical clustering and multidimensional scaling are the two complementary exploratory methods relying on these distances that are used to analyze and map the data. Some interesting findings of the work include a map of the key topics covered in the journal and a set of complementary techniques for investigating more specific questions.