The value of data mining in music education research and some findings from its application to a study of instrumental learning during childhood

Abstract

The use of data mining for the analysis of data collected in natural settings is increasingly recognized as a legitimate mode of enquiry. This rule-inductive paradigm is an effective means of discovering relationships within large datasets - especially in research that has limited experimental design - and for the subsequent formulation of predictions and rules. The method is dramatically under-used in education research in general, and is hardly represented in music education, if at all. The present article reports on several decision trees that emerged from mining for knowledge in datasets constructed from the musical journeys, experiences and abilities of 157 young people in Australia fro..