Importing Unsupervised Data Mining Methods into the course-of-experience framework: Contributions and critical reflections

Currently, mixed methods research (MMR) is of growing interest in the field of sport sciences. To date, epistemological and paradigmatic reflections have been initiated about the articulation of heterogeneous methods, tools and/or data in this type of research. In this vein, this article seeks to enrich these reflections from a critical analysis of studies conducting mixed methods within the course-of-experience framework (COEF). Especially studies using data mining for phenomenological data processing. This reflection is an opportunity to put forward contributions and questionings on the use of data mining, especially an unsupervised hierarchical classification analysis to identify typical modes of experience in sport practice situations. The importation of data mining tools and methods reflect a desire from COEF researchers to sophisticate data processing and the presentation of results.