Clustering Algorithms in an Educational Context: An Automatic Comparative Approach
IEEE ACCESS, pp. 146994-147014, 2020.
Despite an increasing consensus regarding the significance of properly identifying the most suitable clustering method for a given problem, a surprising amount of educational research, including both educational data mining (EDM) and learning analytics (LA), neglects this critical task. This shortcoming could in many cases have a negative...More
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