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Bertolini, Roberto; Finch, Stephen J.; Nehm, Ross H. – International Journal of Educational Technology in Higher Education, 2021
Educators seek to harness knowledge from educational corpora to improve student performance outcomes. Although prior studies have compared the efficacy of data mining methods (DMMs) in pipelines for forecasting student success, less work has focused on identifying a set of relevant features prior to model development and quantifying the stability…
Descriptors: Data Processing, Prediction, Validity, Undergraduate Students