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IV. Studies and Teaching, Continuing Education, Educational Capacities (Organisation of Studies, Study and Examinations System)
B. Essays, Commentaries, Statements
Author KEMPER, Lorenz (VORHOFF, Gerrit; WIGGER, Berthold U.)
Title Predicting student dropout : A machine learning approach / Lorenz Kemper, Gerrit Vorhoff and Berthold U. Wigger
Publication year 2020
Source/Footnote In: European journal of higher education. - 10 (2020) 1, S. 28 - 47
Inventory number 49468
Keywords Hochschulen : Karlsruhe U : Studentenschaft, Studium ; Studentenschaft : Studienverhalten
Abstract We perform two approaches of machine learning, logistic regressions and decision trees, to predict student dropout at the Karlsruhe Institute of Technology (KIT). The models are computed on the basis of examination data, i.e. data available at all universities without the need of specific collection. Therefore, we propose a methodical approach that may be put in practice with relative ease at other institutions. We find decision trees to produce slightly better results than logistic regressions. However, both methods yield high prediction accuracies of up to 95% after three semesters. A classification with more than 83% accuracy is already possible after the first semester. (HRK / Abstract übernommen)