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Supporting academic decision making at higher educational institutions using machine learning-based algorithms

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Decisions made by deans and university managers greatly impact the entire academic community as well as society as a whole. In this paper, we present survey results on which academic decisions they concern and the variables involved in them. Using machine learning algorithms, we predicted graduation rates in a real case study to support decision making. Real data from five undergraduate engineering programs at District University Francisco Jose de Caldas in Colombia illustrate our results. The comparison between support vector machine and artificial neural network is held using the confusion matrix and the receiver operating characteristic curve. The algorithm methods and architecture are presented.

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Correspondence to Rubén González Crespo.

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This article does not contain any studies with human participants or animals performed by any of the authors.

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Communicated by V. Loia.

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Nieto, Y., García-Díaz, V., Montenegro, C. et al. Supporting academic decision making at higher educational institutions using machine learning-based algorithms. Soft Comput 23, 4145–4153 (2019).

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