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

  • Yuri Nieto
  • Vicente García-Díaz
  • Carlos Montenegro
  • Rubén González Crespo
Methodologies and Application

Abstract

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.

Keywords

Machine learning Artificial neural network Support vector machine Decision making Confusion matrix 

Notes

Acknowledgements

This study was no funding.

Compliance with ethical standards

Conflict of Interest

The authors declare that they have no conflict of interest.

Ethical approval

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

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Copyright information

© Springer-Verlag GmbH Germany, part of Springer Nature 2018

Authors and Affiliations

  • Yuri Nieto
    • 1
  • Vicente García-Díaz
    • 1
  • Carlos Montenegro
    • 2
  • Rubén González Crespo
    • 3
  1. 1.Department of Computer ScienceUniversity of OviedoOviedoSpain
  2. 2.District University Francisco José de CaldasBogotáColombia
  3. 3.School of EngineeringUniversidad Internacional de La Rioja (UNIR)LogroñoSpain

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