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Use of machine learning techniques for educational proposes: a decision support system for forecasting students’ grades

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Abstract

Use of machine learning techniques for educational proposes (or educational data mining) is an emerging field aimed at developing methods of exploring data from computational educational settings and discovering meaningful patterns. The stored data (virtual courses, e-learning log file, demographic and academic data of students, admissions/registration info, and so on) can be useful for machine learning algorithms. In this article, we cite the most current articles that use machine learning techniques for educational proposes and we present a case study for predicting students’ marks. Students’ key demographic characteristics and their marks in a small number of written assignments can constitute the training set for a regression method in order to predict the student’s performance. Finally, a prototype version of software support tool for tutors has been constructed.

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Authors and Affiliations

  1. Educational Software Development Laboratory, Department of Mathematics, University of Patras, Patras, Greece

    S. B. Kotsiantis

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  1. S. B. Kotsiantis
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Kotsiantis, S.B. Use of machine learning techniques for educational proposes: a decision support system for forecasting students’ grades. Artif Intell Rev 37, 331–344 (2012). https://doi.org/10.1007/s10462-011-9234-x

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