Genetic algorithms as a tool for development of balanced curriculum

Fuad Dedic, Nina Bijedic and Drazena Gaspar ()
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Fuad Dedic: University of Dzemal Bijedic in Mostar - Faculty of Information Technologies, Mostar, Bosnia and Herzegovina
Nina Bijedic: University of Dzemal Bijedic in Mostar - Faculty of Information Technologies, Mostar, Bosnia and Herzegovina
Drazena Gaspar: University of Mostar - Faculty of Economics, Mostar, Bosnia and Herzegovina

Interdisciplinary Description of Complex Systems - scientific journal, 2020, vol. 18, issue 2B, 175-193

Abstract: The article presents research about the use of genetic algorithms in the analysis of the interrelation among curriculum courses in higher education. The authors used genetic algorithms as a method to analyse the influence that achieved grades in predictors' courses have on achieved grades in dependent courses as well as to observe whether the genetic algorithms can contribute to improving the curriculum. The research was based on a set of data related to the success of students from the Faculty of Information Technologies at the University 'Džemal Bijediæ' in Mostar, Bosnia and Herzegovina. The aim was to anticipate students' grades based on the grades they obtained in previous semester's courses. This research should help educational institutions to evaluate the suitability of the sequence of courses within the curriculum in order to enable personalized learning paths, make the teaching processes more efficient, and promote a balanced curriculum. Namely, a good curriculum can attract new students, improve the success rate of enrolled students, and increase the quality and visibility of the institution. Since the genetic algorithm is search techniques for handling complex spaces, we can use it for the research at each stage of the educational process. Analyses of quantitative data using a genetic algorithm can help educational institutions improve the quality of teaching.

Keywords: balanced curriculum; curriculum evaluation; genetic algorithm; personalized learning (search for similar items in EconPapers)
JEL-codes: C49 I23 (search for similar items in EconPapers)
Date: 2020
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