Fuad Dedić¹
Nina Bijedić² and
Drazena Gašpar^2
1University of Dzemal Bijedic in Mostar - Faculty of Information Technologies
  Mostar, Bosnia and Herzegovina
²University of Mostar - Faculty of Economics
  Mostar, Bosnia and Herzegovina

INDECS 18(2-B), 175-193, 2020 DOI 10.7906/indecs.18.2.8 Full text available here.

Received: 8th September 2019. Accepted: 8th March 2020. Regular article

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 'Dzemal Bijedic' 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.