Abstract
Due to the important advantages it offers, gamification is one of the fastest-growing industries in the world, and interest from the market and from users continues to grow. This has led to the development of more and more applications aimed at different fields, and in particular the education sector. Choosing the most suitable application is increasingly difficult, and so to solve this problem, our study designed a model which is an innovative combination of fuzzy Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) with the Measuring Attractiveness by a Categorical Based Evaluation Technique (MACBETH) and Shannon entropy theory, to choose the most suitable gamification application for the Industrial Manufacturing and Organisation Systems course in the degree programmes for Electrical Engineering and Industrial and Automatic Electronics at the Higher Technical School of Industrial Engineering of Ciudad Real, part of the University of Castilla-La Mancha. There is no precedent in the literature that combines MACBETH and fuzzy Shannon entropy to simultaneously consider the subjective and objective weights of criteria to achieve a more accurate model. The objective weights computed from fuzzy Shannon entropy were compared with those calculated from De Luca and Termini entropy and exponential entropy. The validity of the proposed method is tested through the Preference Ranking Organisation METHod for Enrichment of Evaluations (PROMETHEE) II, ELimination and Choice Expressing REality (ELECTRE) III, and fuzzy VIKOR method (VIsekriterijumska optimizacija i KOmpromisno Resenje). The results show that Quizizz is the best option for this course, and it was used in two academic years. There are no precedents in the literature using fuzzy multicriteria decision analysis techniques to select the most suitable gamification application for a degree-level university course.
Highlights
Gamification is defined as a process that applies gaming elements to non-game contexts [1,2]
This study describes a model combining fuzzy TOPSIS with the MACBETH approach and fuzzy Shannon entropy, in order to choose the most suitable gamification application in the second-year degree programmes in Electrical Engineering and Industrial and Automatic
Fuzzy TOPSIS is usually combined with AHP or fuzzy AHP, despite the many criticisms directed at AHP
Summary
Gamification is defined as a process that applies gaming elements to non-game contexts [1,2]. The choice of fuzzy TOPSIS rather than other fuzzy multicriteria decision analysis techniques is because it has been shown to be a robust technique for handling complex real-life problems [16] and is widely used in many areas [17] This is the first study in the literature to integrate the subjective weights from the judgements given by the lecturer who teaches the course, processed using the MACBETH approach, with objective weights based on objective information (fuzzy decision matrix), calculated using fuzzy Shannon entropy. The model built is described, with the structuring results, the subjective weighs obtained via the MACBETH approach, and the objective weights computed by fuzzy Shannon entropy, fuzzy De Luca and Termini entropy, and exponential Pal and Pal entropy, with a prior introduction to all methods. The results, the validity of the proposed method, the sensitivity analysis, the conclusions, and future lines of work are set out
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