Application of Soft Computing Techniques in the Analysis of Educational Data Using Fuzzy Logic

Marija Mojsilović, Selver Pepić, Gabrijela Popović, Muzafer Saračević and Darjan Karabašević ()
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Marija Mojsilović: Department in Trstenik, Academy of Professional Studies Sumadija, 37240 Trstenik, Serbia
Selver Pepić: Department in Trstenik, Academy of Professional Studies Sumadija, 37240 Trstenik, Serbia
Gabrijela Popović: Faculty of Applied Management, Economics and Finance, University Business Academy in Novi Sad, 11000 Belgrade, Serbia
Muzafer Saračević: Department of Computer Sciences, University of Novi Pazar, 36300 Novi Pazar, Serbia
Darjan Karabašević: Faculty of Applied Management, Economics and Finance, University Business Academy in Novi Sad, 11000 Belgrade, Serbia

Mathematics, 2025, vol. 13, issue 13, 1-28

Abstract: The application of soft computing techniques, with a special emphasis on fuzzy logic, represents a modern approach to analyzing complex educational data. This paper explores the possibilities of applying soft computing to identify and interpret factors that influence the motivation and educational achievement of students in academic and professional studies, with special reference to the differences between these two groups of students in experienced subjects. Fuzzy logic enables more detailed processing of educational parameters that are subject to subjective interpretations and are often not clearly defined. By using this approach, decision support systems are developed that facilitate the understanding of students’ motivational patterns, their preferences, and challenges in mastering different types of content. Analyzing educational data seeks to identify relevant motivational factors that can contribute to shaping more effective and personalized teaching strategies. The goal of the work is to improve the quality of the educational process through the integration of soft computing methods, to raise the level of engagement and success of students in various fields of study.

Keywords: soft computing; fuzzy logic; Anfis; education; student motivation (search for similar items in EconPapers)
JEL-codes: C (search for similar items in EconPapers)
Date: 2025
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