Student opinions on the evaluation of performance with fuzzy logic method in art and design education

Sehran Dilmaç () and Oğuz Dilmaç ()

Asian Journal of Contemporary Education, 2025, vol. 9, issue 2, 199-212

Abstract: This research was conducted to obtain students' views on the evaluation of artificial intelligence (AI)-supported design applications in art and design education using the fuzzy logic method. It aims to provide a new perspective for educators in identifying real learning situations and deficiencies in art and design education. The study utilized the DALL-E AI tool developed by OpenAI in design projects assigned to students in a basic art education course. The research took place during the autumn semester of the 2024-2025 academic year with 21 first-year students from the Visual Communication Department at the Faculty of Art and Design of a university located in western Turkey, all of whom participated voluntarily. A semi-structured interview, a qualitative research method, was employed as the data collection model. The interview questions were validated and analyzed using MAXQDA qualitative data analysis software, with an inter-coder agreement of 97.32%. The findings indicated that evaluating students' work with fuzzy logic increased their creativity, positively influenced their motivation towards the course, proved to be a more reliable evaluation method compared to traditional approaches, and enhanced their self-efficacy by improving their technological skills.

Keywords: Art education; Artificial intelligence; Assessment; Design education; Fuzzy logic; Machine learning. (search for similar items in EconPapers)
Date: 2025
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