THE DIDACTIC PRINCIPLES AND PEDAGOGICAL CONDITIONS OF TEACHING AI DESIGN TO STUDENTS IN THE ART AND DESIGN FIELDS

2025

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DOI 10.63464/3079-3394-2025-3-5-13
Data confidence 70 medium
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Abstract

This study explores the pedagogical conditions and didactic principles required for the effective teaching of AI design to students in art and design fields. The research was conducted at Abai Kazakh National Pedagogical University and Almaty Technological University, involving 60 second year bachelor’s ctudent divided into experimental and control groups. A quasi-experimental strategy was combined with qualitative techniques like focus groups, interviews, and content analysis of student projects in a mixed-method design. Access to AI design infrastructure, interdisciplinary collaboration with computer science students, project-based learning with real cases, and methodological support with ethical guidelines were among the specially created pedagogical conditions that were used to teach the experimental group. Interactivity, practice orientation, tool variability, reflexivity, and ethical transparency were all highlighted in the didactic principles. Students' creative and professional skills significantly improved as a result of quantitative analysis (Torrance Tests, project evaluation, statistical methods). Higher levels of motivation, ethical consciousness, and preparedness to incorporate AI tools into artistic practice were found in qualitative data. The results demonstrate that integrating AI design education into art and design curricula can be accomplished successfully with well-crafted pedagogical conditions and principles.