This study examines group differences in AI dependence, self-efficacy, and design fixation based on learners’ AI utilization experience, and further explores the relationships between AI dependence and perception-related variables within an AI-based design education context. To this end, I surveyed 42 learners who participated in an AI-based design class. I then performed data analysis in IBM SPSS Statistics 26, using one-way analysis of variance (ANOVA) and Pearson correlation. The ANOVA revealed statistically significant group differences in AI dependence by AI usage level, but no significant differences in self-efficacy or design fixation. Furthermore, age and professional experience showed no significant influence on most variables. Meanwhile, the correlation analysis revealed that AI dependence was significantly positively associated with design fixation, but not with self-efficacy. These results suggest that, in AI-based design education, learners’ perceptions and attitudes are not strongly differentiated by personal background factors such as age or professional experience, but are instead associated with their experience with AI use and perceived dependence on AI. By distinguishing and analyzing AI utilization and AI dependence, this study provides empirical evidence that contributes to a more nuanced understanding of learners’ cognitive perceptions in AI-based design education in practice.

Abstract
I. Introduction
Ⅱ. Review of Literature
    1. Self-efficacy theory and design learning
    2. Theoretical distinction between AI utilizationand AI dependency
    3. Design fixation
Ⅲ. Research Method
Ⅳ. Results
    1. Differences by AI utilization level
    2. Differences by years of experience
    3. Differences by age
    4. Relationship between AI dependency andperception-related variables
Ⅴ. Discussion
    1. Implications of AI dependence differentiatedby AI usage experience
    2. Reasons for the absence of group differencesin self-efficacy and design fixation
    3. Interpretation of results for the variables ofwork experience and age
    4. Educational implications
Ⅵ. Conclusion
References

• Sujin Lim(Lecturer, Dept. of Fashion and Textiles, Seoul National University, Korea) Corresponding author