Implementation of AI on Students’ Performance in Visual Communication Design Lessons
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Abstract
Background and Aim: This study investigates the use of Sea Art AI painting software in visual communication design education, focusing on its impact on students’ mastery of color theory, composition, and creativity. Grounded in constructivist learning theory, it aims to assess AI's effectiveness in enhancing personalized and interactive learning experiences.
Materials and Methods: A quasi-experiment using mixed methods assessed the impact of AI-assisted learning on design students’ creativity and efficiency by comparing outcomes between AI and traditional instruction groups.
Results: The results showed that the experimental group’s post-test scores were significantly higher than the control group’s in all evaluated areas. AI tools explained 29.8% to 46.4% of the variance, showing a moderate to substantial impact on learning outcomes. The greatest improvements were seen in creativity (F = 24.314, p < 0.001), visual effects (F = 11.050, p = 0.002), and font design (F = 17.996, p < 0.001). Color comprehension (F = 5.658, p = 0.021) and typography (F = 5.769, p = 0.020) showed smaller effects but were still statistically significant.
Conclusion: The study confirms AI’s effectiveness in enhancing students’ design skills and creative thinking, supporting its integration into design education. Future research should examine its long-term impact and broader applicability in personalized learning contexts.
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