Fostering creativity and self-efficacy through collaborative learning using generative artificial intelligence (ai) in the product design visualization process. Discover how generative AI, like ChatGPT 4.0, enhances product design students' creativity & self-efficacy through collaborative learning & streamlined visualization. Explore its transformative potential in design education.
Generative models in Artificial Intelligence (AI) are increasingly employed across diverse fields, including product design, for tasks like shape recognition and design creation. This trend underscores generative models’ ability to bridge offline and online environments in creative endeavors. The article investigates the potential of integrating generative image AI into visualization process among product design students. Using image-based research analysis and semi-structured interviews, this study involved 50 product design students as respondents. The findings highlight that integrating generative AI tools, particularly the ChatGPT 4.0, significantly improves students’ creativity and self-efficacy through collaborative learning, and streamlines the design process. The findings also close the gap between creative concepts and practical applications, and offers a robust framework for evaluating AI-generated content. The contribution of the study underscores the transformative potential of generative AI tools in product design education, showcasing the effectiveness in fostering creativity, efficiency, and design quality through collaborative learning.
This paper addresses a highly pertinent and contemporary issue: the integration of generative AI into creative educational processes, specifically within product design visualization. The study effectively investigates how generative AI, particularly ChatGPT 4.0, can be leveraged to enhance creativity and self-efficacy among product design students through collaborative learning. Its central contribution lies in demonstrating the transformative potential of these tools in bridging theoretical concepts with practical application, while also offering a robust framework for evaluating AI-generated content, an increasingly critical skill in the digital age. Methodologically, the study employs a mixed-methods approach, combining image-based research analysis with semi-structured interviews involving 50 product design students. This design provides valuable qualitative and potentially quantitative insights into student experiences and learning outcomes. The findings compellingly indicate that AI integration not only streamlines the design process but significantly boosts students' creativity and self-efficacy, particularly within a collaborative learning environment. This specific focus on both creativity and self-efficacy provides valuable insights into the holistic impact of AI on learner development, moving beyond mere efficiency gains to psychological benefits. While the abstract highlights significant contributions, further elaboration on the specific mechanisms of "collaborative learning" facilitated by AI and the detailed structure of the "robust framework for evaluating AI-generated content" would undoubtedly enrich the study. Future research could explore the long-term impacts on design thinking or potential challenges associated with over-reliance on AI. Nevertheless, the research presents a timely and highly relevant contribution to the fields of design education, AI integration, and pedagogical innovation. The findings provide a strong foundation for educators and practitioners seeking to integrate cutting-edge AI tools into creative curricula, making this an important piece of work for publication.
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