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Reflective Practices and Self-Regulated Learning in Designing with Generative Artificial Intelligence: An Ordered Network Analysis

  • Ha Nguyen,
  • Andy Nguyen

摘要

Advances in generative artificial intelligence (AI) have enabled new forms of human-AI interaction. In this work, we explored the utility of using generative AI, specifically OpenAI’s ChatGPT (Chat Generative Pre-trained Transformer) 3.5, to support the design thinking process to identify user needs, ideate, and refine solutions. We examined how 17 students and professionals from a design program engaged in reflective design practices and self-regulated learning (SRL), as they used generative AI to brainstorm ideas. We further explored how participants considered, elaborated upon, and integrated the AI-generated ideas into their design artifacts. Analyses involved qualitative coding of the brainstorming sessions and Ordered Network Analysis, which visualized the co-occurrences between reflective design practices and SRL as indicators of multifaceted learning engagement. Findings illuminate the importance of iterative evaluation and planning of AI-generated ideas, in conjunction with reflection on design moves, to improve design quality. We discuss the importance of reflective practices and SRL in AI-integrated learning.