Fusing Six-Hat thinking with AI: How the Green Hat and ChatGPT Co-Regulate pre-service teachers' instructional design—insights from epistemic network analysis

Abstract

As an innovative AI-driven chatbot, ChatGPT holds substantial potential to redefine human-computer interaction and enhance teaching and learning. However, current applications often prioritize functional utility over active learning facilitation, leaving its role in promoting collaborative knowledge construction and metacognitive regulation empirically underexplored. To address this gap, this study integrated ChatGPT into pre-service teachers' collaborative learning experiences, leveraging the Six Thinking Hats thinking strategy to scaffold instructional design tasks. Using a mixed-methods approach combining co-regulation coding and epistemic network analysis (ENA), this study compared the co-regulation processes and focus patterns of groups using ChatGPT with the Six Thinking Hats strategy versus those using Six Thinking Hats alone. Results indicate that ChatGPT-assisted groups exhibited intensified co-regulatory focus on Evaluation, along with significantly heightened attention to Task Understanding and Content Monitoring. These findings not only illuminate ChatGPT's transformative role in teacher education but also provide actionable insights for educators designing AI-enhanced collaborative learning environments.