Fostering preservice teachers’ interdisciplinary curriculum development through generative AI-mediated knowledge-building practices

This study investigates how generative artificial intelligence (GAI) can support preservice teachers (PSTs) in interdisciplinary curriculum development within a knowledge-building (KB) community guided by a designer thinking framework. Fifteen PSTs participated in a nine-week GAI-mediated KB workshop, during which they iteratively explored ideas, created artefacts, and made refinements. Data sources included records of human–AI interactions, progressive interdisciplinary learning artefacts, and final project presentations. Deductive content analysis revealed that the sophistication of the PSTs’ interdisciplinary learning project designs increased, which was accompanied by effectively crafted explicit and context-sensitive prompts, analysing the reliability and quality of AI-generated content and strategically assimilating the outputs into their design endeavours. GAI played a dual role as both a brainstorming tool and dialogue partner, thereby facilitating innovations, extensive discussions, and reflective practices. The findings underscore the potential of framing GAI-mediated KB practices to foster adaptive, flexible, and innovative professional growth among PSTs while highlighting the importance of balancing design efficiency with depth in human–AI cocreation.