Exploring pre-service teachers’ AI ethics and application strategies in a generative AI-supported knowledge-building community

With the rapid development of generative artificial intelligence (GenAI) and its applications in teacher education, it is essential to understand pre-service teachers’ perceptions and strategies for using GenAI and to explore their learning about AI ethics from an epistemological perspective. This involves integrating GenAI as a non-human epistemic agent into knowledge-building environments with a focus on human-AI collaboration. The participants were 22 pre-service teachers. Using a case study approach, we examined how pre-service teachers engaged with the benefits and limitations of GenAI and the strategies they adopted when using it in a knowledge-building environment. Thematic analysis also found three ethical reasoning patterns, including critical use of GenAI, algorithmic aversion, and cognitive offloading, during pre-service teachers’ AI ethics learning process. The findings highlight an epistemological tension that arises when GenAI participates as a non-human epistemic agent during the knowledge-building process. Based on these findings, we propose a professional development program to help pre-service teachers design and implement GenAI in knowledge-building teaching practice. The study has implications for educators, engineers, and policymakers seeking to design and integrate GenAI effectively and ethically in the AI-supported knowledge era.