Preservice teachers’ prompting practices and decision-making: Exploring pathways from talking to reasoning with generative artificial intelligence

This case study explored 16 preservice teachers’ (PTs) prompting practices during a course-embedded teacher education intervention. Drawing on their chat histories with generative AI (GenAI) and post-intervention interviews, we analyzed participants’ GenAI adoption, prompting strategies, and decision-making while completing weekly learning tasks. Findings revealed that explicit, exploratory, and social prompting strategies were most prevalent. Although participants demonstrated generally high GenAI use, limited evidence of higher-order prompting strategies (adaptive, reflective, and logical) resulted in focused, bounded interactions with few prompt iterations. PTs’ justifications of GenAI use were shaped by task appropriateness, professional values, and perceived tool affordances. These findings suggest that effective and meaningful prompting requires competencies beyond technical skills. Accordingly, we propose a staged professional development framework to facilitate PTs’ development of higher-order prompting competencies.