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

Cheah, Yin Hong orcid logoORCID: 0000-0003-4560-0205, Hsu, Hsiao-Ping orcid logoORCID: 0000-0002-3943-2690, Lu, Jingru orcid logoORCID: 0009-0002-5879-9735 and Alsaka, Raghad orcid logoORCID: 0009-0001-7779-6727 (2026) Preservice teachers’ prompting practices and decision-making: Exploring pathways from talking to reasoning with generative artificial intelligence. Journal of Research on Technology in Education . pp. 1-20. ISSN 1539-1523

Abstract
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.
Metadata
Item Type:Article (Published)
Refereed:Yes
Uncontrolled Keywords:Generative artificial intelligence, preservice teachers, prompt engineering, decision-making, teacher education, human-AI interaction
Subjects:Social Sciences > Education
Social Sciences > Educational technology
DCU Faculties and Centres:DCU Faculties and Schools > Institute of Education > School of STEM Education, Innovation, & Global Studies
Research Institutes and Centres > Research Centre in Science, Technology, Engineering, and Mathematics (STEM) Education (CASTel)
Publisher:Routledge
Official URL:https://doi.org/10.1080/15391523.2026.2704778
Copyright Information:Authors
ID Code:33206
Deposited On:20 Aug 2026 09:33 by Hsiao-Ping Hsu . Last Modified 20 Aug 2026 09:33
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Creative Commons: Attribution 4.0
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