Prospective science teachers’ use of generative AI in chemistry lab reports: patterns in questioning and conceptual understanding

This study examines the impact of artificial intelligence (AI) tools on the questioning skills and conceptual understanding of prospective science teachers (PSTs) in completing chemistry laboratory experiment reports. Before the intervention, a survey assessed PSTs’ AI usage experiences. During the intervention, PSTs used AI tools while preparing experiment reports, incorporating AI-related questions at the end of each report. These questions were analyzed based on difficulty level, topic, and type. Conceptual understanding questions were also posed weekly. A chi-square analysis examined the relationship between PSTs’ conceptual understanding and question difficulty. Results showed a significant relationship between questioning skills and conceptual understanding in the first two experiments. In the last three, PSTs with complete understanding posed moderately difficult questions, whereas those with alternative understanding contributed fewer questions, though no significant correlation was found between question difficulty and conceptual understanding. After the intervention, PSTs reflected on their AI experiences, noting faster access to information, cross-checking AI-derived data, and improved critical thinking and data interpretation. However, they struggled with diversifying their questions to AI. The findings suggest that AI-supported chemistry laboratory reporting provides opportunities for PSTs to refine their questioning and conceptual understanding.