Exploring the Artificial Intelligence Interaction Profiles of Participants With Different Levels of Teaching Experience for Lesson Planning in the Context of Acids and Bases

Abstract

In this multi-case study, the ChatGPT interaction profiles of participants with varying years of teaching experience were examined during lesson planning for the topic of acids and bases. Six participants (i.e., two senior pre-service science teachers, one induction year science teacher, two experienced science teachers, and an experienced science teacher educator) participated in the study. A lesson plan in the Content Representation (CoRe) format, a copy of dialogue with ChatGPT (i.e., conversation history with ChatGPT), a reflection paper on details of the lesson planning with ChatGPT, and online focus group interview data were collected from all participants. Both deductive and inductive analyses of the multiple data sources revealed four profiles, namely, Artificial Intelligence (AI)-reliant planners, AI-collaborative planners, AI-assisted plan refiners, and AI-independent planners. The profiles differed from each other in terms of the flow of lesson planning with AI, the interaction purposes of the participants with ChatGPT during lesson planning, and the extent to which the participants incorporated the content provided by ChatGPT into their lesson plan preparation. In light of the results, science pre-service teachers and teachers should be trained on what AI can offer them, how AI tools can be effectively utilized in science education, and the ethical considerations of AI use.