Exploring potential of ChatGPT for assisting preservice science teachers' pedagogical content knowledge in inquiry-based lesson planning

This study aimed to explore potential applications of ChatGPT for assisting preservice science teachers in developing inquiry-based lesson plans with a focus on their Pedagogical Content Knowledge (PCK). Data were collected from ten volunteer preservice science teachers through interviews, lesson plans, ChatGPT conversations, and field notes. Participants attended a seminar on integrating ChatGPT into inquiry-based lesson planning. Participants' prompts to ChatGPT aimed to improve their science lesson plans with inquiry-based orientations. Modifications in the lesson plans revealed that participants interacted with ChatGPT to receive support in the PCK components of instructional strategies, assessment of scientific literacy, science curricula, students' understanding of science, and orientation to teaching science, in descending order. Analysis showed increased inquiry levels in final lesson plans after interacting with ChatGPT. It was concluded that ChatGPT assisted different domains of PCK of preservice science teachers in inquiry-based lesson planning and assisted them in planning their science instruction with an increased level of inquiry. According to preservice science teachers, ChatGPT was helpful in the inquiry-based lesson planning process. This study demonstrates that integrating artificial intelligence tools into science teacher education programs may contribute to the development of preservice science teachers' PCK and inquiry-based instruction.