  Despite the buzz around ChatGPT's potential, empirical studies exploring its
actual utility in the classroom for learning remain scarce. This study aims to
fill this gap by analyzing the lesson plans developed by 29 pre-service
elementary teachers from a Korean university and assessing how they integrated
ChatGPT into science learning activities. We first examined how the subject
domains and teaching and learning methods/strategies were integrated with
ChatGPT in the lesson plans. We then evaluated the lesson plans using a
modified TPACK-based rubric. We further examined pre-service teachers'
perceptions and concerns about integrating ChatGPT into science learning.
Results show diverse applications of ChatGPT in different science domains.
Fourteen types of teaching and learning methods/strategies were identified in
the lesson plans. On average, the pre-service teachers' lesson plans scored
high on the modified TPACK-based rubric, indicating a reasonable envisage of
integrating ChatGPT into science learning, particularly in 'instructional
strategies & ChatGPT'. However, they scored relatively lower on exploiting
ChatGPT's functions toward its full potential compared to other aspects. The
study also identifies both appropriate and inappropriate use cases of ChatGPT
in lesson planning. Pre-service teachers anticipated ChatGPT to afford
high-quality questioning, self-directed learning, individualized learning
support, and formative assessment. Meanwhile, they also expressed concerns
about its accuracy and the risks that students may be overly dependent on
ChatGPT. They further suggested solutions to systemizing classroom dynamics
between teachers and students. The study underscores the need for more research
on the roles of generative AI in actual classroom settings and provides
insights for future AI-integrated science learning.
