Speaker
Description
Physics education research (PER) shares a rich tradition of designing learning environments that promote valued epistemic practices such as sensemaking and mechanistic reasoning (1-3). Recent technological advancements, particularly artificial intelligence has caught significant traction in the PER community due to its human-like, sophisticated responses to physics tasks. (4,5) In this study, we contribute to the ongoing efforts by comparing AI (ChatGPT) and student responses to a physics task through the cognitive frameworks of sensemaking and mechanistic reasoning. Findings highlight that by virtue of its training data set, ChatGPT’s response provide evidence of mechanistic reasoning and mimics the vocabulary of experts in its responses. On the other hand, half of students’ responses evidenced sensemaking and reflected an effective amalgamation of diagram-based and mathematical reasoning, showcasing a comprehensive problem-solving approach. Thus, while AI responses elegantly reflected how physics is talked about, a part of students’ responses reflected how physics is practiced. In a second part of the study, we presented chatGPT with variations of the task, including an open-ended version and one with significant scaffolding. We observed significant differences in conclusions and use of representations in solving the problems across both student groups and the task formats.
References
[1] T. O. B. Odden and R. S. Russ, Defining sensemaking: Bringing clarity to a fragmented theoretical construct, Science Education 103, (2019) 187
[2] A. Sirnoorkar and J. T. Laverty, Theoretical exploration of task features that facilitate student sensemaking in physics, arXivpreprint arXiv:2302.11478 (2023)
[3] Krist, C. V. Schwarz, and B. J. Reiser, Identifying essential epistemic heuristics for guiding mechanistic reasoning in science learning, Journal of the Learning Sciences 28, 160 (2019)
[4] C. G. West, Ai and the fci: Can chatgpt project an understanding of introductory physics?, arXiv preprint arXiv:2303.01067
[5] Bor Gregorcic and Ann-Marie Pendrill Phys. Educ. 58 (2023) 035021 DOI 10.1088/1361-6552/acc299
| Contribution categories - primary focus | University |
|---|---|
| Contribution categories - type | Research oriented |
