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Direct linkRebeckah K. Fussell; Megan Flynn; Anil Damle; Michael F. J. Fox; N. G. Holmes – Physical Review Physics Education Research, 2025
Recent advancements in large language models (LLMs) hold significant promise for improving physics education research that uses machine learning. In this study, we compare the application of various models for conducting a large-scale analysis of written text grounded in a physics education research classification problem: identifying skills in…
Descriptors: Physics, Computational Linguistics, Classification, Laboratory Experiments
Samuel Boguslawski; Rowan Deer; Mark G. Dawson – Information and Learning Sciences, 2025
Purpose: Programming education is being rapidly transformed by generative AI tools and educators must determine how best to support students in this context. This study aims to explore the experiences of programming educators and students to inform future education provision. Design/methodology/approach: Twelve students and six members of faculty…
Descriptors: Programming, Computer Science Education, Personal Autonomy, Learning Motivation
