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Direct linkMatthew Mears; Louise Dash; Ross Galloway; Calvin Karpenko; Nicolas Labrosse; Victoria Mason; Mark Quinn – Journal of Science Education and Technology, 2025
Digital proficiency, including coding, is increasingly essential in physics education. However, disparities in coding skills among students are influenced by demographic factors and prior educational exposure. This study examines barriers to pre-university coding exposure for first-year physics students across five UK institutions, proposing a…
Descriptors: Foreign Countries, Coding, Physics, Science Education
Rebeckah K. Fussell; Emily M. Stump; N. G. Holmes – Physical Review Physics Education Research, 2024
Physics education researchers are interested in using the tools of machine learning and natural language processing to make quantitative claims from natural language and text data, such as open-ended responses to survey questions. The aspiration is that this form of machine coding may be more efficient and consistent than human coding, allowing…
Descriptors: Physics, Educational Researchers, Artificial Intelligence, Natural Language Processing
