6 citations · 7 across the 5 of their papers we have counts for
5 papers
A Framework for Deductive Semantic Content Analysis at Scale in Science Education Using Text Embeddings
Jonas Timmann Mjaaland, Markus Fleten Kreutzer, Halvor Tyseng +5
Qualitative content analysis of open-ended survey responses is a commonly used research method in science education. However, traditional coding approaches are often time-consuming…
Comparing large language models for supervised analysis of students' lab notes
Rebeckah K. Fussell, Megan Flynn, Anil Damle +2
Recent advancements in large language models (LLMs) hold significant promise in improving physics education research that uses machine learning. In this study, we compare the appli…
A method to assess trustworthiness of machine coding at scale
Rebeckah K. Fussell, Emily M. Stump, N. G. Holmes
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,…
Comparing introductory and beyond-introductory students' reasoning about uncertainty
Emily M. Stump, Mark Hughes, Gina Passante +1
Uncertainty is an important concept in physics laboratory instruction. However, little work has examined how students reason about uncertainty beyond the introductory (intro) level…
Context affects student thinking about sources of uncertainty in classical and quantum mechanics
Emily M. Stump, Matthew Dew, Gina Passante +1
Measurement uncertainty is an important topic in the undergraduate laboratory curriculum. Previous research on student thinking about experimental measurement uncertainty has focus…