6 citations · 6 across the 4 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,…
Instructing nontraditional physics labs: Toward responsiveness to student epistemic framing
Meagan Sundstrom, Rebeckah K. Fussell, Anna McLean Phillips +5
Research on nontraditional laboratory (lab) activities in physics shows that students often expect to verify predetermined results, as takes place in traditional activities. This u…
Hybrid Forecasting of Chaotic Processes: Using Machine Learning in Conjunction with a Knowledge-Based Model
Jaideep Pathak, Alexander Wikner, Rebeckah Fussell +4
A model-based approach to forecasting chaotic dynamical systems utilizes knowledge of the physical processes governing the dynamics to build an approximate mathematical model of th…