Framing: A lens to understand and address student difficulties with Visual Python in University Physics

Computational thinking and modeling are recognized as important skills for educators to help engineering and science students develop.This has led to efforts to integrate computational programming into introductory physics courses, such as the implementation of Visual Python (VPython) as part of the Matter and Interactions curriculum.However, many students have difficulties integrating physics into functional code.Initially, we hypothesized that these difficulties were due to cognitive overload.However, after curricular interventions designed to address that hypothesis were of limited effectiveness, we developed a new hypothesis that focused on how students frame (mentally categorize) their activities, specifically if they are operating out of a "coding frame," a "physics frame," or both.We then tested this new hypothesis through structured observations of groups of students working through VPython exercises, obtaining evidence supporting the framing hypothesis.