Towards a Generalized Assessment of Computational Thinking for Introductory Physics Students
Justin Gambrell, Eric Brewe

TL;DR
This study qualitatively analyzes physicists' perspectives on computational thinking in introductory physics, emphasizing core skills like coding comprehension and explanation, to inform assessment development.
Contribution
It provides insights into what physicists value in computational thinking for introductory physics and highlights key skills and challenges for assessment design.
Findings
Physicists value reading code and core physics concept identification.
Python, VPython, and spreadsheets are preferred tools.
Assessment should focus on basic computational skills relevant to physics.
Abstract
Computational thinking in physics has many different forms, definitions, and implementations depending on the level of physics, or the institution it is presented in. In order to better integrate computational thinking in introductory physics, we need to understand what physicists find important about computational thinking in introductory physics. We present a qualitative analysis of twenty-six interviews asking academic (N=18) and industrial (N=8) physicists about the teaching and learning of computational thinking in introductory physics courses. These interviews are part of a longer-term project towards developing an assessment protocol for computational thinking in introductory physics. We find that academic and industrial physicists value students' ability to read code and that Python (or VPython) and spreadsheets were the preferred computational language or environment used.…
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Taxonomy
TopicsTeaching and Learning Programming · Computational Physics and Python Applications
