  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. Additionally,
the interviewees mentioned that identifying the core physics concepts within a
program, explaining code to others, and good program hygiene (i.e., commenting
and using meaningful variable names) are important skills for introductory
students to acquire. We also find that while a handful of interviewees note
that the experience and skills gained from computation are quite useful for
student's future careers, they also describe multiple limiting factors of
teaching computation in introductory physics, such as curricular overhaul, not
having "space" for computation, and student rejection. The interviews show that
while adding computational thinking to physics students repertoire is
important, the importance really comes from using computational thinking to
learn and understand physics better. This informs us that the assessment we
develop should only include the basics of computational thinking needed to
assess introductory physics knowledge.
