Computation is a central aspect of 21st century physics practice; it is used
to model complicated systems, to simulate impossible experiments, and to
analyze mountains of data. Physics departments and their faculty are
increasingly recognizing the importance of teaching computation to their
students. We recently completed a national survey of faculty in physics
departments to understand the state of computational instruction and the
factors that underlie that instruction. The data collected from the faculty
responding to the survey included a variety of scales, binary questions, and
numerical responses. We then used Random Forest, a supervised learning
technique, to explore the factors that are most predictive of whether a faculty
member decides to include computation in their physics courses. We find that
experience using computation with students in their research, or lack thereof
and various personal beliefs to be most predictive of a faculty member having
experience teaching computation. Interestingly, we find demographic and
departmental factors to be less useful factors in our model. The results of
this study inform future efforts to promote greater integration of computation
into the physics curriculum as well as comment on the current state of
computational instruction across the United States
