Précis

We are looking at the impact of the Flow Vis course from two perspectives:

1.  Are students in the FV course developing visual expertise? Dog show judges and bird watchers can almost instantly categorize the objects of their expertise. Are we training students to recognize fluid physics in a similar way? In collaboration with Prof. Tim Curran  we (Prof. Katherine Goodman and I) developed a visual expertise training experiment. Preliminary results (n=6) demonstrated that subjects can improve their perception of fluid flows, sorting images into turbulent and laminar categories, after one session of error-driven training. These results have encouraged us to ramp up the complexity of the perception training. The eventual goal of this work is to create a reliable, valid measure that can gauge whether students of fluids are gaining visual expertise over the course of a semester of study. The question after that is how such visual expertise affects students perceptions and attitudes towards fluid flows.
2. The other approach is more of a traditional mixed-method education research design to investigate student attitudes towards fluids. We are refining a partially validated survey instrument, the Fluids Perception Survey (FluPerS) that is administered to students before and after they take the Flow Vis course, a traditional Fluid Mechanics course, or a different control course. We have recorded interviews with students, and plan to analyze their work in an effort to get at how the FV course, or any technical course, changes student perceptions and attitudes towards the content. Preliminary work shows that a semester of making artistic images of fluid flows (for art’s sake) convinces students that fluids are more important to them as engineers and to society at large than an entire semester solving real-world quantitative fluids problems.

This work is in early stages. Ultimately, we hope to be able to replicate the impact of Flow Vis in other engineering disciplines, and across all of STEM. I’ve tried a couple of outright transfers into the realm of design courses: Perception of Design and Aesthetics in Design. Great courses, but not as powerful as Flow Vis; we need the answers from our research to inform the design of new curricula.

In the process of assessing student attitudes from surveys we ran up against a common problem in survey analysis: processing open response questions by hand, i.e. hand-coding, which is very time-intensive. Now we are working with a CS professor, Katherina Kann , to train an AI to code survey data.

In the end, can we demonstrate that art and aesthetics are valid motivations for doing science and engineering? Would incorporating art into engineering practice improve recruitment and retention of diverse students in engineering schools and the workforce? We are working on it.

Publications, Presentations and Posters