(186a) Fostering Inclusivity By Linking the Implementation of Computational Simulations to Student Learning Styles

Computational simulations enhance undergraduate engineering education by enabling complex phenomena to be presented in a visual way that appeals to a variety of learning styles and strengthens the link between theory and applications. Embedding visualization throughout the curriculum is also vital to promoting inclusive learning because students whose learning styles place them at the greatest risk for retention receive the most significant positive impact. But simulations are often ineffective because they employ complex computational tools and are implemented without considering the link to student learning style. Here we describe a study aimed at understanding this link by assigning students in an undergraduate chemical engineering transport phenomena class to perform a computational simulation exercise in teams grouped according to learning style. Student learning styles were classified according to the Myers Briggs Personality Type Indicator assessment. The simulation exercise was presented using two computational tools of varying complexity, STAR CCM+ and openFOAM. We describe the initial results of a pilot study and identify insights likely to maximize the impact of simulation-based instruction, particularly for students with at-risk learning styles.