2024 ASEE Annual Conference & Exposition

Work-in-Progress: Chemical Engineering Students' Representational Fluency when Designing in the Context of Fluids Mechanics

Presented at WIP: Classroom Innovations

Incorporating design into the engineering curriculum has become an educational priority, as it significantly influences students' learning, motivation, and development of an engineering identity, among other outcomes. While some research exists about the teaching and learning of engineering design in the first- and last- years of undergraduate education, the second and third years have received comparatively less attention. This study contributes to this gap by exploring the design practices of third-year chemical engineering students. Particularly, it focuses on students' ability to create and translate among multiple representations (i.e., representational fluency) as an essential engineering analysis and design ability. We ask: How do third-year chemical engineering students create and translate across multiple representations when working on a design project in the context of fluid mechanics? We used a qualitative research approach to explore the representations employed by four student teams working on conceptualizing a sustainable and safe fuel storage tank and delivery piping system for an Air Force Base (fictitious client). They completed the project as part of their fluid mechanics course requirements. We coded the five project deliverables using a co-evolution framework of the engineering design process and an adapted version of the Lesh Translation Model, a framework for representational fluency. For this work in progress, we present the results of one of the teams composed of four chemical engineering students. Our initial results showed that the students created or downloaded images and wrote text to communicate their framing of the problem and solutions. However, the students needed scaffolding to translate those representations into symbolic mathematical models. They did not intuitively develop models to test and make decisions. Furthermore, they needed additional support to integrate information from the sociotechnical context into their framing.

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