(273f) Enhancement of Chemical Engineering Education through Design Thinking: Integration of Theory and Cyber-Assisted Methods

Yenkie, K. M., Rowan University
In the engineering discipline, it is of utmost importance to give value to applied learning because as engineers, we are expected to innovate, and innovations happen when theoretical ideas are implemented successfully. Design thinking is one such approach that can enhance the value of theoretical concepts and motivate the students to visualize their ideas in more meaningful ways. The five stages of design thinking include: (i) Empathize, (ii) Define, (iii) Ideate, (iv) Prototype, and (v) Test [1]. Traditional engineering curriculum focuses on the last four stages and thus leads to a skewed perspective among students with regards to problem definition, formulation, and solution. Furthermore, research in chemical engineering education has indicated the need for revisions in the traditional curriculum and teaching methods to meet the needs of a modern chemical engineer [2]–[4]. Utilizing data analysis, programming and simulation tools is one way of demonstrating the virtual implementation of ideas and validating them at low costs and minimum risks. Thus, I have developed cyber-assisted modules as a part of the ‘Process Dynamics and Controls’, ‘Process Optimization’ and ‘Engineering Clinic’ courses offered to the undergraduates in the chemical engineering department at Rowan University, which strive to encompass all the five stages of Design Thinking.

For each topic in the Process Dynamics and Control, Process Optimization and Engineering Clinic courses, a supporting computer lab module was designed to substantiate student learning and simultaneously enhancing their mathematical modeling and computational skills. The lab sessions included a tutorial and an in-class computational assignment consisting of carefully chosen examples to closely resemble the state-of-the-art problems in chemical engineering. The tutorial consisted of an example from each topic, solved using analytical and computational (Matlab, Simulink, GAMS (General Algebraic Modeling Systems), R, Excel, etc.) methods. This provided the students with an opportunity to compare multiple solution platforms and choose the best to their liking and ease-of-implementation of the problem they intended to solve. Allowing students to work on the in-class assignments problems and discussing their computing issues, provided additional insights into learning barriers than traditional lecture-based teaching. We were able to discuss problem formulation errors, incorrect solver or algorithm selection, programming syntax errors, illogical initial guesses, lack of an output block or function, illogical results generated from ill-conditioned problems, etc.

Due to this integrated training, towards the end of these courses, the students were able to formulate and solve large-scale, real-world case studies and problems with broader contexts. Examples of problems solved by the students in team projects include drug dosing policies for chemotherapy treatment, an air-conditioning system in a classroom, configuration of perovskite crystals for harnessing solar energy, refractive-index matching of hydrogels, skiing trail-map optimization to maximize travel efficiency, etc. This integrated effort created a sense of appreciation for the course topics among the students and their application skills were considerably enhanced. They were able to think about the problem from multiple perspectives as well as implement their ideas virtually through cyber-assisted methods.

Keywords: computational tools, design, process control, optimization

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