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Chemical engineers frequently contribute to the advancement of the medical field; however, medical applications are often only covered in elective courses. To introduce medical applications into the core curriculum, we implemented a hands-on learning tool that portrays blood separation principles through microbead settling in a core third-year chemical engineering separations class. Test scores from twenty-six students show significant growth at p < 0.001 from Pretest to Posttest I at average values of 41 % and 68 %, respectively. Posttest II scores reveal a significantly higher average score of 84 % for students who sat through lecture before the hands-on experiment in comparison to 75 % for students who first had the hands-on experiment then lecture with statistical significance of p = 0.046 and a moderate Cohen’s d effect size of 0.442. Students report positive, lasting impressions from the guided-learning worksheet and hands-on learning experience on their feedback surveys and one-on-one interviews. Retention assessments from four students six months post-intervention reveal retention of concepts with an average test score of 74 %. These outcomes suggest hands-on learning tools are most impactful on conceptual and motivational gains when supplemented with pre-experiment lectures and quality complementary learning materials. 

As this NSF LCDLM dissemination, development, and assessment project matures going into our fourth year of support we are moving forward in parallel on several fronts. We are developing and testing an injection-molded shell-and-tube heat exchanger for heat transfer concepts, an evaporative cooler to expand to another industrial-based heat exchange system, and a bead separation module to demonstrate principles of fluid mechanics in blood cell separations applications. We are also comparing experimental data for our miniaturized hydraulic loss and venturi meter LCDLMs to predicted values based on standard industrial correlations. As we develop these new learning components, we are assessing differential gains based on gender and ethnicity, as well as how students learn with existing LCDLMs in a virtual mode with online videos compared to an in-person hands-on mode of instruction.