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Hands-on, active learning in engineering courses fosters deeper understanding, collaboration, and social skills for students. This paper reports on the design, fabrication, and testing of a transparent miniaturized shell-and-tube heat exchanger module for engineering thermo-fluids classes. This module was also implemented for in-class heat exchanger instruction, where students (sample size, N = 75) conducted hands-on experiments following the instructions provided in the associated worksheet, participated in pre-tests and post-tests, analyzed the experimental data, and provided their feedback through motivational surveys. The performance test data obtained from the developed desktop heat exchanger module shows that the experimental heat transfer rates are in good agreement with theoretically predicted values calculated based on the standard correlations and assumptions. The pre-test and post-test assessments show that the use of this miniaturized shell-and-tube heat exchanger module in classroom instruction improves fundamental understanding of the heat exchange process and enhances student comprehension of complex phenomena of fluid flow patterns and heat transfer in the different parts of the heat exchanger. The motivational assessments demonstrate the module’s efficacy in elucidating the underlying heat transfer mechanisms and facilitating active engagement. The developed low-cost, handson heat exchanger can be used in undergraduate thermo-fluids engineering education for visualizing and better understanding of heat transfer principles, enhancing engagement of students, improving retention of fundamental concepts, and finally bridging the gap between theoretical abstractions and real-world applications. 

There is overwhelming research evidence showing that students often struggle with learning key engineering concepts. The Low-Cost Desktop Learning Modules (LCDLMs) are model prototypes of standard industry equipment designed for students to learn some fundamental but abstract engineering concepts in the classrooms. Previous results have shown that students who interact with LCDLMs tend to outperform those who engage in traditional lectures. However, little is known about student profiles and their forms of engagement with this tool. Hence, the present study seeks to investigate the different student profiles that emerge from students working with the LCDLM and the demographic factors that influence student engagement with the tool. Participants (N = 1,288) responded to an engagement survey after working with LCDLMs in engineering classrooms in several states around the United States. We then used a latent profile analysis (LPA) – an advanced statistical approach – to better understand the representation of learner engagement profiles resulting from their self-reported learning engagement beliefs as they reflect on their experience in using LCDLMs. The LPA revealed five distinct profile types – disengaged, somewhat engaged, moderately engaged, highly engaged, and fluctuating engagement. Results showed that those who are more interactive and actively engaged with the LCDLM scored higher on their questionnaire compared to those who passively engaged with the LCDLM. We conclude with a discussion of the theoretical and practical implications of our findings. 

Hands-on experiments using the Low-Cost Desktop Learning Modules (LCDLMs) have been implemented in dozens of classrooms to supplement student learning of heat transfer and fluid mechanics concepts with students of varying prior knowledge. The prior knowledge of students who encounter these LCDLMs in the classroom may impact the degree to which students learn from these interactive pedagogies. This paper reports on the differences in student cognitive learning between groups with low and high prior knowledge of the concepts that are tested. Student conceptual test results for venturi, hydraulic loss, and double pipe heat exchanger LCDLMs are analyzed by grouping the student data into two bins based on pre-test score, one for students scoring below 50% and another for those scoring above and comparing the improvement from pretest to posttest between the two groups. The analysis includes data from all implementations of each LCDLM for the 2020-2021 school year. Results from each of the three LCDLMs were analyzed separately to compare student performance on different fluid mechanics or heat exchanger concepts. Then, the overall pre- and posttest scores for all three LCDLMs were analyzed to examine how this interactive pedagogy impacts cognitive gains. Results showed statistically significant differences in improvement between low prior knowledge groups and high prior knowledge groups. Additional findings showed statistically significant results suggesting that the gaps in performance between low prior knowledge and high prior knowledge groups on pre-tests for the LCDLMs were decreased on the posttest. Findings showed that students with lower prior knowledge show a greater overall improvement in cognitive gains than those with higher prior knowledge on all three low-cost desktop learning modules. 

Our team has developed Low-Cost Desktop Learning Modules (LCDLMS) as tools to study transport phenomena aimed at providing hands-on learning experiences. With an implementation design embedded in the community of inquiry framework, we disseminate units to professors across the country and train them on how to facilitate teacher presence in the classroom with the LC-DLMs. Professors are briefed on how create a homogenous learning environment for students based on best-practices using the LC-DLMs. By collecting student cognitive gain data using pre/posttests before and after students encounter the LC-DLMs, we aim to isolate the variable of the professor on the implementation with LC-DLMs. Because of the onset of COVID-19, we have modalities for both hands-on and virtual implementation data. An ANOVA whereby modality was grouped and professor effect was the independent variable had significance on the score difference in pre/posttest scores (p<0.0001) and on posttest score only (p=0.0004). When we divide out modality between hands-on and virtual, an ANOVA with an F- test using modality as the independent variable and professor effect as the nesting variable also show significance on the score difference between pre and posttests (p-value=0.0236 for hands- on, and p-value=0.0004 for virtual) and on the posttest score only (p-value=0.0314 for hands-on, and p-value<0.0001 for virtual). These results indicate that in all modalities professor had an effect on student cognitive gains with respect to differences in pre/posttest score and posttest score only. Future will focus on qualitative analysis of features of classrooms yield high cognitive gains in undergraduate engineering students. 

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.