2026 ASEE Annual Conference & Exposition

Over the course of an eight-year study, our team created and propagated several Low-Cost Desktop Learning Modules (LCDLMs) used to teach college students fundamental engineering principles. The goal of this project is to provide a hands-on learning opportunity which requires students to engage in interactive group activities. This approach is inspired by Bandura’s Social Cognitive Theory, which posits that optimal learning is a social process, and thus complex ideas are learned best collaboratively. LCDLMs are thus meant to help students not only by providing visual aid and tactile feedback, but by creating an opportunity for an environment where students evolve their understanding by sharing their differing perspectives and observations. Afterwards, students are asked to participate in pre- and posttests to assess their comprehension of the associated concepts, and a survey to gauge their overall opinion of the LCDLMs.

The main data collection period has been completed, although we are still collecting data from willing instructor volunteers using our best practices in exchange for continued technical support. We gathered feedback from long-term faculty participants and are working to revise our recommendations when using the LCDLMs for more uniform and optimal results.

Since the inception of the project, we have worked to expand the number of engineering topics and concepts covered by our project by developing new LCDLMs. Recent additions include a fluidized bed reactor and a glucose spectroscopic analyzer kit, which are meant for use in teaching students the fundamental principles of reaction kinetics in different environments, one being inside a heterogeneous, fluidized bed reactor, the other being a batch process for understanding enzyme kinetics.

Additionally, through a collaborative effort with [Redacted], we have developed a set of virtual DLMs which can be used from anywhere online. To test their efficacy in the classroom, our team performed a side-by-side comparison by randomly dividing a class of undergraduates into two groups, one with the physical modules and one with the virtual replicates. The results for and in-class hydraulic loss learning exercise show a gain of 48% from the pretest to posttest for the hands-on version, and 60% for the web version. There were no statistically significant differences between the pre- and posttest groups based on a two-tailed t-test.