2025 ASEE Annual Conference & Exposition

Active and hands-on learning in engineering education is essential for student engagement and knowledge retention. Research has shown that Low-cost Desktop Learning Modules (LCDLMs) facilitate these learning outcomes (e.g., Khan et al., 2022; Reynolds et al., 2022). However, little research has examined how different LCDLM types and implementation methods (Hands-On, Virtual, Lecture-only) influence engineering student learning outcomes. Our study addresses this gap by exploring the impact of various LCDLMs and instructional methods on student engagement, measured through the ICAP framework, and learning performance in fluid mechanics and thermodynamics courses.
This study was conducted across multiple semesters, including during the COVID-19 pandemic, when digital learning became a necessity for many institutions. A total of 2,316 undergraduate engineering students from eight universities were recruited for this study. Four different types of LCDLMs—Hydraulic Loss, Double Pipe, Shell & Tube, and Venturi Meter—were implemented using three methods: Hands-On, Virtual, and Lecture-only. Pre- and post-tests were used to assess learning performance, while student engagement was measured using the Interactive, Constructive, Active, and Passive learning (ICAP; Chi & Wylie, 2014) framework.
Findings revealed that implementation methods significantly influenced both engagement and learning outcomes. Contrary to expectations, the virtual group consistently outperformed the Hands-On and Lecture-only groups in terms of learning gains (F(2, 2312) = 15.65, p < .001), with the Hydraulic Loss module leading to the highest knowledge growth (F(3, 664) = 18.74, p < .001) in the virtual setting (M = 25.8, SD = 36.9). The Shell & Tube module, when used in a hands-on format, was especially effective in promoting active engagement (F(3, 2188) = 4.36, p < .01), achieving significantly higher active engagement scores (M = 14.75, SD = 2.97) compared to the Hydraulic Loss and Venturi models. Interestingly, the Virtual group also showed significantly higher post-test scores (M = 0.74, SD = 0.27) than the Hands-On group (M = 0.64, SD = 0.23) and the Lecture group (M = 0.63, SD = 0.24).
These results suggest that virtual environments allowed for more flexibility and the ability to revisit materials during the pandemic, which may have contributed to enhanced learning outcomes. Despite the surprising effectiveness of virtual implementation, the results highlight the potential for hands-on learning to foster critical engagement, especially when active participation is required (Chi & Wylie, 2014). However, the physical constraints of pandemic-related disruptions may have limited the effectiveness of hands-on approaches. Future research should examine the long-term impact of virtual versus hands-on learning and investigate how hybrid learning models, which combine virtual and physical interaction, could optimize both engagement and performance in engineering education. Additionally, exploring how different LCDLM designs interact with various learning modalities may offer further insights into best practices for maximizing student outcomes.
Keywords: LCDLM, Student Engagement, ICAP, Hands-On, Virtual Learning, Engineering Education