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Low-Cost Desktop Learning Modules (LCDLMs) are innovative, affordable educational tools designed to enhance hands-on learning experiences in engineering education. Previous studies have shown the effectiveness of LCDLMs in promoting engineering student engagement and learning outcomes. The present study further explored whether different types of LCDLMs could influence student engagement and learning outcomes differently. This study compared four LCDLMs (i.e., Double Pipe, Hydraulic Loss, Shell & Tube, and Venturi). In total, 2190 undergraduate and graduate students from 29 universities in the United States participated in this study. Results of this study showed that the Shell & Tube module significantly outperformed the Hydraulic Loss and Venturi modules in promoting enhancements in student Active scores. However, no significant differences were observed between the Double Pipe module and the other modules on Active scores. Moreover, the Hydraulic Loss module led to significantly higher knowledge growth compared to the Double Pipe, Shell & Tube, and Venturi modules. 

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.