Visualizing Engineering Fundamentals: Design of Mixed Reality and Physical Toolkits for Effective Learning

Synthesis: User study with 24 participants comparing classroom instruction, mixed-reality apps, and physical toolkits for Engineering Mechanics reveals Multimodal AI learning improves engagement but complex visualizations remain challenging.

Key Contributions

• User study with 24 participants comparing classroom instruction, mixed-reality apps, and physical toolkits for Engineering Mechanics reveals multimodal learning improves engagement but complex visualizations remain challenging.

Connections to AI in Education

This paper contributes to the growing body of research on AI applications in educational settings, specifically in the domains of AI in Education, Intelligent Tutoring, and Equity. The findings have implications for how educators design learning experiences that leverage AI while maintaining appropriate pedagogical oversight.

What this means for practice

• Instructors. Pair immersive or physical models with conventional explanation rather than substituting them: participants in all three conditions described lecture-plus-memory-recall workflows as cognitively demanding, and several asked for extended sessions that combine traditional explanation for initial understanding with the toolkit or mixed-reality module for application.
• Instructors. Do not read engagement as comprehension: nearly all participants agreed the toolkit and MR modules enhanced engagement, but many also reported difficulty recalling and applying concepts, and the authors caution against relying on a single modality on the strength of quiz scores alone.
• Designers. Combine tangibility with visualization instead of offering one or the other: toolkit users valued hands-on cause-and-effect interaction but felt constrained by the lack of visualization, MR users wanted greater tangibility, and many participants were not fully satisfied with the modality they were assigned.
• Designers. Add layered, low-clutter visual representations of familiar artifacts and their internal behavior: participants emphasized clearer visual aids for recalling and applying core concepts and noted that the toolkit and MR modules had limits once analysis became more advanced.

Limitations

• The evidence comes from 24 participants recruited at one university from students who had already completed Engineering Statics, all in a single 90-minute session with $20 compensation; the paper does not report the number of participants per condition, and the sample is a small convenience group of prior course completers.
• Learning outcomes rest on a pre/post knowledge quiz plus open-ended survey responses; the paper reports that the MR condition produced the highest quiz scores but offers no statistical test for that comparison, and the qualitative analysis is perception-based.
• Three researchers coded the open-ended responses until consensus, with no inter-rater reliability statistic reported, and the four themes were generated from participant self-report and observation rather than from independent measures.
• The baseline quiz was used to check prior-knowledge equivalence across groups, but participants who were dissatisfied with the modality assigned to them indicate that assignment-materials fit varied, and participants themselves noted that the evaluation method strongly shaped their experience of the system.

Citation

Mohammad Abu Nasir Rakib, Sharmin Akter, Eshwara Prasad Sridhar, Somik Biswas, Md Rassel Raihan, Mahmudur Rahman (2026). Visualizing Engineering Fundamentals: Design of Mixed Reality and Physical Toolkits for Effective Learning. submitted 1 Jul 2026