Drenth, Rick (2026) Design of a Deep Learning Framework for Digital Engineering Tools in Engineering Education. Design Project, Industrial Engineering and Management.
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Abstract
Digital engineering tools are increasingly used in professional engineering practice to support calculations, explore design alternatives, and improve engineering efficiency. Despite their widespread availability, these tools are rarely integrated into engineering education in a manner that promotes engineering judgement and higher-order reasoning. As a result, students often learn to use tools procedurally, without developing the ability to critically interpret results, evaluate alternatives, and justify design decisions. This thesis presents the development of an instructional framework that supports the integration of digital engineering tools into engineering education while promoting deep learning and engineering judgement. It combines case-based learning, scaffolded reasoning activities, tool-supported exploration, comparison of alternatives, and structured reflection. Together, these elements are intended to support engineering judgement and higher-order reasoning rather than procedural tool use. Validation results suggest that digital engineering tools can be integrated into engineering education in a manner that supports reasoning-based decision-making while simultaneously fostering familiarity with industry-relevant tools. The developed framework provides both a theoretical and practical foundation for connecting engineering education, engineering judgement, and long-term technology adoption.
| Item Type: | Thesis (Design Project) |
|---|---|
| Supervisor name: | Larsen, G.K.H. and Jonker, G.H. |
| Degree programme: | Industrial Engineering and Management |
| Thesis type: | Design Project |
| Language: | English |
| Date Deposited: | 25 Aug 2026 13:49 |
| Last Modified: | 25 Aug 2026 13:49 |
| URI: | https://fse.studenttheses.ub.rug.nl/id/eprint/37510 |
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