Sustainable Engineering Design in Education: A Pilot Study of Teaching Right‐to‐Repair Principles through Project‐Based Learning
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Over 60 million tons of E-waste is expected to be generated in 2023, with associated significant impacts on health and the environment. To reduce the number of products sent to landfills, "Right to Repair" (RtR) movements are gaining momentum in many countries, including the UK, USA, and EU member states. While Universities are seen as important stakeholders to drive forward sustainable design practices, there is currently little work looking at training undergraduate design engineers in the principles of designing household products in support of RtR. In particular, the project-based learning (PBL) pedagogy shows promise in engaging and training students with the skills and knowledge required to successfully design products for RtR. In this paper, a pilot-study of teaching engineers is presented to design products compatible with RtR principles, alongside many technical skills, in a first-year PBL course. The key outputs of this paper are the design of the module, which can be used to help inform first-year engineering education, the high engagement of students, with 100% of respondents agreeing that they intend to try to implement sustainable design practices in future, and some of the innovative features that students implement in their projects.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it