Learning Resources for Sustainable Design in Engineering Education
Bibliographic record
Abstract
This paper presents the results of the Circular Design Project, European project funded by Erasmus+ Knowledge Alliance within the social business and the educational innovation field. The project have three major learning objectives: to increase and improve the learning strategies of Design for Sustainability; To gather and cluster open educational resources in Innovative Design for Sustainability; To train up innovative and entrepreneurial designers in Design for Sustainability. This was achieved through a knowledge co-creation process and the development and pilot training materials in order to teach and train students, faculty and enterprise staff of the design sector. The project formed by 12 partners is organised around four country hubs in Ireland, The Netherlands, Catalonia and Sweden. Each country Hub consists of one university, one company and one national design association. The project main results are: - The Open Educational Resources database (http://circulardesigneurope.eu/oer/) where resources in Circular design are clustered in three taxonomies: Categories (First-timers; Practitioners), Level (Beginner; Intermediate; Advanced) and Tags (calculator; report; …); - The Best Practice Publication, shows the whole design process, materials, challenges, problems and other key issues of Circular Design case studies; - Four international one-semester internships for undergraduate design students in the four universities with the participation of 11 companies and 45 students; - The Circular Design Digital Fabrication Lab Handbook to introduce students, companies and academics to the open-source, participatory, experimental and design & build approach within digital fabrication labs; - The Professional Development Course in circular design; - The Policy Paper in Circular Design Education
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.012 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.005 | 0.007 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.013 | 0.010 |
| Open science | 0.002 | 0.013 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.111 | 0.029 |
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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".