INTERNATIONAL COORDINATION OF A FIRST-YEAR COURSE ON SUSTAINABILITY IN ENGINEERING DESIGN
Bibliographic record
Abstract
A growing trend in the recruitment of undergraduate students to engineering programs atCanadian universities is to establish an international presence at a branch campus in a different part of the world. This paper focuses on an example case study of the international collaboration of an introductory engineering course called “Sustainability in Engineering Design” between the University of Prince Edward Island (UPEI) and the Universities of Canada (UofCanada-Cairo) inCairo, Egypt. This course set out as being foundational in the implementation of an identical, international offering of the UPEI Faculty of Sustainable Design Engineering’s (FSDE) Bachelor of Science in Sustainable Design Engineering (BSc-SDE) program at the Cairo campus. This paper describes the implementation of the course at the branch (UofCanada-Cairo) campus and the coauthors, as instructors, provide a self-assessment of the success of the coordination to deliver the learning outcomes for the course. An assessment of how well the main graduate attributes (i.e. GA9: Impact on Society and Environment; GA6: Individual and Team Work, and GA13:Lifelong Learning) linked to the course’s learning outcomes were achieved in developing a sustainability mindset in UPEI FSDE undergraduate students will be presented and recommendations for the course in the context of international collaboration will be discussed.The projects' assessment also affirms that students at both campuses can work in teams to evaluate the impact of current engineering designs on society and environment and design more sustainable products in the future.
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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 | 0.007 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.001 |
| Scholarly communication | 0.004 | 0.001 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.018 | 0.003 |
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".