Incorporating Sustainability Principles into the First-Year Engineering Design Curriculum for International Students
Bibliographic record
Abstract
Courses focusing on engineering design present an excellent opportunity for the introduction of the concepts of sustainability. The purpose of the proposed work is to enhance students’ understanding of sustainability through a project-based approach. For that purpose we developed a new exploratory project consisting of 3 possible real-world inspired case studies and implemented them in the introductory engineering design course. Results show that nearly all of the participating students generally consider sustainability a key aspect of their education; however, the particularities of student opinions with respect to sustainability outcomes in designs largely vary and seem to depend on the goals and design focus of each program. Our analyses show that the project-based learning course had a moderate to large impact on student competencies including systems thinking, environmental literacy, responsible business and economy, social responsibility, environmental impact measurement, materials choice, design, critical thinking, and communication and teamwork. The particular design project implemented here is an excellent learning tool for first-year engineering students, directing them to include sustainability considerations in their products and systems design. It also creates a space for open discussions about global considerations related to sustainability, together with an opportunity for international students to share their personal experience and previous exposure to sustainability issues.
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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 | 0.004 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.011 | 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".