Integrating sustainable development into the undergraduate engineering curriculum through a mandatory first year engineering design course at the University of Toronto
Bibliographic record
Abstract
This paper discusses how Engineering Science, an undergraduate division within the Faculty of Engineering at the University of Toronto in Toronto, Canada, has worked to foster engineers that can meaningfully contribute to sustainable development (SD). Specifically, Engineering Science has developed ESC102: Praxis II, a core course required for all first year undergraduate Engineering Science students, which takes both a systems engineering and an interdisciplinary approach to solving complex problems in a local context. All Engineering Science students take Praxis II, and are exposed to sustainable development concepts even if they had no prior interest in sustainable development (SD). The 2010 Praxis II course integrated SD concepts by explicitly requiring students to consider and develop sustainability requirements, using the "DfX" concepts from the "Design for Sustainability" (DfS) and "Design for Environment"(DfE) literature, and incorporate sustainable design concepts into their final projects. Students were guided in these activities through introductory lectures, discussion groups, and tutorial activities. Sustainable design was also an explicit part of the assignment requirements. This paper discusses the goals, process, and success of the 2010 Praxis II course curriculum integration of sustainable development concepts. It discusses the specific training in problem-solving and sustainability concepts that students received, and the challenges students faced in applying SD concepts to their solutions. We also explore how to improve student engagement in and student acceptance of SD concepts. Finally, we summarize the lessons learned for integrating SD concepts into an engineering design course.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.011 | 0.002 |
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".