Crafting a definition of sustainability for engineering education and applying it to assess curriculum
Bibliographic record
Abstract
In order to be thoughtful practitioners towards the environment and society, engineers must be able to integrate different dimensions of sustainability—knowledge and application—in a holistic manner. This case study, conducted at the Faculty of Applied Science and Engineering at the University of Toronto, focuses on the knowledge aspect of an engineer’s training by (1) creating a framework to define sustainability for engineering, (2) developing and evaluating a method for assessing the sustainability content in engineering curriculum, and (3) assessing holistic aspects by looking at connections among the sustainability pillars within the curriculum. It is challenging to define sustainability: commonly cited definitions are hard to operationalize and not sufficiently specific to engineering; no single existing framework captures all engineering concepts for sustainability. This study developed a new framework and codebook to define sustainability, starting with the three pillars of sustainability: environmental, economic and social, then adding a fourth pillar of professional responsibility, with 4–6 specific themes within each pillar. We then qualitatively analyzed the content in undergraduate engineering courses, assessing and triangulating across course descriptions, then syllabi, and finally an instructor survey. The results indicate the environmental pillar is most prevalent in the curriculum, followed by economic and social, with increasing sustainability moving from descriptions to syllabi to instructor surveys. Sustainability content varied substantially across programs, with Civil Engineering courses covering the most and Electrical Engineering the least. The results also indicate that sustainability tends to be taught by pillar rather than in a holistic manner.
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How this classification was reachedexpand
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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".