What about sustainability? Adding the “S” to leadership and management competency development in the engineering curriculum
Bibliographic record
Abstract
To provide a framework for engineering educators to map leadership and management skills development in the curriculum, the authors previously created a Leadership-Management Development Model (LMDM). In this paper we look to extend the model to include sustainability by using an “environmental limits approach”, creating a Leadership-Management -Sustainability Development Model (LMSDM). Adding the sustainability dimension provides a contextual purpose for leadership and management development as it relates to creating and stewarding sustainable socio-technical engineering solutions. This can set a common language and a harmonized framework in the context of skills development and application in engineering practice to complex socio-technical problems. Ultimately the model will allow programs and instructors to map and situate the development of leadership, management and sustainability concepts in their programs in an integrated manner., and to examine learning outcomes relevant to the Canadian Engineering Accreditation Board (CEAB) graduate attributes (GA). Curricular examples are provided to give insight into application of the LMSDM in engineering courses and programs. Future work will include mapping the developed LMSDM to engineering curriculum at multiple institutions.
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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 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.005 |
| Scholarly communication | 0.007 | 0.007 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".