FACULTY BUY-IN AND THE BOTTOM-UP APPROACH: ACASE STUDY IN INTEGRATED ENGINEERING CURRICULUM REFORM ADVOCACY AND EWB'S GLOBAL ENGINEERING PROGRAM
Bibliographic record
Abstract
A recent Perdue University study identified faculty buy-in as the primary obstacle for engineering curriculum reform in North America. Delegates at the recent 2012 Engineers Without Borders (EWB) Global Engineering Symposium agreed, indicating it is one of the major challenges facing Canadian engineering education institutions today. For over 8 years, EWB Canada has been advocating for Global Engineer-focused education, successfully collaborating with faculty at over 20 Canadian, post-secondary institutions to promote these concepts skills and attitudes to thousands of engineering students. This paper describes the evolution of EWB’s approach to curriculum reform advocacy, which now focuses on building faculty relationships, student driven innovation, and incentivizing cooperation. This bottom-up strategy appropriately addresses the challenges of faculty buyin by promoting integrated curricular and extra-curricular education, which conforms to, but is not limited by, the CEAB attributes.
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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 | 0.025 | 0.033 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.032 | 0.022 |
| Scholarly communication | 0.019 | 0.011 |
| Open science | 0.002 | 0.012 |
| Research integrity | 0.004 | 0.008 |
| Insufficient payload (model declined to judge) | 0.007 | 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 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".