PATHWAYS BETWEEN ENGINEERING AND EDUCATION FACULTIES: EFFORTS TO ESTABLISH AN ENGINEERING EDUCATION GRADUATE PROGRAM AT THE UNIVERSITY OF MANITOBA
Bibliographic record
Abstract
Engineering education is a recognized field of research and inquiry that draws on a number of established disciplines to enhance the practice and teaching of engineering. Within the last ten years, some universities in the U.S. and abroad have developed engineering education graduate programs with an emphasis on drawing from the education discipline in particular. These programs range in scope from those in which graduate students maintain a technical area of expertise alongside a focus on pedagogy to more interdisciplinary collaborations with education faculties. In Canada, such programs are still in development and the more recent movement towards outcomes-based assessment in engineering schools to satisfy changing accreditation requirements, has further mobilized an institutional interest in teaching and learning processes. This paper reports on the evolution of such a program, combining the expertise of both engineering and education faculties at the University of Manitoba to achieve this synergy.
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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 | 0.014 | 0.011 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.023 | 0.005 |
| Scholarly communication | 0.008 | 0.002 |
| Open science | 0.005 | 0.020 |
| Research integrity | 0.003 | 0.007 |
| Insufficient payload (model declined to judge) | 0.007 | 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".