Collaboration between faculty members and the Center for teaching and learning at Polytechnique Montreal
Bibliographic record
Abstract
The Center for teaching and learning at Polytechnique Montreal (PM) was created in 1977. Its mission is to encourage and help instructors to improve their teaching, and ultimately, contribute to improve student learning at both undergraduate and graduate levels. Among its many activities, the CTL provides a compulsory orientation, training, and integration program for new faculty members; offers consultations, workshops, and conferences; manages grants for pedagogical initiatives; and conducts house studies on pedagogical or academic issues. With time, CTL has had the opportunity to collaborate with PM leaders and faculty members, on a number of issues. For example, it has conducted house studies on the following topics: students’ learning strategies; students’ motivation to learn within different pedagogies (project-based; e-learning; traditional lecturing); three year follow-up study on the impact the revised programs have had on student learning and retention. CTL has published many articles whether in scientific or professional journals. CTL encourages and provides support for faculty members that publish in general or discipline specific engineering education journals. PM also funds and conducts engineering education research projects with the MATI (Maison des Technologie, house of technologies), specifically on the use of technology in the classroom and innovative pedagogy. MATI is a three-way partnership between HEC Montreal, University of Montreal and PM. They are currently working on the e-portfolio for the development of professional attributes in engineering. PM has also created a new category of instructors, called “chargé d’enseignement”. Their job is to teach full time at the undergraduate level. What sets them apart from ordinary part time instructors is that they must conduct research on their teaching, and actively participate in engineering education conferences. Finally, PM is contemplating allocating a chair for the scholarship of teaching and learning. This chair would be under a faculty member’ responsibility, and would help fund research on engineering education. It would also allow hiring PhD and master’s degree students.
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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 | 0.011 | 0.018 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.013 | 0.004 |
| Scholarly communication | 0.013 | 0.003 |
| Open science | 0.004 | 0.008 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.092 | 0.015 |
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".