Establishing an Open Education Community of Practice at a Bilingual University: Year 1 Reflections
Bibliographic record
Abstract
This lighting talk explores some of the challenges and benefits that we encountered during the first year of establishing an Open Education Community of Practice (CoP) at the University of Ottawa. The creation of an Open Education CoP builds on the recommendations from a cross-campus working group on open and affordable learning materials. The group found that while the campus had pockets of innovation, the larger university community lacked a cohesive vision for the use, creation, and dissemination of OER. Meant to be a vehicle for awareness building, information sharing, and support, the CoP is also meant to lay the foundation for a culture of open pedagogy. After careful planning, the Open Education CoP met for the first time in October 2021. It has been an enriching experience with some notable benefits, including participation from students and the university press, and hearing from OER champions on campus and elsewhere. The CoP also faced its share of technical, linguistic and strategic challenges, ranging from competing priorities and content hosting to conducting activities in two languages and the limits of "openness".
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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 | 0.024 | 0.022 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.051 | 0.023 |
| Scholarly communication | 0.022 | 0.010 |
| Open science | 0.004 | 0.034 |
| Research integrity | 0.009 | 0.016 |
| 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".