On the Agenda? Deliberations on Experiential Learning at Canadian University Senate Meetings, 2012-2022
Bibliographic record
Abstract
The university’s core teaching mission is being reshaped by the proliferation of experiential learning (EL) pedagogies. The rise of EL is also constituting new connections between the university and its local community, relationships necessary for EL itself to be delivered. This research examines how universities confront these new and mutually interdependent dimensions of teaching and societal engagement. Using qualitative thematic content analysis, the paper documents and analyses university senate deliberations on EL at twelve (12) representative institutions in Canada for the period from 2012 to 2022 (n = 922 monthly meetings). Focusing on senate discussions on matters such as internal university EL governance, engagement with community partners, and impacts on learners and learning, the paper presents a novel analysis of the Canadian university’s understanding and development of EL in this phase of expansion. The paper concludes with a discussion of institutional and sector policy implications for the teaching and learning mission.
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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 | 0.018 | 0.026 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.005 |
| Science and technology studies | 0.058 | 0.021 |
| Scholarly communication | 0.011 | 0.003 |
| Open science | 0.002 | 0.012 |
| Research integrity | 0.003 | 0.005 |
| Insufficient payload (model declined to judge) | 0.008 | 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".