Post-COVID-19 Pandemic Restrictions: Follow-Up on Changes Within Canadian Academic and Fieldwork Curricula
Bibliographic record
Abstract
Background. COVID-19 pandemic restrictions necessitated curricular modifications in Canadian occupational therapy education. Documentation and reflection on temporary or permanent curriculum modifications and their perceived impact on student learning and outcomes is critical. Purpose. To explore and compare reported curricula changes (academic and fieldwork) during restricted and post-restricted delivery periods together with the perceived impact on learners. Method. A cross-sectional online descriptive survey was sent to key representatives from administration, curriculum, and fieldwork at all 14 accredited occupational therapy university programs in Canada. Findings. Overall, many pandemic-restricted curricula delivery and assessment changes shifted back toward pre-pandemic methods. Changes that were maintained were congruent with universal design or perceived limited adverse impact on learning. Both in-person and virtual learning were perceived as important for changing practice needs. Fieldwork placement recruitment remained a challenge, with some programs increasing the use of simulation. Interpersonal competency development and assessment method integrity were more visible and of concern. Conclusion. Interpersonal competency development and assessment method integrity were more visible and of concern. Programs demonstrated remarkable flexibility to shift, adapt, and deliver curricula, but the human cost for this accomplishment is still palpable.
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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 | 0.003 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".