The Impact of Quality Assurance Policies on Curriculum Development in Ontario Postsecondary Education
Bibliographic record
Abstract
Two trends in the evolution of quality assurance in Canadian postsecondary education have been the emergence of outcomes-based quality standards and the demand for balancing accountability and improvement. Using a realist, process-based approach to impact analysis, this study examined four quality assurance events at two universities and two colleges in Ontario to identify how system-wide quality assurance policies have impacted the curriculum development process of academic programs within postsecondary institutions. The study revealed different approaches that postsecondary institutions chose to use in response to quality assurance policies and the mechanisms that may account for different experiences. These mechanisms include endeavours to balance accountability and continuous improvement, leadership support, and the emerging quality assurance function of teaching and learning centres. These findings will help address the challenges in quality assurance policy implementation within Canadian postsecondary education and enrich international discussions on the accountability-improvement dichotomy in the context of quality assurance.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 teacher head, 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".