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Record W4236457953 · doi:10.47678/cjhe.v50i1.188301

The Impact of Quality Assurance Policies on Curriculum Development in Ontario Postsecondary Education

2020· article· en· W4236457953 on OpenAlexfundvenueaboutno aff
Qin Liu

Bibliographic record

VenueCanadian Journal of Higher Education · 2020
Typearticle
Languageen
FieldDecision Sciences
TopicEvaluation and Performance Assessment
Canadian institutionsnot available
FundersSocial Sciences and Humanities Research Council of Canada
KeywordsQuality assuranceAccountabilityCurriculumContext (archaeology)Higher educationQuality (philosophy)Quality managementPostsecondary educationPolitical sciencePublic relationsBusinessPedagogySociologyMarketing

Abstract

fetched live from OpenAlex

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.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.385
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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.

Opus teacher head0.141
GPT teacher head0.483
Teacher spread0.341 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations11
Published2020
Admission routes3
Has abstractyes

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