The Impact of External Quality Assurance Policies and Processes on Curriculum Development in Ontario Postsecondary Education
Bibliographic record
Abstract
Situated in both the global context of quality movement in postsecondary education in the past few decades and the local context of quality assurance for Ontario postsecondary education in 2013-2014, this study aimed to address this research question: How did the external quality assurance policies and processes that emerged from 2000 to 2014 impact curriculum development in Ontario postsecondary education? The purpose was to examine the relationship between two important topics in contemporary postsecondary educationâ external quality assurance, or EQA, and curriculum development. As the fundamental question for EQA research is whether EQA leads to quality improvement, a deeper question for the study was: Did the accountability schemes in the EQA mechanisms for Ontario postsecondary education lead to quality improvement in terms of curriculum development? If so, how did it happen? \nThe conceptual framework for the study was informed by four perspectives: external influences on curriculum development; process causality and the realist approach to impact analysis; conceptual models of EQA impact; and the importance of the context and the connectivity between the global and the local. In light of the paradigm of critical realism, the project drew upon case study and policy analysis as its strategies of inquiry. \nThe study was conducted on two levels. On the macro- or system-level, document analysis and individual interviews informed the intentions and processes of the existing EQA frameworks for Ontario public universities and colleges. On the micro-level, case studies of seven carefully selected outcomes-based education initiatives shed light on the EQA processes and policy implementation. The analysis focussed on the processes in which the EQA mechanisms had affected curriculum development in Ontario. While conducted in one single province, the study was also concerned with an issue of global concernâ the relationship between accountability and improvement in quality assurance for postsecondary education. \nThe study found that the accountability schemes in EQA mechanisms in Ontario led to some areas of improvement in curriculum development within postsecondary institutions; however, there existed implementation gaps. The analysis revealed a complex reality in the EQA impact processes. The dissertation makes a conceptual, methodological and empirical contribution to EQA studies.
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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 | 0.010 | 0.025 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.007 | 0.005 |
| Scholarly communication | 0.006 | 0.002 |
| Open science | 0.001 | 0.006 |
| 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".