Managing quality assurance at community colleges in Ontario, Canada: experiences and perspectives of front-line quality managers
Bibliographic record
Abstract
Purpose This paper aims to examine the roles of quality managers at community colleges, their experiences balancing accountability and improvement and their insights into the future of quality assurance. Design/methodology/approach This phenomenological, qualitative study used semi-structured interviews with eight community college quality managers to investigate their roles, experiences and perspectives. A reflexive thematic approach was used to analyze the interview data. Findings Four themes were identified from participant responses: quality managers frame and enable program quality, quality managers drive program change, quality managers cultivate a culture of quality and quality managers seek system change. The findings illustrate the roles played by quality managers as they work to improve college education at program, institution and system-wide levels. Research limitations/implications The decision of participants to accept the recruitment invitation might reflect particular attitudes, perspectives or experiences. Practical implications Quality assurance has emerged as a key mechanism for ensuring postsecondary programs are current, relevant and meeting the evolving needs of students and employers. This study advances the understanding of how quality assurance processes play out at the operational level and explores the experiences of quality managers as they navigate various quality tensions. Originality/value Quality managers play key roles in leading, evaluating and influencing quality assurance processes in postsecondary education yet they are underrepresented in the literature. The findings of this study shed new light on the aspirational and influential roles they play in advancing quality assurance.
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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 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.019 | 0.008 |
| Scholarly communication | 0.005 | 0.001 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".