Student satisfaction as a managed outcome: relationship with other key performance indicators and expenditure and revenue allocations in Ontario's colleges of applied arts and technology
Bibliographic record
Abstract
In 1998, the Ontario government established performance indicators for its publicly funded colleges and universities. A sub-set of these became the basis for performance funding in 2000. These actions were consistent with those undertaken by a number of governments, on the basis of increasing accountability and improving performance. The implementation of performance funding in Ontario was a significant event and was expected to have an impact on the behaviour of the institutions. This study examined the initial implementation period of the indicators, from 2000 to 2006. Student satisfaction had been identified as a significant outcome in previous research on performance indicators in Ontario. The study examined the relationship between student satisfaction and the other indicators. It also examined the relationship between student satisfaction and revenue sources and expenditure allocations. The study relied on a review of literature on decision making models, performance indicators and their implementation. It built on previous literature on the introduction of performance indicators into Ontario's college system. The study utilized linear multi-regression analysis to determine correlations between the indicators and revenue and expenditure categories. The study found that student satisfaction results of institutions were auto-correlated and becoming increasingly stable over the period of the study. Institutions experienced less change in results year to year and the previous year's result became a better indicator of the subsequent year's. The study also identified correlations between student satisfaction and some revenue and expenditure categories. A significant negative correlation was identified between student satisfaction and expenditures on bursaries and scholarships and a positive correlation was identified between student satisfaction and expenditures on staffing in student services. There was also a positive correlation identified between student satisfaction and ancillary revenues. There was a positive correlation identified between graduate satisfaction and graduate employment. Potential policy implications resulting from the analysis are discussed and suggestions for future research are identified.
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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 | 0.001 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 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".