Quality Assurance of Engineering Education in Canada: its suitability for graduates working in global markets
Bibliographic record
Abstract
The quality of engineering education in Canada is maintained within a very narrow band ofuniformity by virtue of an accreditation process. Since all provinces and territories of Canadarequire that all individuals practicing engineering must be registered professional engineers, allestablished engineering programs offered in Canada are accredited to meet the educationalrequirements for registration. Furthermore, new programs are developed with the objective ofsecuring accreditation at an appropriate time. The Canadian Engineering Accreditation Board(CEAB), acting on behalf of all professional engineering associations, through their parent, theCanadian Council of Professional Engineers (CCPE), conducts accreditation on the invitation ofdeans of engineering and applied science faculties. This paper describes the objectives and theprocess of accreditation. In particular it describes the process of dealing with emerging engineeringdisciplines and the assessment challenges presented by new technologies such as distance education.In order to calibrate educational standards of Canada in an international market, the paper alsooutlines the international activities of the CEAB
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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 | 0.005 | 0.014 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.004 |
| Science and technology studies | 0.006 | 0.002 |
| Scholarly communication | 0.007 | 0.001 |
| Open science | 0.001 | 0.002 |
| 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".