DEVELOPMENT OF PROCESSES AND CRITERIA FOR CEAB GRADUATE ATTRIBUTE ASSESSMENT
Bibliographic record
Abstract
The Canadian Engineering Accreditation Board (CEAB) is following the lead of other accreditation bodies in requiring engineering programs to measure graduate attributes, also known as outcomes. Canadian ministers of education have also established undergraduate degree-level expectations that will imact engineering programs. This paper will review the evolution of outcomes assessment as it pertains to engineering accreditation and compare the new CEAB graduate attribute requirements to those of engineering accreditation bodies in countries including the U.S.A, U.K., and Australia. The process of implementing outcomes assessment at Queen's University will be described, including development of measurable assessment criteria from faculty working groups. Finally, the paper will provide an overview of learning management system software that can manage and report on assessment measures.
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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 | 0.179 | 0.297 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.028 | 0.014 |
| Science and technology studies | 0.006 | 0.004 |
| Scholarly communication | 0.016 | 0.007 |
| Open science | 0.005 | 0.011 |
| Research integrity | 0.003 | 0.006 |
| Insufficient payload (model declined to judge) | 0.003 | 0.003 |
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".