INCORPORATING EMPLOYER AND STUDENT ASSESSMENTS INTO A GRADUATE ATTRIBUTE ASSESSMENT PLAN
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
When faced with assessing the Canadian Engineering Accreditation Board (CEAB) graduate attributes, most programs will start by focusing oninstructor assessments. Course instructors are uniquely positioned to assess their students’ learning, and instructor assessments are sufficient to meet CEAB accreditation requirements. However, for a full picture, data from multiple sources is always desirable. At the University of Victoria, we have chosen to include co-op employer and student assessments in our graduateattribute assessment plan. In this paper, we present the assessment tools we have identified and created, and outline the system we have developed to sustainably produce assessment reports every term for every program. We highlight some of the challenges we have faced, and conclude by discussing our future plans
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it