Framing Student Perspectives into the Higher Education Institutional Review Policy Process
Bibliographic record
Abstract
It is necessary and desirable to enhance student learning in higher education by integrating multiple perspectives during institutional policy reviews, yet few examples of such a process exist. This article describes an institutional assessment policy review process that used a questionnaire to elicit 269 students’ perspectives on a draft policy document. Among the key findings were a lack of focus on using assessment to inform instruction, and a lack of clarity around the purposes for assessment. Within the final policy, there seemed to be an absence of focus on assessment as supporting learning and informing instruction, although there was a significant focus on the role of assessment in measuring achievement, despite students’ emphasis on the former two characteristics. The study’s implications point to the important theoretical contributions students offer to institutional policy reviews, and the practical challenges institutions face in providing mechanisms that facilitate engagement and reflect shifts in culture.
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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 | 0.426 | 0.366 |
| Meta-epidemiology (narrow) | 0.001 | 0.002 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.005 | 0.004 |
| Science and technology studies | 0.029 | 0.037 |
| Scholarly communication | 0.052 | 0.026 |
| Open science | 0.004 | 0.025 |
| Research integrity | 0.017 | 0.025 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".