Engagement in Assessment Change and the Role of SoTL
Bibliographic record
Abstract
This study follows a network-based Assessment Redesign Project at a Canadian university to investigate engagement and sustained implementation. The following strategies were employed in the project: mini-grants, embedded support, a community of practice, and social networks. Assessment facilitators worked in discipline clusters to achieve mutual goals for assessment reform targeted at the authentic assessment of critical thinking and problem-solving. Interviews were conducted with nine of the 25 project members one-year post-implementation. The study adopted a motivational theoretical lens to investigate how the experience of the Assessment Redesign Project affected motivation and the continued adoption or propagation of assessment strategies. Participants commented on how helpful the embedded support had been in building their assessment skills or knowledge. The mini-grants were used (in some cases) to fulfil scholarship of teaching and learning (SoTL) goals. All of those engaged in SoTL demonstrated intrinsic motivation for assessment change and had propagated assessment techniques or activities into other courses. In the few cases where motivation was purely extrinsic, there was no SoTL or continuation of assessment activities. This study highlights the links between SoTL and the longer-term impact of the Assessment Redesign Project. Suggestions are provided for institutions wishing to replicate outcomes from the project.
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.
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 | 0.042 | 0.124 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.010 | 0.011 |
| Scholarly communication | 0.015 | 0.006 |
| Open science | 0.003 | 0.018 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.005 | 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".