Evaluating factors contributing to positive partnership work in a students-as-consultants partnership program
Bibliographic record
Abstract
McMaster University pioneered its Course Design/Delivery Consultants Program (CDDCP) in fall 2016. This program pairs an instructor partner who is teaching or preparing to teach a course with a student partner to obtain a student’s perspective on teaching and learning in their classroom. Although the CDDCP was based on Healey, Flint, and Harrington’s (2014) eight values of partnership, the contribution of other factors to its success was of interest. Participants’ experiences were analyzed using a framework informed by these values. Qualitative analysis showed that these values were reflected in participants’ experiences. Additionally, it was revealed that participants’ experiences in the CDDCP were enhanced by two additional factors: (a) prior experiences and experiences gained through CDDCP participation and (b) the extensive program structure of the CDDCP. These findings suggest that partnership programs involving students, instructors, and coordinators should (a) explicitly acknowledge the value of participants’ experiences and (b) facilitate face-to-face time among participants.
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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 | 0.031 | 0.055 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.013 | 0.006 |
| Scholarly communication | 0.010 | 0.004 |
| Open science | 0.002 | 0.015 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.005 | 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".