Codevelopment action learning as a supervisory tool to support graduate students’ academic persistence
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
A dyadic supervision model is traditionally used to support graduate students throughout their studies. While this model has many advantages, it can sometimes be insufficient. Graduate students report a need for spaces where they can discuss their projects, share experiences, and gain practical information on writing or other milestones in their academic journey. To address this need, a professor at the Université du Québec à Montréal (UQAM) implemented Codevelopment Action Learning (CAL) with her graduate students. This Account of Practice describes her experience preparing, organizing, and facilitating CAL sessions, while navigating the dual role of supervisor and facilitator. It also highlights how this initiative inspired a larger-scale project currently underway, involving more than a dozen CAL groups facilitated by graduate students and supported by two universities. The article concludes with reflections on CAL as a complement to dyadic supervision and as a promising tool for supporting graduate students’ academic persistence.
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 | 0.008 | 0.018 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.005 |
| Insufficient payload (model declined to judge) | 0.001 | 0.002 |
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