Soutenir la persévérance des étudiants (sur campus et à distance) dans leur première session d’études universitaires : constats de recherche et recommandations
Bibliographic record
Abstract
Quelles sont les mesures mises en place pour contrer le phnomne d'abandon des tudes universitaires? Comment des outils d'aide et de soutien la persvrance aux tudes, accessibles en ligne, sont-ils utiliss par des tudiants nouvellement inscrits en premire session d'tudes universitaires? Une tude auprs de 216 tudiants (sur campus et distance) dans trois universits qubcoises montre qu'ils ont des difficults sur le plan des comptences et connaissances pralables, des stratgies d'apprentissage et d'autorgulation ainsi que de la lecture de l'anglais et du franais, et que les mesures de soutien mises en ligne (S@MI-Persvrance) ont t utilises pour rsoudre ces difficults .
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 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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.000 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".