Et si les stratégies d’apprentissage des étudiants et leurs perceptions envers l’évaluation des apprentissages avaient un lien avec l’ajustement académique dans un contexte de persévérance aux études universitaires?
Bibliographic record
Abstract
L'objectif de cette revue de littérature systématique consiste à vérifier les liens qui unissent les caractéristiques individuelles des étudiants (stratégies d’apprentissage, perceptions envers l’évaluation des apprentissages [attrait et croyances]) et l’ajustement académique dans un contexte de persévérance aux études universitaires. Sur la base de la démarche de revue de littérature systématique de Gough (2007), 21 articles scientifiques publiés entre 2006 et 2017 et présentant des études effectuées auprès d’étudiants en enseignement supérieur ont été retenus. Les résultats obtenus confirment l’existence de liens entre les stratégies d’apprentissage et les perceptions des étudiants envers l’évaluation, entre les stratégies et l’ajustement académique, mais aucun lien entre les perceptions des étudiants envers l’évaluation et l’ajustement académique. Il appert aussi une absence d’étude pouvant confirmer ou infirmer les liens entre les trois concepts.
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 | 0.050 | 0.113 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.004 | 0.005 |
| Science and technology studies | 0.004 | 0.007 |
| Scholarly communication | 0.016 | 0.014 |
| Open science | 0.002 | 0.006 |
| Research integrity | 0.003 | 0.005 |
| Insufficient payload (model declined to judge) | 0.007 | 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".