Enseignements du PIRLS-2021 sur la littéracie en lecture des élèves de 4e année: Comparaisons Québec, trois provinces canadiennes, six pays européens
Bibliographic record
Abstract
(in French) La dernière enquête internationale en éducation -- le PIRLS 2021 -- témoigne pour la première fois des résultats en lecture des élèves de 4e année scolarisés au milieu d'une crise sans précédent, la pandémie COVID-19. Les tests confirment la prédiction générale que dans la plupart des juridictions les élèves auraient une performance inférieure comparativement à l'enquête de 2016. Les résultats sont analysés par thème : scores de performance (moyen, tendances, distribution centile, seuils internationaux de compétences) ; résultats associés au statut socioéconomique (élèves et écoles), aux facteurs parentaux (activités éducatives, attentes académiques) et à l'environnement de l'école (ressources matérielles et humaines, emphase sur succès académique, discipline et sécurité). Les tableaux et statistiques construites et commentées, sont faits en retenant comparativement 11 juridictions : quatre pays Nordiques (Danemark, Finlande, Norvège, Suède), les deux régions de la Belgique (Flamande et Française), la France, et les quatre provinces canadiennes participantes à cette vague du PIRLS (Colombie-Britannique, Alberta, Québec, et Terre-Neuve-et-Labrador). Les élèves des juridictions canadiennes et leurs écoles ont généralement des scores parmi les plus élevés qui témoignent de la résilience de leurs systèmes d'éducation. Les écarts socioéconomiques sont parmi les plus faibles, notamment au Québec où les indices de réussite académique ont augmenté. L'analyse présente aussi la satisfaction de l'emploi et les sentiments sur la profession par les enseignants ainsi que le nombre de semaines pour lesquels les opérations des écoles ont été perturbées. Abstract (in English, working paper is in French) The latest international survey in education -- PIRLS 2021 -- is the first to present an international comparative study of fourth grade students' reading achievement that coincided with the height of the COVID-19 pandemic. Tests results confirm the general prediction for a majority of jurisdictions that students would have a lower performance than in the 2006 survey. Results are analysed by subject: scores achievement (mean, trends, percentiles, international benchmarks); relationship between scores and socioeconomic environment (students, schools), parental factors (early Literacy Activities, academic expectations), and school composition (resources, academic emphasis, discipline and security). Constructed and commented tables and statistics are presented on a comparative basis for 11 jurisdictions: four Nordic countries (Denmark, Finland, Norway, Sweden), two Belgian regions (Flemish, French), France, and four Canadian provinces (British-Columbia, Alberta, Québec, Newfoundland-Labrador). Canadian students and their schools generally are among those having the highest scores, which express the resilience of their schooling systems. Socioeconomic achievement gaps are among the lowest, especially in Québec where scores have increased. The analysis also presents job satisfaction and perceptions on the profession by teachers, as well as the number of weeks with school pandemic perturbations.
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 | 0.004 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.005 | 0.007 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.010 | 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".