Development and psychometric properties of the Early Development Instrument (EDI): A measure of children's school readiness.
Bibliographic record
Abstract
L'instrument de mesure du developpement a la petite enfance a ete concu afin de fournir un outil approprie, peu couteux et valide sur le plan psychometrique, permettant d'evaluer les capacites de l'enfant a entrer en premiere annee primaire. Les proprietes psychometriques de l'instrument ont ete evaluees au cours de deux etudes. Une analyse factorielle menee a partir des donnees recueillies aupres de 16 000 enfants de maternelle a permis de tester la presence de cinq facteurs theoriques: sante physique et bien-etre, competence sociale, maturite affective, langage et communication, developpement cognitif et connaissances generales. Les analyses factorielles ont pu confirmer la presence des trois premiers facteurs, mais ont degage la necessite de modifier les deux derniers. Ceci a permis de formuler la version finale de l'instrument de mesure du developpement a la petite enfance qui est composee des cinq facteurs suivants: sante physique et bien-etre, competence sociale, maturite affective, langage et developpement cognitif, habiletes a la communication et connaissances generales. Ces cinq domaines offrent de bons indices de consistance interne, comparable a d'autres instruments. Une seconde etude (N = 82) a demontre la presence d'une bonne concordance entre l'evaluation de parents et des enseignants, la fidelite entre les evaluateurs, la validite concomitante et la validite convergente. Ces resultats confirment que l'instrument de mesure du developpement a la petite enfance est un outil psychometrique adequat pour evaluer les aptitudes de l'enfant lors de l'entree a l'ecole primaire.
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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 | 0.009 | 0.025 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.000 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".