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Record W3089120290

Dépistage des difficultés mathématiques : validation et normalisation franco-québécoise du Tempo Test Rekenen et du Numeracy Screener version française

2020· article· fr· W3089120290 on OpenAlexaboutno aff
Anne Lafay, Helena P. Osana, Sarah Michaud, Nadia Nosworthy

Bibliographic record

VenueDigital Commons - Andrews University (Andrews University) · 2020
Typearticle
Languagefr
FieldMathematics
TopicCognitive and developmental aspects of mathematical skills
Canadian institutionsnot available
Fundersnot available
KeywordsPsychologyTest (biology)Geology
DOInot available

Abstract

fetched live from OpenAlex

L’objectif est d’évaluer les qualités psychométriques de deux tests mathématiques dans le but de développer des normes franco-québécoises pour le dépistage et l’identification des enfants à risque de présenter un trouble des apprentissages en mathématiques : le Tempo Test Rekenen (TTR) visant l’évaluation des capacités de fluence arithmétique et le Numeracy Screener version française (NS-f) visant l’évaluation des habiletés de base du traitement du nombre et des numérosités. Un total de 695 enfants franco-québécois scolarisés de la maternelle à la 6ème année de primaire a été évalué. Les résultats ont montré une bonne cohérence interne, une bonne validité prédictive et une bonne validité de construit. Ils suggèrent ainsi que le présent dispositif de dépistage comportant le NS-f et le TTR, a une bonne validité pour le dépistage et l’identification des enfants à risque de présenter un trouble des apprentissages en mathématiques.

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 imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.788
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0010.006
Open science0.0010.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.001

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.

Opus teacher head0.024
GPT teacher head0.226
Teacher spread0.202 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designNot applicable
Domainnot available
GenreEmpirical

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".

Quick stats

Citations1
Published2020
Admission routes1
Has abstractyes

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