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Record W3212461719

Numeracy Screener: Comparing Symbolic and Non-Symbolic Numerical Magnitude Processing in 4–6-year-old Canadian and Singaporean Children

2021· article· en· W3212461719 on OpenAlexaboutno aff
Nidhi Shah, Daniel Ansari

Bibliographic record

VenueWestern Undergraduate Psychology Journal · 2021
Typearticle
Languageen
FieldMathematics
TopicCognitive and developmental aspects of mathematical skills
Canadian institutionsnot available
Fundersnot available
KeywordsNumeracyMagnitude (astronomy)PsychologyPedagogyLiteracy
DOInot available

Abstract

fetched live from OpenAlex

Background – Students in East Asian countries consistently outperform their Western counterparts on mathematics assessments, with Singaporean students topping all global math competency assessments in 2015. Previous studies suggest that this learning gap between East Asian and Western countries emerges even before students begin formal schooling.   Aim - The present study used existing data to test whether Singaporean children display an early advantage in basic numerical knowledge relative to their Canadian peers. Methods - 4 to 6-year-old Singaporean (n = 214) and Canadian (n = 370) children’s symbolic and non-symbolic magnitude processing skills were evaluated using the Numeracy Screener. Participants were presented with pairs of stimuli and asked to identify which of two numbers or symbols (dot arrays) were larger in magnitude. Results - Canadian children outperformed Singaporean children on both the symbolic and non-symbolic magnitude comparison tasks, suggesting that Singaporean children do not begin with an early advantage in basic math skills. After controlling for age, a subset analysis of 5-year-old participants reduced the main effects of format and country on performance scores. Implications & Future Direction - These findings provide novel evidence of a learning gap between younger children that favours a Western country (Canada), suggesting that the learning gap is not unidirectional. This finding conflicts with previous research, highlighting the need for further investigation into the factors underlying the mathematics achievement gap between East Asian and Western countries.

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.142
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.029
GPT teacher head0.321
Teacher spread0.292 · 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 designObservational
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

Citations0
Published2021
Admission routes1
Has abstractyes

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