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Record W3008653490 · doi:10.1080/03004430.2020.1732364

The moderating role of two learning related behaviours in preschool children's academic outcomes: learning behaviour and executive function

2020· article· en· W3008653490 on OpenAlexaff
Amber Beisly, Kyong‐Ah Kwon, Shinyoung Jeon, Chaehyun Lim

Bibliographic record

VenueEarly Child Development and Care · 2020
Typearticle
Languageen
FieldSocial Sciences
TopicParental Involvement in Education
Canadian institutionsEducation and Early Childhood Development
Fundersnot available
KeywordsPsychologyDevelopmental psychologyActive listeningSocioeconomic statusAcademic achievementLiteracyAssociation (psychology)Executive functionsEarly childhoodCognitionPedagogyPopulation

Abstract

fetched live from OpenAlex

Executive function and learning behaviour play an important role in children's academic outcomes by helping them maintain attention, work cooperatively, and stay focused, especially for those from lower family socioeconomic status (SES) backgrounds. This study explored whether these learning-related skills were associated with children's concurrent math and literacy skills and whether they moderated the associations of family SES with math and literacy skills. Preschool children (n = 179) from early childhood education settings were directly assessed on executive function, math, and literacy skills. Executive function and learning behaviour were significantly correlated with children's math and literacy outcomes. Learning behavior moderated the association between family SES and child math outcomes. Teachers may support learning behaviour by teaching active listening and frustration management techniques, thus motivating children to actively participate in learning. This serves to buffer the negative impacts of family SES on children's academic outcomes, specifically math skills.

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 imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.004
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.018
Threshold uncertainty score0.035

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.016
GPT teacher head0.279
Teacher spread0.263 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
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

Citations23
Published2020
Admission routes1
Has abstractyes

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