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Record W2260881313 · doi:10.4102/sajce.v2i1.19

Ready or not: Kindergarten classroom engagement as an indicator of child school readiness

2012· article· en· W2260881313 on OpenAlexaff
Caroline Fitzpatrick

Bibliographic record

VenueSouth African Journal of Childhood Education · 2012
Typearticle
Languageen
FieldSocial Sciences
TopicEarly Childhood Education and Development
Canadian institutionsMcGill University
Fundersnot available
KeywordsPsychologyCurriculumPreparednessDevelopmental psychologyAcademic achievementPsychological interventionCognitionEarly childhoodVocabularyStudent engagementSocial cognitive theoryMathematics educationPedagogy

Abstract

fetched live from OpenAlex

Children’s preparedness for school is an important predictor of their eventual academic attainment, health, and personal success well into adulthood. Although kindergarten knowledge of numbers and vocabulary represent robust indicators of children’s readiness to learn at school entry, theory and research suggest that self-directed learning skills are also important in meeting the challenges of the elementary school classroom. This review examines evidence related to the potential benefits (e.g. improving children’s academic outcomes) of targeting classroom engagement skills, a person-environment fit characteristic reflecting task-orientation and industriousness. Reviewed studies suggest that classroom engagement skills are malleable and robust predictors of later elementary school achievement. Research also suggests that cognitive control skills in the form of executive functions are likely to underlie individual differences in classroom engagement. This paper provides evidence that developing pre-school and kindergarten curriculum that target cognitive control can be a useful strategy for enhancing student engagement behaviour. Developing early interventions that bolster school readiness can then help social impairments in childhood and adolescence.

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)0.003
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.554
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.025
GPT teacher head0.315
Teacher spread0.290 · 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 designQualitative
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

Citations7
Published2012
Admission routes1
Has abstractyes

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