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Record W2322865646 · doi:10.5539/jedp.v6n1p173

Teacher-Child Relationships and Child Temperament in Early Achievement

2016· article· en· W2322865646 on OpenAlexvenueno aff
Ashleigh Collins, Erin O’Connor

Bibliographic record

VenueJournal of Educational and Developmental Psychology · 2016
Typearticle
Languageen
FieldSocial Sciences
TopicEarly Childhood Education and Development
Canadian institutionsnot available
Fundersnot available
KeywordsTemperamentPsychologyDevelopmental psychologyAcademic achievementPromotion (chess)Association (psychology)Social psychologyPersonality

Abstract

fetched live from OpenAlex

<p>Teacher-child relationship quality and child temperament have been associated with children’s school adjustment and academic performance. However, few studies explore the influence of both child temperament and teacher-child relationship quality on children’s academic development. This study investigates the role of teacher-child relationships on kindergarten children’s temperament and academic performance. Study participants were comprised of 324 kindergarten students, attending 22 schools in urban, low-income communities. A multivariate regression analysis was used to explore whether teacher-child relationships moderate or mediate the association between child temperament and academic performance. The study reinforces previous findings that conflictual teacher-child relationships inhibit children’s academic performance and close teacher-child relationships promote children’s academic performance. For cautious children, close teacher-child relationships moderate mathematics performance. For high maintenance children, conflictual teacher-child mediate children’s critical thinking. The findings have implications for teacher training, on-going teacher development, and the promotion of early academic development for children at-risk for underachievement.</p>

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.185
Threshold uncertainty score0.705

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.034
GPT teacher head0.333
Teacher spread0.299 · 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.

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

Citations10
Published2016
Admission routes1
Has abstractyes

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