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Record W2998788423 · doi:10.1017/9781108553803.011

Mothers’ Use of Questions and Children’s Learning and Language Development

2020· book-chapter· en· W2998788423 on OpenAlexaff
Imac Maria Zambrana, Tone Kristine Hermansen, Meredith L. Rowe

Bibliographic record

VenueCambridge University Press eBooks · 2020
Typebook-chapter
Languageen
FieldPsychology
TopicLanguage Development and Disorders
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsPsychologyLanguage developmentLanguage acquisitionLinguisticsDevelopment (topology)Developmental psychologyMathematics educationPhilosophyMathematics

Abstract

fetched live from OpenAlex

This chapter presents results from a longitudinal investigation of the form and function of mothers' questions to their one–, two–, and three–year–old children in a challenging task context across a diverse sample of 64 families in Norway. We examine the implications of mothers' questions for children's concurrent task performance and later language development. The findings suggest that mothers vary quite a bit in their use of questions. Moreover, the mothers show a decrease in their use of questions that are direct in their informational intent and/or simpler in their form over time, and an increase in questions that are indirect in intent and complex in their form (wh-questions). Mothers who more often ask wh–questions at child age two years have children with higher language skills at age four years, whereas use of simpler questions at child age two is negatively related to children's concurrent task success and later language skills. Together with the existing literature, this study suggests that questions are not just a mechanism for cognitive development because they allow children to obtain the information they need, but also that parental questions scaffold children's language and possibly cognitive development more general by guiding their exploration.

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: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.973
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
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)0.0000.000

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 head0.019
GPT teacher head0.220
Teacher spread0.201 · 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
GenreOther

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

Citations8
Published2020
Admission routes1
Has abstractyes

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