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Record W4225871880 · doi:10.1080/15248372.2022.2058509

An Observational Study of Children’s Problem Solving during Play with Friends

2022· article· en· W4225871880 on OpenAlexaff
Zachary S. Gold, Jesseca Perlman, Nina Howe, Aura Ankita Mishra, Ganie DeHart, Hannah Hertik, Jessica Belue Buckley

Bibliographic record

VenueJournal of Cognition and Development · 2022
Typearticle
Languageen
FieldSocial Sciences
TopicEarly Childhood Education and Development
Canadian institutionsConcordia University
Fundersnot available
KeywordsPsychologyObservational studyNaturalistic observationSet (abstract data type)CognitionTask (project management)Observational methods in psychologyDevelopmental psychologyAssociation (psychology)Cognitive developmentTheory of mindSocial cognitionChild developmentEarly childhoodSocial psychology

Abstract

fetched live from OpenAlex

Problem solving is an important cognitive skill that children use to plan and navigate various developmental and social tasks. Although previous research was theory-grounded and systematic, to our knowledge, no research has observed and documented children’s problem solving as a primary objective in naturalistic developmental contexts, such as home-based play with friends. The current study used a new observational measure to evaluate associations between children’s frequency of verbal and behavioral problem solving during play with friends and the extent to which they completed a toy construction task. Sixty-eight 7-year-old friends from the Northeast United States were observed in 34 play dyads. Results revealed a significant positive association between problem solving and task completion with no significant gender or play set differences. Results provide initial evidence that observing friends’ shared problem solving behavior may have pedagogical implications for cognitive development in typical early childhood settings.

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)0.002
metaresearch head score (Gemma)0.006
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 score0.014
Threshold uncertainty score0.028

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.006
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0000.001
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 head0.050
GPT teacher head0.311
Teacher spread0.260 · 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

Citations7
Published2022
Admission routes1
Has abstractyes

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