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Record W2136477971 · doi:10.1002/icd.470

Effects of task difficulty on sibling teaching in middle childhood

2006· article· en· W2136477971 on OpenAlexafffund
Nina Howe, Marie‐Hélène Brody, Holly Recchia

Bibliographic record

VenueInfant and Child Development · 2006
Typearticle
Languageen
FieldSocial Sciences
TopicParental Involvement in Education
Canadian institutionsConcordia University
FundersSocial Sciences and Humanities Research Council of CanadaNatural Sciences and Engineering Research Council of CanadaSociety for Research in Child Development
KeywordsSiblingPsychologyTask (project management)Developmental psychologyCognitionClass (philosophy)Mathematics education

Abstract

fetched live from OpenAlex

Abstract Teaching styles were investigated in 28 middle‐class sibling dyads (older sibling M age = 8.2 yrs; younger sibling M age =5.11 yrs) using two sets of block design tasks (five easy; five hard). Older siblings employed a greater number of strategies (i.e. physical demonstrations, scaffolding, corrective feedback) in the hard than in the easy tasks, thus demonstrating the ability to adjust teaching strategies according to task difficulty. Teachers also employed more frequent strategies when learners were younger indicating that they may be sensitive to developmental differences. In the hard tasks, learners responded positively to teacher guidance, but were also more likely to reject the teacher's help, perhaps demonstrating responsibility for their own learning. Findings are discussed in light of current social‐cognitive approaches highlighting the important roles of both teacher and learner during episodes of sibling teaching in middle childhood. Copyright © 2006 John Wiley & Sons, Ltd.

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)0.009
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 score0.003
Threshold uncertainty score0.009

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.009
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.001
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0000.000
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 head0.013
GPT teacher head0.263
Teacher spread0.250 · 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

Citations31
Published2006
Admission routes2
Has abstractyes

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