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Record W4247686326 · doi:10.31234/osf.io/hmsd2

“Wow, I did it!”: Unexpected success increases preschoolers’ exploratory play on a later task

2020· preprint· en· W4247686326 on OpenAlexaff
Tiffany Doan, Amanda Castro, Elizabeth Bonawitz, Stephanie Denison

Bibliographic record

Venuenot available
Typepreprint
Languageen
FieldSocial Sciences
TopicChild Development and Digital Technology
Canadian institutionsUniversity of Waterloo
Fundersnot available
KeywordsTask (project management)PsychologyPsychological interventionDevelopmental psychologyExploratory researchCognitive psychologyPoint (geometry)Social psychology

Abstract

fetched live from OpenAlex

Exploratory play supports children’s learning, but the factors that influence play are not fully identified. Here, we investigate whether experiencing an unexpected success on an initial task influences children’s exploration on a subsequent task. In Experiment 1 (N=72), we found that when 4-year-olds successfully completed a puzzle that they were told is hard (compared to when they were told that the puzzle is easy or at baseline when no difficulty information was provided), they spent more time exploring and attempted more different interventions with a subsequent novel toy. This suggests that an unexpected success influences children’s subsequent exploration. In Experiment 2 (N=48) we examined two alternative interpretations of the Experiment 1 findings: that children carried over difficulty assumptions from task 1 to the new toy or that children had unused attentional resources. Children completed the puzzle and then were told that the novel toy itself was either easy or hard. Children did not explore longer or more variably across these conditions, providing evidence against these alternative accounts. Our findings point to an important role for past playful experiences: unexpected success on one task motivates children to explore longer and with more breadth on another task.

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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.438
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.001

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 head0.039
GPT teacher head0.296
Teacher spread0.257 · 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
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

Citations3
Published2020
Admission routes1
Has abstractyes

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