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Record W4282919936 · doi:10.1016/j.jecp.2022.105466

Learning science concepts through prompts to consider alternative possible worlds

2022· article· en· W4282919936 on OpenAlexafffund
Angela Nyhout, Patricia A. Ganea

Bibliographic record

VenueJournal of Experimental Child Psychology · 2022
Typearticle
Languageen
FieldPsychology
TopicChild and Animal Learning Development
Canadian institutionsUniversity of Toronto
FundersSocial Sciences and Humanities Research Council of CanadaNatural Sciences and Engineering Research Council of Canada
KeywordsCounterfactual thinkingPsychologyCounterfactual conditionalComprehensionControl (management)Cognitive scienceComputer scienceSocial psychologyArtificial intelligence

Abstract

fetched live from OpenAlex

We investigated whether prompting children to think counterfactually when learning a complex science concept (planetary habitability) would promote their learning and transfer. In Study 1, children (N = 102 6- and 7-year-olds) were either prompted to think counterfactually about Earth (e.g., whether it is closer to or farther from the sun) or prompted to think about examples of different planets (Venus and Neptune) during an illustrated tutorial. A control group did not receive the tutorial. Children in the counterfactual and examples groups showed better comprehension and transfer of the concept than those in the control group. Moreover, children who were prompted to think counterfactually showed some evidence of better transfer to a novel planetary system than those who were prompted to think about different examples. In Study 2, we investigated the nature of the counterfactual benefit observed in Study 1. Children (N = 70 6- and 7-year-olds) received a tutorial featuring a novel (imaginary) planet and were either prompted to think counterfactually about the planet or prompted to think about examples of additional novel planets. Performance was equivalent across conditions and was better than performance in the control condition on all measures. The results suggest that prompts to think about alternative possibilities-both in the form of counterfactuals and in the form of alternative possible worlds-are a promising pedagogical tool for promoting abstract learning of complex science concepts.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.368
Threshold uncertainty score0.994

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0070.000

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 head0.039
GPT teacher head0.422
Teacher spread0.382 · 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

Citations2
Published2022
Admission routes2
Has abstractyes

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