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Record W4387703407 · doi:10.1038/s41539-023-00190-x

Beware the myth: learning styles affect parents’, children’s, and teachers’ thinking about children’s academic potential

2023· article· en· W4387703407 on OpenAlexaff
Xin Sun, O. P. Norton, Shaylene E. Nancekivell

Bibliographic record

Venuenpj Science of Learning · 2023
Typearticle
Languageen
FieldPsychology
TopicLearning Styles and Cognitive Differences
Canadian institutionsUniversity of ManitobaUniversity of British Columbia
Fundersnot available
KeywordsAffect (linguistics)MythologyPsychologyDevelopmental psychologyPedagogyMathematics educationLiteratureArtCommunication

Abstract

fetched live from OpenAlex

Three experiments examine how providing learning style information (a student learns hands-on or visually) might influence thinking about that student's academic potential. Samples were American and predominately white and middle-class. In Experiment 1, parents (N = 94) and children (N = 73, 6-12 years) judged students who learn visually as more intelligent than hands-on learners. Experiment 2 replicated this pattern with parents and teachers (N = 172). In Experiment 3 (pre-registered), parents and teachers (N = 200) predicted that visual learners are more skilled than hands-on learners at "core" school subjects (math/language/social sciences, except science), whereas, hands-on learners were skilled at non-core subjects (gym/music/art). Together, these studies show that learning style descriptions, resultant of a myth, impact thinking about children's intellectual aptitudes.

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)0.003
metaresearch head score (Gemma)0.012
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 score0.017

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.012
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0020.001
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.015
GPT teacher head0.310
Teacher spread0.295 · 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

Citations21
Published2023
Admission routes1
Has abstractyes

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