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Record W1959649435 · doi:10.3389/fpsyg.2015.01378

Manipulating target size influences perceptions of success when learning a dart-throwing skill but does not impact retention

2015· article· en· W1959649435 on OpenAlexaff
Nicole T. Ong, Keith R. Lohse, Nicola J. Hodges

Bibliographic record

VenueFrontiers in Psychology · 2015
Typearticle
Languageen
FieldNeuroscience
TopicMotor Control and Adaptation
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsThrowingPsychologyMotor learningTask (project management)Motor skillPerceptionDreyfus model of skill acquisitionCognitive psychologyApplied psychologySocial psychologyDevelopmental psychology

Abstract

fetched live from OpenAlex

Positive feedback or experiences of success during skill acquisition have been shown to benefit motor skill learning. In this study, our aim was to manipulate learners' success perceptions through a minor adjustment to goal criterion (target size) in a dart-throwing task. Two groups of novice participants practiced throwing at a large (easy) or a small (difficult) target from the same distance. In reference to the origin/center of the target, the practice targets were alike in objective difficulty and indeed participants in both groups were not different in their objective practice performance (i.e., radial error from the center). Although the groups experienced markedly different success rates, with the large target group experiencing more hits and reporting greater confidence (or self-efficacy) than the small target group, these practice effects were not carried into longer-term retention, which was assessed after a 1-week delay. For success perceptions to moderate or benefit motor learning, we argue that unambiguous indicators of positive performance are necessary, especially for tasks where intrinsic feedback about objective error is salient.

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)0.001
Version: codex-gemma-dda1882f352aValidation 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 score0.280
Threshold uncertainty score0.485

Codex and Gemma teacher scores by category

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

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 head0.043
GPT teacher head0.333
Teacher spread0.290 · 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.

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

Citations33
Published2015
Admission routes1
Has abstractyes

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