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Record W2380641440 · doi:10.1177/0031512516640676

Accuracy of Subjective Performance Appraisal is Not Modulated by the Method Used by the Learner During Motor Skill Acquisition

2016· article· en· W2380641440 on OpenAlexaff
Jae T. Patterson, Matthew McRae, Sharon Lai

Bibliographic record

VenuePerceptual and Motor Skills · 2016
Typearticle
Languageen
FieldNeuroscience
TopicMotor Control and Adaptation
Canadian institutionsBrock University
Fundersnot available
KeywordsTask (project management)Knowledge of resultsMotor skillMotor learningPsychologyTest (biology)Movement (music)Performance appraisalDreyfus model of skill acquisitionPhysical medicine and rehabilitationControl (management)Movement controlComputer scienceDevelopmental psychologyMedicineArtificial intelligenceEngineering

Abstract

fetched live from OpenAlex

The present experiment examined whether the method of subjectively appraising motor performance during skill acquisition would differentially strengthen performance appraisal capabilities and subsequent motor learning. Thirty-six participants (18 men and 18 women; M age = 20.8 years, SD = 1.0) learned to execute a serial key-pressing task at a particular overall movement time (2550 ms). Participants were randomly separated into three groups: the Generate group estimated their overall movement time then received knowledge of results of their actual movement time; the Choice group selected their perceived movement time from a list of three alternatives; the third group, the Control group, did not self-report their perceived movement time and received knowledge of results of their actual movement time on every trial. All groups practiced 90 acquisition trials and 30 no knowledge of results trials in a delayed retention test. Results from the delayed retention test showed that both methods of performance appraisal (Generate and Choice) facilitated superior motor performance and greater accuracy in assessing their actual motor performance compared with the control condition. Therefore, the processing required for accurate appraisal of performance was strengthened, independent of performance appraisal method.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.232
Threshold uncertainty score0.434

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
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 head0.017
GPT teacher head0.277
Teacher spread0.260 · 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 designBench or experimental
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

Citations6
Published2016
Admission routes1
Has abstractyes

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