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Record W4200503146 · doi:10.1080/00222895.2021.2016573

Optimizing Motor Learning: Difficulty Manipulation Combined with Feedback- Frequency Enhance Under-Time-Pressure Fine-Motor-Coordination Skill Acquisition and Retention

2021· article· en· W4200503146 on OpenAlex
Yousri Elghoul, Fatma Bahri, Khaled Trabelsi, Hamdi Chtourou, Mohamed Frikha, Cain C. T. Clark, Jordan M. Glenn, Nicola Luigi Bragazzi, Nizar Souissi

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueJournal of Motor Behavior · 2021
Typearticle
Languageen
FieldNeuroscience
TopicMotor Control and Adaptation
Canadian institutionsYork University
Fundersnot available
KeywordsKnowledge of resultsMotor learningTask (project management)PsychologyMotor skillCognitionConsistency (knowledge bases)Working memoryDreyfus model of skill acquisitionTest (biology)AudiologyCognitive psychologyPhysical medicine and rehabilitationDevelopmental psychologyComputer scienceArtificial intelligenceMedicineEngineeringNeuroscience

Abstract

fetched live from OpenAlex

Improving acquisition and retention of new motor skills is of great importance. This study investigated the effects of progressive task difficulty manipulation (TD), combined with varying knowledge of results frequencies (KR) on performance accuracy and consistency when learning novel fine motor coordination tasks, and examined relationships between novel fine motor task performance and executive function (EF), working memory (WM), and perceived difficulty (PD). Thirty-six, right-handed, novice physical-education students (age = 10.72 ± 0.89 years) participated; participants were separated into three groups, receiving varying KR frequency (100%KR, 50%KR, and 33%KR). For each group, distance to the target was increased progressively (2 m, 2.37 m, and 3.56 m) to obtain three difficulty levels. We assessed performance during test sessions (pretest, post-test, Retention1 and Retention2) under free (FC) and time pressure (TPC) conditions. Results revealed that under FC, 100%KR improved significantly. Results revealed significant linear improvements in accuracy for 50%KR and 33%KR under TPC. New findings indicate that the association between TD and KR (50%KR) may provide more appropriate cognitive loads compared to 33%KR and 100%KR groups. These have implications for practitioners because, while strategies are clearly necessary for improving learning, the efficacy of the process appears to be based on the characteristics of the learners.

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.

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)0.000
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.823
Threshold uncertainty score0.856

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
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 head0.020
GPT teacher head0.253
Teacher spread0.233 · 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