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Record W4412883273 · doi:10.3389/frai.2025.1611534

Artificial intelligence-enhanced assessment of fundamental motor skills: validity and reliability of the FUS test for jumping rope performance

2025· article· en· W4412883273 on OpenAlexaff
Hubert Makaruk, Jared M. Porter, E. Kipling Webster, Beata Makaruk, Paweł Tomaszewski, Marta Nogal, Łukasz Sobański, Bartosz Molik, Jerzy Sadowski

Bibliographic record

VenueFrontiers in Artificial Intelligence · 2025
Typearticle
Languageen
FieldPsychology
TopicChildren's Physical and Motor Development
Canadian institutionsArtificial Intelligence in Medicine (Canada)
Fundersnot available
KeywordsCompetence (human resources)PsychologyMotor skillPhysical educationTest (biology)Developmental psychologyApplied psychologyMedical educationMathematics educationMedicineSocial psychology

Abstract

fetched live from OpenAlex

Introduction: Fundamental motor skills (FMS) are foundational for lifelong physical activity and talent development. However, their development is often overlooked in favor of sport-specific outcomes in physical education (PE). This study aimed to evaluate FMS proficiency among students enrolled in traditional and school-based sport PE programs and explore implications for early specialization and motor competence. Methods: = 2,238) using the validated Fundamental Motor Skills in Sport (FUS) test. Participants were grouped based on enrollment in traditional PE or school-based sport PE programs. Proficiency was classified into four levels based on mastery across six motor tasks. Results: The majority of students in both groups failed to meet the basic FMS proficiency threshold. Specifically, 72% of boys and 77% of girls in sport PE programs were below elementary proficiency, compared to 90% of boys and 92% of girls in traditional PE. While sport PE students outperformed their peers, significant deficits remained. Gender differences showed boys had advantages in object control skills, while girls performed better in coordination-oriented tasks. Discussion: Both traditional and sport PE programs fall short of supporting adequate FMS development, potentially due to overemphasis on early specialization and lack of instructional support for motor competence. These findings underscore the need for curricular reforms and targeted teacher training to prioritize broad motor skill development and promote long-term participation in physical activity.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.576
Threshold uncertainty score0.821

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 studies0.0000.001
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 head0.032
GPT teacher head0.332
Teacher spread0.300 · 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

Citations1
Published2025
Admission routes1
Has abstractyes

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