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Record W4389747692 · doi:10.1123/jtpe.2023-0038

A Modified Delphi Research Study on Fundamental Movement Skill Complexity for Teaching and Learning Physical Literacy

2023· article· en· W4389747692 on OpenAlexaff
Homa Rafiei Milajerdi, Anna Thacker, Mahboubeh Ghayour Najafabadi, Christoph Clephas, Larry Katz

Bibliographic record

VenueJournal of Teaching in Physical Education · 2023
Typearticle
Languageen
FieldPsychology
TopicChildren's Physical and Motor Development
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsLikert scaleDelphi methodPsychologyPhysical educationDelphiMathematics educationPoint (geometry)AffordanceOrienteeringMovement (music)Computer scienceApplied psychologyMultimediaCognitive psychologyMathematicsArtificial intelligenceDevelopmental psychology

Abstract

fetched live from OpenAlex

Purpose : To establish a consensus on the complexity of 16 fundamental movement skills (FMS). Initially, complexity was defined as how difficult it would be to teach FMS to children and for the children to learn them. Method : The study was conducted using a modified Delphi method and a mobile application called Move Improve® to showcase video demonstrations of 16 FMS. Six experts discussed and rated the complexity of each FMS using a 5-point Likert scale until a 75% consensus was obtained during three rounds. Result : Dribble was rated as the most complex (average five) and run as the least (average one). The highest percentage of consensus at 100% was obtained for dribble, overhead throw, run, and skip during Round 3. Conclusion : Eye–hand or eye–foot coordination, laterality, and the environment were deemed as the most influential factors when rating the complexity of FMS.

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)0.003
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesResearch integrity
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.808
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.002
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 head0.101
GPT teacher head0.477
Teacher spread0.376 · 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.

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

Citations0
Published2023
Admission routes1
Has abstractyes

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