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Record W4402627083 · doi:10.1080/02640414.2024.2404777

The impact of an early childhood educator e-Learning course on young children’s fundamental movement skills: A cluster randomized controlled trial

2024· article· en· W4402627083 on OpenAlexafffund
Aidan Loh, Matthew Bourke, Kendall Saravanamuttoo, Brianne A. Bruijns, Patricia Tucker

Bibliographic record

VenueJournal of Sports Sciences · 2024
Typearticle
Languageen
FieldPsychology
TopicChildren's Physical and Motor Development
Canadian institutionsWestern University
FundersWestern University
KeywordsMovement (music)PsychologyCourse (navigation)Motor skillEarly childhoodDevelopmental psychologyRandomized controlled trialEarly childhood educationCluster randomised controlled trialMedicineIntervention (counseling)Physics

Abstract

fetched live from OpenAlex

Early childhood educators (ECEs) are ideally positioned to support the development of children’s fundamental movement skills (FMS). However, ECEs have little specialised training to support the development of FMS in young children. This study aimed to assess the impact of an e-Learning course on the FMS of preschool-aged children. 145 Preschool-aged children and 42 ECEs from 12 childcare centres participated in the study. ECEs in the experimental group were asked to complete the e-Learning course. A subsample of children (n = 48) was objectively assessed using the Test of Gross Motor Development 3rd Edition (TGMD-3). Additionally, parents of all participating children reported perceptions of their child’s FMS to understand if they knew how well their child was progressing. Findings showed a significant increase in TGMD-3 assessed locomotor skills from baseline to follow-up in the intervention group compared to the control group and total FMS but not objective control skills. Parent-reported FMS increased in the intervention group for all locomotor, object control skills, and total FMS. However, the intervention effect for all three measurements was not significant. The results from this study highlight the potential utility of online professional development for ECEs as an approach to improving young children’s 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)0.004
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: Randomized trial · Consensus signal: Randomized trial
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.448
Threshold uncertainty score0.425

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
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 head0.006
GPT teacher head0.304
Teacher spread0.298 · 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 designRandomized trial
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

Citations4
Published2024
Admission routes2
Has abstractyes

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