MétaCan
Menu
Back to cohort
Record W2802827941

Increasing Gross Motor Skill Through Fundamental Skill Development Program

2018· article· en· W2802827941 on OpenAlexaboutno aff
Kuston Sultoni, Adang Suherman, Ricky Wibowo

Bibliographic record

VenueDOAJ (DOAJ: Directory of Open Access Journals) · 2018
Typearticle
Languageen
FieldSocial Sciences
TopicChild Development and Education
Canadian institutionsnot available
Fundersnot available
KeywordsGross motor skillMotor skillTest (biology)PsychologySample (material)Matching (statistics)Session (web analytics)Mathematics educationStatisticsMathematicsDevelopmental psychologyComputer science
DOInot available

Abstract

fetched live from OpenAlex

The aim of this study was to examine Canadian movement program called fundamental skill development programs implemented in Indonesia to increase children’s gross motor skills. By using a quasi-experiment, the matching-only pretest-posttest control group design, the sample was divided into two groups (N = 25 to the experimental group, N = 25 to the control group). The Gross motor skills were measured using the Test of Gross Motor Development - Second Edition TGMD - 2 Ulrich (2000). The experimental group was given training for eight weeks, 1 session per week and each session lasting 60 minutes. Statistical analysis was performed using paired sample t-test and independent sample t-test. The results showed that there is an increase in gross motor skills in the experimental group with P < 0.05. Then the results of independent sample t-test by comparing the Gain score between experimental group and the control group is significant difference with P < 0.05. It can be concluded that the fundamental skill development programs significant effect on gross motor skills in the first-grade student.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.013
Threshold uncertainty score0.025

Distilled classifier scores by category (both heads)

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)0.0020.000

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 head0.293
GPT teacher head0.609
Teacher spread0.316 · 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 source (direct Gemma or distilled Codex), 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

Citations3
Published2018
Admission routes1
Has abstractyes

Explore more

Same venueDOAJ (DOAJ: Directory of Open Access Journals)Same topicChild Development and EducationFrench-language works237,207