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Record W3004197842 · doi:10.5539/jel.v9n1p244

The Effect of Recreative Purpose Modern and Traditional Archery Education on Attention Parameters in Adolescents

2020· article· en· W3004197842 on OpenAlexvenueno aff
Ferhat ÜSTÜN, Erdal Tasgin

Bibliographic record

VenueJournal of Education and Learning · 2020
Typearticle
Languageen
FieldPsychology
TopicSport Psychology and Performance
Canadian institutionsnot available
Fundersnot available
KeywordsRecreationPsychologyTest (biology)NormalityData collectionApplied psychologyDevelopmental psychologyClinical psychologySocial psychologyStatisticsMathematics

Abstract

fetched live from OpenAlex

This study aims to investigate the effect of recreational archery exercise on attention levels of children aged 9–13 years. 20 girls and 20 boys who participated in archery training for 4 weeks held in archery areas of special sports centers in Konya Province. The participants were given archery training 60 minutes a day, 3 days a week for 4 weeks. They participated in the attention test before and after the training. In this study, Bourdon attention test was applied as a data collection tool. The normality test was performed to determine whether the data fit the normal distribution and the data were found to be suitable for parametric tests. In order to determine the difference between the before and after of the test, paired samples t-test was applied. As a result of the study, it was revealed that the attention levels of the participants increased in respect of both total scores and comparisons according to variables (p < 0.001). In this respect, it can be suggested that archery activities will have a positive effect on the attention development of 9–13 age group children. When the general literature is examined, it can be stated that attention levels of children participating in sports and exercise-based recreational activities are positively affected.

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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.353
Threshold uncertainty score0.185

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
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 head0.040
GPT teacher head0.344
Teacher spread0.304 · 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

Citations11
Published2020
Admission routes1
Has abstractyes

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