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Record W4367300638 · doi:10.5539/jel.v12n3p101

The Effects of Rhythm and Dance Games on Aggression in Students with Mild Mental Disabilities

2023· article· en· W4367300638 on OpenAlexvenueno aff
Ali Kemal Taşkın

Bibliographic record

VenueJournal of Education and Learning · 2023
Typearticle
Languageen
FieldHealth Professions
TopicSports and Physical Education Research
Canadian institutionsnot available
Fundersnot available
KeywordsAggressionDancePsychologyTest (biology)RhythmDevelopmental psychologyClinical psychologyMedicine

Abstract

fetched live from OpenAlex

The aim of this study is to examine the effects of rhythm and dance on the aggression levels of students with mild mental disabilities. The sample group of the study consists of 40 students with mild mental disability, 20 of whom are in the experimental group and 20 in the control group, who continue their education in schools affiliated with the Kilis Provincial Directorate of National Education. Buss-Perry’s (1992) aggression scale was applied as pre-test and post-test to both groups, and rhythm and dance training was given to the experimental group for 2 hours, 2 days a week for 8 weeks. In the analysis of the data obtained, frequency and percentage analysis were performed by using the SPSS 22.0 program, and dependent and independent t-test was used in the analysis of the pre-test and post-test data. No significant results were obtained in the pre-test scores of the experimental and control groups (p > 0.05). In the evaluation made between the experimental group and the control group, a significant result was reached in the post-test scores in favor of the experimental group (p < 0.05). In conclusion, based on the data obtained, we can say that rhythm and dance games positively reduce the aggression levels of children with mild mental disabilities.

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)0.001
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 score0.044
Threshold uncertainty score0.235

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
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)0.0000.000

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 head0.031
GPT teacher head0.480
Teacher spread0.450 · 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
Published2023
Admission routes1
Has abstractyes

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