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Enregistrement W3146589631

Influence of BrainGym on Mathematical Achievement of Children

2014· article· en· W3146589631 sur OpenAlexvenueno aff
Sutoro

Notice bibliographique

RevueAsian Social Science · 2014
Typearticle
Langueen
DomaineNeuroscience
ThématiqueNeuroscience, Education and Cognitive Function
Établissements canadiensnon disponible
Organismes subventionnairesnon disponible
Mots-clésTest (biology)Mathematics educationPsychologyImpulse (physics)Control (management)Intervention (counseling)Treatment and control groupsSignificant differenceConstitutionComputer sciencePolitical scienceMathematics
DOInon disponible

Résumé

récupéré en direct d'OpenAlex

AbstractThe focus of this article is to determine the influence of BrainGym on mathematical achievement of children. The main purpose of this research is to optimize brain activity to better mark the changes in mathematical achievement. The research used a pre test - post test control group design. In the intervention program, the treatment group was given exercises such as training the owl, cross crawl, sit up, and cross-legged kick for as long as 30 minutes. Whereas the control group was not given any exercises. Training was given 3 times per week for as long as 8 weeks. Data analysis conducted found that there is a significant difference in the treatment group between pre test-post test while there is no significant difference in the control group pre test-post test results. Therefore, it can be concluded that brain exercises does influence mathematical achievements.Keywords: BrainGym, treatment group, calculation achievement1. IntroductionBased on the National Education constitution of 1945, all the people of Indonesia is to study without limitation of time or to pursue lifelong education. Nowadays, education is a major priority in Indonesia. However the development of education in Indonesia is still far away compared to developed country. From observations, intelligent students in classrooms, are able to do sports activities especially activities involving complex movements. Students' respond to what they see and listen from their teacher, it will be imitated or it will be done, proves that the work of the nervous system determines the result of muscular activities. According to Sutoro (2004), when the impulse goes through the skeletal muscle, it will cause muscle contraction on that part of the body. This is called physical activity.Coordination training is some activities combined to create a series of activities which is systematically compiled. In doing this activity, how the move or the movement is need to be thought first. Then, what is the next sequence of movement is. It is clear as Sidharta (1986) said that the motor cortex is part of the cerebrum dominated by pyramid cell, where this cell functions as the transmitter of psychomotor signals along the central nervous system. Research results shows that intelligence improvement is not only determined by total neuron, but also by total synapse. More synapse is formed, the neuron integration is better (Bundah, 2004).While Dennison and Denisson (2003) said that brain consisted of a few components, generally they are called main brain (cerebral cortex/cerebrum), lateral brain, brain stem, front brain (frontal lobes), and mid brain. Each of them functions differently. Cerebrum and midbrain functions to think abstractly and react to emotional information. Lateral brain functions for psychomotor skill; back brain (occipital) and front brain (frontal lobe) functions is to give attention. According to Maerzyda (2004), frontal lobe is responsible for the ability to do planning, movement, solve problems, and reasoning. Each part of the brain can be optimized by BrainGym training. The movements in BrainGym training are movements usually done by students when they are playing, or doing any sport, while movement orientation in BrainGym is coordination training, which is the combination of eyes movement, hands movement, and body movement.Research by Anderson (1996) in Sutoro (2004) on mouse trained with the tasks of psychomotor skill in over 30 days, found that there are more synapse in the brain of the trained mouse than in the untrained mouse. Researchers in Baylor College of Medicine at the University of Illinois in Urbana-Campaign, found that when the student is seldom invited to play, his/her brain development is 20% to 30% less than the children who constantly play with peers. Research using laboratories animal found that baby mouse grown in a box with all toys shows complexity of behavior compared to baby mouse put in a box with no toys. …

Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.

Comment cette classification a été obtenuedéplier

Prédiction machine sur la base complète

Imitation des enseignants

Ni prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.

score de la tête « metaresearch » (Codex)0,001
score de la tête « metaresearch » (Gemma)0,002
Version: metacan-v3-hybrid-931329e0061cStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Observationnel · Signal consensuel: aucune
GenreSignal candidat: Empirique · Signal consensuel: Empirique
Score de désaccord entre enseignants0,005
Score d'incertitude au seuil0,016

Scores du classifieur distillé par catégorie (deux têtes)

CatégorieCodexGemma
Métarecherche0,0010,002
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0000,000
Bibliométrie0,0010,000
Études des sciences et des technologies0,0000,000
Communication savante0,0000,000
Science ouverte0,0000,001
Intégrité de la recherche0,0000,001
Charge utile insuffisante (le modèle a refusé de juger)0,0050,000

Scores machine (provisoires)

Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.

Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.

Tête enseignante Opus0,018
Tête enseignante GPT0,291
Écart entre enseignants0,274 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découle

Classification

machine, non validée

Prédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.

Les modèles n’ont appliqué aucune catégorie : rien dans la taxonomie ne correspondait à ce travail.
Devis d'étudeObservationnel
Domainenon disponible
GenreEmpirique

Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».

En bref

Citations0
Publié2014
Routes d'admission1
Résumé présentoui

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