Notice bibliographique
Résumé
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 distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,001 | 0,002 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,001 |
| Études des sciences et des technologies | 0,000 | 0,002 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 0,000 |
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.
score_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 découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».