Comparison of the effectiveness of two storytelling methods through visualization and pantomime on emotional dyslexia of children with hearing problems
Notice bibliographique
Résumé
Background and Aim: The present study was conducted with the aim of comparing the effectiveness of two storytelling methods through visualization and pantomime on the emotional dyslexia of students with hearing problems. Methods: The research is of an applied type and an experimental research design and in the form of a pre-test-post-test with a control group. The statistical population of this research includes all deaf female students aged 7-14 years old in District 20 of Tehran who were studying in 1400-1401. The sample used was selected based on the opinion and purpose of the sampling method. 24 students from 14 to 7 years old were selected in an accessible and targeted manner and randomly divided into three groups (8 people in the group of storytelling training through mental imagery, 8 people in the group under training with pantomime and 8 people in the control group) were replaced. In this research, the analysis of emotional dyslexia of Toronto (Bagby, Parker and Taylor, 1994) was used. Results: In the research, it is reported that the deviation of the standards in the pre-test and post-test stages is reported in the experimental and control groups. And you can see that emotional ataxia has decreased in the post-test of the experimental groups. It means that both methods in identification were about the same size. But there was a significant difference between the experimental groups and the control group, which shows that the narration through both methods and pantomime over visualization has been effective in diagnosing the treatment and has become a reduction. Conclusion: The results showed that the difference between the experimental groups of storytelling through illustration and pantomime is not significant in the difficulty in identifying emotions. This means that both methods have been equally effective in the difficulty of identifying emotions. But there was a significant difference between the experimental groups and the control group, which shows that storytelling through both visualization and pantomime methods has been effective and effective on the difficulty in identifying emotions and has led to its reduction.
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 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| 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 ».