The Development of a Physical Education Teaching Model in the Covid - 19 Situation Based on the Concept of Active Learning with Digital Technology Media of Students in the Field of Physical Education and Health, Faculty of Education Thailand National Sports University Chon Buri Campus
Notice bibliographique
Résumé
The objectives of this research were: 1. to develop a teaching model of physical education after the COVID-19 situation based on the concept of proactive learning in combination with digital technology media; 2. to compare the students' proactive learning behavior with digital technology media between the experimental group and the control group 3. Assess the students' higher thinking between the experimental group and the control group 4. Assess the satisfaction of students who manage learning by using a proactive learning management model and digital technology media. Affecting the effect of using the model the sample group used in the interview research there were 5 professors of the Faculty of Education and 15 students. The sample group that used the model to teach students was 30 students, divided into an experimental group of 15, and students trained by students of 300 people, a control group of 15 and students who were trained. 300 teaching students by random sampling. Tools include Document analysis record form interview questions Questionnaire on learning management conditions Program to develop faculty members to measure readiness in learning management Learning Behavior Assessment and Learning Satisfaction Questionnaire Qualitative data were analyzed by content analysis. Quantitative data analysis using basic statistics such as percentage, mean, standard deviation variance the differences between the mean were compared using the covariance analysis (ANCOVA) t-test statistic and the efficiency was analyzed. Process/efficiency of results. The results showed that 1. Physical education teaching style in the situation of COVID-19 Based on the concept of proactive learning with digital technology media there are 6 steps in learning management (PODARE). 2. Comparison of proactive learning behavior with digital technology media the experimental group was significantly higher than the control group at the .01 level. 3. The results of the assessment of advanced thinking of the experimental group of students who received learning management according to the proactive learning management model with digital technology media. Have a good high thinking score. Accounted for 43.83% 4. The results of the satisfaction assessment of the students who participated in the development of the model were of the opinion that the model made the students more clear and clear about proactive learning management with digital technology media. When students change the way they organize learning and activities in the classroom change, students change their learning behavior. Make students have more participation behavior in class
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Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi 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.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,003 | 0,003 |
| 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 | 0,001 | 0,001 |
| Communication savante | 0,001 | 0,001 |
| Science ouverte | 0,001 | 0,002 |
| Intégrité de la recherche | 0,001 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,002 | 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 source (Gemma direct ou Codex distillé), 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 ».