The Effects of Technology - Integrated Course to Enhance Writing Achievement of Grade 6 Students in Primary School at Guangdong
Notice bibliographique
Résumé
This study delves into the integration of technology in sixth-grade primary school English writing education. It aims to understand the complex relationship between technology-integrated teaching, students' writing achievements, and their perspectives on such teaching. The research objectives are 1) to investigate how technology-integrated teaching methods affect students' writing achievement and 2) to explore the aspects of the technology-integrated teaching method that lead students to form specific perspectives, and these perspectives, in turn, affect the further integration of technology in teaching. The study involves two classes of 12-year-old students with low academic achievement. One class serves as the experimental group, receiving technology-integrated teaching, while the other serves as the control group, receiving traditional instruction. Paired samples t-tests were utilized for data analysis over one semester. While the study uses a relatively small sample of 50 students per group, it provides valuable insights into the effects of technology-integrated teaching methods on writing achievement for low-achieving students. Future research with a larger and more diverse sample could help validate and extend these findings. However, the experimental design and focused nature of this study ensure that the results are still meaningful in understanding the impact of technology on student learning outcomes. The study found that 1) the overall of the result was the technology-integrated teaching method significant .05 and positively affects students' writing achievement compared to traditional methods, as evidenced by the experimental group's more substantial and stable score improvement,2) Students also formed diverse perspectives on technology-integrated teaching based on their academic levels, the overall of the result of students’perspective was Mean=3.39,Standard Deviation = 1.15, the teachers’ perspective was Mean= 3.59, Standard Deviation= 1.16. It claimed that the positive perspectives could drive further technology integration, but challenges such as course difficulty were also identified. To address these, it is recommended that teachers strengthen technological tool training, provide better guidance on internet resource use, and optimize course difficulty according to student feedback.
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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 | 0,001 | 0,002 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,001 | 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 ».