Empowering Pre-Service Teachers for the Digital Transformation of Education from New Normal to Next Normal
Notice bibliographique
Résumé
The purposes of research were to comparison of digital technology used for the instructional management during the Covid-19 pandemic during the New Normal period and the endemic Covid-19 during Next Normal period adopted by pre-service teachers; and to develop the landscape of digital technology used for instructional management during the New Normal and the Next Normal periods adopted by pre-service teachers. The participants included 400 pre-service teachers. The research tool was an online questionnaire. The data were analyzed by mean and standard deviation. The results showed the comparison of digital technology for the instructional management in the New Normal and the Next Normal as follows. Regarding the New Normal, the finding were: (a) some websites and applications such as Google Meet, Line, YouTube, and Facebook Messenger were used to communication with students; (b) some websites and applications, namely Google classroom, MS Teams, Moodle, and Thaimooc were used to send and receive student’s works; (c) some learning management systems, namely Google classroom, MS Teams, Moodle, and Thaimooc were used; (d) some digital media libraries such as YouTube, Trueplookpanya, DLTV, Satellite Distance Education Foundation, SciMath Knowledge Library, and IPST were used; (e) some online measurement and evaluation tools such as Google Forms, Kahoot, Quizizz, and Microsoft Forms were used and (f) some teaching guidelines and tools, like Video assignment, General Activities, and Attendance be used later. Regarding the Next Normal, the finding were: (a) some websites and applications were used to communicate with students, including Line, Facebook, Messenger, Youtube and Google classroom; (b) some websites and applications like Line, Facebook Messenger, YouTube, and Google classroom were used to send and receive student’s assignments; (c) some learning management systems like Google classroom, MS Teams, Moodle, Edmodo, and Thaimooc were also used; (d) some digital media libraries like Google classroom, YouTube, Trueplookpanya, OBEC Content Center - NEDA, and DLTV (Satellite Distance Education Foundation) were also helpful; (e) some online measurement and evaluation tools like Google Forms, Kahoot, Quizizz, and Microsoft Forms were also used; and (f) some teaching guidelines and tools like Assignment, Announcements and Update, Student Support, and Grade Book will also be used later. The digital technology landscape consists of 6 parts: (1) the websites and applications used for communication with students; (2) the websites and applications provides for students to submit their assignments; (3) the learning management systems; (4) the digital media libraries; (5) the online measurement and evaluation tools; and (6) the teaching guidelines and tools to be used later.
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 | 0,001 |
| 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 | 0,001 |
| 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 ».