Shifting Pedagogies during COVID-19: The Professional Learning of Teacher Educators regarding Digital Technology in a Time of Crisis and Change
Notice bibliographique
Résumé
The COVID-19 crisis that began in March 2020 presented teacher education with many challenges, among them the urgent need to support teacher educators with the sudden move to remote teaching. Teacher educators immediately started rethinking their pedagogy for a new digital classroom environment as universities rushed to provide overnight supports to help with this transition. Empirical research on how teacher educators have navigated their professional roles during this period of uncertainty is limited. There is also limited research on the professional learning of teacher educators, particularly in the area of digital technology. The aim of this study was to explore teacher educators’ shifts in views and pedagogy using digital technology as they adapted to teaching in an online environment. Investigating those shifts also required examining teacher educators’ backgrounds and experiences with digital technology and their professional learning during the COVID-19 pandemic. In this qualitative multi-case study, I explored the experiences of six teacher educators within a graduate teacher education program in a large urban university in Canada. Each participant took part in two semi-structured interviews and described teaching and learning artifacts that reflected a change in their pedagogy. Three key findings emerged from this study. First, the COVID-19 pandemic served as a catalyst for change in teacher educators’ enacted pedagogies. Second, teacher educators displayed heightened responsivity in two ways. They placed teacher candidate learning at the center of the online classroom and offered flexible and accessible learning experiences. Also, teacher educators’ changes in pedagogy were frequently shaped by inequities exacerbated by the pandemic. Lastly, study participants discussed different possibilities for teacher educator pedagogies, with an emphasis on flexible approaches to teaching and learning, a changed role in an online setting, and digital technology integration. Implications for teacher educators include the need to engage in ongoing learning, understand the role and uses of digital technology in the teacher education classroom, and recognize their ongoing responsibility to foreground equity and social justice in their teaching. Thus, teacher education programs must include formal and informal structures and resources that support the individualized and diverse professional learning of teacher educators.
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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 | 0,008 | 0,017 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,001 |
| Méta-épidémiologie (sens large) | 0,001 | 0,000 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,035 | 0,033 |
| Communication savante | 0,014 | 0,008 |
| Science ouverte | 0,002 | 0,018 |
| Intégrité de la recherche | 0,005 | 0,011 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,002 | 0,001 |
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 ».