The post‐COVID‐19 future of digital learning in higher education: Views from educators, students, and other professionals in six countries
Pourquoi ce travail est dans la base
Une base qui oublie comment elle a trouvé un travail ne peut pas être vérifiée. Voici les voies qui ont admis celui-ci.
Notice bibliographique
Résumé
Abstract Predictions about the post‐pandemic future of digital learning vary among higher education scholars. Some foresee dramatic, revolutionary change while others speculate that growth in educational technology will be buffeted both by modest expansion and unevenness. To this debate we contribute evidence from four groups across six countries on four continents: college and university educators ( n = 281), students ( n = 4243), senior administrators ( n = 15), and instructional design specialists ( n = 43). Our focus is on the future of digital learning after the pandemic‐induced pivot to emergency remote instruction. Using data from interviews and self‐administered questionnaires, our findings reveal a high degree of congruency between respondent groups, with most envisioning more blended/hybrid instruction post‐pandemic and some modest increases in fully online courses. Student opinion is more sceptical about future change than within the other groups. Among respondents in all groups there is little expectation for a full‐blown, revolutionary change in online or digital learning. Practitioner notes What is already known about this topic Digital learning has been growing in higher education, although a digital disconnect continues whereby the availability of educational technology exceeds its application to learning. Expectations regarding technology‐mediated learning post‐COVID‐19 are mixed, hampering planning for the future. Hesitancy about teaching or taking courses with some or full online components persists. What this paper adds A strong majority of respondents in higher education foresee the most growth in blended/hybrid forms of digital learning post‐COVID‐19. A solid percentage, between about two‐thirds and three‐quarters of faculty and students, envision learners and instructors taking or teaching more fully online courses post‐pandemic. A strong congruency exists between faculty, students, senior administrators, and instructional design professionals in their ranking of scenarios for the future of digital learning. Implications for practice and/or policy Educational technology in higher learning will not return to a pre‐COVID‐19 normality—if a pre‐COVID‐19 ‘normal’ could even be defined. As post‐pandemic institutional planning unfolds, it is important to reflect experiences and incorporate insights of instructors, students, and instructional designers. Successfully building on these insights, where more blended/hybrid learning is foreseen, requires a thoughtful integration of face‐to‐face learning and educational technology.
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.
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 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,003 | 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 découle