Student Experiences of Emergency Remote Learning and Teaching During COVID-19
Notice bibliographique
Résumé
This study aimed to explore and understand the University of Cape Town student perceptions and lived experiences of Emergency Remote Teaching and Learning (ERTL) during COVID-19. COVID-19 is a communicable disease instigated by a novel virus (SARS CoV-2 virus). After the inevitable subsequent national lockdown of South Africa, the university placed ERTL measures in place for the second quarter of the first semester to curb the impact of the virus on its students while also enabling learning and teaching activities to continue remotely. ERTL meant that learning and teaching activities were ‘rapidly' shifted from face-to-face learning to remote learning. This study reports on the 707 students who responded to an online survey while engaged in their online courses. The Substitution, Augmentation, Modification, and Redefinition (SAMR) and Andersons' Online Learning Model were used to engage with students on the use of technology that enabled their interaction with lecturers, each other, learning and teaching activities, and other remote learning resources. Understanding the student experiences was achieved through a mixed-method study approach that involved undergraduate and postgraduate students. The Google form online surveys, with both open and closed ended questions with some using the 5-point Likert scale ratings, were distributed using social media platforms and university email system to students in order to collect the data. MAXQDA and Excel software were later utilised to analyse and code the data. Findings for this study indicate that the ERTL experience of the participants during the COVID-19 pandemic presented both opportunities and barriers. Some of the perceived opportunities by students were flexibility and convenience, pedagogical improvements, time saving, self-directed learning (working anytime they want and creating and managing their working schedule), and spending time with family. Interestingly enough, some of these benefits turned out to be challenges for some of the students. Hence, some of the barriers students perceived were distractions, internet connectivity and technical issues, inequitable living and environment conditions, lack of hands-on experience and how this made their degree feel incomplete and difficult, mental health issues, and many other barriers. The disciplinary faculties that experienced most of the obstacles and difficulties associated with ERTL were those whose academic experience depended on practical work in labs and studios or needed software that can only be accessed through labs and would need a specific operating system. The carrying out of this research will help ensure the effectiveness, investment, and continual integration of technology in future programs that involve learning and teaching.
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 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,001 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,001 | 0,001 |
| Intégrité de la recherche | 0,000 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,041 | 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 ».