Instructors' self-efficacy, perceived benefits, and challenges in transitioning to online learning.
Educ Inf Technol (Dordr)
; : 1-36, 2023 Apr 25.
Article
em En
| MEDLINE
| ID: mdl-37361801
Drawing on social cognitive theory, this study investigated instructors' online teaching self-efficacy during the sudden, COVID-19-induced transition to online teaching. The pandemic has forced instructors to shift to online teaching, arming them with valuable hands-on experience in this alternative teaching mode. This study examined instructors' online teaching self-efficacy, perceived benefits, intention to implement online teaching strategies in their future teaching, and the challenges encountered during this transition. A total of 344 instructors completed the developed and validated questionnaire. The data were analyzed using multiple linear regression modeling, using the stepwise estimation technique. The findings demonstrate that affiliated universities, the quality of online learning, and previous use of learning management systems (LMS) are significant predictors of instructors' online teaching self-efficacy. Online teaching self-efficacy, along with gender, quality of online learning, and professional training are significant predictors of the perceived benefits of online learning during emergencies. Meanwhile, the quality of online learning and professional training are significant predictors of instructors' intention to implement online teaching strategies and learning technology tools. Instructors ranked remote assessment as the most challenging factor in online teaching during emergencies, and internet access or internet speed as the first and most complicated hindrance for students in this transition. This study helps in understanding instructors' online teaching self-efficacy during the sudden transition and the positive consequences of shifting to the online mode due to the COVID-19 pandemic on the higher education field. Recommendations and implications are discussed.
Texto completo:
1
Base de dados:
MEDLINE
Tipo de estudo:
Prognostic_studies
Idioma:
En
Ano de publicação:
2023
Tipo de documento:
Article