Investigating Factors That Influence College Students' Online Continuous Learning Intention during COVID-19 Epidemic
2023 11th International Conference on Information and Education Technology, ICIET 2023
; : 380-384, 2023.
Artículo
en Inglés
| Scopus | ID: covidwho-20242867
ABSTRACT
This study aims to explore university students' continuous intention toward online learning during COVID-19 pandemic. A total of 120 students enrolled in online learning were surveyed to collect their perception of an extended model by adding task value to the expectation-confirmation model. Structural equation modeling was employed to verify the hypotheses proposed in this study. The results indicated that task value and technology usefulness were significant predictors of students' continuous intention toward online learning. More specifically, technology usefulness had a direct impact on students' continuous intention, while students' perceived task value played an indirect role in the prediction of their continuous intention. However, the impacts of both confirmation and satisfaction were not statistically significant on students' continuous intention. The results suggest that practitioners and researchers should pay special attention to the technological usefulness of online learning environments and task value, especially task value, in order to enhance students' retention of online learning. This study would contribute to implications to better design and implement online learning. © 2023 IEEE.
expectation-confirmation model; online continuous learning intention; students' learning; task value; Computer aided instruction; COVID-19; E-learning; Education computing; Learning systems; College students; Continuous learning; Expectation-confirmation models; Extended model; Online learning; Structural equation models; Student learning; University students; Students
Texto completo:
Disponible
Colección:
Bases de datos de organismos internacionales
Base de datos:
Scopus
Tipo de estudio:
Estudio observacional
/
Estudio pronóstico
Idioma:
Inglés
Revista:
2023 11th International Conference on Information and Education Technology, ICIET 2023
Año:
2023
Tipo del documento:
Artículo
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