Applying Control-Value Theory and Unified Theory of Acceptance and Use of Technology to Explore Pre-service Teachers’ Academic Emotions and Learning Satisfaction
Academic emotions refer to the emotions related to achievement activities or outcomes. Academic emotions are directly related to learning performance and have been recognized as critical to learners’ learning satisfaction and learning effectiveness in the online learning context. This study aimed to...
Guardado en:
Autores principales: | , , , , , , |
---|---|
Formato: | article |
Lenguaje: | EN |
Publicado: |
Frontiers Media S.A.
2021
|
Materias: | |
Acceso en línea: | https://doaj.org/article/159aab719a814908a0508ae3de574c36 |
Etiquetas: |
Agregar Etiqueta
Sin Etiquetas, Sea el primero en etiquetar este registro!
|
Sumario: | Academic emotions refer to the emotions related to achievement activities or outcomes. Academic emotions are directly related to learning performance and have been recognized as critical to learners’ learning satisfaction and learning effectiveness in the online learning context. This study aimed to explore the relationship between academic emotions and learning satisfaction and their underlying mechanisms in massive open online courses (MOOCs) learning context using mediation models. This study adhered to the theoretical frameworks of the control-value theory (CVT) and the unified theory of acceptance and use of technology (UTAUT). Participants were 283 pre-service teachers who volunteered from a normal university in Southwestern China. Results revealed that: (a) academic emotions did not predict learning satisfaction; (b) learning interest and technology acceptance fully mediated the influence of academic emotions on learning satisfaction; (c) the four dimensions of technology acceptance did not mediate the relationship between academic emotions and learning satisfaction. This study integrated CVT and UTAUT models, and the results emphasized the importance of academic emotions and learning satisfaction in CVT and provision of additional support for UTAUT. Therefore, these findings have significant implications for improving the quality of MOOCs in the post-pandemic era. |
---|