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Predicting Chinese University Students' E-Learning Acceptance and Self-Regulation in Online English Courses: Evidence From Emergency Remote Teaching (ERT) During COVID-19
Sage Open ; 11(4):15, 2021.
Article in English | Web of Science | ID: covidwho-1559083
ABSTRACT
A growing concern for online course learning is to what extent learners are concentrated and self-regulated when they are isolated from their classmates and instructors. To address this issue, this study collected both quantitative and qualitative data from a sample of 580 Chinese university learners from varied majors, who were taking online English courses in Emergency Remote Teaching (ERT) mode during COVID-19. This study identified specific psychological and contextual factors that impact learners' e-learning acceptance and online self-regulation, based upon Technology Acceptance Model (TAM). Learners' actual use of three sub-processes of self-regulated strategies, namely, goal setting, task strategies, and self-evaluation was also examined. Partial least squares (PLS)-structural equation modeling (SEM) technique was used to test hypotheses and proposed research model. The quantitative results indicate that media richness, as a contextual factor, and social presence and flow, as two typical psychological factors, are determining antecedents that impact Chinese learners' e-learning acceptance. Meanwhile, quantitative findings show that learners' behavioral intention to use e-learning is a main contributor of their use of all three sub-processes of self-regulated learning strategies. Furthermore, thematic analysis was conducted to study the qualitative data, revealing that learners held rather divided and mixed perceptions regarding online learning experience. These findings have important implications for effective online English course design and implementation.
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Full text: Available Collection: Databases of international organizations Database: Web of Science Type of study: Prognostic study Language: English Journal: Sage Open Year: 2021 Document Type: Article

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Full text: Available Collection: Databases of international organizations Database: Web of Science Type of study: Prognostic study Language: English Journal: Sage Open Year: 2021 Document Type: Article