A Two-Staged SEM: Artificial Neural Network Approach for Understanding and Predicting the Factors of Students' Satisfaction with Emergency Remote Teaching
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| Title: | A Two-Staged SEM: Artificial Neural Network Approach for Understanding and Predicting the Factors of Students' Satisfaction with Emergency Remote Teaching |
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| Language: | English |
| Authors: | Anupma Sangwan, Anurag Sangwan, Anju Sangwan, Poonam Punia (ORCID |
| Source: | Educational Technology Research and Development. 2024 72(2):1249-1286. |
| Availability: | Springer. Available from: Springer Nature. One New York Plaza, Suite 4600, New York, NY 10004. Tel: 800-777-4643; Tel: 212-460-1500; Fax: 212-460-1700; e-mail: customerservice@springernature.com; Web site: https://link.springer.com/ |
| Peer Reviewed: | Y |
| Page Count: | 38 |
| Publication Date: | 2024 |
| Document Type: | Journal Articles Reports - Research |
| Education Level: | Higher Education Postsecondary Education |
| Descriptors: | Distance Education, Student Satisfaction, Self Efficacy, Internet, Interaction, Foreign Countries, Universities, Learning Strategies, Self Management, Student Attitudes, College Students, Electronic Learning, Predictor Variables |
| Geographic Terms: | India |
| DOI: | 10.1007/s11423-023-10335-9 |
| ISSN: | 1042-1629 1556-6501 |
| Abstract: | This study seeks to address knowledge gaps regarding the role of self-regulated learning as a mediator in the relationship between interactions, internet self-efficacy, and student satisfaction. We conducted a survey of 1590 students from north Indian universities about their level of satisfaction, self-regulated learning, internet self-efficacy, and different interactions (learner-learner interaction, learner-content interaction, and learner-instructor interaction) during emergency remote teaching. By employing a two-stage SEM-ANN approach, this study contributes to methodological advancements and provides a comprehensive analysis of complex relationships. According to the findings, the identified factors are significant predictors of students' satisfaction with online education in synchronous settings. Our research also shows that self-regulated learning fully mediates the effect of internet self-efficacy on student satisfaction during emergency remote teaching. This suggests that internet self-efficacy alone may not guarantee student satisfaction unless accompanied by self-regulated learning skills. |
| Abstractor: | As Provided |
| Entry Date: | 2024 |
| Accession Number: | EJ1424604 |
| Database: | ERIC |
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| Abstract: | This study seeks to address knowledge gaps regarding the role of self-regulated learning as a mediator in the relationship between interactions, internet self-efficacy, and student satisfaction. We conducted a survey of 1590 students from north Indian universities about their level of satisfaction, self-regulated learning, internet self-efficacy, and different interactions (learner-learner interaction, learner-content interaction, and learner-instructor interaction) during emergency remote teaching. By employing a two-stage SEM-ANN approach, this study contributes to methodological advancements and provides a comprehensive analysis of complex relationships. According to the findings, the identified factors are significant predictors of students' satisfaction with online education in synchronous settings. Our research also shows that self-regulated learning fully mediates the effect of internet self-efficacy on student satisfaction during emergency remote teaching. This suggests that internet self-efficacy alone may not guarantee student satisfaction unless accompanied by self-regulated learning skills. |
|---|---|
| ISSN: | 1042-1629 1556-6501 |
| DOI: | 10.1007/s11423-023-10335-9 |
