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Article

Research on the Influence of E-Learning Quality on the Intention to Continue E-Learning: Evidence from SEM and fsQCA

Department of Education Information Technology, Faculty of Education, East China Normal University, Shanghai 200062, China
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Author to whom correspondence should be addressed.
Sustainability 2023, 15(6), 5557; https://doi.org/10.3390/su15065557
Submission received: 19 February 2023 / Revised: 13 March 2023 / Accepted: 17 March 2023 / Published: 22 March 2023

Abstract

This study explores how Chinese college students perceive the quality of e-learning and its impact on their adoption of online learning. The study develops an impact model of e-learning quality on continuous learning intention based on the stimulus-organism-response framework, technology acceptance model, and information system success model. The model is validated using a structural equation model (SEM) and fuzzy set qualitative comparative analysis (fsQCA) with data collected from 253 college students at a university in Eastern China. The SEM analysis shows that perceived ease of use and perceived usefulness positively influence e-learning continuance intention, while system quality and personalization have a positive impact on perceived ease of use, and learning community positively impacts perceived usefulness. The fsQCA analysis shows that college students’ willingness to continue e-learning is not solely dependent on a single factor of e-learning service quality but is also influenced by the interaction between various factors. Therefore, e-learning providers should take into account both external stimuli and internal perception factors when designing e-learning services. The findings of this study have practical implications for improving e-learning quality and enhancing the online learning experience. E-learning providers should consider the importance of system quality, personalization, and learning community in improving perceived ease of use and usefulness, which in turn can increase students’ intention to continue e-learning. The study also highlights the importance of considering the interaction between various factors that influence e-learning adoption rather than relying solely on individual factors.
Keywords: e-learning; intention to continue learning; stimulus-organism-response framework; technology acceptance model; information system success model; structural equation model; qualitative comparative analysis of fuzzy sets e-learning; intention to continue learning; stimulus-organism-response framework; technology acceptance model; information system success model; structural equation model; qualitative comparative analysis of fuzzy sets

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MDPI and ACS Style

Zheng, H.; Qian, Y.; Wang, Z.; Wu, Y. Research on the Influence of E-Learning Quality on the Intention to Continue E-Learning: Evidence from SEM and fsQCA. Sustainability 2023, 15, 5557. https://doi.org/10.3390/su15065557

AMA Style

Zheng H, Qian Y, Wang Z, Wu Y. Research on the Influence of E-Learning Quality on the Intention to Continue E-Learning: Evidence from SEM and fsQCA. Sustainability. 2023; 15(6):5557. https://doi.org/10.3390/su15065557

Chicago/Turabian Style

Zheng, Hao, Yu Qian, Zongran Wang, and Yonghe Wu. 2023. "Research on the Influence of E-Learning Quality on the Intention to Continue E-Learning: Evidence from SEM and fsQCA" Sustainability 15, no. 6: 5557. https://doi.org/10.3390/su15065557

APA Style

Zheng, H., Qian, Y., Wang, Z., & Wu, Y. (2023). Research on the Influence of E-Learning Quality on the Intention to Continue E-Learning: Evidence from SEM and fsQCA. Sustainability, 15(6), 5557. https://doi.org/10.3390/su15065557

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