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.
| Original language | English |
|---|---|
| Article number | 5557 |
| Journal | Sustainability (Switzerland) |
| Volume | 15 |
| Issue number | 6 |
| DOIs | |
| State | Published - Mar 2023 |
UN SDGs
This output contributes to the following UN Sustainable Development Goals (SDGs)
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SDG 7 Affordable and Clean Energy
Keywords
- e-learning
- information system success model
- intention to continue learning
- qualitative comparative analysis of fuzzy sets
- stimulus-organism-response framework
- structural equation model
- technology acceptance model
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