E-Learning in the Postpandemic Era: A Case Study in Taiwan
本研究通过问卷调查，整合预测因子和调节变量，构建因果模型，探讨疫情后用户持续使用电子学习的意愿，并为优化在线学习系统提供建议。
The COVID-19 pandemic is pressing educational institutions across the globe to transfer rapidly from face-to-face learning to e-learning. However, e-learning has some multifaceted problems waiting to be solved and optimized. This study uses a survey questionnaire to collect research data. By integrating two predictors and four moderators into expectation-confirmation model, this article develops a causal research model and studies the continuance intention of using e-learning after the pandemic and how we can optimize online learning systems to benefit the traditional education systems in the long term. This article fills the literature gap of studies on IS continuance intention of e-learning from a problem-driven perspective. Based on the research results, this article suggests policy-makers and educators not only develop continuous training for both instructors and students on e-learning to enhance their ability and acceptance of e-learning systems but also build a more comprehensive technical environment to accelerate the adoption as well as to increase the continuance usage intention of e-learning systems. In addition, high-quality educational designs of e-learning that contain interaction mechanisms and customizations according to students’ perceptions and attitudes toward e-learning are needed. We also call on scholars from around the globe to continue investigating the critical factors of e-learning adaptation and online educational environment optimization for proposing better solutions to counter crises similar to the COVID-19 pandemic in the future.