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The rapid shift to online learning during COVID-19 caused challenges in higher education. Many teachers and students lacked experience with online learning platforms and techniques. The factors why online learning was not effective during the COVID-19 pandemic are examined. A total of 302 questionnaires were collected using Google Form. The quantitative data were analyzed using SPSS and AMOS for item analysis, facet reliability and validity analysis, path analysis, direct and indirect effect analysis, and difference analysis. The effect of online learning flow, online learning cognitive load, and self-efficacy of online learning on unsuccessful online learning was revealed in this study. The result showed that: (1) greater levels of Self-efficacy of Online Learning on Human-system interaction (SOLH) and Self-efficacy of Online Learning on Content (SOLC) were significantly predict higher levels of Flow in Online Learning (FOL); (2) greater levels of Self-efficacy of Online Learning on Human-system interaction (SOLH) and Self-efficacy of Online Learning on Content (SOLC) were not significantly predict higher levels of Cognitive Load of Online Learning (CLOL); and (3) greater levels of Cognitive Load of Online Learning (CLOL) were significantly predicted higher levels of Online Learning Ineffectiveness (OLI). The online learning ineffectiveness can be reduced by decreasing the levels of cognitive load instead the learning flow.

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Ineffective Online Learning During the COVID-19 Pandemic in Higher Education

  • 会议论文

  • 发表日期：

    2026年

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  • Jirarat Sitthiworachart,
  • Jon-Chao Hong,
  • Amanda Pradhani Yanwar,
  • Thoriq Tri Prabowo,
  • Phimpawee Suwanno

摘要

The rapid shift to online learning during COVID-19 caused challenges in higher education. Many teachers and students lacked experience with online learning platforms and techniques. The factors why online learning was not effective during the COVID-19 pandemic are examined. A total of 302 questionnaires were collected using Google Form. The quantitative data were analyzed using SPSS and AMOS for item analysis, facet reliability and validity analysis, path analysis, direct and indirect effect analysis, and difference analysis. The effect of online learning flow, online learning cognitive load, and self-efficacy of online learning on unsuccessful online learning was revealed in this study. The result showed that: (1) greater levels of Self-efficacy of Online Learning on Human-system interaction (SOLH) and Self-efficacy of Online Learning on Content (SOLC) were significantly predict higher levels of Flow in Online Learning (FOL); (2) greater levels of Self-efficacy of Online Learning on Human-system interaction (SOLH) and Self-efficacy of Online Learning on Content (SOLC) were not significantly predict higher levels of Cognitive Load of Online Learning (CLOL); and (3) greater levels of Cognitive Load of Online Learning (CLOL) were significantly predicted higher levels of Online Learning Ineffectiveness (OLI). The online learning ineffectiveness can be reduced by decreasing the levels of cognitive load instead the learning flow.