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Teacher Satisfaction in Online Education: A Two-Factor Model of Extrinsic and Intrinsic Factors Across Diverse Contexts

  • Ning Yan,
  • Andre Batako,
  • Gabriela Czanner,
  • Aiping Zhang

摘要

Blended learning modes are becoming the norm in educational institutions. This research investigates the factors affecting teacher satisfaction with online lesson delivery. This study was undertaken in primary, secondary, and higher education institutions across ten countries worldwide. A total of 247 teachers responded to the survey. This work innovatively validates a two-factor model of teacher satisfaction with online teaching, grounded in Herzberg’s two-factor theory. A first-order confirmatory factor analysis (CFA) was used to validate the constructs, followed by a second-order exploratory factor analysis (EFA) to identify key drivers of teacher satisfaction. The results showed that there were two key hidden drivers of teacher satisfaction i.e., intrinsic factor and extrinsic factor. The two factors explained 75% of the variance in teacher satisfaction. Teachers reported higher satisfaction due to the flexibility and work-life balance that online teaching affords, while dissatisfaction stemmed from institutional policies and insufficient incentives. It was observed that STEM teachers and older educators had lower satisfaction and higher technology anxiety. These insights have potential applications beyond online teaching, extending to teacher satisfaction in physical classroom settings.