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Observing cognitive load during online learning with various task complexities: an eye tracking approach

Author

Listed:
  • Prabaria Vesca Yulianandra
  • Suatmi Murnani
  • Paulus Insap Santosa
  • Sunu Wibirama

Abstract

E-learning has been used to support distance education during the COVID-19 pandemic. Unfortunately, little attention has been paid to the relationship between design complexity of an e-learning system, task complexity, and users' cognitive load. Here we conducted a novel investigation to observe effects of design complexity and task complexity towards users' cognitive load. Each group of participants was exposed to different interfaces of e-learning: low, medium, and high design complexity. Participants were asked to perform both simple and complex tasks. We used four instruments: eye tracking, cognitive load questionnaire, system usability scale (SUS), and user experience questionnaire (UEQ). Experimental results show that task complexity and design complexity significantly affect the eye tracking metrics (p < 0.05) and scores of cognitive load questionnaire (p < 0.05). Based on experimental results, we recommend an e-learning system with medium complexity to achieve minimum cognitive burden in online learning during the COVID-19 pandemic.

Suggested Citation

  • Prabaria Vesca Yulianandra & Suatmi Murnani & Paulus Insap Santosa & Sunu Wibirama, 2023. "Observing cognitive load during online learning with various task complexities: an eye tracking approach," International Journal of Innovation and Learning, Inderscience Enterprises Ltd, vol. 34(1), pages 96-117.
    • Handle: RePEc:ids:ijilea:v:34:y:2023:i:1:p:96-117
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