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

Prabaria Vesca Yulianandra, Suatmi Murnani, Paulus Insap Santosa and Sunu Wibirama

International Journal of Innovation and Learning, 2023, vol. 34, issue 1, 96-117

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.

Keywords: user experience; e-learning; design complexity; task complexity; cognitive load; eye tracking. (search for similar items in EconPapers)
Date: 2023
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