Title: Observing cognitive load during online learning with various task complexities: an eye tracking approach
Authors: Prabaria Vesca Yulianandra; Suatmi Murnani; Paulus Insap Santosa; Sunu Wibirama
Addresses: Department of Electrical and Information Engineering, Faculty of Engineering, Universitas Gadjah Mada, Yogyakarta, 55281, Indonesia ' Department of Electrical Engineering, Universitas Islam Indonesia, Yogyakarta, 55584, Indonesia ' Department of Electrical and Information Engineering, Faculty of Engineering, Universitas Gadjah Mada, Yogyakarta, 55281, Indonesia ' Department of Electrical and Information Engineering, Faculty of Engineering, Universitas Gadjah Mada, Yogyakarta, 55281, Indonesia
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.
International Journal of Innovation and Learning, 2023 Vol.34 No.1, pp.96 - 117
Received: 18 Feb 2022
Accepted: 12 May 2022
Published online: 07 Jul 2023 *