Exploring Interactive Design Strategies of Online Learning Platform Based on Cognitive Load Theory

Abstract

In recent years, online learning has been increasingly popular due to its convenience and accessibility. To improve the quality of online learning, it is essential to understand the learners' cognitive load during online learning interaction. Cognitive load theory and teaching interaction hierarchy theory are employed to explore the impact of learners' cognitive load during online learning interaction. Based on these theories, this study utilizes EEG technology and subjective measurement to measure the cognitive load of learners' operational interaction and information interaction during online learning interaction. Six typical tasks were studied, including login, search, browse, share, and discuss. The results demonstrate that the login and search tasks have a higher cognitive load and the browse and share tasks have a lower cognitive load among the six typical tasks, virtual reality learning environments have a lower cognitive load than online learning environments. Therefore, by correctly identifying the cognitive load of tasks in operational and information interaction, optimization strategies can help to reduce the cognitive load of learners during online learning interaction and improve the quality of online learning.