Impact of Online Courses on University Student Visual Attention During the COVID-19 Pandemic - Gao, Qi; Li, Sining (Frontiers in Psychiatry, 2022)
Background: Under the threat of COVID-19, many universities offer online courses to avoid students gathering, which prevents teachers from collecting responses and optimizing courses. This work collected eye movement data to analyze attention allocation and proposed instruction for improving courses. Methods: Subjects were recruited to watch three online courses, meanwhile their eye movement data were collected through Dikablis Glasses. Mayer’s multimedia cognitive theory was adopted to discriminate pivotal components of online course and Mann-Whitney relevance analysis demonstrated that different representations of courses affected viewers’ attention differently. Results: Three subjects watched three different types of political courses. Course 1, which combined text and explanation, attracted most attentions. Course 2 shows less attractive than course 1 and better than course 3, but subjects were distracted by the animations in course 2. Course 3, which did not use any technique to present learning content, attracts least attention of subjects. Correlation analysis shows that course1 and course 3 have similar results compared with course 2. Conclusion: Online course becomes normal during the COVID-19 pandemic. Improving the quality of online courses can effectively reduce the impact of the epidemic on teaching. These experiment results suggest that text + commentary in the design of online courses can effectively attract the attention of listeners and achieve better learning results. Attention gradually rises in the early stage, then falls after reaching the peak. At this time, the proper introduction of animation can effectively reverses the attention curve. And individual text or commentary quickly loses the listener’s attention.