Educational Data Mining (EDM) 2020

• Author: Gakyung Kim (gakyung.kim@snu.ac.kr), Il-Hyun Jo (ijo@ewha.ac.kr)
• Title: The Effect of Visual Cues on Cognitive Load Depending on Self-Regulation in Video Based Learning
• Paper: https://educationaldatamining.org/files/conferences/EDM2020/papers/paper_263.pdf
• Abstract: Recently, online learning has been increasingly used due to its advantages that allow people to study anytime and anywhere. Learners, on the other hand, are separated from the instructor in video-based learning, which makes learners difficult to maintain their motivation until the end of the activity. Therefore, it is required to provide instructional treatment so that learners keep their motivation and be immersed in learning. Visual cues, lowering cognitive load, are known a putative way in which learners can distinguish essential information from irrelevant one. The aim of this study is to explore the effect of visual cues on cognitive load depending on the level of self-regulation. The result shows that self-regulation lower cognitive load in the nonvisual-cue group as time series, but self-regulation doesn’t have an effect on cognitive load in the visual-cue group. This indicates learners in the non-visual-cue group experience difficulty to keep their motivation so that they are hard to put mental effort into the learning. This study suggests that the pupil dilation which reflects cognitive load can be predicted by behavior log which indicates self-regulation. Therefore, it is necessary to enhance learners’ cognitive strategies, as well as the reduction of the factors causing unnecessary cognitive load.