Paper Info
Title
Identifying the Potential of Danmaku Video from Eye Gaze Data
Abstract
Video-based learning has gained popularity in higher education in recent years. Danmaku video is a kind of video where the screen is overlaid with user comments. In this study, the user comments consist of ideas and explanations about important concepts in the video, thus providing domain-specific knowledge and reducing the cognitive load for comprehension. This study tries to understand the effect of the danmaku video compared to with the normal video. Two groups of sophomore students (N= 20) were exposed to digital videos with or without danmaku. Both groups took part in a pre-and post-test on the topic of the given video. Time-locked eye movements were recorded to characterize participants' attention allocation to the Area of Interest (AOIs) consisting of danmaku, subtitles and teacher's face across the learning period. The results showed that danmaku video group outperformed the normal video group based on the increment of pre-and post-tests. Further, the percentage of fixation duration on each of the AOI was analyzed, and a significant difference was found in the amount of attention paid on different AOIs. The purpose of this study is focused on exploring the effects of Danmaku video in improving students' learning outcomes.
Year
DOI
Venue
2016
10.1109/ICALT.2016.155
2016 IEEE 16th International Conference on Advanced Learning Technologies (ICALT)
Keywords
Field
DocType
video-based learning,danmaku video,eye gaze data
Computer science,Visualization,Popularity,PEVQ,Eye tracking,Eye movement,Animation,Cognitive load,Multimedia,Comprehension
Conference
ISSN
ISBN
Citations 
2161-3761
978-1-4673-9042-2
0
PageRank 
References 
Authors
0.34
8
4
Name
Order
Citations
PageRank
Jing Leng100.68
Jiayu Zhu200.34
Xiaoting Wang300.34
Xiaoqing Gu4449.30