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Use BCI to Generate Attention-Based Metadata for the Assessment of Effective Learning Duration

Authors :
Ju Chuan Wu
Pei Wen Lu
Xin Mao Chen
Yang Ting Shen
Source :
Learning and Collaboration Technologies. Learning and Teaching ISBN: 9783319911519, HCI (25)
Publication Year :
2018
Publisher :
Springer International Publishing, 2018.

Abstract

This paper proposes a novel method for evaluating the video-based learning performance by using brain computer interface (BCI). We develop Interactive Brain Tagging system (IBTS) to collect learns’ physiological affective metadata: attention. IBTS uses the EEG headset to measure learners’ brainwave and convert it into the evaluable attention value. When learners are watching video, their attention values are recorded every one second and marked in each corresponding video clip. We visaulize the variation of attention and tried to find out the continuous duration of higher attention level in a video. We used a 15 min’ video to conduct the experiment with 31 subjects. The result presented the difference of individual and collective attention duration. Moreover, in our case, the collected result suggested that the appropriate video time with higher attention may locate in 232 s.

Details

ISBN :
978-3-319-91151-9
ISBNs :
9783319911519
Database :
OpenAIRE
Journal :
Learning and Collaboration Technologies. Learning and Teaching ISBN: 9783319911519, HCI (25)
Accession number :
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