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Use BCI to Generate Attention-Based Metadata for the Assessment of Effective Learning Duration
- 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.
- Subjects :
- medicine.diagnostic_test
Computer science
Headset
02 engineering and technology
Variation (game tree)
Electroencephalography
Metadata
03 medical and health sciences
0302 clinical medicine
Human–computer interaction
020204 information systems
0202 electrical engineering, electronic engineering, information engineering
medicine
Duration (project management)
Affective computing
Tag system
030217 neurology & neurosurgery
Brain–computer interface
Subjects
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 :
- edsair.doi...........db833cc669d9c19a51d78f93e3ffe2b2