Brain tagging: A BCI and HCI tagging system to evaluate the learning contents

Yang Ting Shen; Pei Wen Lu; Xin Mao Chen

doi:10.1007/978-3-319-58509-3_5

Brain tagging: A BCI and HCI tagging system to evaluate the learning contents

Yang Ting Shen, Pei Wen Lu, Xin Mao Chen

Department of Architecture

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

1 Citation (Scopus)

Abstract

In this paper, we propose a novel interactive video-based learning system, Brain Tagging. Through collecting both the passive BCI and the active HCI tagging information, the learns’ objective and subjective metadata to the video contents are generated. The system gives a way to visualize the learning pattern by timeline chart consisted of BCI metadata (attention and meditation) and HCI metadata (good, question, and disagree). This can help to understand the learning process and performance, and thereby to provide proper improvement in e-learning.

Original language	English
Title of host publication	Learning and Collaboration Technologies
Subtitle of host publication	Novel Learning Ecosystems - 4th International Conference, LCT 2017 Held as Part of HCI International 2017, Proceedings
Editors	Panayiotis Zaphiris, Andri Ioannou
Publisher	Springer Verlag
Pages	46-54
Number of pages	9
ISBN (Print)	9783319585086
DOIs	https://doi.org/10.1007/978-3-319-58509-3_5
Publication status	Published - 2017
Event	4th International Conference on Learning and Collaboration Technologies, LCT 2017, held as part of the 19th International Conference on Human-Computer Interaction, HCI 2017 - Vancouver, Canada Duration: 2017 Jul 9 → 2017 Jul 14

Publication series

Name	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume	10295 LNCS
ISSN (Print)	0302-9743
ISSN (Electronic)	1611-3349

Conference

Conference	4th International Conference on Learning and Collaboration Technologies, LCT 2017, held as part of the 19th International Conference on Human-Computer Interaction, HCI 2017
Country/Territory	Canada
City	Vancouver
Period	17-07-09 → 17-07-14

All Science Journal Classification (ASJC) codes

Theoretical Computer Science
General Computer Science

Access to Document

10.1007/978-3-319-58509-3_5

Cite this

Shen, Y. T., Lu, P. W., & Chen, X. M. (2017). Brain tagging: A BCI and HCI tagging system to evaluate the learning contents. In P. Zaphiris, & A. Ioannou (Eds.), Learning and Collaboration Technologies: Novel Learning Ecosystems - 4th International Conference, LCT 2017 Held as Part of HCI International 2017, Proceedings (pp. 46-54). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 10295 LNCS). Springer Verlag. https://doi.org/10.1007/978-3-319-58509-3_5

Shen, Yang Ting ; Lu, Pei Wen ; Chen, Xin Mao. / Brain tagging : A BCI and HCI tagging system to evaluate the learning contents. Learning and Collaboration Technologies: Novel Learning Ecosystems - 4th International Conference, LCT 2017 Held as Part of HCI International 2017, Proceedings. editor / Panayiotis Zaphiris ; Andri Ioannou. Springer Verlag, 2017. pp. 46-54 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).

@inproceedings{d4c729b7ad274759aa91935b42df1c8b,

title = "Brain tagging: A BCI and HCI tagging system to evaluate the learning contents",

abstract = "In this paper, we propose a novel interactive video-based learning system, Brain Tagging. Through collecting both the passive BCI and the active HCI tagging information, the learns{\textquoteright} objective and subjective metadata to the video contents are generated. The system gives a way to visualize the learning pattern by timeline chart consisted of BCI metadata (attention and meditation) and HCI metadata (good, question, and disagree). This can help to understand the learning process and performance, and thereby to provide proper improvement in e-learning.",

author = "Shen, {Yang Ting} and Lu, {Pei Wen} and Chen, {Xin Mao}",

note = "Funding Information: The financial support from Ministry of Science and Technology (MOST) including project “Brain Tagging System” (MOST 105-2221-E-035-070-) and project “Resilient Livable Smart City:” (MOST 105-2627-M-035-008-), is greatly acknowledged. Publisher Copyright: {\textcopyright} Springer International Publishing AG 2017.; 4th International Conference on Learning and Collaboration Technologies, LCT 2017, held as part of the 19th International Conference on Human-Computer Interaction, HCI 2017 ; Conference date: 09-07-2017 Through 14-07-2017",

year = "2017",

doi = "10.1007/978-3-319-58509-3_5",

language = "English",

isbn = "9783319585086",

series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",

publisher = "Springer Verlag",

pages = "46--54",

editor = "Panayiotis Zaphiris and Andri Ioannou",

booktitle = "Learning and Collaboration Technologies",

address = "Germany",

}

Shen, YT, Lu, PW & Chen, XM 2017, Brain tagging: A BCI and HCI tagging system to evaluate the learning contents. in P Zaphiris & A Ioannou (eds), Learning and Collaboration Technologies: Novel Learning Ecosystems - 4th International Conference, LCT 2017 Held as Part of HCI International 2017, Proceedings. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 10295 LNCS, Springer Verlag, pp. 46-54, 4th International Conference on Learning and Collaboration Technologies, LCT 2017, held as part of the 19th International Conference on Human-Computer Interaction, HCI 2017, Vancouver, Canada, 17-07-09. https://doi.org/10.1007/978-3-319-58509-3_5

Brain tagging: A BCI and HCI tagging system to evaluate the learning contents. / Shen, Yang Ting; Lu, Pei Wen; Chen, Xin Mao.
Learning and Collaboration Technologies: Novel Learning Ecosystems - 4th International Conference, LCT 2017 Held as Part of HCI International 2017, Proceedings. ed. / Panayiotis Zaphiris; Andri Ioannou. Springer Verlag, 2017. p. 46-54 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 10295 LNCS).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

TY - GEN

T1 - Brain tagging

T2 - 4th International Conference on Learning and Collaboration Technologies, LCT 2017, held as part of the 19th International Conference on Human-Computer Interaction, HCI 2017

AU - Shen, Yang Ting

AU - Lu, Pei Wen

AU - Chen, Xin Mao

N1 - Funding Information: The financial support from Ministry of Science and Technology (MOST) including project “Brain Tagging System” (MOST 105-2221-E-035-070-) and project “Resilient Livable Smart City:” (MOST 105-2627-M-035-008-), is greatly acknowledged. Publisher Copyright: © Springer International Publishing AG 2017.

PY - 2017

Y1 - 2017

N2 - In this paper, we propose a novel interactive video-based learning system, Brain Tagging. Through collecting both the passive BCI and the active HCI tagging information, the learns’ objective and subjective metadata to the video contents are generated. The system gives a way to visualize the learning pattern by timeline chart consisted of BCI metadata (attention and meditation) and HCI metadata (good, question, and disagree). This can help to understand the learning process and performance, and thereby to provide proper improvement in e-learning.

AB - In this paper, we propose a novel interactive video-based learning system, Brain Tagging. Through collecting both the passive BCI and the active HCI tagging information, the learns’ objective and subjective metadata to the video contents are generated. The system gives a way to visualize the learning pattern by timeline chart consisted of BCI metadata (attention and meditation) and HCI metadata (good, question, and disagree). This can help to understand the learning process and performance, and thereby to provide proper improvement in e-learning.

UR - http://www.scopus.com/inward/record.url?scp=85025163156&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=85025163156&partnerID=8YFLogxK

U2 - 10.1007/978-3-319-58509-3_5

DO - 10.1007/978-3-319-58509-3_5

M3 - Conference contribution

AN - SCOPUS:85025163156

SN - 9783319585086

T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

SP - 46

EP - 54

BT - Learning and Collaboration Technologies

A2 - Zaphiris, Panayiotis

A2 - Ioannou, Andri

PB - Springer Verlag

Y2 - 9 July 2017 through 14 July 2017

ER -

Shen YT, Lu PW, Chen XM. Brain tagging: A BCI and HCI tagging system to evaluate the learning contents. In Zaphiris P, Ioannou A, editors, Learning and Collaboration Technologies: Novel Learning Ecosystems - 4th International Conference, LCT 2017 Held as Part of HCI International 2017, Proceedings. Springer Verlag. 2017. p. 46-54. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). doi: 10.1007/978-3-319-58509-3_5

Brain tagging: A BCI and HCI tagging system to evaluate the learning contents

Abstract

Publication series

Conference

All Science Journal Classification (ASJC) codes

Access to Document

Other files and links

Fingerprint

Cite this