Abstract
This study aims to develop and evaluate a visualization function of CSCL that is based on social presence. This function automatically categorizes the postings from learners and visually presents social interaction following a social presence indicator. Furthermore, this function seems to enhance social presence and encourage learning behavior, such as active discussion. In order to investigate the validity of auto-categorization, the inter-rater agreement rate and the ability to predict the quality of the discussion were analyzed and compared to the human-categorized data. The results demonstrated that there are several social presence indicators that have high and low inter-rater agreement, but the categorization of the function developed in this study had more prediction power than the human-conducted categorization.
Original language | English |
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Title of host publication | Collaboration Technologies and Social Computing - 8th International Conference, CollabTech 2016, Proceedings |
Editors | Takashi Yoshino, Gustavo Zurita, Takaya Yuizono, Nelson Baloian, Gwo-Dong Chen, Tomoo Inoue |
Publisher | Springer Verlag |
Pages | 174-189 |
Number of pages | 16 |
ISBN (Print) | 9789811026171 |
DOIs | |
Publication status | Published - Jan 1 2016 |
Event | 8th International Conference on Collaboration Technologies and Social Computing, CollabTech 2016 - Kanazawa, Japan Duration: Sep 14 2016 → Sep 16 2016 |
Publication series
Name | Communications in Computer and Information Science |
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Volume | 647 |
ISSN (Print) | 1865-0929 |
Other
Other | 8th International Conference on Collaboration Technologies and Social Computing, CollabTech 2016 |
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Country | Japan |
City | Kanazawa |
Period | 9/14/16 → 9/16/16 |
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All Science Journal Classification (ASJC) codes
- Computer Science(all)
- Mathematics(all)
Cite this
Social presence visualizer : Development of the collaboration facilitation module on CSCL. / Yamada, Masanori; Kaneko, Kosuke; Goda, Yoshiko.
Collaboration Technologies and Social Computing - 8th International Conference, CollabTech 2016, Proceedings. ed. / Takashi Yoshino; Gustavo Zurita; Takaya Yuizono; Nelson Baloian; Gwo-Dong Chen; Tomoo Inoue. Springer Verlag, 2016. p. 174-189 (Communications in Computer and Information Science; Vol. 647).Research output: Chapter in Book/Report/Conference proceeding › Conference contribution
}
TY - GEN
T1 - Social presence visualizer
T2 - Development of the collaboration facilitation module on CSCL
AU - Yamada, Masanori
AU - Kaneko, Kosuke
AU - Goda, Yoshiko
PY - 2016/1/1
Y1 - 2016/1/1
N2 - This study aims to develop and evaluate a visualization function of CSCL that is based on social presence. This function automatically categorizes the postings from learners and visually presents social interaction following a social presence indicator. Furthermore, this function seems to enhance social presence and encourage learning behavior, such as active discussion. In order to investigate the validity of auto-categorization, the inter-rater agreement rate and the ability to predict the quality of the discussion were analyzed and compared to the human-categorized data. The results demonstrated that there are several social presence indicators that have high and low inter-rater agreement, but the categorization of the function developed in this study had more prediction power than the human-conducted categorization.
AB - This study aims to develop and evaluate a visualization function of CSCL that is based on social presence. This function automatically categorizes the postings from learners and visually presents social interaction following a social presence indicator. Furthermore, this function seems to enhance social presence and encourage learning behavior, such as active discussion. In order to investigate the validity of auto-categorization, the inter-rater agreement rate and the ability to predict the quality of the discussion were analyzed and compared to the human-categorized data. The results demonstrated that there are several social presence indicators that have high and low inter-rater agreement, but the categorization of the function developed in this study had more prediction power than the human-conducted categorization.
UR - http://www.scopus.com/inward/record.url?scp=84988485770&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84988485770&partnerID=8YFLogxK
U2 - 10.1007/978-981-10-2618-8_14
DO - 10.1007/978-981-10-2618-8_14
M3 - Conference contribution
AN - SCOPUS:84988485770
SN - 9789811026171
T3 - Communications in Computer and Information Science
SP - 174
EP - 189
BT - Collaboration Technologies and Social Computing - 8th International Conference, CollabTech 2016, Proceedings
A2 - Yoshino, Takashi
A2 - Zurita, Gustavo
A2 - Yuizono, Takaya
A2 - Baloian, Nelson
A2 - Chen, Gwo-Dong
A2 - Inoue, Tomoo
PB - Springer Verlag
ER -