Co-located Collaboration Analytics

Sambit Praharaj

doi:10.1145/3340555.3356087

Abstract

Collaboration is an important skill of the 21st century. It can take place in an online (or remote) setting or in a colocated (or face-to-face) setting. With the large scale adoption of sensor use, studies on co-located collaboration (CC) has gained momentum. CC takes place in physical spaces where the group members share each other's social and epistemic space. This involves subtle multimodal interactions such as gaze, gestures, speech, discourse which are complex in nature. The aim of this PhD is to detect these interactions and then use these insights to build an automated real-time feedback system to facilitate co-located collaboration.

Original language	English
Title of host publication	ICMI '19
Subtitle of host publication	2019 International Conference on Multimodal Interaction
Editors	Wen Gao, Helen Mei Ling Meng, Matthew Turk, Susan R. Fussell, Björn Schuller, Yale Song, Kai Yu
Place of Publication	New York, NY, USA
Publisher	Association for Computing Machinery (ACM)
Pages	473-476
Number of pages	4
ISBN (Electronic)	9781450368605
ISBN (Print)	9781450368605
DOIs	https://doi.org/10.1145/3340555.3356087
Publication status	Published - 14 Oct 2019

Keywords

Co-located collaboration
Multimodal interactions
Multimodal learning analytics
Realtime feedback

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10.1145/3340555.3356087

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Co-located Collaboration Analytics. / Praharaj, Sambit.
ICMI '19: 2019 International Conference on Multimodal Interaction. ed. / Wen Gao; Helen Mei Ling Meng; Matthew Turk; Susan R. Fussell; Björn Schuller; Yale Song; Kai Yu. New York, NY, USA: Association for Computing Machinery (ACM), 2019. p. 473-476.

Research output: Chapter in Book/Report/Conference proceeding › Conference Abstract/Poster in proceeding › Academic › peer-review

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Co-located Collaboration Analytics

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Keywords

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