TY - GEN
T1 - Multimodal data analytics for assessing collaborative interactions
AU - Kim, Yanghee
AU - Butail, Sachit
AU - Liu, Lichual
AU - Tscholl, Michael
AU - Hwang, Jaejin
AU - Cafaro, Francesco
AU - Trajkova, Milka
AU - Kwon, Kyungbin
AU - Espino, Danielle
AU - Lee, Seung
AU - Hamilton, Eric
AU - D'Angelo, Cynthia
AU - Ochoa, Xavier
AU - Kline, Aaron
AU - Lee, Sungchul
N1 - Funding Information:
The authors gratefully acknowledge funding support from the US National Science Foundation for the work included in this symposium: Awards #1848898 (S2), #1612824 (S3), #1839194 (S4), & #1623561 (S5). Views appearing in this paper do not reflect those of the funding agency.
Publisher Copyright:
© ISLS
PY - 2020
Y1 - 2020
N2 - This symposium will discuss the current status of the research and development of multimodal data analytics (MDA) for the observation of collaboration. Five research groups will present their current work on MDA, each with a unique focus on different data sources and different approaches to the analysis and synthesis of multimodal data sets. A few themes emerge from these studies: i) the studies seek to examine collaborative behaviors as a process in ordinary settings, both formal and informal; ii) with MDA being in its early stage, manual and computational approaches are taken complementarily, also using human annotation as the ground truth for the computational approach; and iii) several different discipline-specific research and development lines contribute integrally to generating authentic measures of collaborative interactions in situ, making this line of research transdisciplinary.
AB - This symposium will discuss the current status of the research and development of multimodal data analytics (MDA) for the observation of collaboration. Five research groups will present their current work on MDA, each with a unique focus on different data sources and different approaches to the analysis and synthesis of multimodal data sets. A few themes emerge from these studies: i) the studies seek to examine collaborative behaviors as a process in ordinary settings, both formal and informal; ii) with MDA being in its early stage, manual and computational approaches are taken complementarily, also using human annotation as the ground truth for the computational approach; and iii) several different discipline-specific research and development lines contribute integrally to generating authentic measures of collaborative interactions in situ, making this line of research transdisciplinary.
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M3 - Conference contribution
AN - SCOPUS:85102849624
T3 - Computer-Supported Collaborative Learning Conference, CSCL
SP - 2547
EP - 2554
BT - 14th International Conference of the Learning Sciences
A2 - Gresalfi, Melissa
A2 - Horn, Ilana Seidel
PB - International Society of the Learning Sciences (ISLS)
T2 - 14th International Conference of the Learning Sciences: The Interdisciplinarity of the Learning Sciences, ICLS 2020
Y2 - 19 June 2020 through 23 June 2020
ER -