Automatic Prediction Of Small Group Performance In Information Sharing Tasks
In this paper, we describe a novel approach, based on Markov jump processes, to model small group conversational dynamics and to predict small group performance. More precisely, we estimate conversational events such as turn taking, backchannels, turn-transitions at the micro-level (1 minute windows...
| Main Authors: | , , |
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| Other Authors: | |
| Format: | Article |
| Language: | en_US |
| Published: |
2017
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| Online Access: | http://hdl.handle.net/1721.1/108324 https://orcid.org/0000-0002-8053-9983 |
| Summary: | In this paper, we describe a novel approach, based on Markov jump processes, to model small group conversational dynamics and to predict small group performance. More precisely, we estimate conversational events such as turn taking, backchannels, turn-transitions at the micro-level (1 minute windows) and then we bridge the micro-level behavior and the macro-level performance. We tested our approach with a cooperative task, the Information Sharing task, and we verified the relevance of micro-level interaction dynamics in determining a good group performance (e.g. higher speaking turns rate and more balanced participation among group members). |
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