Predicting social cues during online discussions: Effects of evaluations and knowledge content

Authors:
Gaowei Chen;Ming Ming Chiu;Zhan Wang
Affiliations:
Learning Research and Development Center, University of Pittsburgh, 3939 O'Hara Street, Pittsburgh, PA 15260, USA;Department of Learning and Instruction, Graduate School of Education, 367 Baldy Hall, State University of New York at Buffalo, Buffalo, NY 14260, USA;Learning Research and Development Center, University of Pittsburgh, 3939 O'Hara Street, Pittsburgh, PA 15260, USA
Venue:
Computers in Human Behavior
Year:
2012

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Abstract

This study examined whether evaluations (agreements, disagreements), knowledge content (new ideas, justifications), or social cues (SCs) in recent messages affected a current message's positive or negative SC during asynchronous, online discussions. Using statistical discourse analysis, we modeled 894 messages by 183 participants on 60 high school mathematics topics (typically eight people posted per topic) on a mathematics problem solving website not connected to any class or school. Results showed that recent agreements increased the likelihood of positive SC, whereas justifications reduced it. Disagreements increased the likelihood of negative SC, whereas new ideas reduced it. Meanwhile, recent positive or negative SCs did not affect the likelihood of a subsequent SC. Together, these results suggest that judicious use of positive SCs rather than negative SCs during disagreements can help students both construct knowledge and maintain social relationships.