Collaborative problem-solving with distributed information: The role of inferences from interdependent information

This article studies inferences from distributed, interdependent information in group problem-solving. Three inference types (collaborative, individual, and shared) are distinguished, based on information sharing and distribution, with a special focus on collaborative inferences that generate new information no individual group member could have inferred. In an experiment, n= 27 dyads solved a specifically designed inference task. Inferences from shared information were the most likely, individual inferences from unshared information less likely, and collaborative inferences from unshared, distributed information the least likely to be drawn. An analysis of inference patterns in dyads’ discussions points towards the individual- and group-level processes involved in drawing collaborative inferences, and explains why first support measures explored in this study were not optimally designed.