Visualizing History to Improve Users' Location and Comprehension of Collaborative Work
Association for Computing Machinery
Many applications place users into collaborations with unknown and distant partners. Collaboration between participants in such environments is more efficient if individuals can identify and understand the contributions of others. A traditional approach to supporting such understanding within the CSCW community is to record user activity for later access. Issues with this approach include difficulties in locating activity of interest in large tasks and that history is often recorded at a system-activity level instead of at a human-activity level. To address these issues, this paper introduces CoActIVE, a history mechanism that clusters records of user activity and extracts keywords from manipulated content in an attempt to provide a human-level representation of history. Multiple visualization techniques' based on this processing were compared in their ability to improve users' location and comprehension of the activity of others. The results show the combination of clustering low level history events into activity segments and new visualizations summarizing activity within a segment result in a significant improvement over prior interfaces.