Effects of Sensemaking Translucence on Distributed Collaborative Analysis

Collaborative sensemaking requires that analysts share their information and insights with each other, but this process of sharing runs the risks of prematurely focusing the investigation on specific suspects. To address this tension, we propose and test an interface for collaborative crime analysis that aims to make analysts more aware of their sensemaking processes. We compare our sensemaking translucence interface to a standard interface without special sensemaking features in a controlled laboratory study. We found that the sensemaking translucence interface significantly improved clue finding and crime solving performance, but that analysts rated the interface lower on subjective measures than the standard interface. We conclude that designing for distributed sensemaking requires balancing task performance vs. user experience and real-time information sharing vs. data accuracy.Comment: ACM SIGCHI CSCW 201

Juggling Work Among Multiple Projects and Partner

Prior research suggests people have trouble juggling effort across multiple projects with multiple partners. We investigated this problem, with an experiment where groups of four participants enacted the roles of police detectives. Each detective was assigned two homicide cases, each case with a different partner. To solve each case, detectives read their case documents and discussed relevant information with their partners. Half the groups used IM to communicate and the other half used an enhanced IM tool called Project-View IM (PVIM). PVIM lists partners and joint projects and lets users know what a partner is working on. We analyzed keystroke level computer activity and the content of conversations. Generally, work unfolded as follows: coordinate across cases, start first case, read documents, coordinate within case with partner, switch to second case, and so on, but with frequent interruptions. We describe implications of our findings for theories of multitasking. 1