Context-aware Group-Interaction

Abstract

As today’s group work today becomes more and more distributed across space and time, the demand for supporting group tasks by means of information technology is constantly growing. Available systems provide means for shared manipulation of objects and awareness about these manipulations. For effective teamwork, this artefact-based awareness is not enough. Awareness of what the other group members are currently engaged with, where they are and if they could be reached significantly improves the experience of computer supported collaborative work. Going even one step further, this user-based awareness could be used to provide the computer system with the context of the users and of the whole groups they are working in. Using this context, applications can adapt to the user’s current needs and even proactively trigger services appropiate for the current situation. The goal of this thesis has been to evaluate how user contexts can be utilized to support interaction in groups in spatially bounded areas, namely university campuses, and to prototypically implement an application, which actively supports people in their interaction needs. The result of this work is a fully implemented system for the context-aware support of group interaction that is referred to as GISS (Group Interaction Support System). This system is based on the SiLiCon-Context-Framework (cf. chapter 5.2) and uses an already existing in- stant messenger as user interface (cf. chapter 5.4.3). The system is aware of user identities, locations and activity states and of the local time. Utilizing this knowledge about the user’s context together with meta-information about group structures, the system is able to provide the users with pro-active services they might need to improve their interaction. These services include means for group formation and management, synchronous and asyn- chronous group communication, location awareness and the recognition and support of gath- erings as well as means for context-aware adaptation of one’s availability status and a con- text-aware reminder service. The system has reached a stable version and has already been tested in several artificial set- tings. A field test with more users in a real life setting is subject of future work.

Type
Stefan Oppl
Stefan Oppl
Professor for Technology Enhanced Learning

My research interests include technology-enhanced learning, socio-technical systems design and HCI