Conference proceeding
Articulating common ground in cooperative work: content and process
Proceedings of the SIGCHI Conference on Human Factors in Computing Systems, pp 1637-1646
06 Apr 2008
Abstract
We study the development of common ground in an emergency management planning task. Twelve three-person multi-role teams performed the task with a paper prototype in a controlled setting; each team completed three versions of the task. We use converging measures to document the development of common ground in the teams and present an in-depth analysis of the characteristics of the common ground development process. Our findings indicate that in complex collaborative work, process common ground increases, thus diminishing the need for acts like information querying or strategy discussions about how to organize the collaborative activities. However, content common ground is created and tested throughout the three runs; in fact dialogue acts used to clarify this content increase over time. Discussion of the implications of these findings for the theory of common ground and the design of collaborative systems follows.
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Details
- Title
- Articulating common ground in cooperative work
- Creators
- Gregorio Convertino - Pennsylvania State UniversityHelena M. Mentis - Pennsylvania State UniversityMary Beth Rosson - Pennsylvania State UniversityJohn M. Carroll - Pennsylvania State UniversityAleksandra Slavkovic - Pennsylvania State UniversityCraig H. Ganoe - Pennsylvania State UniversityACM
- Publication Details
- Proceedings of the SIGCHI Conference on Human Factors in Computing Systems, pp 1637-1646
- Conference
- CHI '08: CHI Conference on Human Factors in Computing Systems
- Series
- ACM Conferences
- Publisher
- ACM
- Number of pages
- 10
- Resource Type
- Conference proceeding
- Language
- English
- Academic Unit
- Information Science (Informatics)
- Web of Science ID
- WOS:000268586100197
- Scopus ID
- 2-s2.0-57649244146
- Other Identifier
- 991021916800904721
InCites Highlights
Data related to this publication, from InCites Benchmarking & Analytics tool:
- Web of Science research areas
- Computer Science, Artificial Intelligence
- Computer Science, Software Engineering