Indiana University-Purdue University Indianapolis (IUPUI) / Collaborative helping via social networking conversation threads can pose serious challenges in emergency situations. Interfaces that support complex group interaction and sense-making can help. This research applies human-computer interaction (HCI), computer-supported cooperative work (CSCW), and collaboration engineering in developing an interactive design, the Mega-Collaboration Tool (MCT). The goal is to reduce the cognitive load of a group’s growing mental model, thus increasing the general public’s ability to organize spontaneous collaborative helping. The specific aims of this research include understanding the dynamics of mental model negotiation and determining whether MCT can assist the group’s sense-making ability without increasing net cognitive load. The proposed HCI theory is that interfaces supporting collaborative cognition motivate contribution and reduce information bias, thus increasing the information shared. These research questions are addressed: 1. Does MCT support better collaborative cognition? 2. Does increasing the size of the shared data repository increase the amount of information shared? 3. Does this happen because group members experience 1) a greater sense of strategic commitment to the knowledge structure, 2) increased intrinsic motivation to contribute, and 3) reduced resistance to sharing information? These questions were affirmed to varying degrees, giving insight into the collaborative process. Greater content did not motive group members directly; instead, half of their motivation came from awareness of their contribution’s relevance. Greater content and organization improved this awareness, and also encouraged sharing through increased enthusiasm and reduced bias. Increased commitment was a result of this process, rather than a cause. Also, MCT increased collaborative cognition but was significantly hampered by Internet performance. This challenge indicates MCT’s system components should be redesigned to allow asynchronous interaction. These results should contribute to the development of MCT, other collaboration engineering applications, and HCI and information science theory.
| Identifer | oai:union.ndltd.org:IUPUI/oai:scholarworks.iupui.edu:1805/10894 |
| Date | 06 May 2016 |
| Creators | Newlon, Christine Mae |
| Contributors | Bolchini, Davide P., Faiola, Anthony, McDaniel, Anna M., MacDorman, Karl F. |
| Source Sets | Indiana University-Purdue University Indianapolis |
| Language | en_US |
| Detected Language | English |
| Type | Dissertation |
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