Why do some groups of people work well together while others do not? It is commonly accepted that effective groups communicate well. Yet one of the biggest roadblocks facing the study of group communication is that it is extremely difficult to capture real-world group interactions and analyze the words people use in a timely manner. This project overcame this limitation in two ways. First, a broader and more systematic study of group processes was conducted by using a computerized text analysis program (Linguistic Inquiry and Word Count) that automatically codes natural language using pre-established rules. Groups that work well together typically exchange more knowledge and establish good social relationships, which is reflected in the way that they use words. The group dynamics of over 500 student discussion groups interacting via group chat were assessed by studying their language use. Second, a language feedback system was built to experimentally test the importance of certain group processes on group satisfaction and performance. It is now possible to provide language feedback by processing natural language dialogue using computerized text analysis in real time. The language feedback system can change the way the group works by providing individualized recommendations. In this way it is possible to manipulate group processes naturalistically. Together these studies provided evidence that important group processes can be detected even using simplistic natural language processing, and preliminary evidence that providing real-time feedback based on the words students use in a group discussion can improve learning by changing how the group works together. / text
| Identifer | oai:union.ndltd.org:UTEXAS/oai:repositories.lib.utexas.edu:2152/ETD-UT-2012-08-5971 |
| Date | 20 November 2012 |
| Creators | Tausczik, Yla Rebecca |
| Source Sets | University of Texas |
| Language | English |
| Detected Language | English |
| Type | thesis |
| Format | application/pdf |
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