Abstract
Chat-like conversations are very popular and are often used by members of communities of practice to share ideas, propose solutions and to solve problems. With the advent and increasing popularity of Computer Supported Collaborative Learning (CSCL), chat conversations have also started to be used in a formal educational setting. However, the main problem when tutors tried to assess their students’ chat conversations is that this process is very difficult and time consuming. Therefore, several efforts have been undertaken during the last years to develop a tool that supports the analysis of collaborative chat conversations used in an educational context. In this paper, we propose a solution based on Natural Language Processing (NLP), Social Network Analysis (SNA) and Latent Semantic Analysis (LSA) that can be used for several tasks: assessment of utterances and participants, important topics visualization, summarization and semantic search. Furthermore, a summary with the key findings from the first validation round of using this approach is presented.
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Dascalu, M., Rebedea, T., Trausan-Matu, S. (2010). A Deep Insight in Chat Analysis: Collaboration, Evolution and Evaluation, Summarization and Search. In: Dicheva, D., Dochev, D. (eds) Artificial Intelligence: Methodology, Systems, and Applications. AIMSA 2010. Lecture Notes in Computer Science(), vol 6304. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-15431-7_20
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DOI: https://doi.org/10.1007/978-3-642-15431-7_20
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-15430-0
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