Analyzing Collaborative Learning Processes Automatically: Exploiting the Advances of Computational Linguistics in Computer-Supported . . .

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Analyzing Collaborative Learning Processes Automatically: Exploiting the Advances of Computational Linguistics in Computer-Supported . . . (2008)

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by Carolyn Rosé , Yi-chia Wang , Jaime Arguello , Karsten Stegmann , Armin Weinberger , Frank Fischer

Venue:	INTERNATIONAL JOURNAL OF COMPUTER-SUPPORTED COLLABORATIVE LEARNING
Citations:	63 - 17 self

BibTeX

@MISC{Rosé08analyzingcollaborative,
    author = {Carolyn Rosé and Yi-chia Wang and Jaime Arguello and Karsten Stegmann and Armin Weinberger and Frank Fischer},
    title = {Analyzing Collaborative Learning Processes Automatically: Exploiting the Advances of Computational Linguistics in Computer-Supported . . . },
    year = {2008}
}

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Abstract

In this article we describe the emerging area of text classification research focused on the problem of collaborative learning process analysis both from a broad perspective and more specifically in terms of a new publicly available tool set called TagHelper tools. Analyzing the variety of different facets of learners’ interaction that are important for their learning is a time consuming and effortful process. Improving automated analyses of such highly valued processes of collaborative learning by adapting and applying recent text classification technologies would make it a less arduous task to obtain insights from corpus data. It also holds the potential for enabling substantially improved on-line instruction both by providing teachers and facilitators with reports about the groups they are moderating and by scaffolding technology as in the emerging area of context sensitive collaborative learning support triggered dynamically on an as-needed basis. In this article, we report on an interdisciplinary research project, which has been investigating the effectiveness of applying text classification technology to a large CSCL discourse corpus that had been analyzed by human coders using a theory-based multi-dimensional coding scheme. We report promising results and include an in-depth discussion of important issues such as reliability, validity, and efficiency that should be considered when deciding on the appropriateness of adopting a new technology such as TagHelper tools.

Keyphrases

collaborative learning process automatically computational linguistics taghelper tool in-depth discussion on-line instruction text classification research corpus data different facet available tool set large cscl discourse corpus as-needed basis automated analysis theory-based multi-dimensional coding scheme broad perspective new technology recent text classification technology time consuming interdisciplinary research project effortful process text classification technology context sensitive collaborative collaborative learning human coder important issue process analysis arduous task

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