%0 Journal Article %1 donmez2005sca %A Dönmez, Pinar %A Rosé, Carolyn %A Stegmann, Karsten %A Weinberger, Armin %A Fischer, Frank %D 2005 %I International Society of the Learning Sciences %J Proceedings of th2005 conference on Computer support for collaborative learning: learning 2005: the next 10 years! %K CSCL LDSE analysis comutational learning linguistics scripts technology text %P 125-134 %T Supporting CSCL with automatic corpus analysis technology %U http://www.cs.cmu.edu/~cprose/pubweb/donmez05.pdf %X Process analyses are becoming more and more standard in research on computer-supported collaborative learning. This paper presents the rational as well as results of an evaluation of a tool called TagHelper, designed for streamlining the process of multi-dimensional analysis of the collaborative learning process. In comparison with a hand-coded corpus coded with a 7 dimensional coding scheme, TagHelper is able to achieve an acceptable level of agreement (Cohen's Kappa of .7 or more) along 6 out of 7 of the dimensions when we commit only to the portion of the corpus where the predictor has the highest certainty. In 5 of those cases, the percentage of the corpus where the predictor is confident enough to commit a code is at least 88% of the corpus. Consequences for theory-building with respect to automatic corpus analysis are formulated. Potential applications as a support tool for process analyses, as real-time support for facilitators of on-line discussions, and for the development of more adaptive instructional support for computer-supported collaboration are discussed.

@article{donmez2005sca, abstract = {Process analyses are becoming more and more standard in research on computer-supported collaborative learning. This paper presents the rational as well as results of an evaluation of a tool called TagHelper, designed for streamlining the process of multi-dimensional analysis of the collaborative learning process. In comparison with a hand-coded corpus coded with a 7 dimensional coding scheme, TagHelper is able to achieve an acceptable level of agreement (Cohen's Kappa of .7 or more) along 6 out of 7 of the dimensions when we commit only to the portion of the corpus where the predictor has the highest certainty. In 5 of those cases, the percentage of the corpus where the predictor is confident enough to commit a code is at least 88% of the corpus. Consequences for theory-building with respect to automatic corpus analysis are formulated. Potential applications as a support tool for process analyses, as real-time support for facilitators of on-line discussions, and for the development of more adaptive instructional support for computer-supported collaboration are discussed.}, added-at = {2007-11-27T12:21:46.000+0100}, author = {Dönmez, Pinar and Rosé, Carolyn and Stegmann, Karsten and Weinberger, Armin and Fischer, Frank}, biburl = {https://www.bibsonomy.org/bibtex/26e1cf9f3c72bb44f9e3529035e4f3a93/yish}, interhash = {6a94e9bf6f804ae25b711ca781517e89}, intrahash = {6e1cf9f3c72bb44f9e3529035e4f3a93}, journal = {Proceedings of th2005 conference on Computer support for collaborative learning: learning 2005: the next 10 years!}, keywords = {CSCL LDSE analysis comutational learning linguistics scripts technology text}, pages = {125-134}, publisher = {International Society of the Learning Sciences}, timestamp = {2007-11-27T12:21:47.000+0100}, title = {Supporting CSCL with automatic corpus analysis technology}, url = {http://www.cs.cmu.edu/~cprose/pubweb/donmez05.pdf}, year = 2005 }