- C. Rosé, F. Fischer, Chun-Yen Chang. 2007. Exploring the influence of culture on collaborative learning. Abstract: As on-line learning becomes more ubiquitous, and multi-ethnic on-line classrooms become more commonplace, it becomes more crucial to explore cultural communication issues and how we can design on-line learning environments that can facilitate productive learning experiences under these conditions. Our short term research focus is to develop automatic on-line assessment technologies and adaptive support technologies as infrastructure for supporting and studying collaborative learning in multiple cultures. The specific objective of our international collaboration has been to explore the intersection between the technology research area of text classification and the behavioral research area of collaborative learning process analysis. Beyond simply being an application of existing technology to a well defined framework for discourse analysis, this collaboration has yielded interesting new technical challenges and findings (Donmez et al., 2005; Rosé et al., 2005; Stegmann et al., 2006; Wang et al., 2007; Wang et al., submitted), questions about behavioral research methodology (Gweon et al., 2005), and finally questions about design of new forms of collaboration support that may be enabled by this technology (Gweon et al., 2006; Wang et al., 2007a; Kumar et al., 2007). Using our automatic process analysis technology, we have achieved almost human reliability on automatic application of an existing collaborative learning process analysis coding scheme (Weinberger & Fischer, 2006) to newsgroup style data from a number of large studies of script based support for computer supported collaborative learning in Germany (Donmez et al., 2005; Wang et al., 2007). Using this same analysis technology in conjunction with adaptive support agents (Wang et al., 2006; Kumar et al., 2006), we have run successful collaborative learning studies both in Taiwan (Wang et al., 2007a) and in the US (Kumar et al., 2007). This inter-disciplinary research endeavor brings together three large bodies of work, namely work on international standards for assessment of achievement in science and math education (Chang, 2005; Chang & Tsai, 2005) from the science education community, text classification technology (Rosé & VanLehn, 2005; Wang et al., 2007) in the language technologies community, and work on scripted collaboration (Weinberger, 2003; Weinberger & Fischer, 2006) in the computer-supported collaborative learning community. An important outcome of our research to date has been the development of the publicly available toolkit, TagHelper tools http://www.cs.cmu.edu/~cprose/TagHelper.html), which has been developed to support the analysis of verbal data using text classification technology.
