Carolyn Rosé: Learning analytics and educational data mining in learning discourses
Basic reading
Rosé, C., Wang, Y., Cui, Y., Arguello, J., Stegman, K., Weinberger, A., & Fischer, F. (2008). Analyzing collaborative learning processes automatically: Exploiting the advances of computational linguistics in computer-supported collaborative learning. International Journal of Computer-Supported Collaborative Learning, 3(3), 237-271. [Online]
Additional reading
Gweon, G., Jain, M., Mc Donough, J., Raj, B., Rosé, C. P. (in press).Measuring prevalence of other-oriented transactive contributions using an automated measure of speech style accommodation. International Journal of Computer Supported Collaborative Learning.
Howley, I., Mayfield, E. & Rosé, C. P. (2013).Linguistic analysis methods for studying small groups. In C. E. Hmelo-Silver, A. O’Donnell, C. Chan & C. Chin (Eds.), International Handbook of Collaborative Learning. Taylor and Francis, Inc.
Mayfield, E. & Rosé, C. P. (2013). LightSIDE: Open Source Machine Learning for Text Accessible to Non-Experts. Invited chapter in the Handbook of Automated Essay Grading. Routledge Academic Press.
Mu, J., Stegmann, K., Mayfield, E., Rosé, C. P., Fischer, F. (2012). The ACODEA Framework: Developing Segmentation and Classification Schemes for Fully Automatic Analysis of Online Discussions.International Journal of Computer Supported Collaborative Learning, 7(2), pp285-305.
Rosé, C. P. & Tovares, A. (in press). What sociolinguistics and machine learning have to say to one another about interaction analysis. In L. Resnick, C. Asterhan & S. Clarke (Eds.), Socializing Intelligence Through Academic Talk and Dialogue. Washington, DC: American Educational Research Association.
