Summary

Analysis of discourse data promises insights into the processes of (computer-supported) collaborative learning on multiple levels, from individual to group level processes of thinking and learning. Here we cover segmentation of data, arriving at a coding scheme, coder training and interrater-reliability, aggregation of coded data, and computational tools to support the coding of data.

Syllabi and Slides

Analysis of Discourse Data - Quantifying Qualities slides by Karsten Stegmann and Armin Weinberger

Video Resources

Analysis of Discourse Data - Quantifying Qualities webinar as audio file (.mp3)

Reading:

• Stegmann, K., & Fischer, F. (2011). Quantifying qualities in collaborative knowledge construction: The analysis of online discussions. In Analyzing Interactions in CSCL (pp. 247-268). Springer US.

Additional Reading:

• De Wever, B., Schellens, T., Valcke, M., & Van Keer, H. (2006). Content analysis schemes to analyze transcripts of online asynchronous discussion groups: A review. Computers & Education, 46(1), 6–28. doi:10.1016/j.compedu.2005.04.005
• Mu, J., Stegmann, K., Mayfield, E., Rosé, C. & 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), 285–305.
• Weinberger, A., & Fischer, F. (2006). A framework to analyze argumentative knowledge construction in Computer-Supported Collaborative Learning. Computers and Education, 46(1), 71–95. doi:10.1016/j.compedu.2005.04.003
• Weinberger, A., Stegmann, K., & Fischer, F. (2007). Knowledge convergence in collaborative learning: Concepts and assessment. Learning and Instruction, 17(4), 416-426. doi:10.1016/j.learninstruc.2007.03.007

Learning Scientists Who Have Researched This Topic:

• Michelle Chi
• Bram de Wever
• Gregory Dyke
• Diane Kuhn
• Selma Leitão
• Kris Lund
• Carolyn Rosé
• Karsten Stegmann
• Jan-Willem Strijbos
• Armin Weinberger