Analysis of Discourse Data
Summary
Contributor: Armin Weinberger (Saarland University)
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.
These abstracts are living documents provided and modified by NAPLeS members. The more contributions we have towards refining the documents the more representative they will be of the community as a whole. If you would like to suggest revisions, please contact [email protected].
Syllabi and Slides
Video Resources
Watch the full webinar on Analysis of Discourse Data featuring Karsten Stegmann and Armin Weinberger:
Listen to the Analysis of Discourse Data webinar
Reading
Basic 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