Analyzing Sequential Data in Computer-Supported Collaborative Learning

Abstract

Representations and changes between them play a major role in education (e.g., Hewson, Beeth, & Thorley, 1998), problem solving (e.g., Bauer & Reiser, 1990), cognitive development (e.g., Vosniadou & Brewer, 1992), and the history of science (e.g., Kuhn, 1970). By definition, change of representations is also indispensable for collaborative work since a common understanding or shared knowledge can only be achieved by a partial convergence of the knowledge structures of the collaborating subjects. This articles presents and discusses knowledge tracking (KT), viz., an approach to analyze cognition on the basis of symbolic sequential data. We describe the methodological aspects of KT and delineate the Web-based computer program (knowledge tracking engine, KTE) set up to run KT-analyses (http://www.knowledge-tracking.com/). An empirical study in collaborative learning is taken to exemplify the usage of KT in analysis of computer supported collaboration.

Get full access to this article

View all access options for this article.

References

Bauer

M. I.

Reiser

(1990). Incremental envisioning: The flexible use of multiple representations in complex problem solving. In Proceedings of the 12th Annual Conference of the Cognitive Science Society (pp. 317–324).

Cohen

E. G.

(1994). Restructuring the classroom: Conditions for productive small groups. Review of Educational Research, 64, 1–35.

Collins

A. M.

Loftus

E. F.

(1975). A spreading activation theory of semantic processing. Psychological Review, 82, 407–428.

Fischer

(2001). Collaborative knowledge construction—Analysis and facilitation in computer-supported collaboration scenarios. Unpublished Habilitationsschrift [professorial dissertation]. University of Munich.

Fischer

Mandl

(2001). Facilitating the construction of shared knowledge with graphical representation tools in face-to-face and computer-mediated scenarios. In Dillenbourg

Eurelings

Hakkarainen

(Eds.), European perspectives on computer-supported collaborative learning (pp. 230–236). Maastricht: McLuhan Institute.

Gardinger

C. W.

(1990). Handbook of stochastic methods. Berlin: Springer.

Hewson

P. W.

Beeth

M. E.

Thorley

N. R.

(1998). Teaching for conceptual change. In Tobin

K. G.

Fraser

B. J.

(Eds.), International handbook of science education (pp. 199–218). Dordrecht, Netherlands: Kluwer Academic Publishers.

Janetzko

(1996). Knowledge tracking—A method to analyze cognitive structures. IIG-Berichte, 2.

Janetzko

(2000). Selecting and generating concept structures. In Roy

(Ed.), Knowledge management—A micro-level approach. London: Springer.

10.

Janetzko

(2001). Processing raw data both the qualitative and quantitative way. Forum Qualitative Research, 2, February 2001.

11.

Kuhn

(1970). The structure of the scientific revolution (2nd ed.). Chicago: The University of Chicago Press.

12.

O'Donnell

(1996). Effects of explicit incentives on scripted and unscripted cooperation. Journal of Educational Psychology, 88(1), 74–86.

13.

Roschelle

(1996). Learning by collaborating: Convergent conceptual change. In Koschmann

(Ed.), CSCL: Theory and practice of an emerging paradigm (pp. 209–248). Mahwah, NJ: Erlbaum.

14.

Vosniadou

Brewer

W. F.

(1992). Mental models of the earth: A study of conceptual change in childhood. Cognitive Psychology, 24(4), 535–585.