Please use this identifier to cite or link to this item: https://repository.isls.org/handle/1/805
Title: The Sequential Analysis, Modeling and Visualization of Collaborative Causal Mapping Processes and Effects on Causal Understanding
Authors: Jeong, Allan
Lee, Woon Jee
Issue Date: Jun-2013
Publisher: International Society of the Learning Sciences
Citation: Jeong, A. & Lee, W. J. (2013). The Sequential Analysis, Modeling and Visualization of Collaborative Causal Mapping Processes and Effects on Causal Understanding. In Rummel, N., Kapur, M., Nathan, M., & Puntambekar, S. (Eds.) (2013). To See the World and a Grain of Sand: Learning across Levels of Space, Time, and Scale: CSCL 2013 Conference Proceedings Volume 1 - Full Papers &Symposia. International Society of the Learning Sciences. pp. 248-255.
Abstract: This paper describes a case study that illustrates how particular techniques and two developed software applications can be used to sequentially analyze, model, and visualize the processes and discourse student produce while working collaboratively in pairs to construct a causal diagram. The analysis was conducted at various levels in order to model students' map construction processes, the map construction processes in conjunction with students' discourse, and processes observed within each group versus across all groups. Transitional state diagrams produced from the sequential analysis of each group's behaviors revealed unique sequential patterns in the processes used between the three groups. These observed processes provide potential explanations for the observed differences in the accuracy of the maps between the groups. The implications of the findings and directions for further refinements to the techniques and software tools are identified and discussed in further detail.
URI: https://doi.dx.org/10.22318/cscl2013.V1-248-255
https://repository.isls.org/handle/1/805
Appears in Collections:CSCL 2013

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