Please use this identifier to cite or link to this item: https://repository.isls.org//handle/1/9181
Title: Fostering the Collaborative Diagnosis of Cross-Domain Skills in Video-Based Simulations
Authors: Pickal, Amadeus J.
Engelmann, Katharina
Chinn, Clark A.
Girwidz, Raimund
Neuhaus, Birgit J.
Wecker, Christof
Keywords: CSCL
Issue Date: 2023
Publisher: International Society of the Learning Sciences
Citation: Pickal, A. J., Engelmann, K., Chinn, C. A., Girwidz, R., Neuhaus, B. J., & Wecker, C. (2023). Fostering the collaborative diagnosis of cross-domain skills in video-based simulations. In Damșa, C., Borge, M., Koh, E., & Worsley, M. (Eds.), Proceedings of the 16th International Conference on Computer-Supported Collaborative Learning - CSCL 2023 (pp. 139-146). International Society of the Learning Sciences.
Abstract: Despite the importance of teachers’ diagnostic competences, little is known about how teachers might benefit from interdisciplinary collaboration when diagnosing students’ (cross-domain) skills, like scientific reasoning. The purpose of this study was to investigate whether collaboration improves teachers’ diagnostic accuracy and whether such improvement or the subsequent acquisition of collaborative diagnostic competences is influenced by distribution of information or collaboration support. 194 pre-service teachers generated diagnoses of simulated students, first individually and later in dyads. Depending on the condition, information was either distributed or shared, and collaboration was supported with a collaboration script or not (intervention phase). Results showed that collaborative diagnoses are not per se better, but collaboration support, not distribution of information, can improve diagnostic accuracy. Neither distribution of information nor collaboration support had a significant effect on the acquisition of collaborative diagnostic competences. Further research has to specify how these results can be explained through process data.
Description: Long Paper
URI: https://doi.org/10.22318/cscl2023.638463
https://repository.isls.org//handle/1/9181
Appears in Collections:ISLS Annual Meeting 2023

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