Please use this identifier to cite or link to this item: https://repository.isls.org//handle/1/7325
Title: Measures of Disagreement in Learning Groups as a Basis for Identifying and Discussing Controversial Judgements
Authors: Malzahn, Nils
Aprin, Farbod
Hoppe, H. Ulrich
Eimler, Sabrina C.
Moder, Sarah
Keywords: CSCL
Issue Date: Jun-2021
Publisher: International Society of the Learning Sciences
Citation: Malzahn, N., Aprin, F., Hoppe, H. U., Eimler, S. C., & Moder, S. (2021). Measures of Disagreement in Learning Groups as a Basis for Identifying and Discussing Controversial Judgements. In Hmelo-Silver, C. E., De Wever, B., & Oshima, J. (Eds.), Proceedings of the 14th International Conference on Computer-Supported Collaborative Learning - CSCL 2021 (pp. 233-236). Bochum, Germany: International Society of the Learning Sciences.
Abstract: Learning scenarios that build on socio-cognitive conflict as a trigger of learning constitute an established approach in collaborative learning. The identification of disagreement is an important premise for this approach. We have selected a measure of disagreement based on a comparative mathematical analysis and have applied it in the context of learning about toxic phenomena and discrimination in social media. The data collected in an online study have been used to test the disagreement measure in combination with a game-based tagging tool.
URI: https://doi.dx.org/10.22318/cscl2021.233
https://repository.isls.org//handle/1/7325
Appears in Collections:ISLS Annual Meeting 2021

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