Abstract
We propose a novel method called Quantitative Multimodal Interaction Analysis to understand the meaning of interactions from a set of multimodal observable behavior. We apply this method for the measurement of collaborative problem-solving skills in a dyadic online game specially designed for this purpose. We outline our assumptions and describe the machine learning approach that help us tag multimodal behaviors connecting the theoretical construct with the empirical evidence.
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Andrade, A., Maddox, B., Edwards, D., Chopade, P., Khan, S. (2019). Quantitative Multimodal Interaction Analysis for the Assessment of Problem-Solving Skills in a Collaborative Online Game. In: Eagan, B., Misfeldt, M., Siebert-Evenstone, A. (eds) Advances in Quantitative Ethnography. ICQE 2019. Communications in Computer and Information Science, vol 1112. Springer, Cham. https://doi.org/10.1007/978-3-030-33232-7_24
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DOI: https://doi.org/10.1007/978-3-030-33232-7_24
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