Please use this identifier to cite or link to this item: https://repository.isls.org//handle/1/173
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dc.contributor.authorSiebert-Evenstone, Amanda L.
dc.contributor.authorArastoopour, Golnaz
dc.contributor.authorCollier, Wesley
dc.contributor.authorSwiecki, Zachari
dc.contributor.authorRuis, Andrew R.
dc.contributor.authorShaffer, David Williamson
dc.date.accessioned2017-03-21T12:05:42Z
dc.date.accessioned2017-05-27T14:30:31Z-
dc.date.available2017-03-21T12:05:42Z
dc.date.available2017-05-27T14:30:31Z-
dc.date.issued2016-07
dc.identifier.citationSiebert-Evenstone, A. L., Arastoopour, G., Collier, W., Swiecki, Z., Ruis, A. R., & Shaffer, D. W. (2016). In Search of Conversational Grain Size: Modeling Semantic Structure Using Moving Stanza Windows In Looi, C. K., Polman, J. L., Cress, U., and Reimann, P. (Eds.). Transforming Learning, Empowering Learners: The International Conference of the Learning Sciences (ICLS) 2016, Volume 1. Singapore: International Society of the Learning Sciences.en_US
dc.identifier.urihttps://repository.isls.org/handle/1/173-
dc.identifier.urihttps://dx.doi.org/10.22318/icls2016.82
dc.description.abstractAnalyses of learning based on student discourse need to account not only for the content of the utterances but also for the ways in which students make connections across turns of talk. This requires segmentation of the discourse data to define when connections are likely to be meaningful. In this paper, we present a novel approach to segmenting data for the purposes of modeling connections in discourse. Specifically, we use epistemic network analysis to model connections in student discourse using a temporal segmentation method adapted from recent work in the learning sciences. We compare the results to a purely topic-based segmentation method to examine the affordances of temporal segmentation for modeling connections in discourse.en_US
dc.language.isoenen_US
dc.publisherSingapore: International Society of the Learning Sciencesen_US
dc.titleIn Search of Conversational Grain Size: Modeling Semantic Structure Using Moving Stanza Windowsen_US
dc.typeBook chapteren_US
Appears in Collections:ICLS 2016

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