In Search of Conversational Grain Size: Modelling Semantic Structure Using Moving Stanza Windows

Autor/inn/en	Siebert-Evenstone, Amanda L.; Irgens, Golnaz Arastoopour; Collier, Wesley; Swiecki, Zachari; Ruis, Andrew R.; Shaffer, David Williamson
Titel	In Search of Conversational Grain Size: Modelling Semantic Structure Using Moving Stanza Windows
Quelle	In: Journal of Learning Analytics, 4 (2017) 3, S.123-139 (17 Seiten)Infoseite zur Zeitschrift PDF als Volltext kostenfreie Datei Verfügbarkeit
Sprache	englisch
Dokumenttyp	gedruckt; online; Zeitschriftenaufsatz
ISSN	1929-7750
Schlagwörter	Semantics; Discourse Analysis; Models; Epistemology; Network Analysis; Comparative Analysis; Cooperative Learning; Engineering; Engineering Education; College Students; Internship Programs + Suchen Sie Ihr Suchwort? Semantik; Diskursanalyse; Analogiemodell; Erkenntnistheorie; Netzplantechnik; Kooperatives Lernen; Maschinenbau; Ingenieurausbildung; Collegestudent; Berufspraktische Ausbildung
Abstract	Analyses 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 discourse data to define when connections are likely to be meaningful. In this paper, we present an approach to segmenting data for the purposes of modeling connections in discourse using epistemic network analysis. 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 of this study to a purely conversation-based segmentation method to examine the affordances of temporal segmentation for modeling connections in discourse. (As Provided).
Anmerkungen	Society for Learning Analytics Research. 121 Pointe Marsan, Beaumont, AB T4X 0A2, Canada. Tel: +61-429-920-838; e-mail: info@solaresearch.org; Web site: http://learning-analytics.info/journals/index.php/JLA/
Erfasst von	ERIC (Education Resources Information Center), Washington, DC
Update	2020/1/01