Measuring prevalence of other-oriented transactive contributions using an automated measure of speech style accommodation

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This paper contributes to a theory-grounded methodological foundation for automatic collaborative learning process analysis. It does this by illustrating how insights from the social psychology and sociolinguistics of speech style provide a theoretical framework to inform the design of a computational model. The purpose of that model is to detect prevalence of an important group knowledge integration process in raw speech data. Specifically, this paper focuses on assessment of transactivity in dyadic discussions, where a transactive contribution is operationalized as one where reasoning is made explicit, and where that reasoning builds on a prior reasoning statement within the discussion. Transactive contributions can be either self-oriented, where the contribution builds on the speaker's own prior contribution, or other-oriented, where the contribution builds on a prior contribution of a conversational partner. Other-oriented transacts are particularly central to group knowledge integration processes. An unsupervised Dynamic Bayesian Network model motivated by concepts from Speech Accommodation Theory is presented and then evaluated on the task of estimating prevalence of other-oriented transacts in dyadic discussions. The evaluation demonstrates a significant positive correlation between an automatic measure of speech style accommodation and prevalence of other-oriented transacts (R = .36, p < .05).
Publisher
SPRINGER
Issue Date
2013-06
Language
English
Article Type
Article
Keywords

FRAMEWORK; DIALOGUE; SUPPORT; ANALYZE

Citation

INTERNATIONAL JOURNAL OF COMPUTER-SUPPORTED COLLABORATIVE LEARNING, v.8, no.2, pp.245 - 265

ISSN
1556-1607
DOI
10.1007/s11412-013-9172-5
URI
http://hdl.handle.net/10203/174723
Appears in Collection
KSE-Journal Papers(저널논문)
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