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

  • Gahgene Gweon
  • Mahaveer Jain
  • John McDonough
  • Bhiksha Raj
  • Carolyn P. Rosé
Article
First Online:

Abstract

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).

Keywords

Transactivity Speech-based assessment Machine learning Speech style accommodation 
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Notes

Acknowledgments

This work was supported in part by NSF grant SBE 0836012 to the Pittsburgh Science of Learning Center. We gratefully acknowledge John Levine and Timothy Nokes from the University of Pittsburgh for sharing their data with us for these experiments.

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Copyright information

© International Society of the Learning Sciences, Inc. and Springer Science+Business Media New York 2013

Authors and Affiliations

  • Gahgene Gweon
    • 1
  • Mahaveer Jain
    • 2
  • John McDonough
    • 2
  • Bhiksha Raj
    • 2
  • Carolyn P. Rosé
    • 2
  1. 1.Knowledge Service EngineeringKorea Advanced Institute of Science and TechnologyDaejeonRepublic of Korea
  2. 2.Language Technologies InstituteCarnegie Mellon UniversityPittsburghUSA

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