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Modelling user satisfaction and student learning in a spoken dialogue tutoring system with generic, tutoring, and user affect parameters

Forbes-Riley, K and Litman, DJ (2006) Modelling user satisfaction and student learning in a spoken dialogue tutoring system with generic, tutoring, and user affect parameters. In: UNSPECIFIED.

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Abstract

We investigate using the PARADISE framework to develop predictive models of system performance in our spoken dialogue tutoring system. We represent performance with two metrics: user satisfaction and student learning. We train and test predictive models of these metrics in our tutoring system corpora. We predict user satisfaction with 2 parameter types: 1) system-generic, and 2) tutoring-specific. To predict student learning, we also use a third type: 3) user affect. Al-hough generic parameters are useful predictors of user satisfaction in other PARADISE applications, overall our parameters produce less useful user satisfaction models in our system. However, generic and tutoring-specific parameters do produce useful models of student learning in our system. User affect parameters can increase the usefulness of these models. © 2006 Association for Computational Linguistics.


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Details

Item Type: Conference or Workshop Item (UNSPECIFIED)
Status: Published
Creators/Authors:
CreatorsEmailPitt UsernameORCID
Forbes-Riley, K
Litman, DJdlitman@pitt.eduDLITMAN
Centers: University Centers > Learning Research and Development Center (LRDC)
Date: 1 December 2006
Date Type: Publication
Journal or Publication Title: HLT-NAACL 2006 - Human Language Technology Conference of the North American Chapter of the Association of Computational Linguistics, Proceedings of the Main Conference
Page Range: 264 - 271
Event Type: Conference
Schools and Programs: Dietrich School of Arts and Sciences > Computer Science
Dietrich School of Arts and Sciences > Intelligent Systems
Refereed: Yes
Date Deposited: 18 Dec 2014 16:30
Last Modified: 02 Feb 2019 15:59
URI: http://d-scholarship.pitt.edu/id/eprint/23237

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