Paper: Modelling User Satisfaction And Student Learning In A Spoken Dialogue Tutoring System With Generic Tutoring And User Affect Parameters

ACL ID N06-1034
Title Modelling User Satisfaction And Student Learning In A Spoken Dialogue Tutoring System With Generic Tutoring And User Affect Parameters
Venue Human Language Technologies
Session Main Conference
Year 2006
Authors

We investigate using the PARADISE framework to develop predictive models of system performance in our spoken di- alogue tutoring system. We represent per- formance with two metrics: user satis- faction and student learning. We train and test predictive models of these met- rics in our tutoring system corpora. We predict user satisfaction with 2 parameter types: 1) system-generic, and 2) tutoring- speci c. To predict student learning, we also use a third type: 3) user affect. Al- hough generic parameters are useful pre- dictors of user satisfaction in other PAR- ADISE applications, overall our parame- ters produce less useful user satisfaction models in our system. However, generic and tutoring-speci c parameters do pro- duce useful models of student learning in our system. User affect para...