Targeted help for spoken dialogue systems: intelligent feedback improves naive users' performance
EACL '03 Proceedings of the tenth conference on European chapter of the Association for Computational Linguistics - Volume 1
Evidence of Misunderstandings in Tutorial Dialogue and their Impact on Learning
Proceedings of the 2009 conference on Artificial Intelligence in Education: Building Learning Systems that Care: From Knowledge Representation to Affective Modelling
Dealing with interpretation errors in tutorial dialogue
SIGDIAL '09 Proceedings of the SIGDIAL 2009 Conference: The 10th Annual Meeting of the Special Interest Group on Discourse and Dialogue
BEETLE II: a system for tutoring and computational linguistics experimentation
ACLDemos '10 Proceedings of the ACL 2010 System Demonstrations
AutoTutor: A simulation of a human tutor
Cognitive Systems Research
BEETLE II: a system for tutoring and computational linguistics experimentation
ACLDemos '10 Proceedings of the ACL 2010 System Demonstrations
EC-TEL'10 Proceedings of the 5th European conference on Technology enhanced learning conference on Sustaining TEL: from innovation to learning and practice
Intelligent tutoring with natural language support in the BEETLE II system
EC-TEL'10 Proceedings of the 5th European conference on Technology enhanced learning conference on Sustaining TEL: from innovation to learning and practice
An affect-enriched dialogue act classification model for task-oriented dialogue
HLT '11 Proceedings of the 49th Annual Meeting of the Association for Computational Linguistics: Human Language Technologies - Volume 1
Talk like an electrician: student dialogue mimicking behavior in an intelligent tutoring system
AIED'11 Proceedings of the 15th international conference on Artificial intelligence in education
Exploring user satisfaction in a tutorial dialogue system
SIGDIAL '11 Proceedings of the SIGDIAL 2011 Conference
Beetle II: an adaptable tutorial dialogue system
SIGDIAL '11 Proceedings of the SIGDIAL 2011 Conference
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Supporting natural language input may improve learning in intelligent tutoring systems. However, interpretation errors are unavoidable and require an effective recovery policy. We describe an evaluation of an error recovery policy in the BEETLE II tutorial dialogue system and discuss how different types of interpretation problems affect learning gain and user satisfaction. In particular, the problems arising from student use of non-standard terminology appear to have negative consequences. We argue that existing strategies for dealing with terminology problems are insufficient and that improving such strategies is important in future ITS research.