Resolving pronominal reference to abstract entities
Resolving pronominal reference to abstract entities
Computational Linguistics
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
Deep linguistic processing for spoken dialogue systems
DeepLP '07 Proceedings of the Workshop on Deep Linguistic Processing
Classification errors in a domain-independent assessment system
EANL '08 Proceedings of the Third Workshop on Innovative Use of NLP for Building Educational Applications
Scaling POMDPs for Spoken Dialog Management
IEEE Transactions on Audio, Speech, and Language Processing
AutoTutor: A simulation of a human tutor
Cognitive Systems Research
The impact of interpretation problems on tutorial dialogue
ACLShort '10 Proceedings of the ACL 2010 Conference Short Papers
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
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
Evaluating language understanding accuracy with respect to objective outcomes in a dialogue system
EACL '12 Proceedings of the 13th Conference of the European Chapter of the Association for Computational Linguistics
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We describe an approach to dealing with interpretation errors in a tutorial dialogue system. Allowing students to provide explanations and generate contentful talk can be helpful for learning, but the language that can be understood by a computer system is limited by the current technology. Techniques for dealing with understanding problems have been developed primarily for spoken dialogue systems in informationseeking domains, and are not always appropriate for tutorial dialogue. We present a classification of interpretation errors and our approach for dealing with them within an implemented tutorial dialogue system.