The Architecture of Why2-Atlas: A Coach for Qualitative Physics Essay Writing
ITS '02 Proceedings of the 6th International Conference on Intelligent Tutoring Systems
Describing the emotional states that are expressed in speech
Speech Communication - Special issue on speech and emotion
Correlations between dialogue acts and learning in spoken tutoring dialogues
Natural Language Engineering
Predicting student emotions in computer-human tutoring dialogues
ACL '04 Proceedings of the 42nd Annual Meeting on Association for Computational Linguistics
Responding to Student Uncertainty in Spoken Tutorial Dialogue Systems
International Journal of Artificial Intelligence in Education
Exploiting discourse structure for spoken dialogue performance analysis
EMNLP '06 Proceedings of the 2006 Conference on Empirical Methods in Natural Language Processing
Investigating Human Tutor Responses to Student Uncertainty for Adaptive System Development
ACII '07 Proceedings of the 2nd international conference on Affective Computing and Intelligent Interaction
An overview of spoken language technology for education
Speech Communication
Inferring tutorial dialogue structure with hidden Markov modeling
EdAppsNLP '09 Proceedings of the Fourth Workshop on Innovative Use of NLP for Building Educational Applications
Modeling dialogue structure with adjacency pair analysis and hidden Markov models
NAACL-Short '09 Proceedings of Human Language Technologies: The 2009 Annual Conference of the North American Chapter of the Association for Computational Linguistics, Companion Volume: Short Papers
Leveraging hidden dialogue state to select tutorial moves
IUNLPBEA '10 Proceedings of the NAACL HLT 2010 Fifth Workshop on Innovative Use of NLP for Building Educational Applications
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
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We use X2 to investigate the context dependency of student affect in our computer tutoring dialogues, targeting uncertainty in student answers in 3 automatically monitorable contexts. Our results show significant dependencies between uncertain answers and specific contexts. Identification and analysis of these dependencies is our first step in developing an adaptive version of our dialogue system.