The role of initiative in tutorial dialogue
EACL '03 Proceedings of the tenth conference on European chapter of the Association for Computational Linguistics - Volume 1
Correlations between dialogue acts and learning in spoken tutoring dialogues
Natural Language Engineering
Balancing Cognitive and Motivational Scaffolding in Tutorial Dialogue
ITS '08 Proceedings of the 9th international conference on Intelligent Tutoring Systems
Dialogue Modes in Expert Tutoring
ITS '08 Proceedings of the 9th international conference on Intelligent Tutoring Systems
Using Hidden Markov Models to Characterize Student Behaviors in Learning-by-Teaching Environments
ITS '08 Proceedings of the 9th international conference on Intelligent Tutoring Systems
Going Beyond the Problem Given: How Human Tutors Use Post-Solution Discussions to Support Transfer
International Journal of Artificial Intelligence in Education - "Caring for the Learner" in honour of John Self
The impact of instructor initiative on student learning: a tutoring study
Proceedings of the 40th ACM technical symposium on Computer science education
Modeling learning patterns of students with a tutoring system using Hidden Markov Models
Proceedings of the 2007 conference on Artificial Intelligence in Education: Building Technology Rich Learning Contexts That Work
Beyond the code-and-count analysis of tutoring dialogues
Proceedings of the 2007 conference on Artificial Intelligence in Education: Building Technology Rich Learning Contexts That Work
The Influence of Learner Characteristics on Task-Oriented Tutorial Dialogue
Proceedings of the 2007 conference on Artificial Intelligence in Education: Building Technology Rich Learning Contexts That Work
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
Adapting to Student Uncertainty Improves Tutoring Dialogues
Proceedings of the 2009 conference on Artificial Intelligence in Education: Building Learning Systems that Care: From Knowledge Representation to Affective Modelling
Discovering Tutorial Dialogue Strategies with Hidden Markov Models
Proceedings of the 2009 conference on Artificial Intelligence in Education: Building Learning Systems that Care: From Knowledge Representation to Affective Modelling
Using Natural Language Processing to Analyze Tutorial Dialogue Corpora Across Domains Modalities
Proceedings of the 2009 conference on Artificial Intelligence in Education: Building Learning Systems that Care: From Knowledge Representation to Affective Modelling
To Elicit Or To Tell: Does It Matter?
Proceedings of the 2009 conference on Artificial Intelligence in Education: Building Learning Systems that Care: From Knowledge Representation to Affective Modelling
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
Classifying dialogue in high-dimensional space
ACM Transactions on Speech and Language Processing (TSLP)
Modeling confusion: facial expression, task, and discourse in task-oriented tutorial dialogue
AIED'11 Proceedings of the 15th international conference on Artificial intelligence in education
Exploring effective dialogue act sequences in one-on-one computer science tutoring dialogues
IUNLPBEA '11 Proceedings of the 6th Workshop on Innovative Use of NLP for Building Educational Applications
Predicting facial indicators of confusion with hidden Markov models
ACII'11 Proceedings of the 4th international conference on Affective computing and intelligent interaction - Volume Part I
Toward a machine learning framework for understanding affective tutorial interaction
ITS'12 Proceedings of the 11th international conference on Intelligent Tutoring Systems
Combining verbal and nonverbal features to overcome the 'information gap' in task-oriented dialogue
SIGDIAL '12 Proceedings of the 13th Annual Meeting of the Special Interest Group on Discourse and Dialogue
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Identifying effective tutorial dialogue strategies is a key issue for intelligent tutoring systems research. Human-human tutoring offers a valuable model for identifying effective tutorial strategies, but extracting them is a challenge because of the richness of human dialogue. This paper addresses that challenge through a machine learning approach that 1) learns tutorial strategies from a corpus of human tutoring, and 2) identifies the statistical relationships between student outcomes and the learned strategies. We have applied hidden Markov modeling to a corpus of annotated task-oriented tutorial dialogue to learn one model for each of two effective human tutors. We have identified significant correlations between the automatically extracted tutoring modes and student learning outcomes. This work has direct applications in authoring data-driven tutorial dialogue system behavior and in investigating the effectiveness of human tutoring.