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Demonstration of a Reading Coach that Listens.

, , and . ACM Symposium on User Interface Software and Technology, page 77-78. ACM, (1995)

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Predicting Task Completion from Rich but Scarce Data., and . EDM, page 291-292. www.educationaldatamining.org, (2010)Demonstration of a Reading Coach that Listens., , and . ACM Symposium on User Interface Software and Technology, page 77-78. ACM, (1995)Exploiting Predictable Response Training to Improve Automatic Recognition of Children's Spoken Responses., , and . Intelligent Tutoring Systems (1), volume 6094 of Lecture Notes in Computer Science, page 65-74. Springer, (2010)Adding Human-Provided Emotional Scaffolding to an Automated Reading Tutor That Listens Increases Student Persistence., , , , and . Intelligent Tutoring Systems, volume 2363 of Lecture Notes in Computer Science, page 992. Springer, (2002)A Bayes Net Toolkit for Student Modeling in Intelligent Tutoring Systems., , , and . Intelligent Tutoring Systems, volume 4053 of Lecture Notes in Computer Science, page 104-113. Springer, (2006)What's Most Broken? Design and Evaluation of a Tool to Guide Improvement of an Intelligent Tutor., , and . AIED (1), volume 11625 of Lecture Notes in Computer Science, page 283-295. Springer, (2019)Comparing Student Models in Different Formalisms by Predicting Their Impact on Help Success, , , and . Artificial Intelligence in Education, volume 7926 of Lecture Notes in Computer Science, Springer Berlin Heidelberg, (2013)Using Automatic Question Generation to Evaluate Questions Generated by Children., , and . AAAI Fall Symposium: Question Generation, volume FS-11-04 of AAAI Technical Report, AAAI, (2011)Maximal Consistent Interpretations of Errorful Data in Hierarchically Modeled Domains., and . IJCAI, page 165-171. William Kaufmann, (1977)When do Students Interrupt Help? Effects of Time, Help Type, and Individual Differences., , and . AIED, volume 125 of Frontiers in Artificial Intelligence and Applications, page 819-826. IOS Press, (2005)