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What's Most Broken? A Tool to Assist Data-Driven Iterative Improvement of an Intelligent Tutoring System.

, , and . AAAI, page 9941-9942. AAAI Press, (2019)

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Adapting a duration synthesis model to rate children's oral reading prosody., and . INTERSPEECH, page 769-772. ISCA, (2010)Predictable and educational spoken dialogues: pilot results., and . SLaTE, page 141-144. ISCA, (2009)Detecting prosody improvement in oral rereading., and . SLaTE, page 105-108. ISCA, (2009)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)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)