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JavaTutor: An Intelligent Tutoring System that Adapts to Cognitive and Affective States during Computer Programming.

, , , , , , , , and . SIGCSE, page 599. ACM, (2015)

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Toward Adaptive Unsupervised Dialogue Act Classification in Tutoring by Gender and Self-Efficacy., and . EDM (Workshops), volume 1183 of CEUR Workshop Proceedings, CEUR-WS.org, (2014)Combining Task and Dialogue Streams in Unsupervised Dialogue Act Models., and . SIGDIAL Conference, page 113-122. The Association for Computer Linguistics, (2014)Classifying student dialogue acts with multimodal learning analytics., , , and . LAK, page 280-289. ACM, (2015)A Preliminary Investigation of Learner Characteristics for Unsupervised Dialogue Act Classification., and . EDM, page 373-374. International Educational Data Mining Society (IEDMS), (2014)Choosing to Interact: Exploring the Relationship Between Learner Personality, Attitudes, and Tutorial Dialogue Participation., and . EDM, page 125-128. International Educational Data Mining Society (IEDMS), (2015)Unsupervised modeling for understanding MOOC discussion forums: a learning analytics approach., , , and . LAK, page 146-150. ACM, (2015)RNN for Affects at SemEval-2018 Task 1: Formulating Affect Identification as a Binary Classification Problem., and . SemEval@NAACL-HLT, page 162-166. Association for Computational Linguistics, (2018)In-Context Evaluation of Unsupervised Dialogue Act Models for Tutorial Dialogue., and . SIGDIAL Conference, page 324-328. The Association for Computer Linguistics, (2013)Unsupervised Classification of Student Dialogue Acts with Query-Likelihood Clustering., and . EDM, page 20-27. International Educational Data Mining Society, (2013)A Tutorial Dialogue System for Real-Time Evaluation of Unsupervised Dialogue Act Classifiers: Exploring System Outcomes., and . AIED, volume 9112 of Lecture Notes in Computer Science, page 105-114. Springer, (2015)