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Semi-supervised model personalization for improved detection of learner's emotional engagement.

, , , , , , , and . ICMI, page 100-107. ACM, (2016)

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Towards an Emotional Engagement Model: Can Affective States of a Learner be Automatically Detected in a 1: 1 Learning Scenario?, , , , , , , , and . UMAP (Extended Proceedings), volume 1618 of CEUR Workshop Proceedings, CEUR-WS.org, (2016)Human Expert Labeling Process: Valence-Arousal Labeling for Students' Affective States., , , , and . MIS4TEL, volume 804 of Advances in Intelligent Systems and Computing, page 53-61. Springer, (2018)Towards Human Affect Modeling: A Comparative Analysis of Discrete Affect and Valence-Arousal Labeling., , , , and . HCI (29), volume 851 of Communications in Computer and Information Science, page 372-379. Springer, (2018)Behavioral Engagement Detection of Students in the Wild., , , , , and . AIED, volume 10331 of Lecture Notes in Computer Science, page 250-261. Springer, (2017)Natural Language Interactions in Autonomous Vehicles: Intent Detection and Slot Filling from Passenger Utterances., , , , and . CICLing (2), volume 13452 of Lecture Notes in Computer Science, page 334-350. Springer, (2019)Students' emotional self-labels for personalized models., , , , , , and . LAK, page 550-551. ACM, (2017)Towards Understanding Emotional Reactions of Driver-Passenger Dyads in Automated Driving., , , , and . FG, page 585-592. IEEE Computer Society, (2018)Learner Engagement Measurement and Classification in 1: 1 Learning., , , , , , , , , and . ICMLA, page 545-552. IEEE, (2014)Role of Socio-cultural Differences in Labeling Students' Affective States., , , , and . AIED (1), volume 10947 of Lecture Notes in Computer Science, page 367-380. Springer, (2018)Annotating Student Engagement Across Grades 1-12: Associations with Demographics and Expressivity., , , , and . AIED (1), volume 12748 of Lecture Notes in Computer Science, page 42-51. Springer, (2021)