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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)

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Investigating the Impact of a Real-time, Multimodal Student Engagement Analytics Technology in Authentic Classrooms., , , , , , and . CHI, page 304. ACM, (2019)An unobtrusive and multimodal approach for behavioral engagement detection of students., , , , , and . MIE@ICMI, page 26-32. ACM, (2017)Semi-supervised model personalization for improved detection of learner's emotional engagement., , , , , , , and . ICMI, page 100-107. ACM, (2016)Named Entity Recognition on Twitter for Turkish using Semi-supervised Learning with Word Embeddings., , and . CoRR, (2018)Students' emotional self-labels for personalized models., , , , , , and . LAK, page 550-551. ACM, (2017)Exploring Context, Attention and Audio Features for Audio Visual Scene-Aware Dialog., , , , and . CoRR, (2019)Immersive multi-modal pedagogical conversational artificial intelligence for early childhood education: An exploratory case study in the wild., , , , , , and . Comput. Educ. Artif. Intell., (2024)Modeling Intent, Dialog Policies and Response Adaptation for Goal-Oriented Interactions., , , , and . CoRR, (2019)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)Inspecting Spoken Language Understanding from Kids for Basic Math Learning at Home., , , and . BEA@ACL, page 692-708. Association for Computational Linguistics, (2023)