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La Mort du Chercheur: How well do students' subjective understandings of affective representations used in self- report align with one another's, and researchers'?

, , , , , and . EDM (Workshops), volume 1446 of CEUR Workshop Proceedings, CEUR-WS.org, (2015)

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Reengineering the Feature Distillation Process: A case study in detection of Gaming the System., , , and . EDM, page 284-287. International Educational Data Mining Society (IEDMS), (2014)Student online behaviors: correlations to math identity., , , , , , and . LAK, page 441-445. ACM, (2018)Semantic Features of Math Problems: Relationships to Student Learning and Engagement., , , , , and . EDM, page 223-230. International Educational Data Mining Society (IEDMS), (2016)Improving Engagement in an E-Learning Environment., , , , and . AIED, volume 9112 of Lecture Notes in Computer Science, page 730-733. Springer, (2015)Modeling Learners' Cognitive and Affective States to Scaffold SRL in Open-Ended Learning Environments., , , , , and . UMAP, page 131-138. ACM, (2018)Modeling the Relationships Between Basic and Achievement Emotions in Computer-Based Learning Environments., , , , , , and . AIED (1), volume 12163 of Lecture Notes in Computer Science, page 411-422. Springer, (2020)WTF? Detecting Students Who Are Conducting Inquiry Without Thinking Fastidiously., , , , and . UMAP, volume 7379 of Lecture Notes in Computer Science, page 286-296. Springer, (2012)Field Observations of Engagement in Reasoning Mind., , , , and . AIED, volume 7926 of Lecture Notes in Computer Science, page 624-627. Springer, (2013)Using natural language processing tools to develop complex models of student engagement., , , , , and . ACII, page 542-547. IEEE Computer Society, (2017)The Influence of School Demographics on the Relationship Between Students' Help-Seeking Behavior and Performance and Motivational Measures., , and . EDM, International Educational Data Mining Society (IEDMS), (2019)