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A Crowdsourcing Approach to Collecting Tutorial Videos - Toward Personalized Learning-at-Scale.

, and . L@S, page 157-160. ACM, (2017)

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MOOC Dropout Prediction: How to Measure Accuracy?, , , , and . L@S, page 161-164. ACM, (2017)A Crowdsourcing Approach to Collecting Tutorial Videos - Toward Personalized Learning-at-Scale., and . L@S, page 157-160. ACM, (2017)Automated Evaluation of Classroom Instructional Support with LLMs and BoWs: Connecting Global Predictions to Specific Feedback., and . CoRR, (2023)Harnessing Label Uncertainty to Improve Modeling: An Application to Student Engagement Recognition., and . FG, page 166-170. IEEE Computer Society, (2018)A discriminative approach to frame-by-frame head pose tracking., and . FG, page 1-7. IEEE Computer Society, (2008)Haar Features for FACS AU Recognition., and . FGR, page 97-101. IEEE Computer Society, (2006)Deep Learning with Domain Randomization for Optimal Filtering., , , and . ICMLA, page 1779-1786. IEEE, (2019)Interdisciplinary Approaches to Getting AI Experts and Education Stakeholders Talking., , , , , and . AIED (2), volume 13356 of Lecture Notes in Computer Science, page 115-118. Springer, (2022)Permutation-Invariant Consensus over Crowdsourced Labels., , and . HCOMP, page 21-30. AAAI Press, (2018)How Does Knowledge of the AUC Constrain the Set of Possible Ground-truth Labelings?. CoRR, (2017)