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Understanding in-video dropouts and interaction peaks inonline lecture videos

, , , , , and . Proceedings of the first ACM conference on Learning@ scale conference, page 31-40. ACM, (2014)

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Instructor Dashboards In EdX., , , , and . L@S, page 335-336. ACM, (2016)Model-Based Collaborative Filtering Analysis of Student Response Data: Machine-Learning Item Response Theory., , , , , and . EDM, page 95-102. www.educationaldatamining.org, (2012)Getting to Know English Language Learners in MOOCs: Their Motivations, Behaviors, and Outcomes., , , , , and . L@S, page 209-212. ACM, (2017)Itero: A Revision History Analytics Tool for Exploring Writing Behavior and Reflection., , and . CHI Extended Abstracts, ACM, (2018)Exploring the relationship between course structure and etext usage in blended and open online courses., , and . EDM, page 350-351. International Educational Data Mining Society, (2013)Adapting Bayesian Knowledge Tracing to a Massive Open Online Course in edX., , , and . EDM, page 137-144. International Educational Data Mining Society, (2013)Delving Deeper into MOOC Student Dropout Prediction., , , , and . CoRR, (2017)A MOOC based on blended pedagogy., , , , , , , , and . J. Comput. Assist. Learn., 32 (3): 190-201 (2016)Analysis of Video Use in edX Courses., , , , and . AIED Workshops, volume 1009 of CEUR Workshop Proceedings, CEUR-WS.org, (2013)Probabilistic Use Cases: Discovering Behavioral Patterns for Predicting Certification., , and . L@S, page 141-148. ACM, (2015)