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An Integrated Look at Middle School Engagement and Learning in Digital Environments as Precursors to College Attendance.

, , and . Technol. Knowl. Learn., 22 (3): 243-270 (2017)

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Student online behaviors: correlations to math identity., , , , , , and . LAK, page 441-445. ACM, (2018)Active Learning for Student Affect Detection., , , , and . EDM, International Educational Data Mining Society (IEDMS), (2019)Hello? Who is posting, who is answering, and who is succeeding in Massive Open Online Courses., , and . EDM, International Educational Data Mining Society (IEDMS), (2019)MOOC Learner Behaviors by Country and Culture; an Exploratory Analysis., , , , , , and . EDM, page 127-134. International Educational Data Mining Society (IEDMS), (2016)Semantic Features of Math Problems: Relationships to Student Learning and Engagement., , , , , and . EDM, page 223-230. International Educational Data Mining Society (IEDMS), (2016)Predicting Student Retention from Behavior in an Online Orientation Course., , , , , , and . EDM, International Educational Data Mining Society (IEDMS), (2017)Effect of student ability and question difficulty on duration., , , and . EDM, page 135-142. International Educational Data Mining Society (IEDMS), (2016)Penetrating the black box of time-on-task estimation., , , , , and . LAK, page 184-193. ACM, (2015)Modeling Learners' Cognitive and Affective States to Scaffold SRL in Open-Ended Learning Environments., , , , , and . UMAP, page 131-138. ACM, (2018)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)