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Data-Driven Feedback Beyond Next-Step Hints.

, and . EDM, page 444-446. International Educational Data Mining Society (IEDMS), (2014)

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Extracting Measures of Active Learning and Student Self-Regulated Learning Strategies from MOOC Data., , , and . EDM, page 583-584. International Educational Data Mining Society (IEDMS), (2016)Estimating the Local Size and Coverage of Interaction Network Regions.. EDM, page 671-673. International Educational Data Mining Society (IEDMS), (2015)Experimental Evaluation of Automatic Hint Generation for a Logic Tutor., , , and . AIED, volume 6738 of Lecture Notes in Computer Science, page 345-352. Springer, (2011)Predicting Individualized Learner Models Across Tutor Lessons., , , and . EDM, International Educational Data Mining Society (IEDMS), (2018)Modeling Student Dropout in Tutoring Systems., and . Intelligent Tutoring Systems, volume 8474 of Lecture Notes in Computer Science, page 676-678. Springer, (2014)Exploring networks of problem-solving interactions., , , and . LAK, page 21-30. ACM, (2015)Communities of Performance & Communities of Preference., , , , , , , , and . EDM (Workshops), volume 1446 of CEUR Workshop Proceedings, CEUR-WS.org, (2015)Using sequential pattern mining to increase graph comprehension in intelligent tutoring system student data (abstract only)., , , and . SIGCSE, page 732. ACM, (2013)The EDM Vis Tool., , , and . EDM, page 349-350. www.educationaldatamining.org, (2011)Data-Driven Generation of Rubric Parameters from an Educational Programming Environment., , , , , and . AIED, volume 10331 of Lecture Notes in Computer Science, page 490-493. Springer, (2017)