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Clustering Students in ASSISTments: Exploring System- and School-Level Traits to Advance Personalization., , , and . EDM, International Educational Data Mining Society (IEDMS), (2017)Do students really learn an equal amount independent of whether they get an item correct or wrong?, , , and . EDM, page 304-305. International Educational Data Mining Society, (2013)Improving Retention Performance Prediction with Prerequisite Skill Features., , and . EDM, page 375-376. International Educational Data Mining Society (IEDMS), (2014)The Effect of the Distribution of Predictions of User Models., , , and . EDM, page 620-621. International Educational Data Mining Society (IEDMS), (2015)Improving Student Modeling Through Partial Credit and Problem Difficulty., , , and . L@S, page 11-20. ACM, (2015)An analysis of the impact of action order on future performance: the fine-grain action model., , , and . LAK, page 320-324. ACM, (2015)Modeling Interactions Across Skills: A Method to Construct and Compare Models Predicting the Existence of Skill Relationships., , and . EDM, page 292-297. International Educational Data Mining Society (IEDMS), (2016)Refining Learning Maps with Data Fitting Techniques: Searching for Better Fitting Learning Maps., , , , , and . EDM, page 413-414. International Educational Data Mining Society (IEDMS), (2014)Creating Instructional Elementary Programming Videos for Use in an Adaptive Testing and Remediation System., , , and . SIGCSE (2), page 1882. ACM, (2024)The Opportunity Count Model: A Flexible Approach to Modeling Student Performance., , , and . L@S, page 113-116. ACM, (2016)