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Using Partial Credit and Response History to Model User Knowledge., , , and . EDM, page 313-319. International Educational Data Mining Society (IEDMS), (2015)Going Deeper with Deep Knowledge Tracing., , , and . EDM, page 545-550. International Educational Data Mining Society (IEDMS), (2016)An analysis of the impact of action order on future performance: the fine-grain action model., , , and . LAK, page 320-324. ACM, (2015)The Future of Adaptive Learning: Does the Crowd Hold the Key?, , , , , , and . Int. J. Artif. Intell. Educ., 26 (2): 615-644 (2016)Hint Availability Slows Completion Times in Summer Work., , , , , , , , and . EDM, page 388-393. International Educational Data Mining Society (IEDMS), (2016)The assessment of learning infrastructure (ALI): the theory, practice, and scalability of automated assessment., , , , , and . LAK, page 279-288. ACM, (2016)The Effect of the Distribution of Predictions of User Models., , , and . EDM, page 620-621. International Educational Data Mining Society (IEDMS), (2015)Refusing to Try: Characterizing Early Stopout on Student Assignments., , , and . LAK, page 391-400. ACM, (2019)