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Predicting Student Aptitude Using Performance History.

, , , and . EDM, page 622-623. International Educational Data Mining Society (IEDMS), (2015)

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A Quasi-Experimental Evaluation of An On-Line Formative Assessment and Tutoring System, , and . Journal of Educational Computing Research, 43 (4): 489--510 (Dec 1, 2010)The assessment of learning infrastructure (ALI): the theory, practice, and scalability of automated assessment., , , , , and . LAK, page 279-288. ACM, (2016)Testing the Validity and Reliability of Intrinsic Motivation Inventory Subscales Within ASSISTments., and . AIED (1), volume 10947 of Lecture Notes in Computer Science, page 381-394. Springer, (2018)Comparing Knowledge Tracing and Performance Factor Analysis by Using Multiple Model Fitting Procedures., , and . Intelligent Tutoring Systems (1), volume 6094 of Lecture Notes in Computer Science, page 35-44. Springer, (2010)An Intelligent Tutoring System Incorporating a Model of an Experienced Human Tutor., and . Intelligent Tutoring Systems, volume 2363 of Lecture Notes in Computer Science, page 596-608. Springer, (2002)Educational Data Mining Workshop., , and . AIED, volume 158 of Frontiers in Artificial Intelligence and Applications, page 716. IOS Press, (2007)Incorporating Rich Features into Deep Knowledge Tracing, , , , and . Proceedings of the Fourth (2017) ACM Conference on Learning @ Scale, page 169--172. New York, NY, USA, ACM, (2017)The ASSISTment Builder: Supporting the Life Cycle of Tutoring System Content Creation., , , , , , and . IEEE Trans. Learn. Technol., 2 (2): 157-166 (2009)Can we predict which groups of questions students will learn from?., , , and . EDM, page 218-225. www.educationaldatamining.org, (2008)The Composition Effect: Conjuntive or Compensatory? An Analysis of Multi-Skill Math Questions in ITS., , , and . EDM, page 147-156. www.educationaldatamining.org, (2008)