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Mining Students Pre-instruction Beliefs for Improved Learning., , , , , and . L@S, page 15:1-15:10. ACM, (2019)Large atom number Bose-Einstein condensate machines, , , , , , , , and . Review of Scientific Instruments, 77 (2): 023106 (2006)Estimation of ability from homework items when there are missing and/or multiple attempts., , and . LAK, page 118-125. ACM, (2015)Cooling neutral atoms in a magnetic trap for precision spectroscopy. Physical Review Letters, 51 (15): 1336 (1983)Atom trapping with a thin magnetic film, , , , , , and . Physical Review A (Atomic, Molecular, and Optical Physics), (2007)Model-Based Collaborative Filtering Analysis of Student Response Data: Machine-Learning Item Response Theory., , , , , and . EDM, page 95-102. www.educationaldatamining.org, (2012)Factor Analysis Reveals Student Thinking using the Mechanics Reasoning Inventory., , , , and . L@S, page 197-200. ACM, (2017)Mining Student Misconceptions from Pre- and Post-Testing Data., , and . EDM, International Educational Data Mining Society (IEDMS), (2018)Bringing student backgrounds online: MOOC user demographics, site usage, and online learning., , , , , and . EDM, page 312-313. International Educational Data Mining Society, (2013)Are MOOC Learning Analytics Results Trustworthy? With Fake Learners, They Might Not Be!, , , , and . Int. J. Artif. Intell. Educ., 29 (4): 484-506 (2019)