Intelligent tutoring systems customize the learning experiences of students. Because no two students have precisely the same learning history, traditional analytic techniques are not appropriate. This paper shows how to compare the learning histories of students and how to compare groups of students in different experimental conditions. A class of randomization tests is introduced and illustrated with data from the AnimalWatch ITS project for elementary school arithmetic.
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