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Sense, Florian; van der Velde, Maarten; van Rijn, Hedderik – Journal of Learning Analytics, 2021
Modern educational technology has the potential to support students to use their study time more effectively. Learning analytics can indicate relevant individual differences between learners, which adaptive learning systems can use to tailor the learning experience to individual learners. For fact learning, cognitive models of human memory are…
Descriptors: Predictor Variables, Undergraduate Students, Learning Analytics, Cognitive Psychology
O'Connell, Kyle A.; Wostl, Elijah; Crosslin, Matt; Berry, T. Lisa; Grover, James P. – Journal of Learning Analytics, 2018
Historical student data can help elucidate the factors that promote student success in mathematics courses. Herein we use both multiple regression and principal component analyses to explore ten years of historical data from over 20,000 students in an introductory college-level Algebra course in an urban American research university with a diverse…
Descriptors: Mathematics Instruction, Algebra, College Students, College Mathematics
Dvorak, Tomas; Jia, Miaoqing – Journal of Learning Analytics, 2016
This study analyzes the relationship between students' online work habits and academic performance. We utilize data from logs recorded by a course management system (CMS) in two courses at a small liberal arts college in the U.S. Both courses required the completion of a large number of online assignments. We measure three aspects of students'…
Descriptors: Online Courses, Educational Technology, Study Habits, Academic Achievement