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Rihák, Jirí – International Educational Data Mining Society, 2015
In this work we introduce the system for adaptive practice of foundations of mathematics. Adaptivity of the system is primarily provided by selection of suitable tasks, which uses information from a domain model and a student model. The domain model does not use prerequisites but works with splitting skills to more concrete sub-skills. The student…
Descriptors: Mathematics Achievement, Mathematics Skills, Models, Reaction Time
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Chaplot, Devendra Singh; Yang, Yiming; Carbonell, Jaime; Koedinger, Kenneth R. – International Educational Data Mining Society, 2016
With the growing popularity of MOOCs and sharp trend of digitalizing education, there is a huge amount of free digital educational material on the web along with the activity logs of large number of participating students. However, this data is largely unstructured and there is hardly any information about the relationship between material from…
Descriptors: Graphs, Automation, Instructional Materials, Data
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Backenköhler, Michael; Scherzinger, Felix; Singla, Adish; Wolf, Verena – International Educational Data Mining Society, 2018
Course selection can be a daunting task, especially for first year students. Sub-optimal selection can lead to bad performance of students and increase the dropout rate. Given the availability of historic data about student performances, it is possible to aid students in the selection of appropriate courses. Here, we propose a method to compose a…
Descriptors: Data, Course Selection (Students), Information Utilization, Individualized Instruction