Abstract
We present a so-called supervised educational recommendation framework in this paper aiming to recommend those programming tasks for a student which improve his skills and performance. The main issue of this approach is an appropriate student model w.r.t. his skills and other implicit factors. The student model can be derived from the solutions provided by the student and the teacher's (textual as well as numerical) evaluation of these solutions. © 2013 Springer-Verlag.
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CITATION STYLE
Pero, Š. (2013). Modeling programming skills of students in an educational recommender system. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 7899 LNCS, pp. 401–404). https://doi.org/10.1007/978-3-642-38844-6_49
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