Statistical models for e-learning data |
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Authors: | Silvia Figini Paolo Giudici |
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Institution: | (1) University of Pavia, Strada Nuova 65, Pavia, Italy |
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Abstract: | In this paper we analyse a real e-learning dataset derived from the e-learning platform of the University of Pavia. The dataset
concerns an online learning environment with in-depth teaching materials. The main focus of this paper is to supply a measure
of the relative importance of the exercises (test) at the end of each training unit; to build predictive models of student’s
performance and finally to personalize the e-learning platform. The methodology employed is based on nonparametric statistical
methods for kernel density estimation and generalized linear models and generalized additive models for predictive purposes. |
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Keywords: | E-learning data Predictive models Nonparametric statistical methods |
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