Abstract
Data mining methods have in recent years enabled the development of more sophisticated student models which represent and detect a broader range of student behaviors than was previously possible. This chapter summarizes key data mining methods that have supported student modeling efforts, discussing also the specific constructs that have been modeled with the use of educational data mining. We also discuss the relative advantages of educational data mining compared to knowledge engineering, and key upcoming directions that are needed for educational data mining research to reach its full potential.
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Baker, R.S.J.d. (2010). Mining Data for Student Models. In: Nkambou, R., Bourdeau, J., Mizoguchi, R. (eds) Advances in Intelligent Tutoring Systems. Studies in Computational Intelligence, vol 308. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-14363-2_16
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DOI: https://doi.org/10.1007/978-3-642-14363-2_16
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