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- W1848288052 abstract "Adaptive Learning Systems offer customized learning experiences according to the actual student needs and capabilities. Effective student modelling, adequate representation of the knowledge domain and proper characterization of learning tools are key issues to provide high quality Adaptive Learning Systems. Most current systems are based on Artificial Intelligence techniques (e.g. fuzzy logic, neural networks, Bayesian networks, etc.) trying to reproduce human teaching behaviours by using a computational representation of expertise. This paper offers a survey on Adaptive Learning showing how Computational Science techniques are applied to instructional systems and identifying forthcoming trends for the future." @default.
- W1848288052 created "2016-06-24" @default.
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- W1848288052 date "2003-01-01" @default.
- W1848288052 modified "2023-09-26" @default.
- W1848288052 title "Applying Computational Science Techniques to Support Adaptive Learning" @default.
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- W1848288052 doi "https://doi.org/10.1007/3-540-44862-4_116" @default.
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