Abstract
This paper was carried out mainly for the problem of learner model in adaptive learning system, such as the unscientific attention dimension, poor calculated representation method and single and subjective method to obtain feature values. We have put forward a new learner model to achieve self-organization of learning resources on the basis of learning goals and learner’s personal conditions. It includes three feature items such as knowledge level, cognitive ability and preferences. We respectively introduce the representation and acquisition of feature value of learner model in detail. After that, we propose a push mechanism of learning resources. Experimental results show this learner model is effective and practical in the application.
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Jia, B., Yang, Y., Zhang, J. (2011). Representation and Acquisition of Feature Value of Learner Model in Adaptive Learning System. In: Wang, Y., Li, T. (eds) Foundations of Intelligent Systems. Advances in Intelligent and Soft Computing, vol 122. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-25664-6_43
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DOI: https://doi.org/10.1007/978-3-642-25664-6_43
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-25663-9
Online ISBN: 978-3-642-25664-6
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