The Application Design of Machine Learning in Intelligent Learning Support System

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Abstract:

The key of intelligent learning support system lied in providing personalized service according to different students. Based on cognitive student model, the article designed an intelligent learning support system based on machine learning, which automatically diagnosed students’ cognitive abilities in order to make students in different levels get different depth’s answers, and appropriate level skills training. This would stimulate students' interest in learning and improve students' cognitive ability.

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Periodical:

Advanced Materials Research (Volumes 403-408)

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1535-1538

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Online since:

November 2011

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© 2012 Trans Tech Publications Ltd. All Rights Reserved

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[1] J. Li, The research of adaptive personalized digital library model based on machine learning, Information science, vol. 8, pp.1222-1226, August (2009).

Google Scholar

[2] H. T. Zheng, S. R. Lu, and F. L. Jiang, The application exploration of machine learning in the intelligent management system, Longyan university journal, vol. 25, pp.14-16, June (2010).

Google Scholar

[3] H. Q. Bo. and Q. N. Han, The application research of machine learning in adaptive instructional system, Nanjing normal university Journal, vol. 4, pp.76-79, April (2009).

Google Scholar

[4] K. Chen, and Y. Zhu, The review of machine learning and its related algorithm, Statistics and information BBS, vol. 5, pp.105-112, May (2008).

Google Scholar

[5] Y. Liu, and L. P. He The design and implementation of remote intelligence support service system, Journal of nanjing university of posts and telecommunications (social science edition), vol. 4, pp.44-49, April (2007).

Google Scholar

[6] K. F. Wang, H. Feng, and L. Wang The construction of decision supporting system model in distance learning platform, Computer engineering and application, vol. 8, pp.217-220, August (2009).

Google Scholar