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A learning style classification approach based on deep belief network for large-scale online education

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成果类型:
期刊论文
作者:
Zhang, Hao*;Huang, Tao;Liu, Sanya;Yin, Hao;Li, Jia;...
通讯作者:
Zhang, Hao
作者机构:
[Li, Jia; Liu, Sanya; Zhang, Hao; Huang, Tao; Xia, Yu; Yang, Huali] Cent China Normal Univ, Natl Engn Lab Educ Big Data, Wuhan, Peoples R China.
[Li, Jia; Liu, Sanya; Zhang, Hao; Huang, Tao; Xia, Yu; Yang, Huali] Cent China Normal Univ, Natl Engn Res Ctr E Learning, Wuhan, Peoples R China.
[Yin, Hao] Shenyang Univ, Coll Informat Engn, Shenyang, Peoples R China.
通讯机构:
[Zhang, Hao] C
Cent China Normal Univ, Natl Engn Lab Educ Big Data, Wuhan, Peoples R China.
Cent China Normal Univ, Natl Engn Res Ctr E Learning, Wuhan, Peoples R China.
语种:
英文
关键词:
Large-scale online education;Adaptive learning;Deep belief network;Learning style;High-dimensional
期刊:
Journal of Cloud Computing
ISSN:
2192-113X
年:
2020
卷:
9
期:
1
页码:
1-17
基金类别:
National Key Research and Development Program of China [2017YFB1401300, 2017YFB1401304, 2017YFB1401303]; National Natural Science Foundation of ChinaNational Natural Science Foundation of China (NSFC) [61702211, 61977033, L1724007]; Hubei Provincial Science and Technology Program of China [2017AKA191]; Fundamental Research Funds for the Central UniversitiesFundamental Research Funds for the Central Universities [CCNU19QD004, CCNU17GF0002]
机构署名:
本校为第一且通讯机构
院系归属:
国家数字化学习工程技术研究中心
摘要:
With the rapidly growing demand for large-scale online education and the advent of big data, numerous research works have been performed to enhance learning quality in e-learning environments. Among these studies, adaptive learning has become an increasingly important issue. The traditional classification approaches analyze only the surface characteristics of students but fail to classify students accurately in terms of deep learning features. Meanwhile, these approaches are unable to analyze these high-dimensional learning behaviors in massive...

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