An Early-Warning Method on e-Learning

Jinlong Liu; Zhutian Yang; Xiangyuhan Wang; Xingrui Zhang; Jianying Feng

e-Learning, e-Education, and Online Training. 4th International Conference, eLEOT 2018, Shanghai, China, April 5–7, 2018, Proceedings

Research Article

An Early-Warning Method on e-Learning

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@INPROCEEDINGS{10.1007/978-3-319-93719-9_9,
    author={Jinlong Liu and Zhutian Yang and Xiangyuhan Wang and Xingrui Zhang and Jianying Feng},
    title={An Early-Warning Method on e-Learning},
    proceedings={e-Learning, e-Education, and Online Training. 4th International Conference, eLEOT 2018, Shanghai, China, April 5--7, 2018, Proceedings},
    proceedings_a={ELEOT},
    year={2018},
    month={7},
    keywords={Big data Early-warning e-Learning Prediction modeling Promote teaching effect},
    doi={10.1007/978-3-319-93719-9_9}
}

Jinlong Liu
Zhutian Yang
Xiangyuhan Wang
Xingrui Zhang
Jianying Feng
Year: 2018
An Early-Warning Method on e-Learning
ELEOT
Springer
DOI: 10.1007/978-3-319-93719-9_9

Jinlong Liu¹^,*, Zhutian Yang¹^,*, Xiangyuhan Wang²^,*, Xingrui Zhang¹^,*, Jianying Feng¹^,*

1: Harbin Institute of Technology
2: Harbin No.3 High School

*Contact email: yq20@hit.edu.cn, yangzhutian@hit.edu.cn, wangxyh@yeah.net, zhangxr@hit.edu.cn, fengjy@hit.edu.cn

Abstract

Early-warning is an important way which can promote teaching effect on e-learning. However design a better system of early-warning based on big data is an open issue. This paper systematically analyses five key factors which act on e-learning, compare the effect on early-warning, summarize the insufficient of existing systems. Besides one kind of system framework on e-learning proposed, the system establishes functional model and procedural model for early-warning system. Research results show that the system can promote teaching effect for e-learning and can benefit the development of early-warning model.

Keywords: Big data Early-warning e-Learning Prediction modeling Promote teaching effect

Published: 2018-07-10
Appears in: SpringerLink

: http://dx.doi.org/10.1007/978-3-319-93719-9_9