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Supervised by Ministry of Industry and Information Technology of The People's Republic of China Sponsored by Harbin Institute of Technology Editor-in-chief Yu Zhou ISSNISSN 1005-9113 CNCN 23-1378/T

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Related citation:Chi Zhang,Huan Yan,Ying Fu,Guofeng Han,Fan Feng.Advances in Educational Data Mining Models and the Application of Its Algorithms[J].Journal of Harbin Institute Of Technology(New Series),2016,23(6):32-40.DOI:10.11916/j.issn.1005-9113.2016.06.005.
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Advances in Educational Data Mining Models and the Application of Its Algorithms
Author NameAffiliation
Chi Zhang School of Material Science and EngineeringHarbin Institute of Technology, Harbin 150001, China 
Huan Yan School of Material Science and EngineeringHarbin Institute of Technology, Harbin 150001, China 
Ying Fu School of Material Science and EngineeringHarbin Institute of Technology, Harbin 150001, China 
Guofeng Han School of Material Science and EngineeringHarbin Institute of Technology, Harbin 150001, China 
Fan Feng School of Material Science and EngineeringHarbin Institute of Technology, Harbin 150001, China 
Abstract:
In order to find an effective way to improve the quality of school management, finding valuable information from students’ original data and providing feedback for student management are necessary. Firstly, some new and successful educational data mining models were analyzed and compared. These models have better performance than traditional models (such as Knowledge Tracing Model) in efficiency, comprehensiveness, ease of use, stability and so on. Then, the neural network algorithm was conducted to explore the feasibility of the application of educational data mining in student management, and the results show that it has enough predictive accuracy and reliability to be put into practice. In the end, the possibility and prospect of the application of educational data mining in teaching management system for university students was assessed.
Key words:  educational data mining models  student grade management  neural network
DOI:10.11916/j.issn.1005-9113.2016.06.005
Clc Number:TP391
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