System Development & Application
|
183-187

Multiple factors based personalized learning recommendation system

Kuang Rong
Yang Zhenguo
Liu Wenyin
School of Science and Technology, Guangdong University of Technology, Guangzhou 510006, China

Abstract

In order to solve the problems existing in the learning recommendation algorithm, such as ignoring the analysis of the students'mastery of knowledge points and failing to probabilize the knowledge mastery, this paper proposed a recommendation method based on multiple factors. The method focused on the comprehensive weight of knowledge points, error rate and loss rate, and built a knowledge point mastery probability model, and applied the proposed strategy to implement an online personalized learning recommendation system. In terms of the systematic evaluation, through a survey of 200 high school students, the accuracy of the top-8 knowledge points recommended by this system achieves 91.2% and F1 achieves 78.4%. The results of the systematic survey reflect the effectiveness and reliability of the proposed strategy.

Foundation Support

国家自然科学基金资助项目(61703109)
广东创新研究团队计划资助项目(2014ZT05G157)

Publish Information

DOI: 10.19734/j.issn.1001-3695.2018.07.0471
Publish at: Application Research of Computers Printed Article, Vol. 37, 2020 No. 1
Section: System Development & Application
Pages: 183-187
Serial Number: 1001-3695(2020)01-038-0183-05

Publish History

[2020-01-05] Printed Article

Cite This Article

匡容, 杨振国, 刘文印. 基于多重因素的个性化学习推荐系统 [J]. 计算机应用研究, 2020, 37 (1): 183-187. (Kuang Rong, Yang Zhenguo, Liu Wenyin. Multiple factors based personalized learning recommendation system [J]. Application Research of Computers, 2020, 37 (1): 183-187. )

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  • Application Research of Computers Monthly Journal
  • Journal ID ISSN 1001-3695
    CN  51-1196/TP

Application Research of Computers, founded in 1984, is an academic journal of computing technology sponsored by Sichuan Institute of Computer Sciences under the Science and Technology Department of Sichuan Province.

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