Analysis and application of knowledge points in English network course teaching by using PageRank

Q4 Decision Sciences
Lianmei Deng
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引用次数: 0

Abstract

The research uses PageRank algorithm to calculate the R value of English network teaching knowledge points, and analyses its changes through experiments to give the focus of teaching knowledge points. The results show that learners' enthusiasm for learning English online courses fluctuates significantly, and their final scores are affected by the number of days of study, with the highest pass rate reaching 76.6%. Learners hit the most at the beginning of learning English, which decreased over time, up to 8,650 times. At the same time, the accuracy and recall of PageRank algorithm in knowledge point analysis are at a high level, with the accuracy reaching 88.1%. Using PageRank algorithm to calculate the R value of knowledge points can enable teachers to adjust teaching methods and strategies according to their changes, and learners can also master the learning focus, which is highly practical in the analysis of knowledge points.
运用PageRank分析英语网络课程教学中的知识点及应用
本研究采用PageRank算法计算英语网络教学知识点的R值,并通过实验分析其变化,给出教学知识点的重点。结果表明,学习者学习英语在线课程的积极性波动较大,最终成绩受学习天数的影响较大,通过率最高达到76.6%。学习者在学习英语之初的次数最多,随着时间的推移,次数会减少,最多可达8650次。同时,PageRank算法在知识点分析中的准确率和召回率都处于较高水平,准确率达到了88.1%。利用PageRank算法计算知识点的R值,可以使教师根据知识点的变化调整教学方法和策略,学习者也可以掌握学习重点,在知识点分析中具有很强的实用性。
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来源期刊
International Journal of Networking and Virtual Organisations
International Journal of Networking and Virtual Organisations Decision Sciences-Information Systems and Management
CiteScore
1.40
自引率
0.00%
发文量
25
期刊介绍: IJNVO is a forum aimed at providing an authoritative refereed source of information in the field of Networking and Virtual Organisations.
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