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Design of Evaluation and Recommendation System for High School Physics Learning Based on Knowledge Graph

机译:基于知识图的高中物理学学习评估与推荐制度设计

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The physics subject examination is an effective way to test how much knowledge the students master. It is important to dig out the information which is beneficial to teaching from students' scores and test papers. Taking classes online is very popular because of COVID-19 this year, and the network teaching evaluation system emerges as the times require. In order to review the qualities of learning by the final examination paper, we designed an intelligence learning evaluation and recommendation system to detect qualities of learning, which is based on knowledge graph and machine learning algorithm. The system analyses test papers and gives reports in detail, so that it's clearly to know pain points and obstructions of physics learning, and gets easy to figure things out. Corresponding personalized teaching content recommendation can improve learning in an efficient way.
机译:物理学科检查是测试学生大师知识的有效方法。重要的是要挖掘有利于学生的分数和测试论文的教学的信息。由于Covid-19今年,在线课程非常受欢迎,并且网络教学评估系统随着时间的需求而出现。为了审查最终考试纸的学习质量,我们设计了一个智能学习评估和推荐系统,以检测学习的质量,基于知识图和机器学习算法。系统分析了测试论文并详细介绍了报告,因此清楚地了解物理学学习的疼痛点和障碍,并且很容易弄清楚。相应的个性化教学内容推荐可以以有效的方式改善学习。

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