Peer Assessment Based on the User Preference Matrix

机译：基于用户偏好矩阵的对等评估

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Peer assessment not only provides a solution to inefficient teacher-student interaction between the students and teachers at universities, but can effectively improve the students’ learning efficiency. However, students are seldom engaged in peer assessment tasks and the scores they get from peer assessment differ from those given by the teachers. An automatic ranking method for English essays based on the user preference matrix and the stochastic gradient descent method was proposed in this study. Experiments showed that this new method could improve the performance of the stochastic gradient descent method when the credibility of the student’s evaluation was considered. Teachers can obtain the rankings of students’ essays by analyzing a few peer-assessment scores obtained by this method and optimize their teaching strategies accordingly.

机译：同行评估不仅可以解决大学学生和教师之间的效率效率的效率，而且可以有效提高学生的学习效率。但是，学生很少从事同伴评估任务，并且从同伴评估中获得的分数不同于教师给出的分数。本研究提出了一种基于用户偏好矩阵和随机梯度下降方法的英语散文的自动排序方法。实验表明，当考虑学生评估的可信度时，这种新方法可以提高随机梯度下降法的性能。教师可以通过分析通过这种方法获得的几个同行评估分数来获得学生散文的排名，并相应地优化其教学策略。

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《International Conference on Artificial Intelligence and Education》|2020年|1-4|共4页
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作者
Zhisen Fan; Meixiu LU; Xia Li;
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Training; Mathematical model; Task analysis; Predictive models; Matrix converters; Machine learning; Stochastic processes;

机译：培训;数学模型;任务分析;预测模型;矩阵转换器;机器学习;随机过程;

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3. Collaborative filtering based on user's hidden preference model -extraction user's preference from user's rating [J] . Kawamae Noriaki 電子情報通信学会技術研究報告. デ-タ工学. Data Engineering . 2003,第104期

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机译：基于决策矩阵的用户偏好采集方法研究

Peer Assessment Based on the User Preference Matrix

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