基于粒子群算法的研究生英语教学效果智能评价模型

Jingxian Ma
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引用次数: 0

摘要

在对研究生英语学习效果进行分析和评价的基础上,提出了一种智能评价模型。该模型将粒子群算法应用到研究生成绩分析系统中。该算法通过分析教务系统中的学生成绩数据,找出课程之间的内在联系。据此,教务人员可以科学地安排教学工作。结果表明,该方法对研究生英语教学的评价效果最好,平均评价准确率达90%,评价时间短,测试时间短于10 ms。该模型提高了研究生英语教学评价的准确性和效率,满足了教学的要求。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Intelligent Evaluation Model for Postgraduate English Teaching Effectiveness Based on PSO Algorithm
Based on the analysis and evaluation of the effectiveness of postgraduate English learning, an intelligent evaluation model is proposed. This model applies the PSO algorithm to the achievement analysis system of graduate students. This algorithm analyzes student achievement data in the educational administration system to find out the internal relationship between courses. Based on the result, the educational administration staff can arrange teaching work scientifically. The results show that the method has the best effect on the evaluation of postgraduate English teaching with an average evaluation accuracy of 90%, a short evaluation time, and a test time shorter than 10 ms. This model improves the accuracy and efficiency of the evaluation of postgraduate English teaching and meets the requirements of teaching.
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