基于模糊评价和数据挖掘的教学评估系统设计

Design of teaching evaluation system based on fuzzy evaluation and data mining

为了提升教学评估效率、规范教学评估标准,文中基于B/S架构设计了一套智能教学评估信息系统。该系统在设计时借助软件工程的相关理论进行详尽的需求分析,设计包含用户身份验证、评教基本信息、评教方案设计等模块,覆盖了评估工作的全流程。该系统引入模糊评价算法建立了两级教学评价指标体系,并基于模糊数学理论计算得到各个指标的权重。在数据处理上,采用数据挖掘领域的K-means算法,通过无监督的学习提前对所有采集的评教数据进行分类,显著提升了数据处理的效率。测试结果表明,该系统的评价结果与传统人工评价方法的数据吻合度为89.4%。

In order to improve the teaching evaluation efficiency and standardize the teaching evaluation standards,this paper designs an intelligent teaching evaluation information system based on B/S architecture.The system is designed using software engineering theory for detailed needs analysis.The design includes user authentication,basic information of teaching evaluation,teaching evaluation scheme design and other modules,covering the whole process of evaluation work.The system introduces fuzzy evaluation algorithm to establish a two-level teaching evaluation index system,and calculates the weight of each index based on fuzzy mathematics theory.In data processing,K-means algorithm in the field of data mining is used to classify all the collected teaching evaluation data in advance through unsupervised learning,which significantly improves the efficiency of data processing.The test results show that the evaluation result of the system is 89.4% consistent with the traditional method.