基于数据挖掘算法的高校英语专业教学质量评估系统设计  

Design of teaching quality evaluation system for college English majors based on data mining algorithms

作　　者：韦珊杉 单珂 宋瑞雪 Wei Shanshan;Shan Ke;Song Ruixue(Jilin Institute of Architecture and Technology,Changchun 130000,China)

机构地区：[1]吉林建筑科技学院,吉林长春130000

出　　处：《无线互联科技》2024年第8期36-39,共4页Wireless Internet Technology

基　　金：吉林省高等教育学会《中国式现代化进程中吉林省应用型本科高校英语专业发展的新路径》,项目编号:JGJX2023D807。

摘　　要：文章设计并实现了基于数据挖掘算法的高校英语专业教学质量评估系统,以SLIQ数据挖掘算法为核心,通过分析教学过程中产生的大规模数据,识别影响教学质量的关键因素。系统结构设计包括数据收集与预处理、特征选择、教学质量评估模型构建等模块,确保了从数据处理到分析的高效性和准确性。系统测试在模拟实际应用场景的环境下进行,包括响应时间、系统吞吐量、教学质量评估准确率等关键指标的评估。测试结果显示,系统具备良好的性能和高准确度,能够作为提升高校英语教学质量的有效工具。The aim of this study is to design and implement a data mining algorithm based evaluation system for the teaching quality of English majors in universities.With SLIQ data mining algorithm as the core,the system analyzes large-scale data generated during the teaching process and identifies key factors that affect teaching quality.The system architecture design includes modules such as data collection and preprocessing,feature selection and construction of teaching quality evaluation models,ensuring efficiency and accuracy from data processing to analysis.System testing is conducted in an environment that simulates actual application scenarios,including the evaluation of key indicators such as response time,system throughput and accuracy of teaching quality evaluation.The test results show that the system has good performance and high accuracy,and can serve as an effective tool to improve the quality of English teaching in universities.

关 键 词：数据挖掘算法 英语专业 教学质量评估 

分 类 号：G31[文化科学]