数据挖掘在教学诊断与改进中的智能算法的应用研究  

Research of Data Mining Intelligent Algorithm Used in Teaching Diagnoses and Improvement

作　　者：何晶[1] 范宏宇[1] 杨海卉[1] HE Jing;FAN Hong-yu;YANG Hai-hui

机构地区：[1]安徽机电职业技术学院教务处,安徽芜湖241002

出　　处：《安徽职业技术学院学报》2021年第3期34-37,68,共5页Journal of Anhui Vocational & Technical College

基　　金：2017年安徽省质量工程项目“人才培养状态数据库的数据挖掘在教学诊断与改进工作中的应用”(2017jyxm0796)。

摘　　要：数据挖掘是实现高职院校教学诊断与改进人才培养要素全覆盖、提高诊改结果的实时性与真实性、进一步健全内部质量保证体系的重要手段。文章对数据挖掘在教学诊断与改进工作中的智能算法进行分析,通过对决策树ID3算法的改进,从海量数据中提取出来潜在的、深层次的以及有价值的信息以供决策者及时准确的进行教学诊断,及时做出改进,提升自我诊断改进的准确性、及时性。Data mining is an important method to realize teaching diagnoses and to improve the full coverage of personal training elements and the real time and authenticity of diagnoses and reform results.It can further improve the internal quality assurance system.The intelligent algorithm of data mining in teaching diagnoses and improvement is analyzed in this paper.Through the improvement of decision tree ID3 algorithm,potential,deep and valuable information is extracted from massive data for decision makers to make timely and accurate teaching diagnosis,make timely improvement.The accuracy and timeliness of self-diagnoses is improved in this paper.

关 键 词：数据挖掘 ID3算法 教学诊断 

分 类 号：G712[文化科学—职业技术教育学]