摘要
针对现有计算机辅助教学模式中普遍存在的信息利用率差,智能性、个性化较低等问题,设计一种基于数据挖掘的计算机辅助课堂教学系统。该系统模块设计采用三层B/S结构。利用信息收集模块实现学生信息数据的收集与存储;用户信息预处理模块将信息数据进行预处理后,作为个性化数据分析模块中个性化数据源的数据。通过个性化数据分析模型,采用数据挖掘并行化技术,通过K-means聚类算法和Map Reduce并行计算框架更新数据聚类中心,将聚类性能指标最小化,对个性化数据源内的数据进行有效挖掘分析,对分析后的结论进行规则化生成教学规则,通过人机交互呈现给学生,以提升教学系统的智能化与个性化。实验结果表明,该系统能够有效提升学生学习效率,资源占用率降低32.4%以上。
As for the problems of poor information utilization,low intelligence and individuality in the current computer⁃aided teaching mode,a computer⁃aided classroom teaching system based on data mining is designed.The three⁃layer B/S structure is used in the module design of the system.The students′information data is collected and stored with the information collection module,which is taken as data of the personalized data source in the personalized data analysis module after the information data is preprocessed with the user information preprocessing module.In the personalized data analysis model,the data clustering center is updated with the data mining parallelization technology by means of the K⁃means clustering algorithm and Map Reduce parallel computing framework.The clustering performance indexes are minimized to effectively mine and analyze data in the personalized data sources,the conclusion is regularized to generate teaching rules,and presented to students by means of the human⁃computer interaction,so as to promote the intelligence and personalization of the teaching system.The experimental results show that the system can effectively improve students′learning efficiency and reduce the occupancy rate of its resources by more than 32.4%.
作者
周俊萍
ZHOU Junping(Air Force Engineering University,Xi’an 710051,China)
出处
《现代电子技术》
北大核心
2020年第2期84-86,共3页
Modern Electronics Technique
基金
陕西省自然科学基础研究计划项目（2017JQ6074）
空军工程大学基础部科研基金项目(JK2019123)
关键词
数据挖掘
计算机辅助教学
课堂教学
信息收集
数据分析
教学规则
data mining
computer⁃aided teaching
classroom teaching
information collection
data analysis
teaching rule
