摘要
为了确保高校教学质量评估的客观性、系统性和全面性,提出利用大数据全面服务教育评估,并基于Hadoop构建评测系统,在Hadoop分布式架构基础上,提出利用分布式算法对高校教学质量各方面进行评估。评测系统主要从学校管理质量、教师教学过程、学生的学习行为以及学业质量等4个方面对高校教学质量进行评估,自下而上划分为数据访问层、业务逻辑层和表示层,各功能子系统均采用模块化设计;针对不同大数据的特点,提出利用主成分分析法对学校管理质量大数据进行评估,采用分布式算法对教师教学过程、学生学习行为和学业质量进行评估;当数据量较小时传统单机算法运行效率较高,当数据量较大(大数据样本)时分布式算法的运行时间明显少于单机算法,且随着数据量的增大,运行效率优势越明显。
In order to ensure the objectivity,systematicness and comprehensiveness of college teaching quality evaluation,we propose to use big data to comprehensively serve education,and build an evaluation system based on Hadoop.On the basis of Hadoop distributed architecture,it is proposed to use distributed algorithms to evaluate all aspects of college teaching quality.The system mainly evaluates the college teaching quality from four aspects:school management quality,teachers’teaching process,students’learning behavior and academic quality.It is divided into data access layer,business logic layer and presentation layer from bottom to top.Each functional subsystem adopts modular design.According to the characteristics of different big data,the principal component analysis method is proposed to evaluate the big data of school management quality,and the distributed algorithm is used to evaluate teachers’teaching process,students’learning behavior and academic quality.When the amount of data is small,the traditional stand-alone algorithm runs more efficiently.When the amount of data is large(big data samples),the running time of the distributed algorithm will be significantly less than that of the stand-alone algorithm.With the increase of the amount of data,the advantage of running efficiency becomes more obvious.
作者
董明
牟云环
DONG Ming;MU Yunhuan(Academy of Computer and Software,Shaanxi Institute of Technology,Xi’an 710300,China)
出处
《微型电脑应用》
2024年第2期26-28,37,共4页
Microcomputer Applications
基金
教育部行业职业教育教学指导委员会2021年职业教育改革创新课题(HBKC216059)。
