数据挖掘在高校第二课堂管理中的应用研究

发布时间：2018-06-13 03:44

本文选题：第二课堂系统 + 决策树ID3　；参考：《河北工业大学》2015年硕士论文

【摘要】：第二课堂是指传统的课堂教学之外的教学活动,包括学科竞赛、学术论文、科研活动、校园文化活动、社会实践、社会活动、体育竞赛等有利于学生综合素质提高和身心健康发展的各种活动,是高校素质教育的重要组成部分。随着中国大学本科生招生规模不断扩大,学生的数量迅速增长,因此与学生相关的数据也大大增加,其中包括学生参与第二课堂的数据,这时如何做好数据相关的工作是当前发展的必然要求。开发基于数据挖掘的第二课堂精细化管理系统,将学生在第二课堂中所获得的成果与学分有机结合,把系统作为学生参与第二课堂情况的评价载体,不仅达到量化管理的效果,还能挖掘更好的第二课堂教育策略,调动学生学习的主观能动性、参与的积极性,达到培育能力、陶冶情操、提高素质的目的,提高人才培养效率。首先,本文分析数据挖掘技术中的决策树分类算法,选择ID3算法进行深入研究,探究基于粗糙集理论的ID3算法与传统ID3算法的比较,并提出改进,提高基于粗糙集理论的ID3算法的运算效率。然后,用改进后的基于粗糙集理论的ID3算法分析影响第二课堂成绩的因素,得出是否加入学生组织是影响学生参与第二课堂活动的关键因素等一系列实验结果。最后,依据高校第二课堂管理现状,设计并实现了基于数据挖掘的高校第二课堂管理系统,系统设计了数据查询、数据录入、数据分析和报表的功能,并建立了灵活的管理后台和个性化的个人中心,实现了应用系统的数据集构建影响第二课堂成绩因素的决策树。该系统的建立,提高了第二课堂管理效率,并给出了支持第二课堂教学方案的决策建议,达到了促进提升学生综合素质的目的。
[Abstract]:The second classroom refers to teaching activities other than traditional classroom teaching, including subject competitions, academic papers, scientific research activities, campus cultural activities, social practices, social activities, Sports competition is an important part of quality education in colleges and universities, which is beneficial to the improvement of students' comprehensive quality and the development of physical and mental health. As the enrollment of undergraduate students in Chinese universities continues to expand, the number of students is growing rapidly, so the number of student-related data, including data on students' participation in the second class, has increased significantly. At this time, how to do a good job of data-related work is the inevitable requirement of current development. The second classroom fine management system based on data mining is developed. The results obtained by students in the second class are organically combined with the credits, and the system is regarded as the evaluation carrier of students' participation in the second classroom, which not only achieves the effect of quantitative management. It can also tap better second classroom education strategies, arouse students' subjective initiative in learning, participate in the initiative, achieve the purpose of cultivating ability, edifying sentiment, improving quality, and improving the efficiency of talent training. First of all, this paper analyzes the decision tree classification algorithm in data mining technology, selects ID3 algorithm for in-depth study, explores the comparison between ID3 algorithm based on rough set theory and traditional ID3 algorithm, and proposes some improvements. The computation efficiency of ID3 algorithm based on rough set theory is improved. Then, the improved ID3 algorithm based on rough set theory is used to analyze the factors that affect the second classroom performance, and a series of experimental results are obtained, such as whether joining the student organization is the key factor affecting the students' participation in the second class. Finally, according to the current situation of the second classroom management in colleges and universities, the second classroom management system based on data mining is designed and implemented. The functions of data query, data input, data analysis and report form are designed. A flexible management background and a personalized personal center are established, and the data set of the application system is implemented to construct the decision tree that affects the factors of the second classroom achievement. With the establishment of the system, the efficiency of the second classroom management is improved, and the decision suggestion to support the second classroom teaching scheme is given, which achieves the purpose of promoting the students' comprehensive quality.
【学位授予单位】：河北工业大学
【学位级别】：硕士
【学位授予年份】：2015
【分类号】：G642.4;TP311.13

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