数据挖掘在高职学生心理健康管理系统中的应用研究

发布时间：2018-02-23 00:56

本文关键词： 数据挖掘心理 C4.5算法 Apriori算法　出处：《郑州大学》2017年硕士论文　论文类型：学位论文

【摘要】：随着我国高等教育的教育类型的发展,目前除了普通高等教育以外,国家开始着力发展高等职业教育。高等职业教育是以培养高等专业技能性人才为目标,致力于解决我国的人口就业问题。与普通高校的大学生一样,高职院校的学生在步入社会的起初也会面临各种各样的心理问题,同时由于高职院校学生普遍成绩较差、比较不自信等,可能会存在更多的心理问题。我国对大学生心理问题的重视程度逐年增加,高校不但成立了心理辅导中心,还慢慢使用了现代化的手段来进行心理教育工作,如采用心理测评软件对学生进行心理普查等。也有一些高校在努力探索研究各种心理干预模式,以便更客观地进行心理疏导和预测工作。数据挖掘技术在许多行业已经有了显著的成效,如果将数据挖掘技术应用到心理数据的挖掘上,其体现出来的优势是其他技术不能相比的。本论文通过对大量的相关文献和资料进行搜集和查阅,对数据挖掘在高职学生心理健康管理系统中的应用进行了探讨。本论文阐述了心理健康教育和数据挖掘的研究现状,并对数据挖掘的定义、主要任务、过程和常用的技术进行了介绍,着重介绍了关联规则和分类分析两类方法,并对其进行了分析比较,确定了使用基于矩阵的Apriori算法和C4.5决策树算法来对心理问题数据进行挖掘分析研究。本文以某高职院校2015级学生的入学心理普查数据对研究对象,通过对数据进行预处理,使用基于矩阵的Apriori算法对心理维度因子间的关系进行了挖掘,得到了关联规则;以人际关系敏感为例构造出决策树模型,并最终提取出分类规则。最后,本文利用ASP.NET和Sqlserver2005等技术,完成了心理健康管理系统中的分析预测模块的开发,增强了该院心理健康管理系统的功能。在文章的最后对系统实现进行了总结和展望。
[Abstract]:With the development of higher education in China, in addition to ordinary higher education, the state has begun to develop higher vocational education. Like the ordinary college students, the students of higher vocational colleges will face various psychological problems at the beginning of entering the society. At the same time, the students of higher vocational colleges generally have poor results. If we are less confident, there may be more psychological problems. In our country, the degree of attention to psychological problems among college students has increased year by year. Colleges and universities have not only set up psychological counseling centers, but also slowly used modern means to carry out psychological education work. For example, psychological assessment software is used to conduct psychological survey of students. Some colleges and universities are also trying to explore and study various psychological intervention models. In order to conduct psychological counseling and prediction more objectively. Data mining technology has achieved remarkable results in many industries. If data mining technology is applied to psychological data mining, Its advantages can not be compared with other technologies. This paper collected and consulted a large number of relevant documents and materials. This paper discusses the application of data mining in the mental health management system of higher vocational students. This paper expounds the current research situation of mental health education and data mining, and defines the data mining. The process and common techniques are introduced, and two kinds of methods, association rules and classification analysis, are introduced and compared. Apriori algorithm based on matrix and decision tree algorithm C4.5 are used to mine and analyze mental problem data. The Apriori algorithm based on matrix is used to mine the relationship between psychological dimension factors, and the association rules are obtained. Taking interpersonal sensitivity as an example, the decision tree model is constructed and the classification rules are extracted. In this paper, the analysis and prediction module of the mental health management system is developed by using ASP.NET and Sqlserver2005 techniques, and the function of the mental health management system is enhanced. At the end of the paper, the realization of the system is summarized and prospected.
【学位授予单位】：郑州大学
【学位级别】：硕士
【学位授予年份】：2017
【分类号】：TP311.13

【相似文献】