基于决策树的高校计算机等级考试成绩预测分析研究

发布时间：2018-05-26 10:38

本文选题：高校计算机等级考试 + 决策树　；参考：《广西大学》2013年硕士论文

【摘要】：作为高校非计算机专业学生必须通过的一种计算机水平考试——高校计算机等级考试,是由教育部所属全国各省、市、自治区教育厅主持、各高校考务办公室具体负责组织实施的。考试每年举行两次,目前各高校教务部门积累了大量与考试相关的数据,但对这些数据的利用大部分只停留在成绩的上报、备份、统计和查询等,隐藏在成绩背后与成绩有相关联如学生数据、课程数据、教师数据、考试数据没有得到全面挖掘,对考试、教学潜在有用价值的信息没有得到充分利用。全面的、深层次地对这些数据进行挖掘,找出潜在的影响高校计算机等级考试成绩的重要关键因素和有用规则,不仅利于提高考试的通过率,而且利于提高教学质量。数据挖掘技术是数据库、人工智能、信息检索等多领域结合发展的新技术。使用它可以从数据库中存在的大量信息挖掘出潜在的知识或者发现有用的规则。数据挖掘技术不仅可以对历史数据作出描述,也可以对未来数据作出预测。决策树是数据挖掘技术中的常用的技术,已经广泛应用于不同领域。本文通过发放问卷调查表方式获取学生信息数据,通过教务管理系统获取学生成绩数据,以这两部分数据为数据源,借助数据挖掘工具软件SPSS,使用决策树技术CRT方法及计算机编程语言的相关技术,对高校计算机等级考试成绩及其相关信息进行数据挖掘。然后综合运用概率论、数理统计知识等对挖掘的数据及结果分析研究,作出科学合理的解释。本文研究的结果建立了高校计算机等级考试成绩合格的分类模型,找出潜在的影响高校计算机等级考试成绩的重要关键因素；发现了考试成绩合格分类的有用规则。根据这些规则,可以给学校相关部门提供考试管理和教学改革的理论参考,以便改善教学质量和考试管理水平；提高高校计算机等级考试的合格率。运用分类模型,可以预测学生考试的通过率。
[Abstract]:As a kind of computer level examination that students of non-computer major in colleges and universities must pass, the computer grade examination of colleges and universities is presided over by the education department of the provinces, municipalities and autonomous regions affiliated to the Ministry of Education. The examination office of each university is specifically responsible for organizing the implementation. The examination is held twice a year. At present, the educational administration departments of colleges and universities have accumulated a large amount of examination-related data, but most of these data are used only in the reporting, backup, statistics and inquiry of results. Hidden behind the results and results are related to such as student data, curriculum data, teacher data, test data has not been fully mined, test, teaching potential useful value of information has not been fully utilized. Comprehensively and deeply mining these data and finding out the important key factors and useful rules that may affect the results of computer grade examination in colleges and universities are not only conducive to improving the pass rate of the examination but also to the quality of teaching. Data mining technology is a new technology which combines database, artificial intelligence, information retrieval and other fields. It can be used to mine potential knowledge or find useful rules from the vast amount of information that exists in the database. Data mining technology can not only describe historical data, but also predict future data. Decision tree is a common technology in data mining, which has been widely used in different fields. In this paper, students' information data are obtained by questionnaire, students' achievement data are obtained by educational administration system, and these two parts of data are used as data sources. With the help of the data mining tool software SPSS, using the decision tree technology CRT method and the related technology of computer programming language, this paper carries on the data mining to the university computer grade examination result and its related information. Then the data and results of mining are analyzed and studied by means of probability theory, mathematical statistics and so on, and scientific and reasonable explanation is made. The results of this paper set up a classification model of college computer grade examination scores, find out the potential important key factors that affect the college computer grade examination results, and find out the useful rules for the classification of college computer grade examination results. According to these rules, the theoretical reference of examination management and teaching reform can be provided to the relevant departments in schools, in order to improve the teaching quality and examination management level, and to improve the qualified rate of computer grade examinations in colleges and universities. By using the classification model, the pass rate of students can be predicted.
【学位授予单位】：广西大学
【学位级别】：硕士
【学位授予年份】：2013
【分类号】：TP3-4;G642.474

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