计算机与现代化

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基于高校学生综合素质测评数据预测职业发展方向的案例研究

  

  1. (东北师范大学信息与软件工程学院,吉林 长春 130117)
  • 收稿日期:2017-03-17 出版日期:2017-11-21 发布日期:2017-11-21
  • 作者简介:刘志勇(1977-),男,吉林长春人,东北师范大学信息与软件工程学院副教授,博士,研究方向:教育技术学; 元佳茜(1989-),女(朝鲜族),黑龙江绥化人,硕士研究生,研究方向:教育数据挖掘。
  • 基金资助:
    国家科技支撑计划项目(2014BAH22F03, 2014BAH22F05)

A Case Study to Predict Career Development by Comprehensive Quality Evaluation Data of College Students

  1. (School of Information and Software Engineering, Northeast Normal University, Changchun 130117, China)
  • Received:2017-03-17 Online:2017-11-21 Published:2017-11-21

摘要: 在高校学生就业指导问题的研究中,利用教学管理过程中积累的大量数据,采用数据挖掘方法为指导工作提供客观依据已经成为一种广泛认可的方式。本文针对目前数据维度单一、数据分析方法简单、数据应用不够深入的问题开展案例研究,基于近5年教育部某直属师范院校学生综合素质测评数据,使用分类规则、关联规则等方法,通过灰色预测算法建模对学生的职业发展方向进行预测,为高校学生管理工作者的工作施行提供客观依据。结果表明该方法的预测精度最高可达81.82%。

关键词: 数据挖掘, 灰色预测算法, 高校学生职业生涯规划, 学生职业发展

Abstract: Around the research on the employment guidance of college students, it has become a widely accepted way that uses a large amount of data accumulated in the process of teaching management and data mining methods to provide an objective basis for guiding the work. In this paper, we study a case to solve some problems such as the data dimension is single, the data analysis method is simple and the data application is not enough. Based on the comprehensive quality evaluation data of a normal university students in the past five years, we predict the students career development direction by using the grey prediction model, classification rules, association rules, etc. And we can provide the objective basis of work implementation for college student management workers. The result shows that the accuracy of prediction is up to 81.82%.

Key words: data mining, grey prediction, career planning of college students, students career development

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