摘要
传统的人才培养模式分析能力较差,没有捕捉到社会需求与人才培养之间的相互关系,导致高精尖人才就业方向与所学专业不匹配,最终影响就业人数。因此针对这一现状,设计基于大数据分析的人才培养模式。该模式利用大数据分析技术,根据往年全国学生就业情况,着重分析社会需求与人才培养之间的关联指标;建立"双元化"的教学机制,获取学生投入程度指标,重构以理论为依据、实践为手段的教学体系;通过分析人才供需的正态分布,调整人才培养教学与培训项目,以此建立系统化的人才培养模式。测试结果表明,与传统的人才培养模式相比,此次设计的培养模式分析能力更强,人才就业方向与所学专业更匹配。由此可见,该模式可为社会输出满足发展现状的技术人才。
The traditional talent training mode has poor analysis ability and fails to capture the correlation between social needs and talent training.This has led to a mismatch between the employment direction of sophisticated talents and the majors,and influence on the number of employees.In view of this situation,a talent training mode based on big data analysis is designed.In this mode,the big data analysis technology is used to analyze the relevant indicators between social needs and talent training emphatically according to the employment situation of students in the past years,a"dualistic"teaching mechanism is established to obtain indicators of involvement quantity of students,the teaching system taking the theory as means of basis and practice is reconstructed,and the teaching and training programs for talent cultivation are adjusted by analyzing the normal distribution of talent supply and demand to establish a systematic talent cultivation mode.The testing results show that,in comparison with the traditional talent training mode,the designed training mode has stronger analysis ability,and the employment direction of talents is more matched with their majors.It can be seen that this mode can provide more technical talents meeting the development status for the society.
作者
徐涛
XU Tao(Capital University of Economics and Business,Beijing 100070,China)
出处
《现代电子技术》
北大核心
2020年第20期122-125,共4页
Modern Electronics Technique
基金
北京市自然科学基金(KM20180038002)。
关键词
人才培养
模式设计
大数据分析
就业现状
关联指标分析
教学体系
talent training
mode design
big data analysis
employment status
relevance indicator analysis
teaching system