高等教育招生-培养-就业联动机制研究综述  

A Review on the Linkage Mechanism of Enrollment,Training and Employment in Higher Education

作　　者：王克勤 王婷[3] 刘伟 蔡志强 WANG Keqin;WANG Ting;LIU Wei

机构地区：[1]西北工业大学教务处,西安710072 [2]西北工业大学管理学院,西安710072 [3]西北工业大学机电学院,西安710072 [4]西北工业大学党委学生工作部,西安710072

出　　处：《高教学刊》2023年第34期17-21,26,共6页Journal of Higher Education

基　　金：陕西本科和高等继续教育教学改革研究重点攻关项目“基于大数据分析的高校招生-培养-就业联动反馈机制研究”(21BG007);陕西本科和高等继续教育教学改革研究一般项目“以‘爱国、敬业’引领构建‘精益、创新’的工业工程专业实验实践教学体系”(21BY008);西北工业大学教育教学改革研究重点攻关项目“基于招生-培养-就业深造大数据的招生计划配置优化方法研究”(2022JGWG03)。

摘　　要：建立招生-培养-就业联动机制是近年教育教学改革领域的热点研究问题。围绕联动指标体系和就业率预测模型的研究,既有文献大体从3个方面进行探索。第一,厘清招生、培养、就业的内在关系,构建契合各高校的联动指标体系;第二,优化主客观赋权法,确定指标权重系数,建立招生就业评价模型;第三,将机器学习算法用于就业率分析预测,并以预测精度为标准比较各个模型的优劣。该文从这3个方面对现有文献进行系统梳理,首先,综合3个一级指标、10个二级指标、42个三级指标,提出一套招生-培养-就业联动指标体系;其次,总结已有模型评价方法,以期对指标权重系数进行科学计算;最后,总结已有就业率预测算法,并分析各个预测模型的优劣之处。Establishing the linkage mechanism of enrollment,training and employment is a hot research issue in the field of education and teaching reform in recent years.Focusing on the linkage index system and employment rate prediction model,the existing literature has generally explored from three aspects.First,it is to clarify the internal relationship,then build each system suitable for each university;second,it is to optimize the subjective and objective weighting methods,determine the weight coefficient,then establish the evaluation model;third,the machine learning algorithm is used to analyze and forecast the employment rate,so the advantages and disadvantages of each model are compared.This paper systematically combs the existing researches from these three aspects,and a set of linkage index system is proposed by integrating 3 first-level indicators,10 second-level indicators and 42 third-level indicators;the existing model-evaluation methods are summarized to calculate the index weight coefficient scientifically.Finally,it is to summarize the existing employment rate prediction algorithms,with the excellence and worseness of each model.

关 键 词：联动机制 招生指标体系 指标权重系数 就业率预测 文献综述 

分 类 号：G640[文化科学—高等教育学]