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普及化初级阶段高等教育学生规模增长与结构优化 被引量:8

Scale Growth and Structure Optimization of Higher Education Student in the Early Stages of Universal Access Phase
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摘要 在高等教育普及化初级阶段,伴随学生规模继续增长,结构也应不断优化。20世纪后期,美国学者、智库和政府机构对于其高等教育学生规模预测的误差较大,原因之一在于对学生结构变化预判不足。采用趋势外推,GDP、人口、适龄人口单因素,以及高等教育在学总规模和适龄人口双因素等方法进行测算,我国高等教育毛入学率的规划目标有望再次提前实现。在继续关注学生规模和规划目标的同时,应认真思考学生的多样性趋势,提升学历层次结构,加快发展专业学位研究生教育,适度超前布局博士研究生招生规模;明确职业教育定位,发展多种层次和形式的职业教育;完善成人教育政策法规体系,拓展非学历和非全日制教育,迈向高等教育普及化中级乃至高级阶段。 In the early stage of universal access higher education,the structure should be optimized further following the scale conscious growth.In the late 20th century,the prediction error of higher education students,by some America schoolers,think tanks,and government agents,was large,with one of causes by inadequate prediction of student structure change.The prediction is made by the methods,such as trend extrapolation,some single factors including GDP,population,and 18-22 years’old population,as well as double factors of total scale of higher education and 18-22 years’old population.The target of gross enrolment ratio is expected to be implemented ahead of schedule again.The trend of student diversity should be considered more,while concerning to the student scale and planning objective.It is recommended to heighten the structure of educational level,to develop postgraduate education for professional degree,to advance the distribution of doctoral student recruitment appropriately;to define the position of vocational education,and to develop multiple levels and forms of it;to improve the system of adult education policies and regulations,and to extend non-degree and part-time education,so as to move forward to the intermediate and advanced phases of universal access.
作者 张炜 ZHANG Wei(Northwestern Polytechnical University,Xi'an 710072;China Association of Higher Education,Beijing 100191)
出处 《中国高教研究》 CSSCI 北大核心 2022年第6期11-18,共8页 China Higher Education Research
基金 国家自然科学基金委管理学部2020年第1期应急管理项目“新时代行业特色高校治理模式与创新发展研究”(72041014)的研究成果。
关键词 普及化 毛入学率 规模增长 结构优化 预测方法 universal access gross enrolment ratio scale growth structure optimization prediction methodology
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