摘要
产学研合作培养研究生是高校全面贯彻党的教育方针、适应社会经济发展的需求、培养具有创新精神和实践能力的高素质人才的有效途径,符合当前经济、科技和教育的发展规律。文章依托江苏省产学研合作培养专业委员会,面向全省研究生培养单位开展产学研合作培养问卷调研,受访主体为现在或曾经从事产学研合作培养工作的研究生、研究生指导教师和高校研究生教育管理人员,以期获取产教融合背景下研究生合作培养情况的有效数据。基于二元logistic回归、多重对应分析和多重响应分析的统计学方法对样本进行分析,探索了影响研究生产学研合作培养成效的主要因素。在实证分析的基础上给出合理化对策。
Cooperation between industries, universities and research to supervise postgraduate students is an effective way for colleges and universities to implement the Party’s education policy, adapt to the needs of social and economic development, and cultivate high-quality talents with innovative spirit and practical ability, which is in line with the current development law of economy, science and technology and education. Relying on the professional committee of industry-university-research cooperation training in Jiangsu Province, this paper carries out a questionnaire survey of industry-university-research cooperation training for graduate training units in Jiangsu Province. The interviewees are graduate students, tutors and education administrators who are or have been engaged in the training programme, in order to obtain effective data of graduate cooperation training under the background of industry education integration. Based on the statistical methods of binary logistic regression, multiple correspondence analysis and multiple response analysis, this paper analyzes the samples, and explores the main factors influencing the effectiveness of research production university research cooperation training. On the basis of empirical analysis, the rationalization countermeasures are given.
作者
胡亚民
全力
刘洁
HU Ya-min;QUAN Li;LIU Jie(Jiangsu University,Zhenjiang 212013,China)
出处
《黑龙江高教研究》
北大核心
2022年第1期94-102,共9页
Heilongjiang Researches on Higher Education
基金
江苏大学2020年“三全育人”应用研究专项课题“研究生工作站在专业学位研究生产教融合培养中的作用探析”(编号:JDSQ202005)
2021年度高校哲学社会科学研究一般项目“新时代研究生教育科教、产教双融合培养体系构建与实践路径探索”(编号:2021SJA2058)。
关键词
研究生产学研合作培养
影响因素
二元LOGISTIC回归
多重对应分析
多重响应分析
cooperative training of research production learning and research
influence factor
binary logistic regression
multiple correspondence analysis
multiple response analysis