【作者】 张婷婷；

【导师】 李冲；

【作者基本信息】 大连理工大学 ， 管理科学与工程（教育管理）， 2023， 博士

【摘要】 为应对新一轮科技革命和产业变革的挑战,中国启动并实施“新工科”建设战略计划,推动企业、高校等多元主体联合培养高质量工程人才。然而,由于产业界与教育界之间的组织壁垒,协同育人效果差强人意。如何有效破解产教认知脱节、育人主体关系冲突和资源配置不均衡等问题,成为突破这一困境的关键。本研究从产业需求的适度嵌入性与多元育人主体关系协同的角度,构建“目标—关系—行动”研究框架,以理论分析与实证研究相结合的方式探讨新工科人才培养的目标嵌入机制、任务协同机制和嵌入式协同的行动机制。首先,论文从产业实际需求出发,研究产业价值链分工对新工科人才培养的目标嵌入机制。基于产业价值链不同分工需求,采用访谈法、内容分析法对新疆、江苏等地区参与产教融合、产学研项目的政、校、企相关责任人进行一对一半结构化访谈,并辅以近五年内相关访谈报道、研究成果等文献资料,使用Max QDA软件对获取的一手和二手资料进行概念节点编码、节点分析和提炼,识别与定位现阶段我国新工科人才培养的目标类型和培养标准。研究结果表明,新工科人才培养目标类型呈“橄榄球”型结构分布。具体而言,位于“橄榄球”两端的卓越精英型和精益工匠型人才需求“少而精”,是服务国家战略发展,实现关键核心技术研发创新的精锐先锋;位于中部的实践创新型、管理复合型、综合应用型人才需求“大而全”,是国家实现产业结构升级,社会经济发展的中坚力量。在人才培养标准上,受育人主体通用性和个性化需求的影响,人才培养目标被进一步分解成知识、能力、素质子模块,并以自由搭配、灵活组合的方式形成新工科人才培养的具体标准。其次,论文以知识整合为育人主体关系匹配的纽带,研究新工科人才培养的任务协同机制。围绕多元主体关系匹配、知识整合与协同育人效果之间的关系机理,建立结构方程模型并提出研究假设。采用问卷调查法,通过线上线下相结合的方式对参与产学研合作、产教融合的企业、高校发放问卷,分两阶段进行数据收集与汇总,获取充足可靠的一手研究数据。使用AMOS软件对结构方程模型进行信度与效度检验、模型拟合优度检验和多元回归分析,探寻多元主体协同育人的任务关系匹配与任务协同机制。研究发现,多元主体关系匹配是以价值一致和战略互补为内外驱动力,通过知识整合实现协同育人任务。具体而言,价值一致对知识整合和协同育人效果的影响不显著;战略互补对知识整合和协同育人效果影响显著,是育人主体参与新工科人才培养的主要动力来源。知识整合是任务协同的中介“桥梁”,通过“战略互补性→知识交互→知识融通→协同育人效果”的路径协调多元育人主体的协同关系与互动。再次,论文聚焦中国工业发展的现实背景,研究面向工业4.0生产模块的新工科人才培养嵌入式协同行动机制。以“数智化人才”培养为切入点,从目标维、标准维和结构维三重维度出发,构建新工科人才培养嵌入式协同行动机制模型。采用多案例分析法,选取教育部“2021年度产学合作协同育人”优秀项目中多个典型案例为样本来源,通过实地调研、官媒报道、网络信息公开等多渠道获取一手和二手可靠资料,借助Max QDA软件对样本数据进行内容分析。研究结果显示,产业价值链分工需求嵌入“数智化人才”培养目标与培养标准;育人主体根据各自需求选择子模块任务,通过对接模块通用性指标和个性化指标,实现任务关系匹配并建立协同育人行动网络。其中,“外循环”机制将产业需求嵌入协同育人关系网络;“内循环”机制通过价值一致和战略互补驱动资源流动与跨组织合作,形成松散耦合抑或紧密耦合的关系网络;由“外循环”和“内循环”互动形成的“双循环”机制,构成了新工科人才培养的嵌入式协同行动系统。最后,论文围绕新工科人才培养的目标嵌入机制、任务协同机制和嵌入式协同行动机制角度出发,提出完善我国新工科人才培养机制的对策建议。一是树立“融合创新”的大工程人才培养观,注重产业价值链分工的多样化需求导向,强化教育、科技、人才内在联系,促进多元主体间利益融合与价值共创。二是适应产业需求变化,确立多类型结构的新工科人才培养目标,制定通专融合的新工科人才培养标准体系。三是协调多元主体协同育人任务关系匹配,不仅要拓宽育人主体协同关系的广度,还要增强育人主体协同关系的深度,促进短期任务与长期任务动态平衡。四是落实多元主体协同育人嵌入式协同行动,建立松散耦合与紧密耦合共存的行动关系网络,推动“双循环”协同育人系统行动并完善嵌入式协同人才培养的制度保障体系。更多还原

【Abstract】 In order to cope with the new round of scientific and technological revolution and industrial technological change,China has initiated and implemented the strategic plan of "Emerging Engineering Education",and carried out collaborative education programs such as industry-teaching fusion,industry-academia collaboration,and school-enterprise collaboration,which have promoted the joint cultivation of high-quality talents by enterprises,colleges and universities and other diversified subjects,and promoted the upgrading of the industrial structure and the transformation of enterprises in terms of digital intelligence.However,due to the existence of institutional barriers between industry and education,the cognitive disconnect between industry and education,the conflict between the relationship between the main bodies of training and the uneven allocation of resources,resulting in the contradiction between industrial demand and the supply of talents,the lack of enthusiasm of enterprises to participate in the collaborative training action is difficult to coordinate and other phenomena.How to balance the moderate embedding of industrial demand and the functional synergy between multiple subjects has become the key point to solve the above contradictions and differences.Based on these,this dissertation analyzes the internal mechanism of "cognition-goal","relationship-task" and "structure-action",builds the research framework of "goal-relationship-action" and adopted the technical route combining content analysis,structural equation modeling and multi-case analysis to explore the target embedding mechanism of industrial value chain division of labor situation on emerging engineering talents cultivation,the task synergistic mechanism matching the relationship of multiple subjects,and the embedded coordination system action mechanism of emerging engineering talents training,so as to explore the following issues.First of all,this part of dissertation focused on the embedding mechanism of emerging engineering talents training in the context of industrial value chain.Based on the theory of situational cognition embedding,this research identified and positioned the type structure and standard of emerging engineering talents training at present.First of all,the theoretical framework was designed,and the interview and content analysis method were used to interview the enterprises,universities and governments in collaborative education.Secondly,the training objectives and standards of emerging engineering talents were determined by Max QDA software.The analysis result shows that the demand for structural type of emerging engineering talents is like football shape.The middle of industrial value chain demanded the largest number of applied and interdisciplinary talents.A small number of elite and artisan talents are needed at both ends of the value chain.Finally,the industrial value chain needs both general and personalized standards for the emerging engineering talents training.Those results provided the goal guidance for multi-educator relationship matching.Secondly,this part of dissertation focused on the relationship matching in the task coordination mechanism of collaborative education.Based on embedding theory and organization-stakeholder fit theory,this research conducted a questionnaire survey on the university and enterprise in the industry-university collaborative education programs.Firstly,the theoretical model and research hypothesis were established.Then select research objects from the fusion of education and issue questionnaires.Secondly,SPSS software and AMOS software were used to test the model fitting accuracy,reliability and validity of the collected data.Finally,the driving factors and practice path of the sub-research hypothesis were verified and discussed.The analysis results of structural equation model shows that the value congruence has no significant effect on talent training and knowledge integration ability.The strategic complementary has a significant positive impact on the educational effect,and it is the main driving force for matching the relationship between education and industry.The path of collaborative education is based on knowledge interaction,and it achieves relational connectivity through knowledge fusion.The knowledge integration plays a connecting role in collaborative education.Thirdly,this part of dissertation focused on the action coordination mechanism of modular system structure.Based on the concept of modularization and embedded collaboration,this sub research construct the embedded collaborative module system of emerging engineering talents training for Industry 4.0 value chain in China.Then appropriate outcome cases from domestic school-running collaborative projects were selected to analyze the internal mechanism and action mechanism of the digital and intelligent technology talents with the Max QDA software.The final result shows that the demand of industrial value chain is divided into knowledge goals,ability goals and quality goals in the training of digital and intelligent technical talents.Educators chose suitable partners according to different task requirements.The collaborative relationship network within the module is composed of universality and individuation index flexibly.And the establishment of an embedded collaborative mechanism for the cultivation of emerging engineering talents are an circular function of both internal and external.Finally,based on the above research conclusions,the last part of this dissertation focuses on three core mechanisms of action: target embedding,relational synergy,and system action.Then put forward three suggestions: The first is to establish a "Integration and Innovation" concept of big engineering.The second is to multiple types of training objectives and standards in emerging engineering talents training.The third is to coordinate the breadth and depth of the collaborative education relationship between multiple subjects.The fourth is to implement the embedded collaborative action of multi-agent collaborative education,and establish the multi-coupling relationship network to achieve the "double cycle" collaborative education system action and improve the system of embedded collaborative talent training.更多还原