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作 者:林萍 伍琳瑜[1] LIN Ping;WU Linyu(School of Management,Nanjing University of Posts&Telecommunications,Nanjing 210003;Research Center of Information Industry Integrated Innovation&Emergency Management,Nanjing University of Posts&Telecommunications,Nanjing 210003,China)
机构地区:[1]南京邮电大学管理学院,江苏南京210003 [2]南京邮电大学信息产业融合创新与应急管理研究中心,江苏南京210003
出 处:《物流技术》2023年第10期157-160,共4页Logistics Technology
基 金:南京邮电大学教学改革项目“基于OBE理念的商务数据分析类课程教学内容与方法的改革与研究”(JG00119JX93);南京邮电大学教学改革项目“经管类课程以评促学的过程性评价探索与实践”(JG01118JX40)。
摘 要:基于数据需求方视角,以国内企业主导的供应链相关数据大赛为突破口,剖析供应链数据分析人才的能力要求。赛事分析结果表明,数据获取能力、分析能力、表达能力是数据分析人才应具备的基本素质,多目标决策、多模态数据、多方法融合是数据分析人才应具备的重要技能。因此,借鉴“全视角学习理论”,将数据大赛以多元化形式嵌入高校供应链管理相关专业和课程的教学环境,构建师生互动、高校交流、校企合作的多主体、多阶段、多情景的大学生数据分析能力培养框架,以激发、引导、支持大学生供应链数据分析能力持续成长。In this paper,from a demand-side perspective,and with the supply chain-related data competition led by domestic enterprises as the breakthrough point,we analyzed the ability requirements for the supply chain data analysis talent.According to the analysis of the competition information,data acquisition ability,data analysis ability,and data expression ability are the basic qualities that the data analysis talent should possess,while multi-objective decision-making,mastery of multi-modal data,and multi-method fusion are important skills that the data analysis talent should possess.Therefore,drawing on the full perspective learning theory,we proposed to embed data competition into the teaching environment of supply chain management-related majors and courses in universities in diversified forms,and construct a multi-subject,multi-stage,and multi-scenario data analysis ability training framework for college students via teacher-student interaction,university exchanges,and school-enterprise cooperation to inspire,guide,and support the continuous growth of the college students'supply chain data analysis abilities.
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