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“以赛促教”模式下艺术类专业创新创业教育生态构建研究

Research on the Ecological Construction of Innovation and Entrepreneurship Education for Art Majors under the Mode of“Promoting Teaching by Competition”
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摘要 构建高校创新创业教育生态是推动我国创新创业教育生态建设的重要组成部分,其中艺术类专业在我国创新创业教育体系中经过多年发展,已经初具规模。该文通过对艺术类专业创新创业教育现状进行分析,发现仍然存在“赛教融合”教学模式有待优化、创新创业教育课程与专业竞赛结合度不足等问题。通过分析高校艺术类专业优化创新创业教育生态的必要性及“以赛促教”模式开展的意义,围绕“以赛促教”模式开展研究,通过改进教学方法、创新创业平台建设等渠道,探索高校艺术类专业“以赛促教”教学模式下创新创业教育生态优化的对策。 Constructing university's innovation and entrepreneurship education ecology is an important part of promoting our overall innovation and entrepreneurship ecological construction.Among them,art majors have already taken shape after many years of development in our innovation and entrepreneurship education system.Through the analysis of the current situation of innovation and entrepreneurship education of art majors,this paper finds that there are still some problems such as the teaching model under the"integration of competition and teaching"to be optimized,and the lack of integration of innovation and entrepreneurship education courses and professional competitions.By analyzing the necessity of college art professional optimize innovative entrepreneurial ecology and the meaning of"in order to promote teaching"mode to carry out,around"in order to promote teaching"mode to carry out the study,by improving teaching methods,innovative entrepreneurial platform construction exploration channels,such as professional art"in order to promote teaching"teaching mode innovation entrepreneurship ecological optimization countermeasures.
作者 秦晋 霍楷 QIN Jin;HUO Kai(College of Art,Northeast University,Shenyang Liaoning,110819,China)
出处 《创新创业理论研究与实践》 2023年第5期61-65,共5页 The Theory and Practice of Innovation and Enterpreneurship
基金 中国学位与研究生教育学会课题“基于目标和成果导向的立体混合式硕士专业学位研究生教育改革研究”(2020MSB29) 教育部产学合作协同育人项目“‘双一流’背景下艺术类专业立体混合式创新竞赛育人模式研究”(202102160021)
关键词 以赛促教 艺术类专业 创新创业 教育生态构建 教学模式 生态优化 Competition to promote teaching Major in art Innovation and entrepreneurship Ecological construction of education Teaching mode Ecological optimization
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