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基于AIGC的专创融合课程教学创新实践研究——以“管理预测与决策技术”课程为例

Research on Teaching Innovation of Professional-Innovative Integrated Curriculum Based on Artificial Intelligence Generated Content(AIGC)

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【作者】 祝丽云; 邓郁; 李思靓; 薛宝颖;

【Author】 ZHU Liyun;DENG Yu;LI Siliang;XUE Baoying;Hebei Agricultural University;

【机构】 河北农业大学;

【摘要】 “工业4.0”时代,创新智能型人才成为产业数字化转型不可或缺的智力资源,且面临着较大的供给缺口。生成式人工智能(AIGC)赋能的专创融合教育,引发教育空间、教学方式与教学资源的全面革新,能满足AIGC时代对人才的需求。以“管理预测与决策技术”课程为例,基于课程专创融合建设现状,分析AIGC赋能专创融合课程建设目标革新,从优化课程内容设计、智能化教辅工作、创新教学方式、课程图谱辅助线上学习、AI助教助力个性化学习等方面全面阐述了AIGC赋能专创融合课程教学实践。研究表明,AIGC赋能专创融合建设在培养学生自主学习能力、形成科学的预测与决策思维方式、加强过程性与成长性评价、打造全方位实训体系和引领行业前沿创新方面取得了很好的效果。

【Abstract】 In the era of “Industry 4.0”, innovative and intelligent talents have become indispensable human resources for industrial digital transformation and are in short supply. Artificial Intelligence Generated Content(AIGC)-empowered education, rooted in the concept of smart education and intelligent teaching technologies, has triggered a comprehensive renewal of educational methods and resources for professional-innovative integrated education, which highly aligns with the talent requirements of the artificial intelligence era. Taking the course Management Forecasting and Decision-making Technology as a case study, this paper analyzes the teaching objectives of AIGC-empowered professional-innovative integrated courses. Based on the current integration status of professional and innovative education in this course, it explores the innovative construction goals of AIGC-enabled professional-innovative integration and expounds the teaching practices from multiple dimensions: optimizing course content design, intelligent teaching auxiliary services, innovative teaching methods, graph-based online learning assistance, and AI teaching assistants for personalized learning support. The practice has achieved remarkable outcomes in cultivating students’ independent learning ability, forming scientific prediction-decision thinking patterns, strengthening process-oriented and growth-focused evaluation, establishing a comprehensive talent training system, and guiding industry-leading innovation.

【基金】 中国农学会教育教学类第九批科研课题“教育数字化转型背最下农林高校教师AI素养评价实证研究”(PCE2427);河北农业大学第十二批教学研究项目“AI赋能管理预测与决策技术课程专创融合建设研究”(202328)
  • 【文献出处】 中国农业教育 ,China Agricultural Education , 编辑部邮箱 ,2025年03期
  • 【分类号】G642;C93-4
  • 【下载频次】53
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