摘要
数据挖掘课程是大数据和人工智能方向重要的核心课程,主要培养学生在数据驱动的范式下结合问题场景和社会需求,具备利用数据挖掘方法和技术分析、解决实际问题的能力。针对数据挖掘课程教学过程中存在的“痛点”问题,以培养工程型创新性人才为导向,从课程内容体系、学科竞赛体系和课程队伍体系三个维度,探索并构建基于“教赛协同”的数据挖掘课程教学改革的策略和方法,为地方高等院校大数据和人工智能相关专业的发展提供思路。
Data Mining is an important core course in the direction of big data and artificial intelligence,and this course mainly trains students to combine problem scenarios and social needs under the data-driven paradigm,and have the ability to use data mining methods and techniques to analyze and solve practical problems.In response to the"pain points"in the teaching process of data mining courses,to cultivate innovative talents with engineering skills,this article explores and constructs strategies and methods for teaching reform of data mining courses based on"teaching and competition collaboration"from three dimensions:curriculum content system,discipline competition system,and curriculum team system.This provides ideas for the development of big data and artificial intelligence-related majors in local universities.
出处
《高教学刊》
2024年第10期136-139,共4页
Journal of Higher Education
基金
平顶山学院教学改革项目“基于‘教赛协同’的数据挖掘课程教学改革研究与实践”(2022-JYZD03)
平顶山学院博士科研启动基金项目“基于深度学习的图像生成与复原方法研究”(PXY-BSQD-2023019)
国家自然科学基金青年项目“树和若干多环化合物分子图的子树数与BC子树数的广义计算及拓扑特性研究”(61702291)
河南省科技攻关项目“数字赋能-深度学习在中国传统山水画生成中的关键技术研究”(232102210011)。
关键词
教学改革
教赛协同
数据挖掘
课程内容
竞赛体系
课程队伍
teaching reform
teaching and competition collaboration
data mining
course content
competition system
course team
