摘要
深化高等学校创新创业教育改革,是国家实施创新驱动发展战略的重要举措。大数据时代要求统计学合理分析数据要素加速向数据动能转换。应用统计学属于数学院系交叉学科,专业师资紧缺制约人才培养模式更迭,亟须融入新一代信息技术,完善课程体系和校园文化建设,强化创新创业教育理念,推动学生高质量就业。桂林电子科技大学数学与计算科学学院依托教师创新创业团队,借助产业命题的数据应用创新竞赛,驱动应用统计学专业的优秀学生,提前接触学科交叉知识和双创实践活动,主动完成计算机处理和数据分析的全流程工作,探索创新人才培养的新路径。
Innovation and entrepreneurship educational reform in universities is very important to the country for implementing the innovation-driven development strategy.The era of big data requires applied statistics to analyze data elements and accelerate data transformation.Applied statistics belongs to the interdisciplinary disciplines of mathematics colleges,they lack of professional teachers lead to the restriction of talent training mode.It is urgent to integrate the new generation of information technology,improve the curriculum system and campus culture construction,strengthen the concept of innovation and entrepreneurship education,then promote high-quality employment for students.Relying on the innovation and entrepreneurship team of teachers,with the help of the data application innovative competition,the school of Mathematics&Computing Science of GUET drives the outstanding students of applied statistics to contact the interdisciplinary knowledge and innovation practice,actively complete the whole process of computer application and data analysis,so as to explore a new path of innovative talents cultivation.
作者
徐增敏
毛睿
XU Zengmin;MAO Rui(School of Mathematics and Computing Science,Guangxi Colleges and Universities Key Laboratory of Data Analysis and Computation,Guilin University of Electronic Technology,Guilin Guangxi,541004,China;Center for Applied Mathematics of Guangxi(GUET),Guilin Guangxi,541004,China;Anview.ai,Guilin Guangxi,541010,China)
出处
《创新创业理论研究与实践》
2024年第10期69-71,共3页
The Theory and Practice of Innovation and Enterpreneurship
基金
2023年度广西教育厅高等教育本科教学改革工程项目“基于数学创新应用能力培养的‘项目化’实践教学模式研究”(2023JGB210)
关键词
交叉学科
数据应用
创新创业
新质生产力
非结构化数据
机器学习
Interdisciplinary
Data application
Innovation and entrepreneurship
New Productive Forces
Unstructured data
Machine learning
