本科数据挖掘课程教学内容的结构化设计

Structural Design of Teaching Content for Undergraduate Data Mining Curriculum

大数据时代,数据挖掘成为数据科学领域的核心关键技术。越来越多的高校开设数据科学类本科专业,开展数据挖掘课程建设成为数据科学人才培养和学科建设的重要组成部分。针对本科生的特点,对本科数据挖掘课程的理论和实践教学内容进行结构化设计,在实践教学部分按照项目开发流程,将理论知识的教学融入实践教学的结构化框架,起到巩固理论知识和加深算法理解的作用。教学实践表明,这种结构化设计有助于加深学生对教学内容的理解,能更好地开展实践教学,提高学生学习的积极性,进而提高教学质量。

In the era of big data,data mining has become a key technology in data science domain.More and more universities and colleges offer a ma⁃jor in data science,thus the curriculum construction of data mining has become an important part of talent training and discipline construc⁃tion in data science.According to the features of the undergraduate students,the structural design is done for the theory and practice teach⁃ing content of undergraduate data mining curriculum,which can consolidate the theoretical knowledge and deepen understanding of the al⁃gorithms.The teaching practice show that the structural design pattern can expand understanding of the teaching content,can carry out practical teaching even better,can improve the study enthusiasm of the student,and finally can improve the teaching quality.