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Research on Curriculum Design of Data Mining in Different Majors
DOI: https://doi.org/10.62381/H241205
Author(s)
Yong Luo1, Yingyang Chen2, Junwei Gan1*
Affiliation(s)
1School of Economics and Management, Sichuan Tourism University, Chengdu, Sichuan, China 2Innovation and Entrepreneurship Institute, Sichuan Tourism University, Chengdu, Sichuan, China *Corresponding Author.
Abstract
With the increasing attention paid to the application value of big data, data mining has become an important major course not only in big data, computer and information technology, but also in most majors in colleges and universities. This course involves the explanation of classic algorithms of data mining as well as the application of classical algorithms of data mining, so it usually has both theoretical and practical hours in the composition of teaching form. Because of the differences in the knowledge structure of students in different majors, there should be differences in the theoretical teaching and practical teaching design of data mining courses among different majors. The teaching content should be selected according to the characteristics and needs of students in different majors, and should also consider the development and trends of big data technology. In addition, in order to improve the teaching quality and effectiveness of data mining courses, it is also necessary to use modern teaching methods and technologies to support teaching, such as online teaching resources, flipped classroom teaching, etc. In short, it is necessary to carry out targeted teaching design for data mining courses in different majors to match the basic situation of students in different majors, ensure better teaching effect and play a better role in different fields of specialization.
Keywords
Data Mining; Theory Teaching; Practical Teaching
References
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