Big Data General Education Courses in Local Application-oriented Universities: Research and Practice in Weifang University
DOI: 10.23977/curtm.2024.070624 | Downloads: 15 | Views: 782
Author(s)
Chunlei Chen 1, Jinkui Hou 1, Huihui Zhang 1, Jiangyan Dai 1, Guoxu Liu 1, Yujie Li 1, Jing Sun 1, Huihui Yan 2
Affiliation(s)
1 School of Computer Engeering, Weifang University, 5147 Dongfeng Street, Weifang, Shandong, China
2 Shandong Institute of Quantum Science and Technology Co. Ltd, 789 North Shuntai Road, Jinan, Shandong, China
Corresponding Author
Chunlei ChenABSTRACT
With the rapid development of technology and society, big data technology has become increasingly crucial for technological innovation and social progress. The implementation of big data general education courses aims to equip students with essential knowledge and skills needed in the big data era. However, we are facing significant challenges to implement such courses in local application-oriented universities like Weifang University. First, the threshold for data-thinking cultivation is somewhat high. Second, it is difficult to combine big data general education and specialty applications. Third, the existing courses lack ideological and political elements. In view of these challenges, we propose our solutions. First, concretization of data thinking: we impart data-thinking with concrete examples. Second, industry-academia cooperation: we make the knowledge application-oriented by leveraging real cases from enterprises. Third, full coverage of ideological and political elements: we integrate ideological and political elements into every chapter of the courses. Teaching practice validates our solutions.
KEYWORDS
Big Data, General Education Course, Local Application-oriented UniversitiesCITE THIS PAPER
Chunlei Chen, Jinkui Hou, Huihui Zhang, Jiangyan Dai, Guoxu Liu, Yujie Li, Jing Sun, Huihui Yan, Big Data General Education Courses in Local Application-oriented Universities: Research and Practice in Weifang University. Curriculum and Teaching Methodology (2024) Vol. 7: 160-166. DOI: http://dx.doi.org/10.23977/curtm.2024.070624.
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