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Research on Teaching Reform of Machine Learning Course Based on OBE Orientation

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DOI: 10.23977/curtm.2023.061213 | Downloads: 8 | Views: 317

Author(s)

Wenting Li 1, Yang Li 1

Affiliation(s)

1 Computer and Information Engineering College, Guizhou University of Commerce, Guiyang, Guizhou, China

Corresponding Author

Wenting Li

ABSTRACT

With the rapid development of artificial intelligence, machine learning has become one of the most essential courses in many universities, given its importance as a core technology in this field. As a multidisciplinary subject with complex and evolving content, machine learning raises many challenges, including a lack of diversity in course materials and teaching methods, little connection between theory and practice, and traditional assessment methods. To address these challenges, it is necessary to reform and enhance the teaching of machine learning. Outcomes-Based Education (OBE) is a new learning approach that emphasizes the development of students abilities and practical skills. It can be used to improve and enhance the machine learning course curriculum. This paper investigated the difficulties surrounding machine learning education, the measures adopted to reform machine learning teaching based on the OBE concept, and strategies for promoting the reform of machine learning teaching based on the OBE approach. This study aims to improve teaching outcomes and enhance students' application skills, cultivate highly skilled professionals with practical application capabilities, and enable machine learning courses to better meet practical application needs.

KEYWORDS

Outcomes-Based Education; machine learning; teaching reform; talent cultivation

CITE THIS PAPER

Wenting Li, Yang Li, Research on Teaching Reform of Machine Learning Course Based on OBE Orientation. Curriculum and Teaching Methodology (2023) Vol. 6: 82-87. DOI: http://dx.doi.org/10.23977/curtm.2023.061213.

REFERENCES

[1] Wei Nan, Yin Lihua, Ning Hong, Fang Binxing. Preliminary study on the reform of machine learning teaching. Chinese Journal of Network and Information Security, 2022, 8(04): 182-189.
[2] Zhou Xiabing, Chen Fei. Teaching Exploration of Machine Learning. Computer Knowledge and Technology, 2020, 16(30): 129-131+150. DOI:10.14004/j.cnki.ckt. 2020.3100.
[3] Jiang Lin, Liu Xingbao, Yang Junfeng, Huang Hua. Application of the "class-competition integration" mode in machine learning course teaching. Computer Education, 2022(11): 133-136+141. DOI: 10.16512/j.cnki.jsjjy. 2022.11. 032.
[4] Ye Jingzhen, Kang Sheng, Fang Zihe. Teaching practice of machine learning course. Electronic Technology, 2021, 50(09): 292-293.
[5] Yu Bo. Teaching reform of “machine learning” course based on outcome-oriented approach. Industry and Information Technology Education, 2022(08): 24-28.
[6] Cheng Buyun, Liang Yuanhui. Research on course design for machine learning. Electronic Component and Information Technology, 2022, 6(01): 145-146. DOI: 10.19772/j.cnki.2096-4455.2022.1.066.
[7] Li Dawei, Ai Xin. Case study teaching reform of data analysis and machine learning course. Laboratory Research and Exploration, 2021, 40(02): 186-190. DOI: 10.19927/j.cnki.syyt.2021.02.037.
[8] Ma Cheng. Exploration and practice of machine learning course teaching in application-oriented universities. Journal of Anshun University, 2021, 23(02): 111-114.
[9] Jiang Lei, Zhang Li, Yan Jun. Discussion on the reform of open practice course teaching for undergraduate education of machine learning. Contemporary Educational Practice and Teaching Research, 2020(10):145-146+182. DOI: 10.16534/j.cnki.cn13-9000/g.2020.1156.
[10] Zhu Hongyan, Liang Shikai, He Fuyun, Li Haisheng, Xia Haiying. Exploration of Machine learning course teaching based on project practice under the background of new engineering. Guangxi Physics, 2022, 43(02): 146-154.
[11] Liu Yuanyuan, Fang Fang, Wang Yu, Zhou Shunping. Introduction to machine learning curriculum group construction function. Journal of horizon of science and technology, 2021 (29): 88-89. The DOI: 10.19694 / j.carol carroll nki issn2095-2457.2021.29.39.
[12] Ji Tingting, Jiang Yongling, Liu Lanfang, Yang Hui. The Effectiveness Analysis of Practice Assessment System Reform Based on OBE—Taking Python Programming Foundation as an example. Education and Teaching Forum, 2020(47): 147-149.
[13] Li Yuzhu. Based on the concept of OBE middle school mathematical modeling teaching design. Ningxia University, 2021. The DOI: 10.27257 /, dc nki. GNXHC. 2021.001518.
[14] Li Zhen. Research on Business Data Analysis and Application Curriculum Construction Reform Based on OBE Concept. Logistics science and technology, 2023, 46-48(11): 179-180 + 184. DOI: 10.13714 / j.carol carroll nki. 1002-3100.2023.11.048.
[15] Song J. Research on the Teaching Reform of Logistics-Flipped Classroom under the OBE Concept. 2021, 5(11): 7.
[16] Gao X. Role of 5G network technology and artificial intelligence for research and reform of english situational teaching in higher vocational colleges. Journal of intelligent & fuzzy systems: Applications in Engineering and Technology, 2021, 40(2).
[17] Du J. Exploration and Practice of Modern Logistics Management Course Teaching Reform Based on OBE Concept. Francis Academic Press, 2021(6).

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