Learning Path Planning Algorithm Based on Career Goals and Artificial Intelligence

Authors

  • Zhiwei Shi Tianjin University of Technology and Education https://orcid.org/0000-0002-6995-7164
  • Zhifeng Wu Tianjin University of Technology and Education
  • Zhe Zhang Tianjin University of Technology and Education
  • Yutong Chen Zhejiang Gongshang University
  • Xuemeng Liu Tianjin University of Technology and Education

DOI:

https://doi.org/10.3991/ijet.v17i10.28455

Keywords:

Learning path planning, course recommendation, online education, vocational education, artificial intelligence, big data

Abstract


With the development of the Internet, various forms of learning resources continue to flood the public, especially the promotion of video learning plat-forms. More and more people use their spare time to learn what they need. However, there is a general lack of intelligence in online learning platforms at present, which greatly reduced the utilization of online learning platforms and their educational advantages. The innovation of this paper is proposing and explaining that with the integration of big data, online education and ar-tificial intelligence, the contradiction of online education has turned into one between the lack of intelligence in online education and the demand of users. To solve this contradiction, this paper researches from the perspective of an algorithm. Course recommendation is the core algorithm of online ed-ucation. However, the current recommendation algorithm based on collabo-rative filtering has the disadvantages of cold start and useless recommenda-tion content. In this paper, Apriori and ACO algorithms in artificial intelli-gence are studied, and the proposal of an algorithmic framework named Posi-tion-Apriori-ACO brings forth new ideas in solving online education prob-lems. The Position-Apriori-ACO algorithm can effectively carry out course recommendation and learning path planning, and also provides a research di-rection for the intelligent development of online education.

Author Biographies

Zhiwei Shi, Tianjin University of Technology and Education

Zhiwei Shi, a postgraduate student of Software Engineering from Tianjin University of Technology and Education, his research direction is artificial intelligence, big data and intelligentization of vocational education. Presided over the Tianjin Research Innovation Project for Postgraduate Students (2021YJSS226).

Zhifeng Wu, Tianjin University of Technology and Education

Zhifeng Wu, born in 1974, Ph.D., professor, postgraduate tutor, visiting scholar of Washington University in St. Louis University, member of China Computer Federation. His main research interests are machine learning, intelligent computing, data mining, complex network community discovery, link prediction, etc. He has published more than 30 papers in core journals and conferences at home and abroad, and edited and participated in the editing (translation) of 3 textbooks. He has made many achievements in the reform of vocational education and the exploration of the integration of production and education.

Zhe Zhang, Tianjin University of Technology and Education

Zhang Zhe, Master of Software Engineering from Tianjin University of Technology and Education, research direction is artificial intelligence.

Yutong Chen, Zhejiang Gongshang University

Yutong Chen, female, master degree from Zhejiang Gongshang University. Re-search direction: English translation.

Xuemeng Liu, Tianjin University of Technology and Education

Xuemeng Liu, Master of Vocational and Technical Education from Tianjin University of Technology and Education, her research direction is intelligentization of vocational education.

Cover iJET Vol. 17 No. 10 (2022)

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Published

2022-05-24

How to Cite

Shi, Z., Wu, Z., Zhang, Z., Chen, Y., & Liu, X. (2022). Learning Path Planning Algorithm Based on Career Goals and Artificial Intelligence. International Journal of Emerging Technologies in Learning (iJET), 17(10), pp. 256–272. https://doi.org/10.3991/ijet.v17i10.28455

Issue

Vol. 17 No. 10 (2022)

Section

Papers

License

Copyright (c) 2022 Zhiwei Shi, Zhifeng Wu, Zhe Zhang, Yutong Chen; Xuemeng Liu

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