Proceedings of the 2023 4th International Conference on Education, Knowledge and Information Management (ICEKIM 2023)

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On Studying Students’ Professional Aptitude Based on the Clustering Quality Evaluation

Authors
Guiqin Duan1, 2, Yongsong Chen1, Chensong Zou3, *, Liu Feng4
1School of Computing and Information Engineering, Guangdong Songshan Polytechnic College, Shaoguan, China
2Shaoguan Ecological Culture Big Data Engineering Technology Research Center, Shaoguan, China
3School of Electrical Engineering of Guangdong Songshan Polytechnic College, Shaoguan, China
4Department of Information Engineering, Luoding Polytechnic College, Luoding, China
*Corresponding author. Email: 190352915@qq.com
Corresponding Author
Chensong Zou
Available Online 30 June 2023.
DOI
10.2991/978-94-6463-172-2_54How to use a DOI?
Keywords
cluster; clustering quality evaluation; evaluation standard; data mining; professional ability
Abstract

When solving the problems of educational research and teaching practice, it is difficult to determine the number of clusters of the clustering algorithm, and the standard for clustering quality evaluation are diverse. Aiming at these problems, a clustering analysis model of professional ability has been designed. The model first uses affinity propagation to calculate the similarity matrix of professional ability and screen out the representative points of the cluster center by alternately updating the attractiveness and membership degree to determine the clustering upper limit kmax and complete the compression of cluster space. On this basis, DB, CH, Dunn and IGP indexes are used to obtain the optimal clustering disaggregation, and then the average value is taken as the final k value to achieve the clustering division of professional abilities. The study results show that the model can reasonably mine students’ professional aptitude, providing a new idea for the implementation of educational reform such as students’ professional ability analysis, career development planning, and hierarchical classification training.

Copyright
© 2023 The Author(s)
Open Access
Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

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Volume Title
Proceedings of the 2023 4th International Conference on Education, Knowledge and Information Management (ICEKIM 2023)
Series
Atlantis Highlights in Computer Sciences
Publication Date
30 June 2023
ISBN
10.2991/978-94-6463-172-2_54
ISSN
2589-4900
DOI
10.2991/978-94-6463-172-2_54How to use a DOI?
Copyright
© 2023 The Author(s)
Open Access
Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

Cite this article

risenwbib
TY  - CONF
AU  - Guiqin Duan
AU  - Yongsong Chen
AU  - Chensong Zou
AU  - Liu Feng
PY  - 2023
DA  - 2023/06/30
TI  - On Studying Students’ Professional Aptitude Based on the Clustering Quality Evaluation
BT  - Proceedings of the 2023 4th International Conference on Education, Knowledge and Information Management (ICEKIM 2023)
PB  - Atlantis Press
SP  - 486
EP  - 496
SN  - 2589-4900
UR  - https://doi.org/10.2991/978-94-6463-172-2_54
DO  - 10.2991/978-94-6463-172-2_54
ID  - Duan2023
ER  -