On Studying Students’ Professional Aptitude Based on the Clustering Quality Evaluation
- 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.
Cite this article
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 -