Applying K-Means Algorithm to Students’ Online Learning Data Mining: From Perspective of “1+X” BIM Vocational Skill Level System Reform

DOI

10.2991/978-94-6463-044-2_56How to use a DOI?

Keywords

data mining; clustering; “1+X” reform; BIM; online learning

Abstract

Currently, vocational skills training is getting more and more attention. China is in full swing with the “1+X” BIM vocational skills level system reform. However, there is little research on student learning assessment in the context of this reform. To address these issues and gain practical insights into student learning analysis in the context of the “1+X” BIM vocational skills leveling system reform, this paper first collects an online learning dataset of vocational skills levels from a specific university in China. Second, a clustering algorithm called K-Means was used to evaluate the student learning analysis in the context of the “1+X” BIM vocational skill level system reform. Based on the obtained online learning data, we found that the optimal number of clusters was 3 (silhouette coefficient of 0.54). This led to 3 levels of student online learning evaluation: excellent (23.33%), good (53.67%) and fair (23%). Based on these results, we further propose corresponding policy recommendations. The results of this paper provide meaningful practical insights into the national policy and government strategy for reforming the “1+X” BIM vocational skill level system.

Copyright

© 2022 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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TY  - CONF
AU  - Lili Zhang
AU  - Xiaorong Chen
AU  - Dunhua Huang
AU  - Mengyuan Lin
AU  - Tingting Liu
PY  - 2022
DA  - 2022/12/27
TI  - Applying K-Means Algorithm to Students’ Online Learning Data Mining: From Perspective of “1+X” BIM Vocational Skill Level System Reform
BT  - Proceedings of the 2022 3rd International Conference on Modern Education and Information Management (ICMEIM 2022)
PB  - Atlantis Press
SP  - 441
EP  - 449
SN  - 2667-128X
UR  - https://doi.org/10.2991/978-94-6463-044-2_56
DO  - 10.2991/978-94-6463-044-2_56
ID  - Zhang2022
ER  -