Proceedings of the 2023 4th International Conference on Artificial Intelligence and Education (ICAIE 2023)

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Research on Online Learning Behavior of Higher Vocational Students Based on Data Mining

Authors
Fenglin Qu1, *
1Chengdu Agricultural Technology Vocational College, Chengdu, 611130, China
*Corresponding author. Email: 396280794@qq.com
Corresponding Author
Fenglin Qu
Available Online 22 September 2023.
DOI
10.2991/978-94-6463-242-2_5How to use a DOI?
Keywords
online learning; Learning behavior; T-test; K-means clustering algorithm; Data mining
Abstract

Exploring the characteristics of online learning behavior of students in higher vocational colleges has important guiding significance for improving the teaching level of higher vocational colleges. This paper collects more than 3000 online learning data of “Fundamentals of digital photography” courses of three majors in Cheng du polytechnic. Firstly, t-test is used to study the relationship between learning behavior and learning results, which selected 8 learning behavior indicators such as video resource learning, classroom performance, brainstorming and teamwork. Then, K-means clustering algorithm is used to analyze the path data of students’ online learning behavior. The experiment divides students’ learning behavior into four categories, and excavates each category of students’ learning behavior habits. Provide optimization suggestions for teachers’ teaching and students’ learning, and provide reference for improving the quality of teaching (learning).

Copyright
© 2024 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 Artificial Intelligence and Education (ICAIE 2023)
Series
Atlantis Highlights in Computer Sciences
Publication Date
22 September 2023
ISBN
10.2991/978-94-6463-242-2_5
ISSN
2589-4900
DOI
10.2991/978-94-6463-242-2_5How to use a DOI?
Copyright
© 2024 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  - Fenglin Qu
PY  - 2023
DA  - 2023/09/22
TI  - Research on Online Learning Behavior of Higher Vocational Students Based on Data Mining
BT  - Proceedings of the 2023 4th International Conference on Artificial Intelligence and Education (ICAIE 2023)
PB  - Atlantis Press
SP  - 30
EP  - 37
SN  - 2589-4900
UR  - https://doi.org/10.2991/978-94-6463-242-2_5
DO  - 10.2991/978-94-6463-242-2_5
ID  - Qu2023
ER  -