Application of Data Mining in Computer-Aided Bilingual Teaching System
- DOI
- 10.2991/978-94-6463-242-2_25How to use a DOI?
- Keywords
- data mining; Computer-aided; teaching system
- Abstract
In order to understand the significance of computer-aided bilingual teaching systems, this article proposes a study that utilizes data mining technology to enhance computer-aided bilingual teaching systems. Firstly, the structure of the computer-aided teaching system was analyzed, and the advantages and benefits of data mining technology in computer-aided teaching were elaborated in detail. Through repeated experimentation and testing, we have found that compared to traditional teaching systems, the total resource utilization of computer-aided bilingual teaching systems has decreased by 50%, indicating that the system has lower resource utilization and certain advantages. Applying data mining technology to the constituent modules of computer-aided teaching systems can improve the intelligence of the system and provide personalized learning assistance to students in a targeted manner. Therefore, the application of data mining technology in computer-aided bilingual teaching systems is of great significance and value.
- 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
TY - CONF AU - Wentao Meng AU - Jing Zhou AU - Weiyi Zhang PY - 2023 DA - 2023/09/22 TI - Application of Data Mining in Computer-Aided Bilingual Teaching System BT - Proceedings of the 2023 4th International Conference on Artificial Intelligence and Education (ICAIE 2023) PB - Atlantis Press SP - 209 EP - 214 SN - 2589-4900 UR - https://doi.org/10.2991/978-94-6463-242-2_25 DO - 10.2991/978-94-6463-242-2_25 ID - Meng2023 ER -