An Empirical Study of Higher Vocational English Learning Efficiency Based on DEA Model
- DOI
- 10.2991/978-94-6463-172-2_194How to use a DOI?
- Keywords
- Higher vocational English; Learning efficiency; DEA projection analysis
- Abstract
The evaluation of learning efficiency is an important part of teaching work. However, traditional evaluation methods mainly focus on learning results and ignore the input factors of students. In view of this, this paper considers the relationship between input and output of learning and constructs DEA model to study the efficiency of English learning in higher vocational colleges. The model is applied to evaluate the learning efficiency of five students in a higher vocational college in Yunnan Province. The results show that 75% of the students have low comprehensive learning efficiency in preparing for the AB-level exam. The main reason is that the input of training time and resource use is not optimized. At the same time, the learning efficiency evaluation method based on DEA model is effective, and this model can become an important tool for teachers to improve teaching quality.
- 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 - Anlin Hu PY - 2023 DA - 2023/06/30 TI - An Empirical Study of Higher Vocational English Learning Efficiency Based on DEA Model BT - Proceedings of the 2023 4th International Conference on Education, Knowledge and Information Management (ICEKIM 2023) PB - Atlantis Press SP - 1750 EP - 1756 SN - 2589-4900 UR - https://doi.org/10.2991/978-94-6463-172-2_194 DO - 10.2991/978-94-6463-172-2_194 ID - Hu2023 ER -