Numerical Analysis and Optimization of Computer-Aided English Reading Corpus
- DOI
- 10.2991/978-94-6463-230-9_102How to use a DOI?
- Keywords
- computer aided; English reading teaching; corpus
- Abstract
In order to improve the scientificity and effectiveness of English reading teaching, a computer-aided numerical analysis and optimization method of English reading corpus is proposed. This paper introduces the relevant knowledge and theory of corpus, discusses the theoretical basis of computer-assisted English teaching based on corpus, and preliminarily discusses the classification of teaching materials and the application of different content corpora in English teaching. In particular, a pioneering attempt has been made to extract language materials from film and television subtitle files for auxiliary teaching, and a film and television corpus with a capacity of more than 1.1 million words, which contains more than 110 English subtitles of film and television works, has been constructed. The results show that computer-assisted corpus can fully improve the efficiency of English reading teaching in senior high schools.
- 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 - Ke Wang PY - 2023 DA - 2023/09/04 TI - Numerical Analysis and Optimization of Computer-Aided English Reading Corpus BT - Proceedings of the 3rd International Conference on Internet, Education and Information Technology (IEIT 2023) PB - Atlantis Press SP - 849 EP - 855 SN - 2667-128X UR - https://doi.org/10.2991/978-94-6463-230-9_102 DO - 10.2991/978-94-6463-230-9_102 ID - Wang2023 ER -