The Effectiveness of Using Corpus Technology in College English Teaching
- DOI
- 10.2991/978-94-6463-044-2_68How to use a DOI?
- Keywords
- corpus; effectiveness; word frequency
- Abstract
Corpus analysis adopts computer assisted method to process electronic language database to reveal language operational models with statistic methods, which usually centered on phenomenon of probability. The research tries to explore ways to integrate corpus technology in college English and to investigate if corpus-based teaching is effective. It adopted constructivism approach to design the lessons with corpus technology. Students were asked to translate corpus produced basic word list in their filed, learn vocabulary with corpus’s processed results and retell text with high-frequency word cloud. A quasi-experiment with 81 non-English major colleges students was carried out for 6 weeks. The results showed students’ post test scores were significantly higher than the pretest scores. Therefore, it drew the conclusion that corpus-based college English was effective. This research shed lights on the possible use of corpus technology in college English to promote the vocabulary learning outcome of college students.
- 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.
Cite this article
TY - CONF AU - Shan Xia PY - 2022 DA - 2022/12/27 TI - The Effectiveness of Using Corpus Technology in College English Teaching BT - Proceedings of the 2022 3rd International Conference on Modern Education and Information Management (ICMEIM 2022) PB - Atlantis Press SP - 539 EP - 547 SN - 2667-128X UR - https://doi.org/10.2991/978-94-6463-044-2_68 DO - 10.2991/978-94-6463-044-2_68 ID - Xia2022 ER -