Research on Data-Driven Text Adaptation of ESP Course Based on “ENG-EDitor” Tool

DOI

10.2991/978-94-6463-064-0_5How to use a DOI?

Keywords

text adaptation; data-driven; Eng-Editor

Abstract

The promotion of big data promotes the development of applied linguistics, and the cultivation of reading ability in foreign language teaching has always been the focus of research. In the process of learning ESP Courses, learners need to be provided with texts of appropriate difficulty for extended reading, which often requires the selection and adaptation of the original content of the text, that is, the regulation of text difficulty. Based on the situation of foreign language teaching and research in China, the study illustrates that text adaptation research is shifting towards the “data driven” stage by using the tool of “Eng-Editor”. Using “Wisdom Learning” as the theme, the research conducts a questionnaire survey of students form four aspects, which are vocabulary, grammar, difficulty, exercises, personal attitudes. Questionnaire survey and statistics are conducted with SPSS at the later stage to investigate the significance of the study and provide operational suggestions for future research.

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.

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TY  - CONF
AU  - Sun Rong
PY  - 2022
DA  - 2022/12/27
TI  - Research on Data-Driven Text Adaptation of ESP Course Based on “ENG-EDitor” Tool
BT  - Proceedings of the 2022 3rd International Conference on Big Data and Social Sciences (ICBDSS 2022)
PB  - Atlantis Press
SP  - 36
EP  - 42
SN  - 2589-4900
UR  - https://doi.org/10.2991/978-94-6463-064-0_5
DO  - 10.2991/978-94-6463-064-0_5
ID  - Rong2022
ER  -