Applying CQPweb in Academic Writing Course for ESL Biomedical PhD Students: An Exploratory Study

CQPweb, a web-based fourth-generation corpus analysis tool, combines corpus resource sharing with online retrieval functions. This paper selects online corpora based on CQPweb and introduces data-driven learning (DDL) to a medical academic writing course for English as a second language (ESL) biomedical PhD candidates. The study indicates that query through CQPweb not only helps to solve lexico-grammatical problems encountered in PhD students' writing process such as word choice and collocation, but also discover and summarize syntactic discourse problems such as sentence form and text structure. Although the post-course questionnaire showed that learners faced difficulties such as "too many concordance lines" and "difficulty in formulating search formulas for syntax searches". However, overall, respondents provided positive feedback on the CQPweb-based corpus-assisted academic writing. The results show that CQPweb serves as an effective reference tool and reliable resource for academic writing, and the CQPweb-based DDL is conducive to promoting students' interest in learning, increasing the quality of academic writing, boosting their confidence, and cultivating independent learning capability. However, teachers should strengthen the training of corpus searching, especially syntax search, and also randomly thin the query results to reduce the cognitive load, protect students' learning motivation, and increase the use of corpus-assisted writing after class, in order to improve the quality of research paper writing.