Influence of “Corpus Data Driven Learning + Learning Driven Data” Mode on ESP Writing Under the Background of Artificial Intelligence

Abstract

Objective: at present, in the actual process of foreign language teaching, there are still some deficiencies in the language materials and the knowledge of language analysis. The research aims to better stimulate the academic paper writing of college students of Traditional Chinese Medicine (TCM) by constructing the model of “Corpus Data Driven Learning (C-DDL) + Learning Driven Data (LDD)”. Methods: The junior students (n = 80) in one university of TCM were divided into experimental group (n = 40) and control group (n = 40). After the no difference comparison, the educational experiment was carried out 12 times in 3 months. In the experimental group, the Chinese-English Parallel Corpus of TCM created by Hyconc software and the artificial intelligence network evaluation system were used, while the control group was taught by traditional style. The research tool is the ESP Writing Ability Scale of TCM. Results: in the five dimensions of word accuracy, sentence structure, text structure, writing efficacy and writing motivation, the post test of the experimental group and the control group were significantly better than the pre test (p 0.05). Conclusion: through the “Corpus Data Driven Learning (C-DDL) + Learning Driven Data (LDD)” mode, students gradually adapt to the beginning of independent language mining and exploration. In the process of academic language processing, construction, transformation and experiment of TCM English, it can make language knowledge more systematic and academic.