A Study on Pivot Sentences Acquisition of International Students based on Natural Language Processing Technologies
In the context of the rapid development of globalized education, the demand for Chinese language learning among international students continues to rise. As a special and complex sentence structure in Chinese, the acquisition of "pivot sentences" is of great importance. Traditional acquisi...
Saved in:
Published in | Membrane technology pp. 205 - 213 |
---|---|
Main Author | |
Format | Journal Article |
Language | English |
Published |
23.01.2025
|
Online Access | Get full text |
ISSN | 0958-2118 0958-2118 |
DOI | 10.52710/mt.239 |
Cover
Summary: | In the context of the rapid development of globalized education, the demand for Chinese language learning among international students continues to rise. As a special and complex sentence structure in Chinese, the acquisition of "pivot sentences" is of great importance. Traditional acquisition research methods often rely on manual annotation and empirical analysis, which are difficult to handle large-scale data and are subject to a high degree of subjectivity. With the rapid advancement of natural language processing (NLP) technologies, new opportunities have emerged for research in this field. This paper utilizes various techniques from NLP, such as pre-trained language models (e.g., BERT, GPT) and grammar error detection methods based on Bayesian classification algorithms, to automatically analyze the production of pivot sentences by international students. These technologies enable precise identification of grammatical errors, syntactic structure anomalies, and inappropriate word usage in serial verb constructions. By deeply exploring the underlying causes of error patterns, this research provides a comprehensive and systematic understanding of the acquisition process of pivot sentences by international students, offering strong support for targeted teaching and promoting the advancement of Chinese as a second language education to a new level. |
---|---|
ISSN: | 0958-2118 0958-2118 |
DOI: | 10.52710/mt.239 |