Article: Natural language processing for automatic error detection in Chinese language learning Journal: International Journal of Information and Communication Technology (IJICT) 2026 Vol.27 No.8 pp.36 - 52 Abstract: With the rapid development of global Chinese language education, the demand for efficient and accurate automated teaching assistance tools is growing. Traditional manual grading methods are often time-consuming and yield inconsistent results, highlighting the necessity for intelligent technological solutions. This paper explores the application of natural language processing techniques in automatic error detection for Chinese as a second language. It proposes a method based on pre-trained language models and evaluates it using a publicly available corpus of Chinese learner compositions. Experimental results demonstrate the strong performance of the proposed method in identifying grammatical and lexical errors, achieving detection accuracy exceeding 80% for major error categories. This represents a significant improvement over baseline systems (over 25% increase). This technology shows great potential as an efficient teaching support tool, enabling more effective and consistent feedback mechanisms within intelligent educational environments. Inderscience Publishers - linking academia, business and industry through research

Title: Natural language processing for automatic error detection in Chinese language learning

Authors: Zhengxin Li; Rongzhen Wu

Addresses: School of Public Teaching Department, Fujian Vocational College of Agriculture, Fuzhou, 350303, China ' School of Information Engineering, Fujian Vocational College of Agriculture, Fuzhou, 350303, China

Abstract: With the rapid development of global Chinese language education, the demand for efficient and accurate automated teaching assistance tools is growing. Traditional manual grading methods are often time-consuming and yield inconsistent results, highlighting the necessity for intelligent technological solutions. This paper explores the application of natural language processing techniques in automatic error detection for Chinese as a second language. It proposes a method based on pre-trained language models and evaluates it using a publicly available corpus of Chinese learner compositions. Experimental results demonstrate the strong performance of the proposed method in identifying grammatical and lexical errors, achieving detection accuracy exceeding 80% for major error categories. This represents a significant improvement over baseline systems (over 25% increase). This technology shows great potential as an efficient teaching support tool, enabling more effective and consistent feedback mechanisms within intelligent educational environments.

Keywords: natural language processing; NLP; Chinese language teaching; automatic bias detection; applicability analysis.

DOI: 10.1504/IJICT.2026.151599

International Journal of Information and Communication Technology, 2026 Vol.27 No.8, pp.36 - 52

Received: 19 Sep 2025
Accepted: 22 Oct 2025
Published online: 09 Feb 2026 *

Title: Natural language processing for automatic error detection in Chinese language learning

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