<abstract xmlns="http://www.w3.org/1999/xhtml">

<p>A corpus is a large and authentic language collection that can provide a large number of valuable, statistically significant, and retrievable material examples for Chinese language teaching. In this paper, we first design the processing model for participle and deactivation and then construct a statistically based method for labeling Chinese lexical categories. After building the Applied Linguistics Corpus for Chinese language teaching, it is used in Chinese language teaching to analyze conjunctive use bias. A controlled trial was conducted in the international college of a university using the applied linguistics corpus for teaching the Chinese language to test its practical utility. It was found that the top four conjunctions in terms of the total number of conjunctive biases were “and,” “and,” “because,” “or”. The bias of the word “and” mainly appeared in Japanese and Korean students, accounting for 38.69% and 36.07% respectively. The average score of the pre-test of writing in the experimental class was 51.26, while that of the control class was 50.88. The average score of the post-test of writing in the experimental class was 74.95, while that of the control class was 62.64, and the increase of the score of the experimental class was larger than that of the control class, which verifies the great effectiveness of applying applied linguistics corpus in teaching Chinese as a foreign language. This study can help improve students’ writing level and learning initiative in Chinese language teaching and effectively enhance students’ ability to express themselves in Chinese.</p>
</abstract>

A corpus is a large and authentic language collection that can provide a large number of valuable, statistically significant, and retrievable material examples for Chinese language teaching. In this paper, we first design the processing model for participle and deactivation and then construct a statistically based method for labeling Chinese lexical categories. After building the Applied Linguistics Corpus for Chinese language teaching, it is used in Chinese language teaching to analyze conjunctive use bias. A controlled trial was conducted in the international college of a university using the applied linguistics corpus for teaching the Chinese language to test its practical utility. It was found that the top four conjunctions in terms of the total number of conjunctive biases were “and,” “and,” “because,” “or”. The bias of the word “and” mainly appeared in Japanese and Korean students, accounting for 38.69% and 36.07% respectively. The average score of the pre-test of writing in the experimental class was 51.26, while that of the control class was 50.88. The average score of the post-test of writing in the experimental class was 74.95, while that of the control class was 62.64, and the increase of the score of the experimental class was larger than that of the control class, which verifies the great effectiveness of applying applied linguistics corpus in teaching Chinese as a foreign language. This study can help improve students’ writing level and learning initiative in Chinese language teaching and effectively enhance students’ ability to express themselves in Chinese.

Building an Applied Linguistics Corpus for Chinese Language Teaching and Learning

Applied Mathematics and Nonlinear Sciences

This work is licensed under the Creative Commons Attribution 4.0 International License.

A corpus is a large and authentic language collection that can provide a large number of valuable, statistically significant, and retrievable material examples...

Building an Applied Linguistics Corpus for Chinese Language Teaching and Learning

Publicado en línea: 02 jul 2024

Páginas: -

Recibido: 11 mar 2024

Aceptado: 03 jun 2024

DOI: https://doi.org/10.2478/amns-2024-1508

Palabras clave
Natural language processing, HMM modeling, Corpus, Chinese language teaching

© 2024 Yanrong Ma, published by Sciendo

This work is licensed under the Creative Commons Attribution 4.0 International License.

Building an Applied Linguistics Corpus for Chinese Language Teaching and Learning

Publicado en línea: 02 jul 2024

Páginas: -

Recibido: 11 mar 2024

Aceptado: 03 jun 2024

DOI: https://doi.org/10.2478/amns-2024-1508

Palabras claveNatural language processing, HMM modeling, Corpus, Chinese language teaching

© 2024 Yanrong Ma, published by Sciendo

This work is licensed under the Creative Commons Attribution 4.0 International License.

Palabras clave
Natural language processing, HMM modeling, Corpus, Chinese language teaching