Research on AI-Assisted Task-based Teaching Method in the Design of International Chinese Digital Teaching Centered on Verbal Communication
This paper, with reference to the International Standards for Chinese Language Proficiency (2021), and in combination with the definitions of the three evaluation dimensions of verbal communication ability, topic task content and language quantification indicators in the standards, explores the teaching effectiveness and evaluation system of the task-based teaching method oriented by the “verbal communication” evaluation dimension, An analysis of the challenges and operational difficulties faced by task-based teaching methods in teaching practice. While affirming the enhancement of learners' verbal communication skills by the task-based teaching method, this paper proposes task-based teaching solution strategies and operational processes based on AI artificial intelligence and big data analysis technology, that is, the cutting-edge technical methods of applying artificial intelligence to language teaching. Such as natural language processing, automatic speech recognition, machine learning, large language models and computer vision graphs, etc. Typical application scenarios of AI digital instructional design include automatic question answering and chatbots, interlanguage corpus data analysis, Chinese intelligent guidance and Chinese intelligent assessment, etc. It is hoped that this article will provide useful teaching references for international Chinese language educators, promote the effective application of AI-enabled task-based teaching methods in international Chinese language education, and improve teaching quality.
Authors
- Zicheng Su (ORCID: https://orcid.org/0000-0001-5149-570X)
Institutions
- Sichuan International Studies University (CN)
Publication Details
- Journal
- Journal of language, culture and education.
- Published
- 2025-08-11
- DOI
- https://doi.org/10.70267/jlce.2025.v2n3.2734
- Primary Topic
- Educational Technology and Pedagogy
- Type
- article
- Field-Weighted Citation Impact
- 0.00