About the Journal

Journal of AI and International Chinese Language Education (JAIICLE) is an international, peer-reviewed journal devoted to research on artificial intelligence in the learning, teaching, assessment and use of Chinese as a second, foreign, heritage or additional language.

The journal treats the Chinese language learner, teacher and test — not the algorithm — as its primary object of study. Submissions are expected to begin from a problem in Chinese language education and to treat AI as the means rather than the end.

Scope. JAIICLE publishes empirical, methodological and conceptual work in six areas: (1) AI and the acquisition and processing of Chinese; (2) AI and Chinese language pedagogy, including teacher development and human–AI collaboration; (3) AI and Chinese language assessment, including validity, fairness and automated feedback; (4) Chinese language resources, corpora, knowledge graphs and learning analytics; (5) policy, ethics, equity and academic integrity in AI-mediated Chinese language education; (6) reviews of AI-related tools, datasets, textbooks and research syntheses.

The journal welcomes work on the features that make Chinese distinctive as a target language — the writing system, tone and prosody, graded literacy, and the global infrastructure of Chinese language provision — and on learners and settings that are under-represented in the existing literature, including heritage and community-school learners, non-target-language environments, and low-resource contexts.

JAIICLE does not publish papers whose contribution is primarily to natural language processing or computer science without a Chinese language learning, teaching, assessment or use question; general educational technology studies without Chinese-language specificity; general area studies or Chinese political economy; translation technology unrelated to translator or interpreter education; or descriptive product announcements.

The journal publishes in English, with abstracts also available in Chinese. Research involving learners, including minors, must report ethical approval and data governance procedures. Authors must disclose generative AI use, and empirical work must report model versions, prompts and data availability to a standard that permits replication.