The Personalized Scene-Based AI Agents: Exploring Chinese Language Learning Among International Students

With the development of deep learning and large language model (LLM) technologies, AI agents, as a key application of generative artificial intelligence (AIGC), have demonstrated significant potential in the field of international Chinese education. Personalized scenario AI agents, leveraging open-source AI chat frameworks, large-scale Chinese language corpora, and dynamic adjustment mechanisms (RAG, PAL, ReAct), effectively address key challenges in Chinese language acquisition for international students. These challenges include a lack of communicative practice, difficulties in acquiring everyday expressions, the inability of large-class instruction to accommodate individual differences, and the absence of real-time feedback. By constructing immersive interactive scenarios, personalized learning pathways, and intelligent feedback systems, AI agents enhance learning efficiency and flexibility while providing new pathways for the intelligent development of international Chinese education.

Authors

Institutions

Publication Details

Published
2025-05-14
DOI
https://doi.org/10.1109/icaie64856.2025.11158030
Primary Topic
Educational Technology and Pedagogy
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

The Personalized Scene-Based AI Agents: Exploring Chinese Language Learning Among International Students

Heng Xu, Jun Peng, Baohua Su, Kaiyi Chen et al.
Educational Technology and Pedagogy
article

The Personalized Scene-Based AI Agents: Exploring Chinese Language Learning Among International Students

Heng Xu, Jun Peng, Baohua Su, Kaiyi Chen, Zhihua Zhou, Liu Hua
article en

Abstract

With the development of deep learning and large language model (LLM) technologies, AI agents, as a key application of generative artificial intelligence (AIGC), have demonstrated significant potential in the field of international Chinese education. Personalized scenario AI agents, leveraging open-source AI chat frameworks, large-scale Chinese language corpora, and dynamic adjustment mechanisms (RAG, PAL, ReAct), effectively address key challenges in Chinese language acquisition for international students. These challenges include a lack of communicative practice, difficulties in acquiring everyday expressions, the inability of large-class instruction to accommodate individual differences, and the absence of real-time feedback. By constructing immersive interactive scenarios, personalized learning pathways, and intelligent feedback systems, AI agents enhance learning efficiency and flexibility while providing new pathways for the intelligent development of international Chinese education.

Ningbo University (CN), Chongqing University (CN), Jinan University (CN)
Openalex Percentile: Top 86%
Educational Technology and Pedagogy
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.