Author(s)

Ziyi Li ¹

Affiliation(s)

¹ Guangxi Normal University, Guilin, Guangxi,‌ 541000, China

Corresponding Author

Ziyi Li

ABSTRACT

The deep integration of artificial intelligence (AI) technologies into language education provides new opportunities for transforming Teaching Chinese as a Foreign Language (TCFL) from standardized instruction toward personalized learning pathways. In response to learners’ diverse first-language backgrounds, linguistic proficiency levels, cognitive characteristics, and learning goals, this study examines the practical value of AI-driven personalized instructional pathway generation in TCFL and identifies three major challenges: insufficient accuracy in learner-profile identification, delays in the dynamic adjustment of instructional pathways, and limitations in ensuring the effectiveness of personalized instruction. To address these challenges, the study proposes optimization strategies in three areas: improving mechanisms for the precise identification and continuous updating of learner profiles, establishing dynamic pathway-adjustment mechanisms based on real-time learning feedback, and strengthening evaluation and teacher-review mechanisms to ensure instructional effectiveness. Through the coordinated use of data analytics, intelligent recommendation, and teachers’ professional judgment, AI-driven personalized instructional pathways can better align instructional content, task difficulty, and learning progression with learners’ evolving needs, thereby providing practical support for enhancing the precision, adaptability, and effectiveness of TCFL instruction.

KEYWORDS

Artificial Intelligence; Teaching Chinese as a Foreign Language; Personalized Instruction; Instructional Pathways

CITE THIS PAPER

Ziyi Li. AI-Driven Generation of Personalized Instructional Pathways for Teaching Chinese as a Foreign Language. Lecture Notes on Language and Literature (2026). Vol. 9, No. 2, 56-61. DOI: http://dx.doi.org/10.23977/langl.2026.090207.

REFERENCES

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