An Empirical Study on Enhancing the Course-Work Integration in Vocational Chinese through Generative AI

DOI

10.2991/978-94-6239-691-3_39How to use a DOI?

Keywords

course-work integration; higher vocational Chinese; teaching reform; generative AI

Abstract

Deepening the integration of curriculum and workplace requirements is currently a key focus for enhancing the quality of higher vocational education. The rapid development of Generative Artificial Intelligence (GenAI) has introduced new approaches and tools into this field. Focusing on Chinese language teaching in vocational early childhood education programs, this study addresses critical issues in course-work integration, such as the inadequate vocational orientation of teaching materials and inaccurate job competency analyses. Based on the Outcome-Based Education (OBE) framework and supported by GenAI, a “dual-drive, triple-center” teaching model was constructed and implemented via a four-step strategy: 1) developing a precise Chinese language competency map for early childhood education roles; 2) restructuring modularized teaching content; 3) establishing a knowledge and competency transfer mechanism driven by professional scenarios; 4) creating a collaborative human-machine evaluation system based on the theory of multiple intelligences. Empirical results demonstrate that this model significantly improves students’ knowledge and skill acquisition, competency transferability to professional roles, and overall learning outcomes, thereby providing a replicable pathway for deepening course-work integration in higher vocational Chinese language education.

Copyright

© 2026 The Author(s)

Open Access

Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

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TY  - CONF
AU  - Yun Deng
AU  - Jieyun Zhong
AU  - Zhiyan Chen
AU  - Yanting Wen
AU  - Shuoying Zhang
PY  - 2026
DA  - 2026/05/31
TI  - An Empirical Study on Enhancing the Course-Work Integration in Vocational Chinese through Generative AI
BT  - Proceedings of the 2026 5th International Conference on Educational Innovation and Multimedia Technology (EIMT 2026)
PB  - Atlantis Press
SP  - 379
EP  - 388
SN  - 2667-128X
UR  - https://doi.org/10.2991/978-94-6239-691-3_39
DO  - 10.2991/978-94-6239-691-3_39
ID  - Deng2026
ER  -