Construction and Empirical Research on a Generative AI-Driven Integrated Teaching-Learning-Assessment Model for Higher Vocational English

DOI: https://doi.org/10.62517/jhve.202616211

Author(s)

Yin Qin

Affiliation(s)

Suzhou Vocational Institute of Industrial Technology, Suzhou, Jiangsu, China

Abstract

Against the backdrop of digital transformation in education and the deepening reform of Higher Vocational English teaching, traditional pedagogy often suffers from the decoupling of teaching, learning, assessment, delayed feedback and a lack of personalized instruction. Generative Artificial Intelligence (GenAI), with its technical advantages in content generation, intelligent assessment, data analysis and adaptive delivery, offers a viable pathway for constructing an integrated teaching system. Focusing on Higher Vocational English courses, this study employs literature analysis, questionnaires, teaching experiments and statistical data analysis to systematically examine the current state of teaching and assessment. It constructs a GenAI-driven integrated model and proposes actionable implementation strategies.

Keywords

Generative AI; Higher Vocational English; Integration of Teaching-Learning-Assessment; Dynamic Assessment; Personalized Learning

References

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