A Triadic Teacher-Student-AI Model for Vocational English 
Education

Honger Dai

doi:10.70711/neet.v4i2.8673

A Triadic Teacher-Student-AI Model for Vocational English Education

Honger Dai

Abstract

Public higher vocational colleges face a critical challenge: massive classes (70110 students) with proficiency heterogeneity and
divergent examination goals. Approximately 70% must pass PRETCO Level A/B for vocational graduation, while 30% aspire to CET-4 or
"Zhuan Sheng Ben"(transfer to bachelor's degree) entrance examinations. Traditional instruction cannot serve both groups. This paper proposes a Teacher-Student-AI Triadic Model leveraging Generative AI as an adaptive mediator for simultaneous differentiated instruction. The
model operationalizes Vygotsky's Zone of Proximal Development by delegating adaptive scaffolding to AI while preserving the teacher's roles
in conceptual framing, emotional support, and assessment. The paper presents: (1) theoretical foundation in ZPD; (2) four-phase implementation strategies; (3) assessment approaches (Prompt Engineering Score and AI Defense Protocol); and (4) scalability analysis. The model addresses both equity (psychological safety, acceleration) and efficiency (one teacher serving two tracks) imperatives.

Keywords

Vocational Education; Differentiated Instruction; Generative AI; Zone of Proximal Development; Large-Class Instruction

Full Text:

PDF

Included Database

References

[1] Wang, L., & Zhang, J. (2022). A study on stratified teaching in vocational colleges. Vocational and Technical Education, 43(15), 5559.

[2] Celik, B., & Gunduz, N. (2022). Artificial intelligence in language education: Promises, challenges, and realities. Education and Information Technologies, 27(2), 21412165.

[3] Bandura, A. (1977). Self-efficacy: Toward a unifying theory of behavioral change. Psychological Review, 84(2), 191215.

[4] Mollick, E., & Mollick, L. (2024). Using AI to implement effective teaching strategies in classrooms: A classroom experiment. Journal

of Educational Research and Practice, 14(1), 4562.

[5] Zhang, Y. Application of ChatGPT in teaching evaluation reform. Journal of Chongqing Creation & Evaluation, 12(4), 88-92.

[6] Krashen, S. D. (1982). Principles and practice in second language acquisition. Pergamon Press.

[7] Horwitz, E. K., Horwitz, M. B., & Cope, J. (1986). Foreign language classroom anxiety. The Modern Language Journal, 70(2), 125132.

[8] Vygotsky, L.S. (1978). Mind in society. Harvard University Press.

DOI: http://dx.doi.org/10.70711/neet.v4i2.8673

Refbacks

There are currently no refbacks.