Jingyi Shi, Jian Liu, Ying Gu

Ying Gu

August 23, 2026

Generative AI, College-level English, Customized learning, Human-machine collaboration, UTAUT model, IMTA framework.

Generative artificial intelligence is changing the way college students learn English on their own. Traditional large classes are not suitable for students with different language levels, different exam goals, or different learning speeds. As a result, we see problems like uniform training, slow feedback, and a lack of systematic support for self-study. This study adopts two theoretical frameworks: the Unified Theory of Acceptance and Use of Technology (UTAUT), and the Integrated Model of Technology Acceptance (IMTA). On the basis of reviewing previous literature, foreign policy and security, study in both domestic and foreign language acquisition, this paper will analyze the advantages and disadvantages of various types of intelligent English software; then, building an overall customized learning route covering listening, reading, writing, and vocabulary. This path has four parts: academic diagnosis, tiered resource provision, human-machine collaborative training, and dynamic evaluation. The paper also points out some real problems, such as over-reliance on technology, low digital skills, and poor connection with classroom teaching. It offers solutions from the viewpoints of students, teachers, and technology ethics. With the two theories as its base, this study creates a complete learning framework with different levels and different goals. It gives both theoretical and practical help for reforming college English teaching in the digital age.

© 2026, the Authors. Published by ISCCAC

This is an open access article distributed under the CC BY-NC license