Author(s)

YongQin Wang

Affiliation(s)

School of Foreign Languages, Harbin University of Science and Technology, Harbin 150000, Heilongjiang, China.

Corresponding Author

YongQin Wang

ABSTRACT

This study integrates the SAMR model (Substitution, Augmentation, Modification, Redefinition) with AI-driven e-learning to develop a unified online-offline academic English framework for mechanical engineering students in China’s new engineering education context. Specific AI applications include: substitution-level AI grammar checkers and vocabulary apps, augmentation-level adaptive algorithms delivering real-time feedback, modification-phase automated essay scoring and speech recognition for multidimensional assessment redesign, and redefinition-stage AI-generated VR simulations for immersive language practice. Using a mixed-methods approach—pre/post-tests, technology fluency evaluations, and focus groups—the research demonstrates that this framework significantly enhances students’ academic English proficiency, critical thinking, and interdisciplinary communication skills. Results confirm substantial gains in engagement and satisfaction, highlighting AI’s transformative role in redefining pedagogical paradigms for engineering education.

KEYWORDS

AI-driven education; SAMR model; Academic English; Online and offline integration

CITE THIS PAPER

YongQin Wang. Integrating SAMR model with AI-driven e-learning in academic English: a unified framework for online and offline courses. World Journal of Educational Studies. 2026, 4(2): 41-48. DOI: https://doi.org/10.61784/wjes3140.

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