Three-Dimensional Closed-Loop Classroom for Maritime English in Vocational Colleges Enabled by Generative AI

Abstract

Driven by the dual forces of educational digital transformation and high-quality development of the shipping industry, generative artificial intelligence (Generative AI) provides a new technical path for innovating vocational foreign language teaching models. As a type of English for Specific Purposes (ESP), maritime English in vocational colleges is highly job-oriented and practice-intensive. At present, vocational maritime English teaching generally suffers from rigid models, difficulties in differentiated instruction, lack of practical scenarios, and fragmented teaching links. Traditional linear teaching fails to form an effective closed loop, restricting the development of students’ job-related English competence. Based on generative AI, this study integrates closed-loop teaching theory and personalized learning theory, and adopts bibliometric analysis, questionnaire surveys, quasi-experimental research, and fuzzy comprehensive evaluation. Focusing on pre-class, in-class, and post-class dimensions, it deeply analyzes current shortcomings in maritime English classroom construction. It explores existing pain points in three-dimensional classrooms, details the implementation paths of AI-enabled closed-loop instruction, constructs an intelligent teaching model consisting of diagnosis, training, and consolidation layers, and establishes supporting mechanisms for technology, faculty, and evaluation. Teaching practice shows that this model effectively alleviates problems such as differentiated learning difficulties, insufficient practice, and weak connectivity, enabling cyclic data feedback and dynamic teaching optimization. This study emphasizes practicality and implementability, providing a practical model for digital reform of maritime English teaching and a reference for intelligent construction of similar specialized foreign language classrooms.