This conceptual study proposes a pedagogical framework that integrates Generative Artificial Intelligence tools (AIGC) and Chain-of-Thought (CoT) reasoning, grounded in the cognitive apprenticeship model, for the Pragmatics and Translation course within Master of Translation and Interpreting (MTI) programs. A key feature involves CoT reasoning exercises, which require students to articulate their step-by-step translation reasoning. This explicates cognitive processes, enhances pragmatic awareness, translation strategy development, and critical reflection on linguistic choices and context. Hypothetical activities exemplify its application, including comparative analysis of AI and human translations to examine pragmatic nuances, and guided exercises where students analyze or critique the reasoning traces generated by Large Language Models (LLMs). Ethically grounded, the framework positions AI as a supportive tool, thereby ensuring human translators retain the central decision-making role and promoting critical evaluation of machine-generated suggestions. Potential challenges, such as AI biases, ethical concerns, and overreliance, are addressed through strategies including bias-awareness discussions, rigorous accuracy verification, and a strong emphasis on human accountability. Future research will involve piloting the framework to empirically evaluate its impact on learners’ pragmatic competence and translation skills, followed by iterative refinements to advance evidence-based translation pedagogy.
Mengyao Liu (Thu,) studied this question.