Case-Driven, AI-Assisted, and Competence-Transfer: A Three-Phase Pedagogical Model for Medical Terminology Management and Translation Course

Abstract

 Master of Translation and Interpreting (MTI) programs in China often face insufficient practical opportunities, monolithic instructional formats, and limited systematic training with authentic cases. Case-based teaching, as a pedagogical paradigm well aligned with the cultivation of application-oriented professionals, can compensate for students’ lack of real-world translation experience and help them understand how theoretical knowledge is applied in practice. Taking the course Medical Terminology Management and Translation as an example, this paper reports the construction and implementation of a “Case-Driven—AI-Assisted—Competence-Transfer” teaching model grounded in case-based pedagogy. With translation cases as the organizing vehicle, the model guides students through typical cases toward generative AI-assisted medical translation, with the aim of strengthening their accuracy in medical terminology translation and their proficiency in using AI tools.This study is presented as a teaching-practice exploration that reports the design rationale and implementation process of the model, treating the observed pedagogical effects as hypotheses for further validation. It thus seeks to offer a practical pathway for medical translation education reform in the age of artificial intelligence.