Summary:
In the context of ongoing educational reform in Vietnam, there is increasing emphasis on sustainability, internationalization, and digital transformation in language education. For medical students, English proficiency is essential for accessing global knowledge, engaging in research, and participating in professional communication. However, existing resources such as printed bilingual dictionaries and static glossaries remain insufficient, as they often lack contextual accuracy, pronunciation support, and learner-friendly explanations. This study adopts an exploratory cross-sectional design to investigate medical students’ needs and perceptions regarding English medical terminology and to inform the conceptual development of an AI-assisted English English-Vietnamese (EEV) medical dictionary. Data was collected from 235 second-year medical students at the University of Medicine and Pharmacy at Ho Chi Minh City using a structured questionnaire. The findings indicate a high frequency of dictionary use alongside substantial difficulties related to unclear definitions, unreliable sources, and fragmented learning processes. Students expressed strong demand for simplified definitions, IPA-based pronunciation, and contextualized usage examples. Based on these findings, the study conceptually proposes a chatbot-based EEV medical dictionary that would integrate AI-generated content with human validation. While the proposed tool is not empirically evaluated in this study, it should be regarded as a preliminary conceptual direction rather than a validated educational intervention. Therefore, claims regarding educational effectiveness, institutional value, and broader applicability remain tentative and require future empirical investigation. The study provides preliminary learner-centered insights and suggests possible directions for the future development and empirical evaluation of AI-assisted language resources in medical education.
Refers:
Journal: