ENGLISH SPOKEN AND WRITTEN MEDICAL DATA COMMENTARY: A QUALITATIVE INVESTIGATION ON THE UTILITIES, CHALLENGES AND STRATEGIES - Khrismawan, Beleven (Erudio Journal of Educational Innovation, 2025)
The ability to interpret, synthesize, and communicate visually presented data, such as graphs, tables, charts, and process diagrams, is instrumental to both academic performance and evidence‑based clinical practice. However, as noted in research on English for Medical Purposes (EMP), explicit instruction in data commentary remains limited, particularly in non‑English speaking contexts where students must navigate complex non‑verbal elements (NVEs) through English‑medium scientific discourse. This qualitative case study examines how Indonesian medical students perceive and practice spoken and written data commentary in English within an elective course. Five senior undergraduates participated in ten sessions (1,200 minutes in total) that foregrounded graphs, charts, tables, mixed visuals, and process descriptions. The data were the medical students’ perceptions taken from a focus‑group discussion and five student written portfolios. Transcripts and the portfolios were coded inductively and thematically by two coders. Students reported clear academic and professional value as they felt better able to identify salient data points, organize ideas, and deliver concise descriptions that support coursework, research writing, and presentation needs, including international engagement. The results also found students struggled with mixed visual data, complex procedural cycles, and selecting appropriate academic vocabulary. To cope, they drafted in online word processors for grammar and structure and used translation tools to refine lexical choices, while still manually checking accuracy. The findings point to a curricular gap in which data commentary skills are often implicit and under‑scaffolded, despite their relevance to clinical communication and evidence‑based practice. It is recommended that to provide students with explicit, genre‑aware instruction that integrates writing‑to‑speak activities and guided use of AI‑enabled tools, to help learners build both linguistic accuracy and interpretive confidence.