Lexical Coverage and Reading Comprehension in Medical English Effects of AI-Assisted Text Simplification
Key Points
This research aims to examine the relationship between vocabulary knowledge and reading comprehension in the context of AI-assisted text simplification for medical texts.
Conducted a quasi-experimental design with 199 medical students.
Compared comprehension performance on original and AI-simplified biochemistry texts.
Analyzed the correlation between vocabulary knowledge and reading comprehension.
No significant improvement in overall reading comprehension was observed.
A stronger correlation between vocabulary knowledge and comprehension was found in the simplified texts.
Indicates that AI simplification changes reading processes without directly enhancing understanding.
Abstract
This study investigates how vocabulary knowledge (lexical coverage) relates to reading comprehension in English for Medical Purposes (EMP), with a focus on AI-assisted text simplification. Using a quasi-experimental design with 199 medical students, the research compares performance on original and AI-simplified biochemistry texts. Results show no significant improvement in overall comprehension, but a stronger correlation between vocabulary knowledge and comprehension in the simplified condition. The findings suggest that AI simplification reshapes reading processes by reducing structural complexity and increasing the role of vocabulary knowledge, rather than directly enhancing understanding. This work contributes to research on L2 reading, medical English pedagogy, and AI-assisted language learning.