DEVELOPING AND VALIDATING AN AI-DRIVEN ADAPTIVE LEARNING SYSTEM FOR MEDICAL TERMINOLOGY ACQUISITION AND RETENTION IN A NON-ENGLISH SPEAKING MEDICAL UNIVERSITY CONTEXT

This study explores the development of an AI-driven adaptive learning system for improving medical terminology acquisition among medical students in non-English speaking environments. The research proposes integrating machine learning and natural language processing tools into EMP curricula and evaluates their effectiveness in enhancing vocabulary retention, communicative competence, and personalized learning outcomes.

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Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2026-04-21
DOI
https://doi.org/10.5281/zenodo.19676744
Primary Topic
Second Language Acquisition and Learning
Type
article
Field-Weighted Citation Impact
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article

DEVELOPING AND VALIDATING AN AI-DRIVEN ADAPTIVE LEARNING SYSTEM FOR MEDICAL TERMINOLOGY ACQUISITION AND RETENTION IN A NON-ENGLISH SPEAKING MEDICAL UNIVERSITY CONTEXT

F. S. Sharipova
Zenodo (CERN European Organization for Nuclear Research)
Second Language Acquisition and Learning
article

DEVELOPING AND VALIDATING AN AI-DRIVEN ADAPTIVE LEARNING SYSTEM FOR MEDICAL TERMINOLOGY ACQUISITION AND RETENTION IN A NON-ENGLISH SPEAKING MEDICAL UNIVERSITY CONTEXT

F. S. Sharipova
article en

Abstract

This study explores the development of an AI-driven adaptive learning system for improving medical terminology acquisition among medical students in non-English speaking environments. The research proposes integrating machine learning and natural language processing tools into EMP curricula and evaluates their effectiveness in enhancing vocabulary retention, communicative competence, and personalized learning outcomes.

Zenodo (CERN European Organization for Nuclear Research)
Tashkent State University of Law (UZ), Tashkent Pediatric Medical Institute (UZ), Tashkent State University of Economics (UZ)
Quality Education
Openalex Percentile: Top 5%
Second Language Acquisition and Learning
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