Exploring the influence of artificial intelligence integration on personalized learning: a cross-sectional study of undergraduate medical students in the United Kingdom

AI has the potential to greatly enhance personalized learning for medical students. However, issues surrounding accuracy, misinformation, and equitable access need to be addressed to optimize AI integration in medical education. Further research is recommended to explore the longitudinal effects of AI usage on learning outcomes.

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Publication Details

Journal
BMC Medical Education
Published
2025-04-17
DOI
https://doi.org/10.1186/s12909-025-07084-z
Citations
15
Primary Topic
Artificial Intelligence in Healthcare and Education
Type
article
Field-Weighted Citation Impact
9.81
Controls
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article

Exploring the influence of artificial intelligence integration on personalized learning: a cross-sectional study of undergraduate medical students in the United Kingdom

Kehinde Sunmboye, Hannah Strafford, Samina Noorestani, Malena Wilison-Pirie
15 citations
BMC Medical Education
Artificial Intelligence in Healthcare and Education
9.81
article

Exploring the influence of artificial intelligence integration on personalized learning: a cross-sectional study of undergraduate medical students in the United Kingdom

Kehinde Sunmboye, Hannah Strafford, Samina Noorestani, Malena Wilison-Pirie
article en
15 citations

Abstract

AI has the potential to greatly enhance personalized learning for medical students. However, issues surrounding accuracy, misinformation, and equitable access need to be addressed to optimize AI integration in medical education. Further research is recommended to explore the longitudinal effects of AI usage on learning outcomes.

BMC Medical EducationVol. 25(1)
University of Leicester (GB)
Quality Education
Openalex Percentile: Top 2%
Artificial Intelligence in Healthcare and Education
9.81
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