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Journals / International Journal of Computers in Education / 2026 / Volume: 9 Issue: 1

Systematic Examination of Artificial Intelligence Readiness Levels of Medical Faculty Students

Tıp Fakültesi Öğrencilerinin Yapay Zekâ Hazırbulunuşluk Düzeylerinin Sistematik İncelenmesi

Mert Duman(İZMİR DEMOKRASİ ÜNİVERSİTESİ)0009-0001-3004-7657
Kadir Demir(İZMİR DEMOKRASİ ÜNİVERSİTESİ)0000-0001-9568-9450
Pages
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Publication Date
2026-06-30
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AI Summary & Key Takeaways

AI Insight
⚡ TL;DR(Too Long; Didn't Read)

Findings indicate that students’ overall AI readiness is at a moderate level.

📌 3 Key Takeaways

🎯
Objective & Hypothesis:This study aims to systematically review the existing literature examining artificial intelligence (AI) readiness levels of medical faculty students.
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Key Findings & Data:Eight cross-sectional studies meeting the inclusion criteria were included, encompassing a total of 3,243 medical students from Turkey, India, Morocco, Kuwait, Indonesia, and Malaysia.
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Conclusion & Impact:Findings indicate that students’ overall AI readiness is at a moderate level.
🔬Design:Review & Systematic Survey
📍Scope:Comprehensive Sample
⚙️Variables:artificial intelligence readiness · medical education · medical students

Abstract

This study aims to systematically review the existing literature examining artificial intelligence (AI) readiness levels of medical faculty students. Following PRISMA guidelines, a comprehensive search was conducted across PubMed, Scopus, Web of Science, and Google Scholar databases. Eight cross-sectional studies meeting the inclusion criteria were included, encompassing a total of 3,243 medical students from Turkey, India, Morocco, Kuwait, Indonesia, and Malaysia. Findings indicate that students’ overall AI readiness is at a moderate level. MAIRS-MS total scores ranged from 61 to 73, with the cognitive subdimension consistently scoring lowest and the ethics subdimension scoring highest. Gender, academic year, and prior technological experience were identified as key factors influencing readiness. The results highlight the urgent need for systematic integration of AI education into medical curricula, particularly targeting the cognitive knowledge gap.

Özet

Bu çalışma, tıp fakültesi öğrencilerinin yapay zekâ (YZ) hazırbulunuşluk düzeylerini inceleyen mevcut literatürü sistematik olarak derlemeyi amaçlamaktadır. PRISMA kılavuzu temel alınarak PubMed, Scopus, Web of Science ve Google Scholar veri tabanlarında gerçekleştirilen tarama sonucunda, dahil etme kriterlerini karşılayan sekiz kesitsel çalışma derlemeye alınmıştır. Toplam 3.243 tıp öğrencisini kapsayan bu çalışmalar Türkiye, Hindistan, Fas, Kuveyt, Endonezya ve Malezya’dan gerçekleştirilmiştir. Bulgular, öğrencilerin genel YZ hazırbulunuşluk düzeyinin orta seviyede olduğunu göstermektedir. MAIRS-MS toplam puanları 61–73 aralığında kalmış olup bilişsel alt boyut en düşük, etik alt boyut ise en yüksek puanları almıştır. Cinsiyet, sınıf düzeyi ve teknolojik deneyim hazırbulunuşluğu etkileyen temel faktörler olarak belirlenmiştir. Sonuçlar, tıp müfredatlarına yapay zekâ eğitiminin sistematik biçimde entegre edilmesi gerektiğine işaret etmektedir.

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Cite This Article

Duman, M., Demir, K. (2026). Systematic Examination of Artificial Intelligence Readiness Levels of Medical Faculty Students. International Journal of Computers in Education, Volume: 9 Issue: 1. https://doi.org/10.64693/ijce.1947516

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