Medical students’ attitudes toward AI in education: perception, effectiveness, and its credibility
Abstract Background The rapid advancement of artificial intelligence (AI) has revolutionized both medical education and healthcare by delivering innovative tools that enhance learning and improve overall outcomes. The study aimed to assess students’ perceptions regarding the credibility and effectiv...
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| Format: | Article |
| Language: | English |
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BMC
2025-01-01
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| Series: | BMC Medical Education |
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| Online Access: | https://doi.org/10.1186/s12909-025-06704-y |
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| author | Abdul Sami Fateema Tanveer Khadeejah Sajwani Nafeesa Kiran Muhammad Ahsan Javed Dilber Uzun Ozsahin Khalid Muhammad Yasir Waheed |
| author_facet | Abdul Sami Fateema Tanveer Khadeejah Sajwani Nafeesa Kiran Muhammad Ahsan Javed Dilber Uzun Ozsahin Khalid Muhammad Yasir Waheed |
| author_sort | Abdul Sami |
| collection | DOAJ |
| description | Abstract Background The rapid advancement of artificial intelligence (AI) has revolutionized both medical education and healthcare by delivering innovative tools that enhance learning and improve overall outcomes. The study aimed to assess students’ perceptions regarding the credibility and effectiveness of AI as a learning tool and to explore the dynamics of integrating AI in medical education. Methodology A cross-sectional study was carried out across medical colleges in Pakistan. A 26-question survey was developed using Google Forms from previously validated studies. The survey assessed demographics of participants, basic understanding of AI, AI as a learning tool in medical education and socio-ethical impacts of the use of AI. The data was analyzed using SPSS (v 26.0) to derive descriptive and inferential statistics. Result A total of 702 medical students aged 18 to 26 years (mean age 20.50 ± 1.6 years) participated in the study. The findings revealed a generally favorable attitude towards AI among medical students (80.3%), with the majority considering it an effective (60.8%) and credible (58.4%) learning tool in medical education. Students agreed that AI learning optimized their study time (60.3%) and provided up-to-date medical information (63.1%). Notably, 65.7% of students found AI more efficient in helping them grasp medical concepts compared to traditional tools like books and lectures, while 66.8% reported receiving more accurate answers to their medical inquiries through AI. The study highlighted that medical students view traditional tools as becoming increasingly outdated (59%), emphasizing the importance of integrating AI into medical education and creating dedicated AI tools (80%) for the medical education. Conclusion This study demonstrated that AI is an effective and credible tool in medical education, offering personalized learning experiences and improved educational outcomes. AI tools are helping students learn medical concepts by cutting down on study-time, providing accurate answers, and ultimately improving study outcomes. We recommend developing dedicated AI tools for medical education and their formal integration into medical curricula, along with appropriate regulatory oversight to ensure AI can enhance human abilities rather than acting as a replacement for humans. |
| format | Article |
| id | doaj-art-47976a769a514103ad8577a8b61ea477 |
| institution | Kabale University |
| issn | 1472-6920 |
| language | English |
| publishDate | 2025-01-01 |
| publisher | BMC |
| record_format | Article |
| series | BMC Medical Education |
| spelling | doaj-art-47976a769a514103ad8577a8b61ea4772025-01-26T12:38:59ZengBMCBMC Medical Education1472-69202025-01-0125111010.1186/s12909-025-06704-yMedical students’ attitudes toward AI in education: perception, effectiveness, and its credibilityAbdul Sami0Fateema Tanveer1Khadeejah Sajwani2Nafeesa Kiran3Muhammad Ahsan Javed4Dilber Uzun Ozsahin5Khalid Muhammad6Yasir Waheed7NUST School of Health Sciences, National University of Sciences and Technology (NUST)NUST School of Health Sciences, National University of Sciences and Technology (NUST)NUST School of Health Sciences, National University of Sciences and Technology (NUST)NUST School of Health Sciences, National University of Sciences and Technology (NUST)CMH Institute of Medical Science (CIMS)Department of Medical Diagnostic Imaging, College of Health Sciences, Sharjah UniversityDepartment of Biology, College of Science, UAE UniversityNUST School of Health Sciences, National University of Sciences and Technology (NUST)Abstract Background The rapid advancement of artificial intelligence (AI) has revolutionized both medical education and healthcare by delivering innovative tools that enhance learning and improve overall outcomes. The study aimed to assess students’ perceptions regarding the credibility and effectiveness of AI as a learning tool and to explore the dynamics of integrating AI in medical education. Methodology A cross-sectional study was carried out across medical colleges in Pakistan. A 26-question survey was developed using Google Forms from previously validated studies. The survey assessed demographics of participants, basic understanding of AI, AI as a learning tool in medical education and socio-ethical impacts of the use of AI. The data was analyzed using SPSS (v 26.0) to derive descriptive and inferential statistics. Result A total of 702 medical students aged 18 to 26 years (mean age 20.50 ± 1.6 years) participated in the study. The findings revealed a generally favorable attitude towards AI among medical students (80.3%), with the majority considering it an effective (60.8%) and credible (58.4%) learning tool in medical education. Students agreed that AI learning optimized their study time (60.3%) and provided up-to-date medical information (63.1%). Notably, 65.7% of students found AI more efficient in helping them grasp medical concepts compared to traditional tools like books and lectures, while 66.8% reported receiving more accurate answers to their medical inquiries through AI. The study highlighted that medical students view traditional tools as becoming increasingly outdated (59%), emphasizing the importance of integrating AI into medical education and creating dedicated AI tools (80%) for the medical education. Conclusion This study demonstrated that AI is an effective and credible tool in medical education, offering personalized learning experiences and improved educational outcomes. AI tools are helping students learn medical concepts by cutting down on study-time, providing accurate answers, and ultimately improving study outcomes. We recommend developing dedicated AI tools for medical education and their formal integration into medical curricula, along with appropriate regulatory oversight to ensure AI can enhance human abilities rather than acting as a replacement for humans.https://doi.org/10.1186/s12909-025-06704-yArtificial intelligenceDeep learningEducational technology: healthcareMedical educationMachine learning |
| spellingShingle | Abdul Sami Fateema Tanveer Khadeejah Sajwani Nafeesa Kiran Muhammad Ahsan Javed Dilber Uzun Ozsahin Khalid Muhammad Yasir Waheed Medical students’ attitudes toward AI in education: perception, effectiveness, and its credibility BMC Medical Education Artificial intelligence Deep learning Educational technology: healthcare Medical education Machine learning |
| title | Medical students’ attitudes toward AI in education: perception, effectiveness, and its credibility |
| title_full | Medical students’ attitudes toward AI in education: perception, effectiveness, and its credibility |
| title_fullStr | Medical students’ attitudes toward AI in education: perception, effectiveness, and its credibility |
| title_full_unstemmed | Medical students’ attitudes toward AI in education: perception, effectiveness, and its credibility |
| title_short | Medical students’ attitudes toward AI in education: perception, effectiveness, and its credibility |
| title_sort | medical students attitudes toward ai in education perception effectiveness and its credibility |
| topic | Artificial intelligence Deep learning Educational technology: healthcare Medical education Machine learning |
| url | https://doi.org/10.1186/s12909-025-06704-y |
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