Abstract
Background:
Artificial intelligence (AI) is rapidly reshaping health profession education through tools such as virtual simulation, adaptive learning platforms, intelligent tutoring systems and ChatGPT-assisted learning. However, its effectiveness compared with traditional teaching methods remains unclear.
Aim:
To evaluate whether AI-based and technology-enhanced educational tools improve learning outcomes among healthcare professionals and students compared with traditional teaching approaches.
Methods:
This systematic review was conducted according to Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) and registered in PROSPERO CRD420251233817. Six databases were searched, with key terms relating to healthcare staff, AI and education. Papers published in English language were sought from 2015 to 2025. Nine studies met all the inclusion requirements and were incorporated into the final synthesis. Risk of bias was assessed using Cochrane Risk of Bias tool for RCT’s (RoB-2). Level of evidence is assigned to studies based on the research design, quality of the study and applicability to patient care.
Results:
The review noted virtual simulation, AI-supported problem-based learning and AI-generated personalised feedback were particularly beneficial. Findings related to critical thinking, clinical decision-making and skill performance and learner satisfaction were mixed, with several studies reporting comparable rather than superior outcomes in comparison to traditional instructional methods. Evidence on time efficiency was limited but generally suggested that certain AI tools may streamline learning and reduce faculty workload compared to lectures or low-fidelity simulation.
Conclusion:
AI-based educational tools provide meaningful benefits, especially for diagnostic accuracy and sustained knowledge and skill retention, but do not consistently outperform traditional methods across all educational outcomes. AI-based educational tools are beneficial to the lecturers as it enhances teaching efficiency, improves assessment quality, provides real-time learning analytics and saves time in administrative tasks.
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Supplementary Material
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