The usefulness of artificial intelligence-mediated learning in medical education
Keywords:
Artificial intelligence; medical education; systematic review; clinical competenciesAbstract
Introduction: Artificial intelligence (AI) is transforming medical education globally by enhancing clinical competencies and curricula. However, its adoption in Latin America remains limited due to digital inequalities, insufficient teacher training, ethical concerns, and gaps in local research. In Ecuador, initiatives such as the implementation of AI-enabled health solutions in regions with limited medical infrastructure reflect a commitment to improving healthcare. These solutions, such as mobile platforms with AI-based voice assistants, seek to strengthen the delivery of care in resource-limited areas.
Objective: To systematically analyze the effectiveness of AI-mediated learning in the acquisition of clinical skills in medical students.
Material and Method: A systematic review was conducted following PRISMA 2020 guidelines, structured around the PICO framework: population (medical students and educators), intervention (AI strategies such as simulators and adaptive platforms), comparison (traditional methods), and outcomes (competencies, performance, motivation, satisfaction).
Results: AI implementation patterns in Latin America showed variable efficacy (e.g., improvements in clinical skills) and encountered barriers such as inadequate infrastructure. Evidence from Ecuador is scarce, highlighting significant gaps in longitudinal studies and rural contexts. AI was found to transform medical education through personalized learning, simulation of clinical environments, and feedback optimization.
Conclusions: AI offers significant opportunities to personalize medical education; however, successful implementation requires overcoming digital gaps, educators training, and developing local ethical frameworks. Strategic investments in technology, teacher training, and context-specific research are recommended.
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