Assessment is a key component of learning in medical education. Wars, humanitarian crises, and disruptions to educational infrastructure have shown that traditional assessment methods, especially face-to-face, high-stakes assessments, are not sufficiently effective and fair in times of crisis. They also have limitations in measuring complex competencies such as clinical reasoning, communication skills, decision-making, and resilience under pressure. In contrast, competency-based assessment approaches and longitudinal and formative assessments provide greater flexibility for continuing education and assessment in a crisis. Recent advances in artificial intelligence have also created new opportunities for designing clinical scenarios, adaptive testing, virtual patients, virtual OSCEs, and providing automated feedback. However, challenges such as algorithmic bias, overreliance on automated systems, and limitations of technology infrastructure in crisis settings highlight the need for cautious use of this technology.
Accordingly, the use of a hybrid assessment model is suggested, while maintaining the central role of faculty members and using artificial intelligence as an assistant tool. Also, developing competency-based assessments, using diverse assessment methods and paying attention to the different conditions of students during times of crisis can help improve educational quality and equity.