Artificially Intelligent (AI) Techniques in Student Assessment: Insight and Future Directions

Education is fundamental to development of any society anywhere and effective assessment is crucial for ensuring the quality and results of educational processes. With the swift progress in technology, Artificial Intelligence (AI) has become a revolutionary tool in education, especially in assessment techniques. This review examines the use, advantages, challenges, and future directions of AI-driven assessments in medical education. A systematic literature review was performed utilizing PubMed, Scopus, and Google Scholar, concentrating on studies that investigate the role of AI in medical education and evaluation. From an initial pool of 3,051 studies, 31 were selected based on strict inclusion criteria after a thorough multi-stage selection process. The findings suggest that AI can improve assessment accuracy, transparency, and efficiency through automated grading, adaptive testing, and prompt feedback. AI-driven assessments also have the potential to reduce human biases, lessen the workload for educators, and promote personalized learning experiences. However, challenges such as data privacy, algorithmic bias, and the necessity for AI literacy among educators continue to pose significant issues. In summary, the integration of AI into medical education assessments offers a chance to enhance evaluation standards, support competency-based education, and cultivate the development of more proficient healthcare professionals.