Rethinking Multiple Choice Questions: A Narrative Review of Evidence, Challenges, and Innovations

Abstract

Background: Multiple-choice questions (MCQs) remain one of the most widely used assessment methods in higher education and health professions education due to their efficiency, reliability, and scalability. However, concerns regarding recall-based testing, guessing, and limitations in assessing complex competencies have led to ongoing debate about their educational value. Recent advances in digital assessment and artificial intelligence (AI) have further transformed the development and application of MCQs.

Objective: This narrative review aims to examine the strengths and limitations of MCQs, explore challenges associated with item design and implementation, and evaluate emerging pedagogical and technological innovations shaping the future of MCQ-based assessment.

Methods: A narrative review was conducted using literature identified from major academic databases, including PubMed, Scopus, Web of Science, ERIC, and Google Scholar. Studies addressing MCQ validity, item-writing principles, educational applications, digital assessment, and AI-assisted question generation were reviewed and thematically synthesized.

Results: The evidence indicates that well-designed MCQs can provide reliable and valid assessment of knowledge, application, and higher-order cognitive skills when supported by appropriate item-writing strategies and psychometric evaluation. Major challenges include poor distractor quality, ambiguous wording, guessing effects, and limited authenticity when items are poorly constructed. Innovations such as clinical vignette-based questions, student-generated MCQs, computer-based testing, adaptive assessment, and AI-assisted item generation are expanding the potential role of MCQs. However, AI applications require expert validation due to concerns regarding accuracy, contextual relevance, and assessment quality.

Conclusion: MCQs remain effective and adaptable assessment instruments when designed according to evidence-based principles. Future developments should focus on improving item quality, integrating digital technologies responsibly, and combining MCQs with authentic assessment approaches to enhance educational validity and learning outcomes.

CME J 2026; 5(1): 54-63