Pattern recognition as a concept for multiple-choice questions in a national licensing exam

Area of Science:

• Medical Education
• Assessment and Evaluation
• Clinical Reasoning

Background:

• Multiple-choice questions (MCQs) remain prevalent in high-stakes medical examinations.
• The study investigates the application of pattern recognition in testing applied clinical knowledge within a national licensing exam.

Purpose of the Study:

• To determine the extent to which pattern recognition is employed in a national medical licensing exam.
• To analyze the variation in the use of pattern recognition questions (PRQ) across different medical disciplines.

Main Methods:

• Analysis of 4,134 German National medical licensing exam questions from 2006-2012.
• Categorization of questions by discipline, year, and type (knowledge questions, PRQ, inverse PRQ, pseudo PRQ).
• Focus on four major disciplines: internal medicine, neurology, pediatrics, and surgery.

Main Results:

• Over 51% of questions were higher-order taxonomical types (PRQ and inverse PRQ).
• A significant decrease in higher-order questions was observed from 61.5% in 2006 to 41.6% in 2012.
• Internal medicine and surgery showed significantly lower proportions of PRQs/inverse PRQs compared to neurology and pediatrics.

Conclusions:

• Pattern recognition is utilized differently across medical disciplines in high-stakes exams.
• Awareness of pattern recognition's role can inform the design and balance of MCQs for assessing clinical reasoning.
• This understanding is crucial for postgraduate medical education assessment.