About the Study - AI in Medical Education

This international research study aims to comprehensively explore the current landscape of Artificial Intelligence (AI) adoption and perception within medical education globally. We seek to understand the experiences, views, and perceived challenges of medical students regarding the integration of AI tools and concepts into their learning journey.

Background & Rationale

Artificial Intelligence is rapidly transforming various sectors, including healthcare and medicine. Its potential impact on medical training is immense, ranging from personalized learning platforms and intelligent tutoring systems to advanced diagnostic simulation tools. However, the extent and nature of AI integration into medical curricula vary significantly worldwide.

There is a growing need to understand how current medical students, the future generation of healthcare professionals, are experiencing and perceiving these changes. Identifying their familiarity, usage patterns, perceived benefits, and concerns is crucial for developing effective and ethical AI integration strategies in medical education.

Study Objectives

The primary objectives of this study are to:

Assess the level of awareness and familiarity medical students have with AI concepts and tools relevant to medicine.
Identify the types of AI tools currently used by medical students and the purposes for which they are used.
Explore students' perceptions regarding the benefits, limitations, and potential risks of using AI in their education.
Gauge opinions on the future role of AI in medical practice and education, including ethical considerations.
Analyze potential variations in experiences and perceptions based on geographic region, year of study, and other demographic factors.

Methodology

This study employs an international multicentre cross-sectional study design. Data is collected through a comprehensive, anonymous online questionnaire hosted on this dedicated website.

The questionnaire includes sections on:

Demographic information (collected anonymously).
Prior exposure to and usage of AI tools.
Perceptions of AI's impact using Likert scales and multiple-choice questions.
Views on ethical considerations and future integration.

Participation is open to all medical students globally. Data analysis will involve descriptive statistics and comparative analyses to identify trends and potential correlations.

Expected Significance

The findings of this global study are expected to provide valuable, large-scale insights into the student perspective on AI in medical education. This information can inform medical schools, curriculum developers, policymakers, and technology creators in designing and implementing AI solutions that are effective, equitable, and ethically sound, ultimately contributing to the better preparation of future doctors in an AI-driven healthcare landscape.