AI Educational Engagement Patterns and Their Association With Attitudes Toward AI Integration in Anatomical Science...

Area of Science:

• Medical Education
• Artificial Intelligence in Education
• Anatomical Sciences

Background:

• Artificial intelligence (AI) is increasingly integrated into medical education.
• Understanding student learning patterns and attitudes towards AI is crucial for effective implementation.
• Anatomical sciences present a unique area for AI integration in medical training.

Purpose of the Study:

• To explore the association between medical students' learning patterns and their attitudes towards AI-integrated teaching in anatomical sciences.
• To identify factors influencing medical students' acceptance and perceived limitations of AI tools in anatomy education.
• To provide insights for optimizing AI integration in medical curricula.

Main Methods:

• A cross-sectional study was conducted among 368 undergraduate medical students (years 2-6) at Al-Balqa Applied University, Jordan.
• A questionnaire assessed demographics, attitudes towards AI, and perceived limitations of AI use.
• Data were collected via institutional emails and student communication platforms between September and November 2025.

Main Results:

• Chatbots were the most used AI tool (73.9%), while lecture slides remained the primary resource (91.9%).
• Students using 3D/VR models or AI tools showed significantly more positive attitudes toward AI (p < 0.001).
• Higher perceived limitations and male gender correlated with less positive attitudes; higher GPA and use of 3D/VR/AI tools predicted more positive attitudes.

Conclusions:

• Medical students preferring AI tools reported better experiences in AI-integrated anatomy education.
• Traditional textbook reliance was associated with perceiving AI integration as more limiting.
• Institutional guidance and exposure are key to maximizing the utility of AI as a practical educational tool.