Introducing expert systems to medical students using ESTA, expert system teaching aid

Area of Science:

• Medical Education
• Artificial Intelligence in Medicine
• Computerized Decision Support

Background:

• Limited curriculum time restricts medical students' exposure to expert systems.
• Effective integration of technology is crucial for modern medical training.

Purpose of the Study:

• To describe student interaction with ESTA, a novel expert system model.
• To present student reactions to expert system concepts and their role in medicine.
• To inform pedagogical approaches for teaching computer science in medical curricula.

Main Methods:

• Development of ESTA, a computer model simulating an expert system.
• Observation and analysis of medical students' interaction with ESTA.
• Qualitative assessment of student feedback on expert system concepts.

Main Results:

• ESTA facilitated effective use of limited instructional time.
• Students demonstrated varied reactions to expert system concepts.
• Student feedback highlighted perceptions of AI's place in medical practice.

Conclusions:

• Expert systems can be effectively taught within constraints of medical curricula.
• Understanding student perceptions is key to successful technology integration.
• This approach offers valuable insights for teaching broader computer applications in medicine.