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Harnessing artificial intelligence for automatic feedback in a virtual anatomy study tool: A Q-methodology study.

Yasmeen Mezil1, Philip Yu2, Layla Rahimpour2

  • 1Department of Anatomy and Genetics, College of Medicine, Alfaisal University, Riyadh, Kingdom of Saudi Arabia.

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Summary
This summary is machine-generated.

An AI-powered online tool enhances anatomy education by providing accessible practice for objective structured practical examinations (OSPEs). Students found the AI OSPE valuable, with differing preferences for 3D versus 2D anatomical visualizations.

Keywords:
artificial intelligencedecision tree learningobjective structured practical examinationpersonalized feedbackq‐methodologyvirtual anatomy study tool

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Area of Science:

  • Anatomy Education
  • Artificial Intelligence in Education
  • Educational Technology

Background:

  • Objective Structured Practical Examinations (OSPEs) are standard anatomy evaluation methods.
  • Student preparedness is limited by access to study materials and mock exams.
  • Resource constraints and pandemic-related access issues necessitated innovative solutions.

Purpose of the Study:

  • To develop and evaluate an AI-powered online tool for OSPE study.
  • To assess student perceptions of the AI OSPE tool using Q-methodology.
  • To identify student preferences for virtual anatomy study resources.

Main Methods:

  • Development of a web-based AI OSPE study tool.
  • Pilot testing with first-year Occupational Therapy students.
  • Q-methodology and by-person factor analysis to identify student groups.

Main Results:

  • Two distinct student groups emerged: Spatial Learners and Practical Thinkers.
  • Spatial Learners preferred 3D anatomical structures for better orientation.
  • Practical Thinkers valued the tool's utility and course relevance.

Conclusions:

  • AI-driven educational tools can supplement traditional anatomy study methods.
  • Student preferences vary, highlighting the need for diverse virtual learning resources.
  • Findings inform quality improvement for AI-based anatomy study tools.