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How Artificial Intelligence Can Affect Physician Assistant Student Self-Efficacy When Preparing for Objective
Andrew Chastain1,2, Anne Schempp1,2
1Andrew P. Chastain, DMS, PA-C, is a student at Shenandoah University, Winchester, VA.
Abstract:
To review the existing literature that examines the potential effect artificial intelligence (AI) has on increasing health care student self-efficacy related to objective structured clinical examinations (OSCEs). This review examines current research on student self-efficacy related to OSCE assessment, strategies to increase student self-efficacy and confidence, and emerging studies on applying AI in health care education. This analysis will identify how AI tools might affect student preparation unique to OSCE assessments. Current evidence suggests that despite the widespread acceptance of OSCEs as a valid assessment tool to measure student proficiency in clinical skills, these types of assessments generate disproportionately lower self-efficacy in students preparing for OSCEs than traditional written assessments. Studies show that although student performance on OSCE assessments is not affected by their anxiety, they continue to harbor a negative perception of this type of examination. Evidence has shown that study strategies that enhance student self-efficacy and confidence through preparatory resources produce a mitigating effect on student anxiety. Emerging research has shown evidence that student engagement with, or to produce, AI-generated preparatory tools creates a more self-efficacious student who is confident in their ability to take and pass an OSCE. Using AI as a tool for students to prepare for OSCE assessments holds promise. Training students to engage with AI to generate study tools that focus on strengthening areas where knowledge gaps or weaknesses exist can help to improve their clinical skills and reasoning. Being more self-efficacious and familiar with these tasks only builds self-confidence in performing them.
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