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Related Experiment Video

Updated: Aug 29, 2025

Project-Based Learning Guidelines for Health Sciences Students: An Analysis with Data Mining and Qualitative Techniques

Project-Based Learning Guidelines for Health Sciences Students: An Analysis with Data Mining and Qualitative Techniques

Published on: December 9, 2022

Clinical shadowing experience PIF rubric.

Jordana B Owens¹, Jennifer E Tucker^2,3, William G Pearson⁴

¹Medical College of Georgia, Augusta University, Augusta, Georgia, USA.

The Clinical Teacher

|September 8, 2022

Summary

This summary is machine-generated.

A new rubric effectively documents preclinical medical students' professional identity formation (PIF) through reflective writings on clinical shadowing. Further development could enhance its reliability using machine learning.

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Area of Science:

Medical Education
Professional Identity Development

Background:

Professional identity formation (PIF) is crucial for medical students.
Assessing PIF in preclinical years presents unique challenges.
Reflective writings (RWs) offer a window into student experiences.

Purpose of the Study:

To develop and evaluate an analytic rubric for documenting PIF.
To assess PIF in preclinical medical students using reflective writings on clinical shadowing experiences.

Main Methods:

Comprehensive literature analysis informed rubric development.
An iterative immersion/crystallisation process was used.
Rubric underwent empirical testing, reliability assessment, and refinement.

Main Results:

The developed rubric is theory-informed and analytic.
It demonstrates feasibility for measuring PIF in student RWs.
Twenty-nine first-year reflective writings were evaluated.

Conclusions:

The clinical shadowing experience PIF rubric is a viable tool.
Current reliable use necessitates a team approach.
Machine learning integration could improve rubric reliability.