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Related Experiment Video

Updated: Dec 1, 2025

Author Spotlight: Evaluating Clinicians' Adoption of Ultrasound-Guided Vascular Cannulation Through Simulation Training

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Practice-Based Learning Using Smart Class: A Competency-Based Model in Undergraduate Radiology Education.

Yun Qin¹, Zixing Huang¹, Jianqun Yu¹

¹Department of Radiology, West China Hospital, Sichuan University, No.37 Guoxue Alley, Chengdu 610041, Sichuan, China; Teaching and Research Office of Medical Imaging, West China School of Medicine, Sichuan University, Chengdu 610041, Sichuan, China.

Academic Radiology

|November 7, 2020

Summary

A competency-based smart class model for undergraduate radiology education improved students' application skills and satisfaction. This practice-based learning approach enhances early exposure to radiology and competency development for medical students.

Keywords:

PACS simulator Practice-based learning Smart class Undergraduate radiology education e-Learning

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Published on: December 9, 2022

Area of Science:

Medical Education
Radiology Training
Competency-Based Education

Background:

Increasing need for early and adequate radiology practice exposure for undergraduates.
Focus on competency development in undergraduate radiology education.

Purpose of the Study:

To develop and evaluate a competency-based model for practice-based learning in undergraduate radiology education.
To assess the effectiveness of a smart class environment integrated with case-based learning and simulators.

Main Methods:

A randomized controlled experiment involving 114 third-year medical students.
Comparison between a 'Smart-Class' group (n=57) and a 'Traditional' group (n=57).
Assessment through seven quizzes, a final exam, and a student perception survey.

Main Results:

The Smart-Class group demonstrated significantly higher mean scores in quizzes (r=-0.4, p<0.001) and the application subscore of the final exam (r=-0.3, p=0.005).
Students in the Smart-Class group reported higher satisfaction with learning interests, radiology skills, and diagnostic reasoning (r=-0.2 to -0.3, p=0.001-0.034).

Conclusions:

Practice-based learning utilizing a smart class environment enhances application abilities and satisfaction in undergraduate radiology education.
This model offers a practical approach for early radiology exposure and competency development in medical students.