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Currently submitted to: Journal of Medical Internet Research

Date Submitted: Feb 6, 2020
Open Peer Review Period: Feb 5, 2020 - Apr 1, 2020
(currently open for review)

Wechat App Combined Case-Based Learning in Clinical Training of Oral Medicine: Comparison and Feasibility Study

  • Hong He; 
  • Xinyu Xia; 
  • Xiaotong Deng; 
  • Mimi Zhou; 
  • Chao Liu; 
  • Lijie Fan; 
  • Li Zeng; 

ABSTRACT

Background:

Case Based Learning (CBL) is being hottly used in student-centered medical education worldwide. In China, Wechat is the most popular communication app in China and is widely used in all walks of life. We have practiced several years combining Wechat and CBL in the clinical training of oral medicine, promoting outcomes in traditional bedside training.

Objective:

This study aimed to demonstrate the acceptability and merits of Wechat CBL in the clinical training of oral medicine.

Methods:

A total of eighty students and two tutors participated in this study within a 2-month training during Jan. 2018 and Jan. 2020. The control group used bedside mode and the experimental group used bedside plus Wechat CBL mode. The evaluations included participation passion and routine and finial test. The students of clerkship as 10 and residents as 30 in same number respectively between experiment and control groups.

Results:

The participants in the experimental group had a higher degree of participation in the discussion. And the daily assessment and final examination scores of the participants in the experimental group were significantly better than those in the control group (P<0.001).

Conclusions:

Wechat CBL mode has a positive effect on students’ learning enthusiasm and knowledge assessments & technology evaluations in clinical training of oral medicine.


 Citation

Please cite as:

He H, Xia X, Deng X, Zhou M, Liu C, Fan L, Zeng L

Wechat App Combined Case-Based Learning in Clinical Training of Oral Medicine: Comparison and Feasibility Study

JMIR Preprints. 06/02/2020:18144

DOI: 10.2196/preprints.18144

URL: https://preprints.jmir.org/preprint/18144


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