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Related Experiment Video

Updated: Apr 15, 2026

Setting Up a Stroke Team Algorithm and Conducting Simulation-based Training in the Emergency Department - A Practical Guide
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Is remediation program using team-based learning effective for at-risk medical students?

Kyung Duk Park1, Bora Kim, Taeyeon Kim

  • 1Office of Medical Education, Seoul National University College of Medicine, Seoul, Korea.

Korean Journal of Medical Education
|March 26, 2015
PubMed
Summary

Team-based learning (TBL) effectively remediates at-risk medical students. This approach improved scores and confidence, ensuring all participants passed their graduation examination.

Keywords:
Clinical knowledge examinationMedical educationRemediationTeam-based learning

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Area of Science:

  • Medical Education
  • Student Remediation

Background:

  • Effective remediation strategies for at-risk medical students are lacking.
  • Medical education requires robust methods for student reassessment and support.

Purpose of the Study:

  • To evaluate the efficacy of a team-based learning (TBL) program for remediating at-risk medical students.
  • To provide guidelines for designing and implementing remediation programs in medical education.

Main Methods:

  • Fourth-year medical students identified as needing remediation were assigned to teams of 4-5.
  • A 3-week remediation program focused on clinical topics relevant to the Korean Medical License Examination was implemented.
  • Student performance was assessed via re-examination, and feedback was collected.

Main Results:

  • Students in the TBL remediation program showed significant improvement in re-examination scores compared to a control group.
  • The majority of students reported the TBL program was instructive and aided examination preparation.
  • All students who participated in the remediation program successfully passed their graduation examination.

Conclusions:

  • Team-based learning (TBL) is a viable and effective method for remediating at-risk medical students.
  • Further research is necessary to optimize the design and implementation of TBL-based remediation programs.