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Res Dev Med Educ. 2023;12: 10.
doi: 10.34172/rdme.2023.33081
  Abstract View: 128
  PDF Download: 132

Original Research

Explaining medical students’ perceptions of virtual assessment in the pandemic COVID-19: A content analysis study

Soleiman Ahmady 1 ORCID logo, Amin Habibi 1, Esmat Radmanesh 2* ORCID logo

1 Department of Medical Education, Virtual School of Medical Education and Managment, Shahid Behshti University of Medical Sciences, Tehran, Iran
2 Department of Medical Education, Smart University of Medical Sciences, Tehran, Iran
*Corresponding Author: Esmat Radmanesh, Email: e.radmanesh@abadanums.ac.ir

Abstract

Background: The COVID-19 pandemic has presented a significant challenge to education systems worldwide, disrupting traditional teaching and learning methods. This study aims to explore the perceptions of medical students at Abadan University of Medical Sciences regarding electronic assessment methods during the pandemic.

Methods: This qualitative study utilized conventional content analysis and involved medical students in their second semester of 2021 who had chosen a unit during the pandemic.

Results: Through the analysis process, the participants’ experiences were categorized into six main classes, which included the following: information technology infrastructure, teaching methods of teachers, design of virtual exam questions, monitoring of online exams, psychological issues, and types of virtual assessment.

Conclusion: The medical students shared their experiences with virtual assessment during the pandemic, highlighting challenges related to internet infrastructure, communication issues between teachers and students, exam monitoring, psychological factors, reduced learning efficiency due to virtual summative assessment alone, and better learning efficiency through formative assessment alongside summative assessment. They also suggested improvements to online exams, such as increasing the number of questions on each page, allowing the possibility to return to previous questions, and ensuring non-randomness in clinical questions.

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Abstract View: 129

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Submitted: 18 Sep 2022
Revision: 25 Jul 2023
Accepted: 27 Jul 2023
ePublished: 18 Oct 2023
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