JMIR Publications

ABSTRACT

Background:

The COVID-19 pandemic prompted rapid changes in medical education, accelerating the adoption of online and distance learning methods as alternatives to traditional teaching. While these approaches offered logistical advantages, students worldwide reported significant limitations, particularly in terms of motivation, clinical exposure, and hands-on skill acquisition. Despite increased use of digital teaching during the pandemic, core educational objectives and the mission of medical training remained unchanged, emphasizing the continued importance of practical experience.

Objective:

This study investigates the impact of the COVID-19 pandemic on current teaching methods in medical education and explores students’ perceptions of online learning, telemedicine, artificial intelligence, and other modern educational alternatives.

Methods:

This observational, cross-sectional multicentric study surveyed Romanian medical students using a self-developed 48-item online questionnaire distributed via social media. Data were collected over six weeks (February–March), yielding 451 responses, of which eligible participants included students in clinical years or preclinical students interested in surgical or orthopedic careers. Statistical analysis was performed using Microsoft Excel and Jasp.

Results:

A total of 436 responses were analyzed, with students favoring online or hybrid formats for lectures but preferring onsite teaching for practical training. Reduced patient interaction and limited skill acquisition were the main drawbacks of online practical education. Acceptance of hybrid learning correlated with more positive perceptions of teaching methods and a lower perceived desire to cheat.

Conclusions:

The COVID-19 pandemic brought significant changes to the way medicine is being taught in Romania, but it also brought a clearer picture for students and medical staff on how they want medical education to be done. Online cheating remains a significant challenge, but it is being tackled at the moment with different algorithms being tested.