ReviewJournal of advances in medical education & professionalism2025
The Advantages and Challenges of Electronic Exams: A Qualitative Research based on Shannon Entropy Technique.
Review in Journal of advances in medical education & professionalism, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
4 citing papers in PubMed.
- Mapping Personalized Learning in Medical Education: A Meta-Synthesis of Artificial Intelligence Applications.Journal of advances in medical education & professionalism · 2026Review
- An Analysis of the Application of Metaverse in Medical Education: A Qualitative Meta-Synthesis.Journal of advances in medical education & professionalism · 2026Review
- The Role of AI in Shaping Medical Education: Insights from an Umbrella Review of Review Studies.Journal of advances in medical education & professionalism · 2025Review
- Integrating Artificial Intelligence in Medical Education: A Meta-Synthesis of Potentials and Pitfalls of ChatGPT.Journal of advances in medical education & professionalism · 2025Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Introduction: The electronic exam is one of the foremost imperative instruments for evaluating students' execution. Accordingly, this study aimed to identify the advantages and challenges of electronic exams based on Iranian and international studies. Methods: The present qualitative study used meta-synthesis in the first phase. Thus, keywords such as electronic exams, online exams, electronic assessment, and online assessment in Iranian and international databases for 2005-2021 were searched. In the second phase, using the Shannon entropy technique, the advantages and challenges of electronic exams were weighted. Results: Challenges of e-exams were classified into seven sub-categories (poor technical knowledge, security challenges, complexity and challenges in designing examination, complexity and challenges during examination, complexity and challenges after examination, lack of infrastructure, socio-cultural challenges). The advantages of e-exams were also classified into five sub-categories, including improvement of teaching and learning process, effectiveness of student performance assessment, advantages in designing exams, advantages during examinations, and advantages after examinations. In Shannon's entropy findings, challenges (complexity and challenges after examination and poor infrastructure) and advantages (advantage after exams implementation) had the largest weight. Conclusion: Considering the importance of electronic exams, especially with the outbreak of the COVID-19 epidemic, the inevitable movement of university systems, increasing concerns about student performance assessment, and improving educational performance in the current situation, decision-makers are expected to emphasize the advantages of this kind of exam and address its challenges to help improve the student assessment mechanisms.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.