ReviewJournal of advances in medical education & professionalism2025
Intelligent Assessment Systems in Medical Education: A Systematic Review.
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, 1 of them a synthesis that pooled it.
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, 1 synthesis or guideline pooled it.
- Application of deep machine learning in dental education: a systematic review of effectiveness in dental students' teaching learning outcomes.Evidence-based dentistry · 2026Pooled it
- The FUSION Model: Smart Integration of Tradition and Innovation in Medical Education.Journal of advances in medical education & professionalism · 2026Article
- Benchmarking Large Language Models for Scientific Writing: A Mixed‑Methods Evaluation of Chatgpt, Deepseek, and Human Authors.Journal of advances in medical education & professionalism · 2026Article
- The digital transformation of medical education collaborative governance in the era of smart education: an innovative management restructuring of medical talent cultivation systems.Frontiers in medicine · 2026Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
2 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Introduction: Using Intelligent Assessment Systems (IAS) in medical education has garnered attention as an advanced tool for enhancing educational processes and student evaluation. These systems leverage advanced algorithms to rapidly assess the students' performance and learning progress. This systematic review aimed to examine the role and impact of Intelligent Assessment Systems in improving educational processes, academic evaluation, and learning progress in medical students compared to traditional assessment methods. Methods: This study was conducted using the PRISMA framework for reporting systematic review articles. Databases such as Embase, PubMed, ProQuest, Web of Science, and Scopus up to March 2024 were reviewed using relevant keywords. Eligible articles were selected and evaluated based on predefined inclusion and exclusion criteria. Results: Out of 2741 articles identified, 10 studies were selected for final analysis. This systematic review analyzed 10 studies, demonstrating that interactive assessment systems (IAS) can enhance learning outcomes by up to 40% in certain settings. The findings emphasized the benefits of immediate feedback and reduced instructor workload. The significant role of IAS in enhancing student performance, providing immediate feedback and reducing the workload of instructors was indicated. These systems, through the use of machine learning algorithms and virtual reality simulators, enable more accurate and comprehensive assessment of students' clinical and cognitive skills. Conclusion: Intelligent Assessment Systems (IAS) significantly improve educational processes and academic evaluation by providing immediate and precise feedback, enhancing student self-efficacy and self-awareness and reducing the training time and costs. The successful implementation of IAS requires careful system design, user training, and continuous technical support. Further studies are recommended to explore the advantages and challenges of these systems and to optimize their implementation in medical education. The long-term impacts of IAS and scalability across educational contexts require further studies. In conclusion, IAS offers transformative potential in medical education globally, provided that challenges are addressed.
Indexed as
Identifiers
What OpenQuestion holds
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.