Scoping Review of AI-Supported Case-Based Learning in Medical Education

A 2025 scoping review synthesizes evidence on generative AI's role in case-based learning from 2019 to 2025. The analysis, conducted by Syed Hani Abidi, maps key themes including clinical reasoning, case creation, and ethical issues. The findings are based on a systematic search of multidisciplinary databases like PubMed and Scopus.

Use Cases

• Analyze the thematic distribution of studies across six key themes such as clinical reasoning and faculty adaptation.
• Map the evolution of GenAI applications in medical education from 2019 to 2025 based on the reviewed literature.
• Identify research gaps and challenges highlighted in the review, such as accuracy and ethical issues.

Strengths

• Systematic review methodology involving independent screening by two reviewers.
• Evidence synthesis organized into six distinct key themes.
• Clear temporal coverage of publications from 2019 to 2025.

Limitations

• The dataset is a single 127.7 KB PDF document, not a structured data table for computational analysis.
• Findings are based on a literature review, not primary empirical data, limiting direct statistical use.
• No columnar data or sample records are provided for machine learning applications.

Provenance

Source

figshare, authored by Syed Hani Abidi.

Collection Method

Comprehensive scoping review via systematic search of PubMed, ERIC, Scopus, Web of Science, and Google Scholar.

Time Range

2019 to 2025

Freshness

Last updated on 2026-03-25.