Harnessing the Generative Power of AI to Move Closer to Personalized Medical Education
The 2-Sigma platform has the potential to address Bloom's 2-sigma problem by providing scalable one-on-one style interactions and feedback. This platform allows educators to collect and analyze data from the case transcripts that would otherwise be inaccessible or complicated to obtain, providing new opportunities to assess students' clinical reasoning behaviors and to tailor feedback. Planned refinements include expanded analysis of learners' behaviors, ensuring AI accuracy, and improved personalization of feedback. Future work will systematically evaluate how AI-generated feedback influences clinical reasoning and learners' attitudes.
Authors
- Weibing Zheng
- Danielle Weber (ORCID: https://orcid.org/0000-0002-4857-6936)
- Laurah Turner (ORCID: https://orcid.org/0000-0002-4567-1313)
- Matthew Kelleher (ORCID: https://orcid.org/0000-0002-6400-1745)
- Sally A. Santen (ORCID: https://orcid.org/0000-0002-8327-8002)
- Mohammad Hadi Gharib (ORCID: https://orcid.org/0000-0003-4847-921X)
- Seth Overla
- A. Zahn
- Alexander Gregath
Institutions
- Twitter (United States) (US)
Publication Details
- Journal
- Academic Medicine
- Published
- 2025-08-11
- DOI
- https://doi.org/10.1097/acm.0000000000006185
- Citations
- 5
- Primary Topic
- Artificial Intelligence in Healthcare and Education
- Type
- article
- Field-Weighted Citation Impact
- 3.27