MAPLES Walkthrough: From Rubric Upload to Faculty Review
Watch Ameer Hamza Shakur walk through the MAPLES workflow: upload a rubric, group OSCE encounters, run AI-assisted grading, review cited evidence, and export validated results.
Funded by UT REAL Health AI · University of Texas System
Scaling AI-Based
OSCE Assessment
Across Six UT Medical Schools
The MAPLES AI grading platform is being prepared for multi-site validation across UT System medical schools, with engagement through the UT Health Intelligence Platform underway and funding from the UT-REAL Health AI initiative.
LIVE
UTSW Production
6
UT Partner Sites
7,000+
Encounters Graded
Participating Medical Schools
Partnering across the UT System to validate AI-enabled clinical assessment.
Latest Updates
View all posts »Milestones, publications, and announcements from the project.
SAIL 2026: MAPLES Multimodal OSCE Grading
SAIL 2026 poster walkthrough.
Project MAPLES Holds All-Site Kickoff
Participating UT medical school partners met to launch the UT REAL-funded MAPLES project and begin phased deployment planning.
Six UT Medical Schools
Collaborating across the UT System to validate AI-enabled clinical assessment.
View all participating sites →Our Mission
Empowering Educators, Improving Doctors
Our mission is to give medical educators better tools so they can give students better feedback — faster, more consistent, and at a scale that wasn't possible before.
Share Best Practices for AI-Ready Rubrics
Share strategies and best practices for designing AI-compatible OSCE rubrics, while allowing each school to customize assessment to their own educational philosophy and clinical needs.
Scale AI Grading Infrastructure
Prepare MAPLES for governed multi-site deployment across partner sites, with the UT Health Intelligence Platform (UT-HIP) as the preferred infrastructure path under active planning.
Validate AI vs. Human Concordance
Conduct rigorous validation studies comparing AI grading accuracy against expert human raters across diverse patient scenarios and institutions.
Multi-Site Data Collection Planning
Evaluate UT-HIP as the preferred hosting path for a governed multi-institutional OSCE dataset, pending site-specific IRB, DUA, and hosting decisions.
Cross-Institutional Collaboration
Six UT medical schools sharing rubrics, best practices, and lessons learned — building a community of practice around AI-assisted clinical education.
Publication & Dissemination
Publish findings in high-impact venues (NEJM AI, JMIR AI) and present at national conferences to advance the field of AI in medical education.
UTSW Pilot Results
Production metrics from UTSW — the foundation we're scaling across the UT System.
0.830
AI-Human Agreement (kappa)
7,000+
Encounters Graded at UTSW
6
Partner Institutions
$300K
Grant Award
Phase Progress
From single-site proof-of-concept to UT System-wide deployment.
Phase 1: UTSW Proof-of-Concept (Complete)
AI grading system developed and deployed in production at UT Southwestern. 7,000+ encounters graded, 3,200+ students assessed. Published in NEJM AI and JMIR AI. AI agreement (kappa = 0.830) exceeds human inter-rater reliability (kappa = 0.732).
Phase 2: Award & Planning (Current)
Funded by the UT REAL Health AI Pilot Program, March 2026 ($300K, 18 months). Award setup complete. Infrastructure engagement with UT-HIP and UTSW Enterprise Data Services underway. IRB template protocol in review. Site inventory and governance planning in progress.
Phase 3: Multi-Site Deployment
Phased onboarding of partner sites beginning with Wave 1 institutions. Site-specific technical audits, IRB/DUA routing, and data ingestion pipeline setup.
Phase 4: Validation & Dissemination
Cross-institutional validation studies, publication of multi-site results, open-source governance playbook, and framework for national adoption.
Where It All
Started
Born at the UT Southwestern Simulation Center, the MAPLES platform has graded over 7,000 clinical encounters in production — proving that AI can match and exceed human inter-rater reliability. Published in NEJM AI and JMIR AI, with multimodal assessment research on preprint. Now, through the UT-REAL initiative and the UT Health Intelligence Platform, we're scaling that capability across the UT System.