MET Enclave

About the MET Enclave

ICPSR’s MET Enclave is a secure research environment for working with the Measures of Effective Teaching classroom videos and linked quantitative data in a protected cloud setting. This scalable environment is designed to support high-compute projects that use AI/ML methods with the MET data.

The MET Enclave is currently in a pilot phase.

We are seeking collaborators to help shape the environment through hands-on use and feedback.

Interested in participating?

 

Application deadline: June 8, 2026

Pilot Timeline: Summer 2026 – June 2027

 

      Apply Today      

About the MET Data

MET LogoThe Measures of Effective Teaching (MET) project stands as the largest study of classroom teaching ever conducted in the U.S., involving over 2,500 teachers across 317 schools in six major school districts during the 2009–10 and 2010–11 academic years.

  • Classroom Videos: 12,000+ authentic classroom sessions (ELA, Math, Biology) across grades 4–9
  • Video Scoring: Videos evaluated by trained raters using established protocols (CLASS, FFT, MQI, PLATO, QST)
  • Robust Linked Data: Student test scores, teacher surveys, and pedagogical knowledge assessments
  • Scale & Diversity: Multiple districts, thousands of teachers, and a wide range of instructional contexts
  • Reliability & Validation: Double-scored videos and millions of observation scores

MET Enclave Research Pilot Requirements

STEP 1: Apply

STEP 2: If Selected, provide:

  • A signed Restricted Data Use Agreement (RDUA) (signed by the Principal Investigator and the PI’s institutional representative)
  • An IRB determination for the intended project

What’s Included

  • Secure, high-compute access to MET video and quantitative data in a protected cloud environment
  • The ability to run approved analytic and AI/ML workflows within the enclave

* Tools and capabilities may change during the pilot as we learn from participants and collaborators

Who Should Apply

  • K–12 researchers, methodologists, data scientists, and others advancing classroom observation or instructional research—especially those interested in working with classroom video and AI/ML methods.