Rigorous Evaluation
for Scalable AI
We welcome research and evaluation collaborations to strengthen the evidence base for AI literacy, improve delivery fidelity, and support replication at scale.
Collaboration Areas
Help us answer critical questions about AI adoption in underserved communities.
Learning Measurement
Design and validation of baseline/endline assessments for AI literacy.
Safety Competency
Developing frameworks to measure behavioral changes in digital safety.
Implementation Fidelity
Studying adoption patterns and quality across diverse partner sites.
Unit Economics
Validating cost-per-learner models for scalable replication.
Ethics & Privacy
Reviewing safeguarding protocols and privacy-by-design implementations.
Research & M&E FAQ
How can academic researchers collaborate?
Researchers can collaborate by designing impact studies, validating our assessment tools, or conducting qualitative reviews of our delivery models.
Do you provide anonymized data for research?
Yes, we can provide anonymized, aggregated impact data to authorized research partners following strict privacy and ethics reviews.