Rigorous Impact Evaluation
for Scalable AI
We welcome research and impact evaluation collaborations to strengthen the evidence base for AI literacy, improve monitoring and evaluation framework delivery, and conduct robust education research.
Collaboration Areas
Help us answer critical questions through impact assessment, learning assessment, and process evaluation in low-resource environments.
Learning Assessment
Validation of baseline assessment and endline assessment tools for AI education.
Assessment and Evaluation in Education
Developing frameworks for behavioral evaluation in education and digital safety.
Process Evaluation
Studying adoption quality, impact assessment, and training fidelity across diverse sites.
Impact Reporting Systems
Validating cost-per-learner models and impact reporting for scalable replication.
Safeguarding & Policy Research
Reviewing privacy-by-design implementations and monitoring safety guidelines.
Research & M&E FAQ
What methods do you use for impact evaluation in education?
We deploy a standardized monitoring and evaluation framework. This includes a baseline assessment before training, ongoing learning assessment, and an endline assessment to support robust impact reporting and education research.
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.