The Knowledge Network was pressure-tested with approximately 50 cross-sector leaders at ASU GSV and covered by EdTech Innovation Hub. The premise is simple: reliable findings shared with decision-makers in real time, while the decisions are still being made.
The study is structured around two questions:
Are students building durable computer science skills when AI tools are part of the learning environment? Do those gains look different from students in non-AI programs?
Does students' use of AI predict their performance without AI? And do those patterns differ for underrepresented students or for those with more prior experience?
The questions are designed to surface differential effects across student populations.
Founding members sit in one of two tiers:
Active Members get early access to findings framed for decision-making. In return, they pressure-test results, share observations from their own institutions and portfolios, and help extend distribution to the networks where findings get acted on.
Community Members stay connected through bimonthly virtual calls and the online community.
Both tiers participate in bimonthly calls and sign a lightweight MOU covering data sharing and confidentiality. The first research briefing is planned for late spring, with the first in-person gathering for Active Members in later this Fall.
Higher education system leaders, funders, workforce and talent development organizations, researchers, and practitioners working at the intersection of AI, education, and economic mobility.
If your organization should be part of this work, submit your interest in joining the network.