The Learn to Earn Fund aims to support and accelerate the development of 10 million more career-ready Americans by 2025. To do this the Fund works to scale postsecondary and career solutions with proven impact for low-income and under-represented students in order to: 1.) prove that effective low-income student interventions can be scaled and sustained, 2.) discredit the excuses given for the career-readiness gap, and 3.) demonstrate effective strategies that next-generation innovators can draw upon.
Power Skills XPRIZE - Cross-sector efforts have identified that “Power Skills”—leadership, critical thinking, problem solving, grit, communication, and teamwork—form the foundation for success in careers and the classroom. Through a global prize, we seek to align the field, and incentivize the development of effective and scalable tools that will help millions of entry level employees launch their careers successfully.
College Access & Success Learning Lab - The Learning Lab is a cross-sector commons through which social entrepreneurs, funders, college and K-12 leaders, and researchers identify key barriers to scale in the College Access & Success field, build a productive cross-sector network, surface high-potential collaborations, and share practices with one another.
Financial Security - The Financial Security Fund empowers students to use financial tools and resources to succeed in postsecondary. We bring together leading funders, social entrepreneurs, researchers, policymakers, and systems leaders to align efforts and scale transformative innovations, with a current focus on emergency aid, on-campus work, and financial capability building.
Hybrid Partnership Investments - Students from low-income backgrounds have few affordable postsecondary options that produce high success rates. Investments in postsecondary partnerships between innovative community-based organizations and top online postsecondary providers have the potential to produce high graduation rates for under-represented students at low-cost and meaningful scale.