Our Funding Model

We take a two-pronged approach to investing: helping early-stage initiatives develop and validate their programs, and scaling evidence-based growth-stage programs looking to achieve greater impact. We believe this approach allows us to support promising organizations early, while also funding the growth of programs with a strong evidence base so they can reach more children and families.

What We Look For

We look for grantees that meet the following conditions:

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Support the Foundation’s mission by measurably enhancing education inside or outside the classroom

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Align to a portfolio area and its strategies (Early Impact, Exceptional Educators, Innovative Schools, Inspired Minds, or Data for Action)

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Fit into Foundation’s funding approach: early-stage initiatives looking to develop or validate their program, or growth-stage organizations looking to scale

Two children working on a project on a computer. Image provided by NewSchools Venture Fund.

Grantmaking Approach

We seek to live our core values in our approach to grantmaking.

Connect genuinely

Seek to be a true partner, supporting grantees in creating measurable impact for children and families

Think & act with rigor

Build accountability to goals, metrics, and milestones by measuring what is important

Learn better, together

Learn transparently from successes and failures

Data Values & Practices

We aspire to support our grantees in developing the skills and capacity needed to operate rigorous organizations and drive improvement in their work. And because actions speak louder than words, we strive to model the data practices we expect from our grantees by being a data-informed organization that is continually learning and improving.

Internally, we commit to:

  1. Ensuring responsible data use by employing data standards, thoroughly documenting data, following best practices in data privacy, and demonstrating strong data ethics
  2. Transparently discussing how we intend to use data and acknowledging the tensions between data for accountability and data for improvement
  3. Maintaining empathy about the difficulty of building a learning- and data-informed culture
  4. Defining “data” comprehensively by valuing a combination of qualitative and quantitative data, and a broad set of analytical techniques and methodologies
  5. Democratizing access to data, when possible, especially from research
  6. Highlighting the connections between data and people through storytelling and narrative
  7. Looking at data in context to understand the nuances
  8. Disaggregating data by subgroups in order to facilitate deeper understanding about what works for whom, under what conditions, and why
  9. Gathering only the data required to inform decisions and action
  10. Tracking what data are useful for measurement and evaluation and regularly assessing our data requirements based on what we’ve learned