When we introduced our updated funding model in April of this year, we made a commitment to increasing our support of early stage organizations that may not have previously qualified for funding. Today, we’re announcing our financial support of the 2021-22 Learning Engineering Tools Competition, alongside Schmidt Futures, Citadel founder and CEO Ken Griffin, Walton Family Foundation, and Siegel Family Endowment. Co-funding this event is an important next step in ensuring that we continue to make progress in our goal of finding and funding early stage organizations, and supporting them to develop, innovate, and test new solutions and programs that improve key academic and socio-emotional outcomes for all children. 

Last year, we had the honor of participating as a reviewer in the inaugural Tools Competition event, which drew almost 900 initial proposals. Given the quality of the entries, from both established and emerging global entrepreneurs, and the emphasis on developing novel approaches to mitigate COVID-19-related learning loss, we were excited to become more involved in 2021. We were particularly impressed to see the reach that the winners are expected to have from last year, which is projected at more than 1 million learners in 2021 alone.

We’re particularly excited about joining other funders as part of a joint effort to spur innovation in education, especially through the use of technology.

This year’s Tools Competition will offer more than $3 million in prize awards—more than double last year’s—and will be one of the largest edtech competitions ever convened. The competition will maintain the focus on learning engineering but update the tracks to reflect current education opportunities and priorities, which include accelerated learning, assessment, adult learning, and research-driven experimentation. Overdeck Family Foundation will focus our support on the two tracks that are most aligned with our Innovative Schools and Exceptional Educator portfolios:

  • Accelerated learning in elementary and secondary literacy and math. Tools that help students achieve or exceed proficiency in grade-level literacy or math skills, despite unfinished learning due to COVID. 
  • Transformed K-12 assessment. Tools that improve the quality of assessment to better meet the needs of educators, students, and families while reducing the time and/or cost to develop or administer. This includes diagnostic, formative, interim, summative, and direct-to-family assessments.

We’re particularly excited about joining other funders as part of a joint effort to spur innovation in education, especially through the use of technology. The Schmidt team’s learning engineering philosophy, which seeks to design learning systems through partnership with the research community and feedback loops that allow for continuous improvement, is very much aligned with our Foundation’s values of thinking and acting with rigor and learning better, together. By working with a diverse group of funders, we believe that we will not only have more impact, but also work more quickly and effectively to measurably enhance education and improve key academic and socio-emotional outcomes for all children. As we all know given the challenges of the last year, time is of the essence.

The Learning Engineering Tools Competition has a phased selection process in order to give competitors time and feedback to strengthen their programs and build a team. Submissions are now open, and the deadline for initial proposals is October 1st with phase II proposals due on December 17th.  The pitch before a panel of judges will take place in March 2022 with competitors notified in April 2022. 

We’re proud to partner with Schmidt Futures and the other funders to bring this competition to life for the second time, and are looking forward to learning alongside our partners and the applicants as we review applications, select the winning organizations, and work with them to ensure that they enable as much impact as possible for today’s children and families.

-George Khalaf, Program Director