DARPA is especially interested in surfacing ideas that leverage intelligent tutoring to allow adult learners to self-direct learning and develop critical skills. A growing body of evidence demonstrates the power of tutoring as a means to teach all learners quickly and effectively. Yet, programs that rely on human tutors are costly. Recent advances in AI have made way for computer-based tutoring systems that use AI to personalize instruction in real-time based on learner responses. These systems have the potential to drastically reduce the cost of high-quality tutoring, and therefore increase access for all learners.

In addition to receiving funds, winners will have the opportunity to connect with prominent learning science researchers, ed tech leaders, and representatives of large philanthropic organizations to scale their work.

Each proposal will be evaluated on six criteria in addition to the eligibility requirements for the given award level:

• Potential impact and likelihood to improve learning
• Attention to equity to support learning of historically marginalized populations
• Demand from adults, employers, and communities
• Ability to support rapid experimentation and continuous improvement
• Ability to scale to additional users and/or domains
• Team passion, and readiness to execute

There are three award levels:

• Catalyst Phase Awards: These awards are designed for participants including students, teachers, civic technologists, or those who need that initial spark of support to get started. Participants requesting a Catalyst Phase award need not have pre-existing users.
• Growth Phase Awards: These awards are designed for teams that have a minimum viable product with some users upon which their new idea will build.
• Transform Phase Awards: These awards are designed for established platforms with more than 10,000 users.

• Others (see text field entitled "Additional Eligibility Criteria" for clarification)

Estimated Total Program Funding: