AI-Augmented Learning for Individuals with Disabilities: New Funding Opportunity, Current Research, and the Potential for Improving Student Outcomes

This March, IES Director Mark Schneider released a blog in which he discussed exploring a partnership with the National Science Foundation (NSF) to encourage scientists with expertise in AI and related fields to address the important post-pandemic need for accelerating learning. IES is now excited to announce our resulting participation in NSF’s National Artificial Intelligence (AI) Research Institutes—Accelerating Research, Transforming Society, and Growing the American Workforce solicitation. In this blog, we describe this new funding opportunity, provide examples of existing NCSER-funded research in this area, and highlight the potential for such research to further improve outcomes for learners with disabilities.

With funding from the American Rescue Plan, NCSER plans to support research under Theme 6, Track B: AI-Augmented Learning for Individuals with Disabilities. Proposals must discuss how the work will respond to the needs of learners with or at risk for a disability in an area where the COVID-19 pandemic has further widened existing gaps and/or resulted in decreased access and opportunities for students with disabilities to learn and receive support services. Please review the solicitation, the webinar (November 16), and the frequently asked questions for more information. Interested applicants should note the primary focus of this institute:

“The primary focus of an institute in AI-Augmented Learning includes research and development of AI-driven innovations to radically improve human learning and education. Achievement and opportunity gaps, particularly for learners from disadvantaged or underserved communities, have always been present, but COVID-19 has exacerbated them. Institute plans for this theme should address and measure outcomes with direct education impact, in both the short- and long- term, that have practical significance to educators, parents, or other decision-makers. Plans must also directly address algorithmic bias, model transparency, security and data privacy in the support of learning.”

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