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.
Artificial Intelligence Research Funding Opportunity
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.”
Current NCSER-Funded Grants Applying Artificial Intelligence and Machine Learning
Prior to the new collaboration between IES and NSF, NCSER funded several grants that apply artificial intelligence and machine learning approaches, including those described below.
With a 2018 NCSER grant, Dr. Maithilee Kunda and her team at Vanderbilt University are building on a technology-based intervention known as Betty’s Brain. This computer-based instructional program for middle school science, designed with the support of a 2006 NCER grant, allows students to teach a computer agent to understand certain concepts, increasing their own knowledge and understanding. Dr. Kunda and her team are developing a new game called Film Detective, which is designed to improve theory of mind (ToM) reasoning in adolescents with autism spectrum disorder (ASD). More information about this project can be found in this IES blog.
With a 2021 NCSER grant, Dr. Patrick Kennedy and his team at University of Oregon are using machine learning to validate a well-known assessment, Dynamic Indicators of Basic Early Literacy Skills, 8th Edition® (DIBELS 8) as a screener for dyslexia. As of 2020, 47 states require that students be screened for dyslexia in early elementary school and many states use DIBELS for this screening. However, it remains to be validated for this purpose. To address the validity of the DIBELS for screening, this research team is using machine learning approaches to predict and classify scores in relation to a pre-defined target. This will allow the research team to draw conclusions about the validity of the DIBELS 8 for dyslexia screening. These conclusions will be disseminated widely to state and local education agencies and other stakeholders.
The Potential of AI for Improving Outcomes for Learners with Disabilities
In addition to the work that IES is funding, AI has already demonstrated potential for improving outcomes for learners with disabilities in many other ways:
- AI has been used to support children with ASD who have difficulties understanding people’s emotions, with AI-driven apps and robots helping students practice emotion recognition and other social skills.
- AI has informed the development of algorithms that can help those involved in assessment identify disabilities in students, such as ASD, specific learning disabilities (dyslexia, dysgraphia, and dyscalculia), and attention-deficit/hyperactivity disorder (ADHD).
- AI-embedded interventions have included error analysis to inform instruction and personalized feedback in spelling and math for students with disabilities.
Despite these advancements, there appear to be persistent gaps in AI research for students with disabilities, such as AI for students with intellectual and developmental disabilities. This is an especially important area of work because many of these learners have multiple disabilities and/or serious health conditions. For example, children with intellectual and developmental disabilities who also have hearing loss or visual impairment have compounded challenges. Some students with Down syndrome also have hearing loss and other health complications, such as cardiac issues. AI affords an opportunity to integrate health information across different applications to improve the quality of life for these students. These technological solutions can assist in managing information about the students and communicating health information between teachers, physicians, and caregivers.
AI has the potential to transform special education. We hope that this NCSER-NSF partnership will encourage researchers to be creative in planning projects that move the field of AI forward as well as provide innovative solutions to support learners with disabilities.
This blog was co-authored by Sarah Brasiel (Sarah.Brasiel@ed.gov), program officer at NCSER and Bennett Lunn (Bennett.email@example.com), Truman-Albright Fellow for NCSER and the National Center for Education Research (NCER). IES encourages special education researchers to partners with experts in Artificial Intelligence to submit to this NSF AI Institute solicitation 22-502 to increase the evidence base on use of AI for this population.