Sttr phase i: automating employability skills development for individuals with autism spectrum disorder and developmental disabilities

Directed Analytics Inc. received a $276,000 National Science Foundation Project Grant under the NSF Technology, Innovation, and Partnerships program to develop an automated employability skills framework. The one-year project will create a scalable software platform integrating data from school districts and higher education programs on transition methods and employment outcomes for individuals with autism spectrum disorder or other developmental disabilities. Using machine learning, the framework aims to help educators more accurately assess an individual's job task abilities and effectively scale employability skill development. The structured data collection and interlinking is intended to generate analytics on how programmatic factors and educator interventions contribute to competitive employment for approximately 8 million Americans with intellectual disabilities in the education system.

Abstract

The broader impact/commercial potential of this small business technology transfer (sttr) phase i project seeks to increase the competitive employability of individuals with developmental disabilities. For individuals with developmental disabilities (autism spectrum disorder and other intellectual disabilities) employment disparities are far greater than their non-disabled peers; approximately 20% of working-age adults supported by state developmental disability agencies are employed in a paid job and only 15% were employed competitively. The proposed project will develop a product for school districts and higher education establishments to address the needs of approximately 8 million intellectually disadvantaged individuals in the united states education system. The implementation of this innovation seeks to impact the rates of employment in this population, resulting in increases in personal income, reduction of poverty levels, and better health outcomes for individuals. This small business technology transfer (sttr) phase i project plans to create a scalable software framework which integrates, evaluates, and analyzes data from school districts and higher education programs in order to enable the use of machine learning to improve the relationship between transition intervention methods and employment outcomes. Using this innovation, school districts would be able accurately predetermine an individuals? Ability to successfully perform tasks associated with employment. Higher education programs which enroll adults with developmental disabilities may then effectively scale and develop an individual?s employability skills. The framework will provide structured data collection, data alignment, and data interlinking for roadmaps which will be implemented into the product, enabling educators and individuals to interact, learning how employability programmatic factors and educator corrective actions contribute to employability skills development. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the foundation's intellectual merit and broader impacts review criteria.