STTR Phase I: Automating Employability Skills Development for Individuals with Autism Spectrum Disorder and Developmental Disabilities

这个小企业技术转让（STTR）第一阶段项目的更广泛的影响/商业潜力旨在提高发展性残疾人的就业竞争力。对于发育性残疾（自闭症谱系障碍和其他智力残疾）的个人来说，就业差距远远大于他们的非残疾同龄人;大约20%的工作年龄成年人得到国家发育性残疾机构的支持，从事有报酬的工作，只有15%的人有竞争力。拟议的项目将为学区和高等教育机构开发一个产品，以满足美国教育系统中约800万智力弱势者的需求。这一创新的实施旨在影响这一人群的就业率，从而增加个人收入，降低贫困水平，改善个人健康状况。小企业技术转移（STTR）第一阶段项目计划创建一个可扩展的软件框架，该框架集成，评估和分析来自学区和高等教育项目的数据，以便使用机器学习来改善过渡干预方法与就业结果之间的关系。利用这一创新，学区将能够准确地预先确定个人成功执行与就业相关任务的能力。 招收有发育障碍的成年人的高等教育课程可以有效地扩展和发展个人的就业技能。该框架将提供结构化的数据收集、数据对齐和数据互连，用于将实施到产品中的路线图，使教育工作者和个人能够进行互动，了解就业能力的计划因素和教育工作者的纠正措施如何有助于就业能力的技能发展。这个奖项反映了NSF的法定使命，并已被认为是值得通过评估使用基金会的智力价值和更广泛的支持影响审查标准。

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.