SBIR Phase I: Data-Driven Guiding Technology- Transforming Training and Therapy

The innovation is an agent-based, data-driven guiding technology that will augment the human facility to evaluate task performance by overcoming human limitations to recall complex processes that require high expertise. The cloud-based, mobile technology will assist teams of varying expertise and capabilities to more effectively instruct, coordinate, and assess learning progress of students, especially those with developmental delays. The technology will provide natural, hands-free support for the instructor who guides the student in each attempt within a complex program of study. The technology will 1) select the task, 2) provide pre-evaluation guidance on setup, prompts, target response and instructions, 3) using speech recognition, record task performance evaluations, 4) provide post-evaluation guidance on what reinforcement to provide, if any, and 5) select the next task. The enabling of automatic capture of rich, high quality data for each task attempt will facilitate the use of advanced artificial intelligence techniques, such as associative data mining, to provide more customized programs of instruction. This project will overcome instructor expertise and process complexity barriers and eliminate data collection burdens while increasing data and program fidelity that will result in better, faster learning. The broader/commercial impact of this innovation will occur in both Applied Behavior Analysis (ABA) and non-ABA areas. Initially it will help tackle the crisis in providing cost effective, quality therapy to individuals with autism. Autism affects more than 1% of the world?s population. ABA is the gold standard in treating autism. Up to fifty percent of children with autism who undergo early treatment improve their IQs and developmentally progress so they can mainstream into standard classrooms with no educational assistants. Without early intervention, there is almost no chance. ABA is most effective when the team of certified ABA analysts, non-certified ABA therapists, educational assistants and family members coordinate instruction. However, expertise and process complexity barriers experienced by instructors, coupled with the burdens of data collection, limit its effectiveness, while the shortfall of trained therapists and its high costs (60K/child/year) limit its availability. The technology will increase available ABA therapy by 1) accelerating training, 2) enabling team members to instruct more easily and effectively with greater data and program fidelity and 3) lowering costs. This innovation will accelerate the availability of transformational, affordable technology that will improve the lives of many and ameliorate a major world health problem.