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

这项创新是一种基于代理的数据驱动的指导技术，它将通过克服人类在回忆需要高度专业知识的复杂流程方面的局限性，增强人类评估任务绩效的能力。基于云的移动的技术将帮助不同专业知识和能力的团队更有效地指导、协调和评估学生的学习进度，特别是那些有发育迟缓的学生。该技术将为指导学生在复杂的学习计划中进行每次尝试的教师提供自然的免提支持。该技术将1）选择任务，2）提供有关设置，提示，目标响应和指令的评估前指导，3）使用语音识别，记录任务性能评估，4）提供有关提供什么强化的评估后指导，如果有的话，以及5）选择下一个任务。为每个任务尝试自动捕获丰富、高质量的数据将有助于使用先进的人工智能技术，如关联数据挖掘，以提供更定制的教学计划。该项目将克服教师专业知识和过程复杂性障碍，消除数据收集负担，同时提高数据和程序的保真度，从而实现更好、更快的学习。这一创新的更广泛/商业影响将发生在应用行为分析（阿坝）和非ABA领域。最初，它将帮助解决危机，为自闭症患者提供具有成本效益的高质量治疗。自闭症影响了世界上超过1%的人。的人口。阿坝是治疗自闭症的金标准。在接受早期治疗的自闭症儿童中，高达50%的人提高了他们的智商和发育进步，因此他们可以在没有教育助理的情况下进入标准教室。如果没有早期干预，几乎没有机会。当认证的阿坝分析师，非认证的阿坝治疗师，教育助理和家庭成员的团队协调指导时，阿坝是最有效的。然而，教师所经历的专业知识和过程复杂性障碍，加上数据收集的负担，限制了其有效性，而训练有素的治疗师的短缺及其高昂的成本（60 K/儿童/年）限制了其可用性。该技术将通过以下方式增加可用的阿坝治疗：1）加速训练，2）使团队成员能够更轻松，更有效地指导更大的数据和程序保真度，3）降低成本。这一创新将加速提供变革性的、负担得起的技术，这些技术将改善许多人的生活，并改善一个重大的世界卫生问题。

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.