RET Site: Machine Learning and Smart System Design

由于制造过程自动化程度的提高，行业对具有工业自动化相关知识和技能的工人的需求很高。此外，高速传感器在现场的日益广泛的部署允许收集大量的数据。机器学习技术可以应用于这些数据，使自动化系统能够适应不断变化的条件，也就是说，成为智能系统。这个RET网站将为高中教师提供学习机器学习和智能系统的机会，重点是与工业自动化相关的应用和职业；承担相关科研项目；开发和共享新的教学资源。该计划将加强机器学习和智能系统设计方面的教育，最终增强美国的劳动力和美国的经济竞争力。选择自动化行业的学生也将受益；与自动化相关的入门级工作薪水不错，通常不需要四年的学位。这个RET网站将为高中教师提供与德州农工大学工程学院的教职员工和学生研究人员合作的机会。项目目标包括：1)为教师提供机器学习和智能系统设计专业发展的机会；2)丰富工程概念教学；3)为他们提供与行业导师、大学教师和学生研究人员建立联系的机会；4)使他们能够鼓励、引导和激发学生对项目主题领域的职业兴趣，特别是那些在这些领域历史上代表性不足的学生；5)鼓励他们将所学传播给该领域的其他教师；6)在项目团队、参与教师及其机构和行业之间建立长期的合作关系。该奖项反映了美国国家科学基金会的法定使命，并通过使用基金会的知识价值和更广泛的影响审查标准进行评估，被认为值得支持。

Due to increased automation of manufacturing processes, industry demand for workers with knowledge and skills related to industrial automation is high. In addition, increasingly widespread deployment of high-speed sensors in the field allows vast amounts of data to be collected. Machine learning techniques can be applied to these data to enable automated systems to adapt to changing conditions—that is, to become smart systems. This RET site will provide opportunities for high school faculty to learn about machine learning and smart systems with emphasis on applications and careers related to industrial automation; to work on related research projects; and to develop and share new instructional resources. The program will strengthen education in machine learning and smart system design and ultimately strengthen the U.S. workforce and U.S. economic competitiveness. Students who choose careers in automation will also benefit; entry-level jobs related to automation pay well and often do not require a four-year degree.This RET site will provide opportunities for high school teachers to collaborate with faculty and student researchers in the College of Engineering at Texas A&M University. Program goals include: 1) provide teachers opportunities for professional development in machine learning and smart system design; 2) enrich their teaching of engineering concepts; 3) provide opportunities for them to network with industry mentors, and university faculty and student researchers; 4) equip them to encourage, guide and stimulate their students’ interest in careers in the program’s theme area, especially students historically underrepresented in these areas; 5) encourage them to disseminate what they learn to other teachers in the field; and 6) develop long-term collaborative relationships between the project team, participating instructors and their institutions, and industry.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.