RET Site: Physically and Biologically Inspired Computational Models and Systems

该奖项在圣母大学建立了一个新的教师研究经验（RET）网站。该网站的重点是吸引当地高中教师参与暑期研究项目，探索受物理和生物系统启发的计算模型。RET网站将在圣母大学和大南本德地区的学校之间建立强有力的伙伴关系，包括公立，私立和教区学校。该网站将招募科学、技术、工程和数学（STEM）领域的高中教师，他们将在夏季与教师导师和研究团队一起从事引人注目的研究项目，然后在学年期间在课堂上实施相关的基于探究的学习模块和活动。该研究主题的跨学科性质将为开发符合州和国家课程标准的生物、物理、数学和其他工程学科的创造性和有吸引力的高中课程和教学活动提供肥沃的土壤。RET Site的教师将参加一个为期7周的暑期学院，在工程学院的指导下参与前沿研究项目，这些工程学院在三个重点领域领导当前的研究项目。第一个领域包括深度学习算法，解决语言理解和行为预测等问题，最常用的是使用深度卷积神经网络。这些数据饥渴和计算密集型的方法往往会产生比传统方法更准确的模型。第二个线程涉及以模拟方式处理数据的非布尔/非冯·诺伊曼神经形态硬件。这样的系统可能会受到人类视网膜的启发，它以一种连续的方式运作，并以真实的时空动态处理连续的输入流。第三条线索包括直接受物理学启发的计算模型。这包括光学启发计算模型等领域，涉及自旋波、磁透镜和耦合振荡器等元素来处理信息。这些项目将提供关于计算、波和光学的真正深入的学习，这些都是高中物理课程的基础。教师将与pi和教师导师合作，开发创新的、符合标准的课程模块，并参与一些专业发展活动。教师创建的模块和课程将通过RET手册、圣母大学RET网站以及年度研讨会在当地传播，并通过全国公认的可搜索、基于标准的工程课程存储库TeachEngineering.org传播。我们计划在整个学年开展广泛的后续活动，以确保将实验室经验转化为课堂实践，并促进和加强工程学院与当地学区之间的长期合作关系。第三方专业项目评估人员将对项目进行跟踪和评估，并提供改进反馈。

This award establishes a new Research Experiences for Teachers (RET) Site at Notre Dame University. The site focuses on engaging local high school teachers in summer research projects that explore computational models inspired by physical and biological systems. The RET Site will develop a strong partnership between Notre Dame and schools in the greater South Bend area, including public, private, and parochial schools. The site will recruit cohorts of high school teachers in the areas of Science, Technology, Engineering and Mathematics (STEM) who will work on compelling research projects with faculty mentors and research teams in the summer and then will implement related inquiry-based learning modules and activities in their classrooms during the academic year. The interdisciplinary nature of the research theme will provide a fertile ground for developing creative and appealing high school lessons and teaching activities in biology, physics, math, and other engineering disciplines that align with state and national curricular standards. RET Site teachers will attend a 7-week summer institute to participate in cutting-edge research projects with mentoring from engineering faculty who lead current research programs in the three areas of emphasis. The first area includes deep learning algorithms that solve problems such as language understanding and a behavior prediction most commonly using deep convolutional neural networks. These data-hungry and computationally intensive methods tend to produce models that are far more accurate than their conventional counterparts. The second thread involves non-Boolean/non-von Neumann neuromorphic hardware that processes data in an analog fashion. Systems that function like this could be inspired by the human retina which operates in a continuous fashion and processes continuous input flows with real spatial-temporal dynamics. The third thread encompasses computation models that are directly inspired by physics. This includes areas such as optically inspired computing models involving elements such as spin waves, magnetic lenses, and coupled oscillators to process information. These projects will provide true in-depth learning about computation, waves, and optics which are fundamental to the high school physics curriculum. Working with PIs and faculty mentors, teachers will develop innovative, standards-compliant curriculum modules and participate in a number of professional development activities. The teacher-created modules and lessons will be disseminated local through a RET handbook and on the Notre Dame RET website as well as at the annual workshop and disseminated through TeachEngineering.org, a nationally recognized repository for searchable, standards-based engineering curricula. Extensive follow-up activities are planned throughout the academic year to ensure the translation of lab experiences into classroom practice, and to foster and strengthen long-term partnership between engineering faculty and the local school districts. A third-party professional program evaluator will track and evaluate the program and provide feedback for improvement.