RET Site: Physically and Biologically Inspired Computational Models and Systems

这一奖项在圣母大学建立了一个新的教师研究经验(RET)网站。该网站专注于让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网站将在巴黎圣母院和大南本德地区的学校之间建立牢固的合作伙伴关系，包括公立、私立和教区学校。该网站将招聘一批科学、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开展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探究式学习模块和活动。研究主题的跨学科性质将为开发具有创造性和吸引力的高中课程和教学活动提供肥沃的土壤，这些课程和教学活动涉及生物、物理、数学和其他工程学科，符合州和国家课程标准。RET SITE的教师将参加一个为期7周的暑期学院，在工程学教师的指导下参与尖端研究项目，这些教师领导着当前三个重点领域的研究项目。第一个领域包括深度学习算法，这些算法解决了语言理解和行为预测等问题，最常用的是深度卷积神经网络。这些数据匮乏和计算密集的方法往往会产生比传统方法更准确的模型。第二个线索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。像这样运作的系统可能会受到人类视网膜的启发，人类视网膜以连续的方式运行，并以真正的时空动态处理连续的输入流。第三个线程包含直接受物理启发的计算模型。这包括一些领域，例如涉及自旋波、磁透镜和处理信息的耦合振荡器等元素的光学启发计算模型。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，并参与许多专业发展活动。教师编写的单元和课程将通过RET手册和巴黎圣母院RET网站以及年度讲习班在当地传播，并通过TeachEngineering ering.org传播，这是一个全国公认的可搜索的、基于标准的工程课程的资料库。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教师与当地学区之间的长期伙伴关系。第三方专业计划评估员将跟踪和评估计划，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.