EXTREEMS-QED: LABORATORY FOR INTERDISCIPLINARY STATISTICAL ANALYSIS AND MATHEMATICS LEARNING THROUGH QUANTITATIVE EXPLORATION OF DATA (LISA-QED)

该项目的重点是设计有效的教学途径，利用大数据教育下一代数学和统计本科生，以应对计算和数据支持的科学和工程(CDS&amp；E)方面的新挑战。主要目标是1)建立一种培养下一代数学和统计本科专业学生成为跨学科协作者的文化，并促进数学和统计思维在推进CDS&amp；E方面的价值；2)开发一种新的教学方法来教授数学和统计课程，以实验为补充，让学生利用支持网络基础设施(CI)的技术开展动手活动。该项目是跨学科的，整合了研究、教育、培训和教师专业发展/外联部分，这些部分巧妙地导致了CI资源中心的建立和可持续性。该中心为杰克逊州立大学(JSU)的研究社区协调CI资源需求以及超级计算中心和CDS&A；E合作者的访问。研究部分侧重于对通过信息技术远程获取的气候、天气和基因组的大量数据集进行量化探索，以解释已知的数学和统计理论，并发展新的代数和统计结构和理论。主要目标是：1)让28名数学或统计、生物和气象学专业的本科生参与为期一年的CDS&A；E研究，在教师导师的跨学科团队的指导下，为期至少两年；以及2)引导参与研究的学生在CDS&A；E进行夏季本科生研究。教育和培训部分的重点是发展统计学学士学位，以及数学和统计教学的新教学方法。教学将讲课与实验活动结合起来，课堂上学到的概念与CI实验室活动相结合，将特定的数学和统计概念与基因组和气象应用联系起来。具体目标是1)修订抽象和线性代数、集合论和逻辑、现代几何、常微分方程式和数学建模的课程内容，将CDS&A；E整合到CI数据和可视化活动的特定课程主题中；2)为统计学学士学位开发课程；以及3)创建LISA-QED实验室，配备OptI门户和相关技术，用于本地和远程协作、访问NOAA资源和极端科学与工程发现环境(XSEDE)系统，以加强CDS&A；E活动。教师专业发展和外展部分侧重于发展数学教师在CDS&E方面的专业知识，并创造意识。具体目标是1)组织一系列关于生物信息学、系统生物学、气象学、网络学习-XSEDE系统和OptI门户的夏季、秋季和春季CDS&Amp；E培训讲习班，并为JSU的数学和其他教职员工提供后续会议；2)每年组织CI日活动，为教职员工和学生提供机会分享关于CI资源及其在研究中的使用的信息，展示研究海报，并演示OptI门户；3)邀请来自6所HBCU、K-12和大专的至少30名数学教师参加CI日活动；以及4)赞助至少两名数学教师和学生到高端计算(HEC)网站进行实地考察。这些活动旨在作为一个论坛，在CI实验室的授课和实践活动的指导下，就CDS和E驱动的本科数学/统计教育提供一个学习、讨论和信息交流的论坛。以CDS&Amp；E为基础的数学和统计项目模块教学方法强调创造性和原创性地利用CI技术进行可视化分析和协作。它的成功需要教师和数学或统计专业的相关生物学、计算机编程和气象学学科的良好教育背景。28名学生(主要是少数族裔)通过研究、教师指导和公开CI日活动参与进来，既扩大了CDS&A；E教育，也扩大了人们的认识。与超级计算中心和HEC网站的合作，以获得CDS&amp；E的合作者，将使更多的学生和教职员工接触CDS&amp；E，并有助于提高研究生产率。教师和学生都将在专业会议上展示他们的研究成果。LISA-QED的结构和统计学中的BS将导致定性和定量学科的重大课程变化。

The focus of the project is on the design of efficient pedagogical pathways to utilizing big data to educate the next generation of mathematics and statistics undergraduates to confront new challenges in computational and data-enabled science and engineering (CDS&E). The main goals are to 1) build a culture of training the next generation of mathematics and statistics undergraduate majors to become interdisciplinary collaborators and promote the value of mathematical and statistical thinking in advancing CDS&E and 2) develop a new pedagogical approach to teaching mathematics and statistics courses that complements lecturing with experimentation where students engage in hands-on activities with cyberinfrastructure (CI) enabling technologies. The project is interdisciplinary and integrates research, education, training, and faculty professional development/outreach components that subtly lead to the establishment and sustainability of a CI resource center. The center coordinates the CI resource needs and access to supercomputing centers and CDS&E collaborators for the research community at Jackson State University (JSU). The research component focuses on the quantitative exploration of large data sets from climate, weather and genomic acquired remotely through CI enabling technologies to explain the known mathematical and statistical theories and to develop new algebraic and statistical structures and theories. The main objectives are to: 1) Engage 28 undergraduate students majoring in mathematics or statistics, biology, and meteorology in a year-long collaborative CDS&E research for a minimum of two years under the supervision of an interdisciplinary team of faculty mentors; and 2) Guide participating students to place in summer undergraduate research in CDS&E. The educational and training component focuses on developing a BS in statistics and new pedagogical approaches to teaching mathematics and statistics. The teaching combines lecturing with lab activities where concepts learned in class are reinforced with CI lab activities connecting specific mathematical and statistical concepts to genomic and meteorological applications. The specific objectives are to 1) revise the course contents for abstract and linear algebra, set theory and logic, modern geometry, ordinary differential equations and mathematical modeling to integrate CDS&E in specific course topics for CI data and visualization activities; 2) develop a curriculum for the Bachelor of Science degree in statistics; and 3) create a LISA-QED lab equipped with the OptiPortal and associated technologies for local and distant collaboration, access to NOAA resources and Extreme Science and Engineering Discovery Environment (XSEDE) systems to enhance CDS&E activities. The faculty professional development and outreach components focus on developing mathematics faculty expertise in CDS&E and creating awareness. The specific objectives are to 1) Organize a series of Summer, Fall, and Spring CDS&E training workshops on bioinformatics, system biology, meteorology, cyberlearning-XSEDE systems, and OptiPortal with follow ups sessions for mathematics and other faculty members at JSU; 2) Organize CI Days events each year to provide opportunities for faculty and students to share information about CI resources and their use in research, present research posters, and OptiPortal demonstrations; 3) Invite at least 30 mathematics faculty from six HBCUs, K-12 and junior colleges to CI Days events; and 4) sponsor at least two mathematics faculty and students on field trips to High-End Computing (HEC) sites.The activities are structured to serve as a forum for learning, discussion and exchange of information on the CDS&E driven undergraduate mathematics/statistics education guided by a combination of lecturing and hands-on activities in a CI lab. The CDS&E-based project modules approach to teaching mathematics and statistics emphasize creative and original applications in the use of CI technologies for visual analytic and collaboration. The success of it requires a sound educational background of both the faculty and the mathematics or statistics majors in the relevant biology, computer programming, and meteorology disciplines. The engagement of 28 students, mostly minorities, through research, faculty as mentors, and open CI Days events broadens both the CDS&E education and expanded awareness. The collaboration with Supercomputing Centers and HEC sites to gain access to collaborators of CDS&E will expose more students and faculty to CDS&E and contribute to increase in research productivity. Both faculty and students will present their research at professional meetings. The structure of LISA-QED and the BS in statistics will lead to significant curricula changes in both qualitative and quantitative academic disciplines.