EAGER: Remote Sensing Curriculum Enhancement using Cloud Computing

EAGER提案的总体目标是调查计算科学课程和使用云计算的研究可以很好地适合少数民族服务机构（MSI）的概念。 云计算的许多方面对MSI来说都很有吸引力。 该项目将加强HBCU校园的遥感研究生课程，并后续增加两门课程，以调查其目标。 该项目是伊丽莎白城州立大学（ECSU），HBCU和印第安纳州大学（IU）之间的合作。 遥感应用程序收集的大量数据超过了传统计算系统的能力。 这促使人们使用云服务和高性能计算（HPC）来支持相关的存储和计算。 ECSU和IU开发的课程将通过基于云的在线技术交付给ECSU。这是一个高风险的探索性工作，无论是在其目标和方法，如果成功将提供一个可扩展的模板，为MSI和非MSI机构的教学和研究的云平台上进行。 这一试点项目将尝试在HBCU使用具有共享模块的遥感课程，为一套非常多学科的主题引入课程和研究，但有多种限制，包括多机构合作课程开发和教学，以及新兴课程平台的使用。 一个重要的目标是确定所需的改进和资源，以扩大他们的想法，以便在MSI研究生和本科生课程和研究中更广泛地采用他们的模型。云计算潜在地具有托管并行和分布式计算两者的能力（例如，使用Hadoop）和学习资源（例如，大规模开放式在线课程（MOOC），使其成为没有主要研究历史的大学的一个有吸引力的焦点，希望参与研究密集型大学。该项目活动将包括课程开发和交付使用MOOC的ECSU遥感类由ECSU和IU教师与虚拟和住宅模式的混合授课。一个关键目标是培训MSI的教员，使他们能够有效地教授高级课程。 为此，计划在少数民族机构计算机和信息科学/工程部门协会（ANOMA）2016年年会期间为MSI计算机科学教师举办MOOC教师研讨会，并为MSI学生举办MOOC机会研讨会。 项目基础设施和技术的可扩展性和稳健性将通过另外两个课程进行测试。 将对这些课程的成果进行评估，以了解跨多个学科和机构的这种共享课程的最佳做法。该框架可以作为一个模板，系统地介绍多个课程，课程，教师培训，研究支持和电子资源在整个AEOM的MSI网络。 该项目将根据课程开发的程度进行评估，并提供使用云计算和MOOC技术进行遥感的必要培训，教师如何能够在他们的课程中采用，以及ANOOC学院如何能够在其课程中将云计算制度化。

The overarching goal of this EAGER proposal is to investigate the concept that Computational Science curricula and research using Cloud Computing can be well suited for Minority Serving institutions (MSI's). Many aspects of Cloud are compelling for MSI's. This project will employ enhancements to a graduate level course on Remote Sensing at a HBCU campus and follow up with two additional courses to investigate its goals. The project is a collaboration between Elizabeth City State University (ECSU), an HBCU, and Indiana University (IU). Remote sensing applications collect high volumes of data that exceed the capabilities of conventional computing systems. This motivates the use of Cloud services and high performance computing (HPC) to support the associated storage and computation. Classes developed at ECSU and IU will be delivered by cloud-based online technologies to ECSU. This is a high-risk exploratory work both in its goals and methods, and if successful will provide a scalable template for MSI and non-MSI institutions for their conduct of teaching and research over Cloud platforms. This pilot project will attempt to introduce curricula and research for a very multidisciplinary set of topics using the Remote Sensing course with shared modules at a HBCU with multiple constraints including multi-institutional collaborative curriculum development and teaching, and employment of emerging curricular platforms. An important goal is to identify needed improvements and resources to scale their ideas for following up on a broader adoption of their model in MSI graduate and undergraduate curricula and research. Cloud Computing potentially has the capability to host both parallel and distributed computation (e.g., using Hadoop) and learning resources (e.g., for massive open online courses or MOOC's), making them an attractive focus for universities without a major research history looking to participate with research intensive universities. The project activities will include course development and delivery using MOOC's for an ECSU Remote Sensing class taught by ECSU and IU faculty with a mix of virtual and residential modes. A key goal is to train the instructors at the MSI's to enable them to effectively teach the advanced course. For this, a MOOC teach-the-teacher workshop for MSI computer science faculty members and a MOOC opportunities workshop for MSI students are planned during the 2016 annual conference of Association of Computer and Information Science/Engineering Departments at Minority Institutions (ADMI). The scalability and robustness of the project infrastructure and techniques will be tested with two additional courses. The courses' outcomes will be evaluated to understand the best practices of such shared curriculum across multiple disciplines and institutions. The framework can then be utilized as a template to systematically introduce multiple courses, curricula, teacher training, research support and electronic resources across the ADMI's MSI network. The project will be evaluated based on the extent to which the curriculum develops and provides the necessary training on remote sensing using Cloud Computing and MOOC technologies, how the instructors are able to adopt in their courses, and how the ADMI colleges are able to institutionalize Cloud computing in their course offerings.