EAGER: Remote Sensing Curriculum Enhancement using Cloud Computing
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.

EAGER: Remote Sensing Curriculum Enhancement using Cloud Computing
Center of Excellence in Remote Sensing Education and Research

1704 Weeksville Road, Box 672, Elizabeth City, North Carolina 27909 
Phone (252) 335-3696 Fax (252) 335-3790

NSF Award #1550720