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Introduction |
ETHR R&D supports Federal activities in computer- and communications-related education and training to advance learning technologies at all levels including K-12, community college, technical school, trade school, university undergraduate and graduate, and lifelong learning. R&D in learning technologies is needed to enable citizens to use the Nation's information infrastructure and to provide universal access to the resources necessary for efficient and effective education and training. This will lead to more knowledgeable and productive citizens who will use cutting-edge information technologies to maintain U.S. competitiveness in today's highly aggressive market environment. ETHR R&D encourages and facilitates interagency collaborations for Federal education and training R&D and evaluation of advanced technologies for high quality, affordable software learning tools; information-based models of educational systems and learning productivity; research on information technology applied to learning and cognitive processes; and demonstrations of innovative technologies and networking applications. The ETHR Working Group coordinates Federal cooperation with schools and other educational and training venues. |
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Experimental and integrative activities, education, and training |
In the 21st century, there will be an ever-increasing need for a workforce trained in using advanced high performance computing and communications. NSF's ETHR R&D activities focus on increasing the pool of people with the knowledge, skills, and insights to lead research in science and technology needed to make high performance computing and information processing more useful and to pursue fundamental knowledge in all disciplines of science and engineering. Activities include new course and curriculum development, and collaborative research in high performance computing and communication and information processing in undergraduate education. |
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PACI outreach |
The Education Outreach and Training activities of NSF's Partnerships for Advanced Computational Infrastructure (PACI) partners focus on enabling all citizens to use emerging computing technologies to advance their ability to understand and solve problems in education, science, business, government, and society. |
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Learning and Intelligent Systems (LIS) |
NSF supports undergraduate and graduate research to provide the human resources needed for information technology research, education, and industry. Through its KDI initiative, NSF is investing in Learning and Intelligent Systems (LIS). The LIS goal is to stimulate research that will advance and integrate concepts of learning and intelligence emerging from theoretical and experimental work in education, cognitive science, computer science, neuroscience, engineering, social science, and physical science. LIS encompasses studies of learning and intelligence in systems, including (but not limited to) the nervous systems of humans or other animals; networks of computers performing complex computations; robotic devices that interact with their environments; social systems of human or non-human species; and formal and informal learning situations. LIS also includes research that promotes the development and use of learning technologies across a broad range of fields. |
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DOE's Computational Science Graduate Fellowships |
The Computational Science Graduate Fellowship Program encourages talented college students to undertake study and research in computational science accompanied by practical work experience at DOE research facilities. The program encourages students with outstanding academic records to continue their graduate studies in preparation for careers in computational science. |
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Biomedical informatics training grants |
To help address the current shortage of biomedical professionals trained in using modern computing and telecommunications systems, NLM continues to expand its successful predoctoral and postdoctoral grants program for career training in biomedical informatics. For example, the NLM-supported bioinformatics training program of the W. M. Keck Center for Computational Biology -- a joint endeavor of Baylor College of Medicine, Rice University, and the University of Houston -- will prepare researchers and clinicians to integrate high performance computing technologies into all levels of healthcare. NLM supports medical informatics short courses at Stanford University that are also made available via distance learning technologies. A key aim of this course work is to provide hands-on experience with software programs in a training laboratory environment. Medical informatics training at the Yale Center for Medical Informatics (YCMI) focuses on the creative use of computers in support of clinical medicine, biomedical research, and medical education. The goal is to provide fellows with experiences that will prepare them for careers based wholly or in part in medical informatics. |
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Learning Technologies Project (LTP) |
The goal of NASA's Learning Technologies Project (LTP) is to promote the growth of a national information infrastructure using the vast amount of information NASA has acquired since its creation. The LTP projects will increase public access to scientific databases, develop new applications and pilot programs for using science data, and create new curriculum products and tools for K-12 and K-14 education via the Internet. LTP has five components:
This Learning Technologies Web site, supported by NASA's Glenn Research Center
at Lewis Field (formerly known as the Lewis Research Center) in Cleveland, Ohio,
provides educational links to both students and teachers focusing on aeronautics
and aerodynamics.
NASA's "Observatorium" site provides a wealth of scientific images and
information, including this snapshot of astronauts Jerry Ross and Jim Newman
working on the exterior of the Unity space station module during their first
spacewalk on December 7, 1998.
Information travels both ways at the "Observatorium" Web site. Here is a young
Virginia artist's concept of a space probe called Starjourner, designed to
travel to our nearest neighboring star. According to this promising engineer,
"It would be launched with a powerful rocket ship. It would then be launched to
the star with a nuclear rocket engine. It would arrive in fourteen years."
This 3-D look at the Venusian Volcano Maat Mons combines Magellan synthetic
aperture radar data with radar altimetry. From the north side of the mountain,
the lava flows extend hundreds of kilometers across the fractured plains in the
foreground to the base of Maat Mons.
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