Statistics – Computation
Scientific paper
Dec 2007
adsabs.harvard.edu/cgi-bin/nph-data_query?bibcode=2007aas...211.9411c&link_type=abstract
American Astronomical Society, AAS Meeting #211, #94.11; Bulletin of the American Astronomical Society, Vol. 39, p.893
Statistics
Computation
Scientific paper
We are developing a set of multimedia-based instructional modules emphasizing technical and scientific aspects of the Giant Segmented Mirror Telescope project. The modules will be open-ended and problem-based to promote development of problem-solving skills. Problem-based-learning modules that emphasize work on open-ended complex real world problems are particularly valuable in illustrating and promoting a perspective on the process of science and engineering. Research in this area shows that these kinds of learning experiences are superior to more conventional student training regarding gains in student learning and problem-solving skills. The format for the modules will be based on the award-winning multi-media educational Astronomy Village products. Students are presented with a simulated environment: a mountaintop community surrounded by a cluster of telescopes, satellite receivers, and telecommunication towers. A number of "buildings” are found in the Village, including a library, a laboratory, and an auditorium. Each building contains an array of information sources and computer simulations. Students navigate through their research with a mentor via imbedded video. The first module will be "Observatory Site Selection.” Students will use astronomical data, basic weather information, and sky brightness data to select the best site for an observatory. Students will investigate the six GSMT sites considered by the professional site selection teams. Students will explore weather and basic site issues (e.g., roads and topography) using remote sensing images, computational fluid dynamics results, turbulence profiles, and scintillation of the different sites. The second module will address aspects of system engineering and optimization for a GSMT-like telescope.
Croft Steven
Pompea Stephen M.
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