The GAVRT Partnership: Bringing the Universe to K-12 Classrooms

Abstract

The Goldstone Apple Valley Radio Telescope (GAVRT) project is a venture bringing hands-on scientific discovery to America’s classrooms. GAVRT is a science education partnership involving NASA, the Jet Propulsion Laboratory (JPL) and the Lewis Center for Educational Research (LCER) located in Apple Valley, CA. The project enables pre-college students to carry out radio astronomy observations from their classrooms using a dedicated 34m (110ft) radio astronomy telescope at NASA’s Deep Space Network (DSN) Goldstone Complex. Students use computers to record faint radio waves collected by the radio telescope and analyze real data. Scientists at JPL ultimately validate and incorporate the data into their research. Through this process, students learn that they can make valuable contributions to the world of science.A major objective of the GAVRT project is to improve scientific literacy among America’s school children. Teachers receive in-depth training and they are provided with a broad-based, multidiscipline curriculum designed to meet National Science Standards and tailored for each teacher to meet their State Science Standards. With the support and participation of NASA/JPL scientists and engineers, along with staff and volunteers at LCER, GAVRT enables a compelling experience for children and teachers in the real disciplines of science. Students have the opportunity to become part of a science/education team, participating with scientists in ongoing missions and special observing campaigns. Their measurements are often included in papers appearing in major scientific journals. With each pass of a planet or quasar, students join the ancient family of explorers who have gazed into the night sky since the beginning of time to understand their place in the universe.KeywordsRadio EmissionRadio TelescopeRadio AstronomyDeep Space NetworkCurriculum ModuleThese keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.