The Eighth Annual AMS Student Conference

P1.56

An interactive instructional pathway to LEAD portal data and tools

Sean States, Millersville Univ., Millersville, PA; and R. Junod, S. Cecelski, B. Kerschner, R. Carp, J. Kurdzo, K. Ketchell, D. S. Yalda, and D. R. Clark

Linked Environments for Atmospheric Discovery (LEAD) is making meteorological data, tools for visualization and analysis, and forecast models available to a broad range of users from educators to researchers. One of the principal goals of LEAD is to not only democratize the availability of advanced weather technologies for research and education, but to also enable users with different levels of knowledge and ability. The LEAD education initiative has been focusing on means to integrate data, tools, and services available on the LEAD portal into undergraduate meteorology education to provide an authentic and contextualized environment for teaching and learning. Towards this goal, meteorology undergraduate students at Millersville University have teamed with undergraduate students of the Cybereducation Group at the National Center for Supercomputing Applications (NCSA) to design and develop learning materials, new tools and features to enhance the use of the LEAD portal and its capabilities in an educational setting. The development of educational materials has been focused on developing an interactive module for specific atmospheric phenomena. The module incorporates a demo familiarizing the user with the subject matter, an interactive guided piece testing the user's understanding of the material, and a discovery section allowing the user to interact with real-time data to further explore and understand a particular phenomenon. In addition to education, the LEAD student research team at Millersville University has also been involved in testing the experiment builder component of the LEAD portal. Members have been able to integrate the data into the University's Campus Weather Service to allow for the use of LEAD data, tools, and services in the development of short range forecasts.

Poster Session 1, Student Conference Posters
Sunday, 11 January 2009, 5:30 PM-7:00 PM

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