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Direct linkCao, Qing; Yeary, M. B.; Zhang, Guifu – IEEE Transactions on Education, 2012
The U.S. weather radar network is currently being upgraded with dual-polarization capability. Weather radar polarimetry is an interdisciplinary area of engineering and meteorology. This paper presents efficient ways to learn weather radar polarimetry through several basic and practical topics. These topics include: 1) hydrometeor scattering model…
Descriptors: Meteorology, Electronic Equipment, Internet, Engineering
Davis, C. E.; Yeary, M. B.; Sluss, J. J., Jr. – IEEE Transactions on Education, 2012
This paper discusses an all-encompassing approach to increase the number of students in engineering through innovative outreach, recruiting, and retention programs. Prior to adopting these programs, the School of Electrical and Computer Engineering (ECE) at the University of Oklahoma (OU), Norman, experienced a reduction in engineering enrollment…
Descriptors: Engineering Education, State Universities, Declining Enrollment, Enrollment Trends
Chilson, P. B.; Yeary, M. B. – IEEE Transactions on Education, 2012
Learning modules provide an effective means of encouraging cognition and active learning. This paper discusses several such modules that have been developed within a course on weather radar applications intended for students from Electrical Engineering and Meteorology. The modules were designed both to promote interdisciplinary exchange between…
Descriptors: Experiential Learning, Active Learning, Meteorology, Science Education
Yeary, M. B.; Yu, T.; Palmer, R. D.; Monroy, H.; Ruin, I.; Zhang, G.; Chilson, P. B.; Biggerstaff, M. I.; Weiss, C.; Mitchell, K. A.; Fink, L. D. – IEEE Transactions on Education, 2010
Students are not exposed to enough real-life data. This paper describes how a community of scholars seeks to remedy this deficiency and gives the pedagogical details of an ongoing project that commenced in the Fall 2004 semester. Fostering deep learning, this multiyear project offers a new active-learning, hands-on interdisciplinary laboratory…
Descriptors: Meteorology, Data Analysis, Prediction, Natural Disasters
