Lecture-Tutorials for Introductory Astronomy were developed to integrate the needs of busy, research-focused faculty who teach in challenging environments with existing, effective teaching strategies. Chapter topics include the Solar System, stellar magnitudes, techniques in astronomy, moon phases, stellar evolution, and more. For college professors, instructors and other professionals who are interested in a lively, engaging method of teaching introductory astronomy.
lecture tutorials for introductory astronomy preliminary version
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For one-semester Introduction to Astronomy courses. A brief, introductory astronomy text designed for students with little or no scientific background, A Beginner's Guide incorporates an exceptionally clear writing style, an emphasis on critical thinking and visualization, and a leading-edge technology program. The authors present a broad view of astronomy without complex mathematics, yet the text discusses important concepts without simplification. - Over 100 new photos and line drawings - Added throughout the book.-Provides students with exciting visual imagery, holding their interest. - New information - Includes the following new sections and text: a summary of Kirchhoff's laws of spectroscopy; Is Pluto a Planet?; new references to scientific method; new emphasis on cosmic evolution; new examples of astronomical scale; and more. - Gives students a more comprehensive and current text. Assures instructors that they are presenting the best text available. - Greatly revised and updated material - Includes the latest advances in telescope technology; recent satellite observations; implications for theory of solar system formation; observations from the Galileo space probe; expanded
All papers were peer reviewed. The 2006 Physics Education Research Conference brought together researchers studying a wide variety of topics in physics education including transfer of knowledge, learning in upper level physics courses, pre-service education, and cross-disciplinary learning. The theme of this conference was Discipline-Based Education Research in Other STEM Disciplines.
Over the past 15 years, there has been a growing need in the medical image computing community for principled methods to process nonlinear geometric data. Riemannian geometry has emerged as one of the most powerful mathematical and computational frameworks for analyzing such data. Riemannian Geometric Statistics in Medical Image Analysis is a complete reference on statistics on Riemannian manifolds and more general nonlinear spaces with applications in medical image analysis. It provides an introduction to the core methodology followed by a presentation of state-of-the-art methods. Content includes: • The foundations of Riemannian geometric methods for statistics on manifolds with emphasis on concepts rather than on proofs • Applications of statistics on manifolds and shape spaces in medical image computing • Diffeomorphic deformations and their applications As the methods described apply to domains such as signal processing (radar signal processing and brain computer interaction), computer vision (object and face recognition), and other domains where statistics of geometric features appear, this book is suitable for researchers and graduate students in medical imaging, engineering and computer science. • A complete reference covering both the foundations and state-of-the-art methods • Edited and authored by leading researchers in the field • Contains theory, examples, applications, and algorithms • Gives an overview of current research challenges and future applications