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Divided into two volumes, the Handbook of Special Education Research provides a comprehensive overview of critical issues in special education research. Volume II addresses research-based practices, offering a deep dive into tiered systems of support and advances in interventions and assessments, as well as socially, emotionally, culturally, and linguistically relevant practices. Each chapter features considerations for future research and implications for fostering continuous improvement and innovation. Essential reading for researchers and students of special education, this handbook brings together diverse and complementary perspectives to help move the field forward.
Foundations of Orientation and Mobility, the classic professional reference and textbook has been completely revised and expanded to two volumes by the most knowledgeable experts in the field. The new third edition includes both the latest research in O&M and expanded information on practice and teaching strategies. Volume 1, History and Theory, includes the bases of O&M knowledge, including perception, orientation, low vision, audition, kinesiology, psychosocial issues, and learning theories, as well as chapters on technology, dog guides, orientation aids, and environmental accessibility. A section on the profession of O&M includes its international history; administration, assessment and program planning; and a chapter on research in O&M. No O&M student or professional can afford to be without this essential resource.
Building on the foundation set in Volume I—a landmark synthesis of research in the field—Volume II is a comprehensive, state-of-the-art new volume highlighting new and emerging research perspectives. The contributors, all experts in their research areas, represent the international and gender diversity in the science education research community. The volume is organized around six themes: theory and methods of science education research; science learning; culture, gender, and society and science learning; science teaching; curriculum and assessment in science; science teacher education. Each chapter presents an integrative review of the research on the topic it addresses—pulling together the existing research, working to understand the historical trends and patterns in that body of scholarship, describing how the issue is conceptualized within the literature, how methods and theories have shaped the outcomes of the research, and where the strengths, weaknesses, and gaps are in the literature. Providing guidance to science education faculty and graduate students and leading to new insights and directions for future research, the Handbook of Research on Science Education, Volume II is an essential resource for the entire science education community.
Presents scholars, students and general readers with the major fiction for adults, much of the best of juvenile fiction, and a selection of the educational and occasional writings of Maria Edgeworth. MARIA EDGEWORTH was born in 1768. Her first novel, Castle Rackrent (1800) was also her first Irish tale. The next such tale was Ennui (1809), after which came The Absentee, which began life as an unstaged play and was then published (in prose) in Tales of Fashionable Life (1812), as were several of her other stories. They were followed in 1817 by the last of her Irish tales, Ormond. Maria Edgeworth died in 1849. Edited with an introduction and notes by Marilyn Butler.
This volume offers a comprehensive overview of the many facets of musical experience, behaviour and development in relation to the diverse variety of educational contexts in which they occur.
This second edition of the International Handbook of Mathematics Teacher Education builds on and extends the topics/ideas in the first edition while maintaining the themes for each of the volumes. Collectively, the authors look back beyond and within the last 10 years to establish the state-of-the-art and continuing and new trends in mathematics teacher and mathematics teacher educator education, and look forward regarding possible avenues for teachers, teacher educators, researchers, and policy makers to consider to enhance and/or further investigate mathematics teacher and teacher educator learning and practice, in particular. The volume editors provide introductions to each volume that highlight the subthemes used to group related chapters, which offer meaningful lenses to see important connections within and across chapters. Readers can also use these subthemes to make connections across the four volumes, which, although presented separately, include topics that have relevance across them since they are all situated in the common focus regarding mathematics teachers. Volume 2, Tools and Processes in Mathematics Teacher Education, describes and analyze various promising tools and processes, from different perspectives, aimed at facilitating the mathematics teacher learning and development. It provides insights of how mathematics teacher educators think about and approach their work with teachers. Thus, as the second volume in the series, it broadens our understanding of the mathematics teacher and their learning and teaching.
Image processing and machine learning are used in conjunction to analyze and understand images. Where image processing is used to pre-process images using techniques such as filtering, segmentation, and feature extraction, machine learning algorithms are used to interpret the processed data through classification, clustering, and object detection. This book serves as a textbook for students and instructors of image processing, covering the theoretical foundations and practical applications of some of the most prevalent image processing methods and approaches. Divided into two volumes, this second installment explores the more advanced concepts and techniques in image processing, including morphological filters, color image processing, image matching, feature-based segmentation utilizing the mean shift algorithm, and the application of singular value decomposition for image compression. This second volume also incorporates several important machine learning techniques applied to image processing, building on the foundational knowledge introduced in Volume 1. Written with instructors and students of image processing in mind, this book’s intuitive organization also contains appeal for app developers and engineers.