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This book provides a single source of reference for educators interested in understanding how industry-based ideas have been adapted into different educational contexts, and supports their utilisation in practice. The link between industry-based ideas and their application in education has enabled educators to develop engaging, collaborative, and creative learning environments, as well as better preparing their students for an increasingly complex and dynamic global environment. This book includes contributions from educators, researchers, and practitioners, who have integrated industry-based ideas into their teaching, and explores how these concepts and practices support the creation of effective learning environments. Through these diverse, international contributions, this book enables wider engagement with, and critical analysis of, the application of industry practices, processes and techniques in the development of collaborative and creative learning environments.
The book describes a novel method of engaging rural communities in partnership initially with nurse learners to research and employ the Community Health Assessment Sustainability Education (CHASE) model. CHASE provides a consolidated structure that immerses nurse learners in community development in partnership with their group peers, community organisations and educational supervisors. The book engages with community development practitioners, community activists including rural health practitioners who provide services to rural populations, undergraduate health disciplines, postgraduate learners, educators, and researchers. The CHASE system is described in detail and offers case studies on its application in a variety of geographical contexts. CHASE is a starting point that does not set out to impose a single understanding – it is adapted in practice to rural communities’ requirements. Therefore, capturing how this model has been adapted within diverse international rural communities to accommodate community needs is paramount and aligned with each individual case study presented in the book. CHASE enhances collaborative relationships in the global landscape informing nursing curricula, and teaching and learning pedagogy internationally with a view to reduce health disparities. This book is a valuable resource of pioneering work that spans disciplines and promotes collaboration among stakeholders invested in rural community health. By weaving together connections between disciplines and communities, the authors highlight the importance of spatial thinking and its impact on health and well-being. Readers are given a comprehensive exploration of the challenges of indigenous, minority, and vulnerable rural populations presented as insightful narrative, case studies. - Kate Emond, Rural Department of Nursing and Midwifery, La Trobe University, Australia The Editors have skillfully incorporated on interdisciplinary focus on the CHASE Model. The authors facilitate and evaluate favorable social change, enhance healthcare delivery systems and improve social determinants of health via interdisciplinary actions within community development. - Angeline Bushy, University of Central Florida College of Nursing, USA
This book covers computational statistics-based approaches for Artificial Intelligence. The aim of this book is to provide comprehensive coverage of the fundamentals through the applications of the different kinds of mathematical modelling and statistical techniques and describing their applications in different Artificial Intelligence systems. The primary users of this book will include researchers, academicians, postgraduate students, and specialists in the areas of data science, mathematical modelling, and Artificial Intelligence. It will also serve as a valuable resource for many others in the fields of electrical, computer, and optical engineering. The key features of this book are: Presents development of several real-world problem applications and experimental research in the field of computational statistics and mathematical modelling for Artificial Intelligence Examines the evolution of fundamental research into industrialized research and the transformation of applied investigation into real-time applications Examines the applications involving analytical and statistical solutions, and provides foundational and advanced concepts for beginners and industry professionals Provides a dynamic perspective to the concept of computational statistics for analysis of data and applications in intelligent systems with an objective of ensuring sustainability issues for ease of different stakeholders in various fields Integrates recent methodologies and challenges by employing mathematical modeling and statistical techniques for Artificial Intelligence
The application of mixed methods research design in the built environment discipline by students and academics has continued to grow exponentially. However, with no dedicated mixed methods research design textbook in this domain, students have struggled to conduct research projects involving a mixed methods research design. Mixed Methods Research Design for the Built Environment provides a useful research methodololgy resource for students, academics, and researchers across various disciplines in the built environment such as construction management and project management, property and real estate management, quantity surveying and commercial management, building surveying, building services engineering, civil and geodetic engineering, and other built environment disciplines. The book can also be useful for students and academics outside the built environment knowledge domain. This textbook offers practical and step-by-step guidance on how to apply mixed methods research design, including an elucidation of the various philosophical and methodological underpinnings upon which the choice of a particular variant of the mixed methods research design is predicated. It provides practical case examples and guidance on the processes involved to design and undertake mixed methods research, the advantages and disadvantages of using mixed methods research, and how multiple sources of qualitative and quantitative data can be combined and applied to carry out research projects.