This collection of insightful essays gives teachers’ perspectives on the role of space and presence in teaching performance. It explores how the demand for remote teaching can be met while at the same time successfully educating and working compassionately in this most ‘live’ of disciplines. Teaching Performance Practices in Remote and Hybrid Spaces reframes prevailing ideas about pedagogy in dance, theatre, and somatics and applies them to teaching in face-to-face, hybrid, and remote situations. Case studies from instructors and professors provide essential, practical suggestions for remotely teaching a vast range of studio courses, including tap dance, theatre design, movement, script analysis, and acting, rendering this book an invaluable resource. The challenges that teachers are facing in the early twenty-first century are addressed throughout, helping readers to navigate these unprecedented circumstances whilst delivering lessons, guiding workshops, rehearsing, or even staging performances. This book is invaluable for dance and theatre teachers or leaders who work in the performing arts and related disciplines. It is also ideal for any professionals who need research-based solutions for teaching performance online.

Arts Education: A Global Affair highlights the adaptations that arts educators and researchers have undertaken to successfully adjust to the changes in arts education practices as a consequence of the global pandemic and its ongoing variants. Moreover, teaching and research in arts education have changed significantly as a consequence of the world-wide pandemic, COVID-19. Emerging variants have exacerbated the situation and show no signs of subsiding. In response to these challenges, arts educators and researchers have developed new modes of instructional delivery and data collection. These include asynchronous, synchronous, hybrid and bi-modal online learning, and online questionnaires, surveys, focus groups, and video interviews. This volume highlights the adaptations that arts educators and researchers have undertaken to successfully adjust to this new reality in education.

This book presents a mobile technology capacity building framework that offers academics, students, and practitioners involved in workplace education a deeper understanding of, and practical guidance on, how mobile technology can enhance professional learning. Approaching professional and workplace learning as a hybrid space in which work, learning and technology meet, the book discusses the value of mobile technology in shaping professional education, particularly during student placements. The framework focuses on staying professional and safe, considering issues of time and place, planning learning activities, initiating dialogue, networking, creating learning opportunities on-the-go, and deepening reflection. It is designed to assist students and their educators to use mobile technology knowledgeably and responsibly, and to help bridge the gap between university learning and workplace practice. This book also contributes to a better understanding of the interconnectedness between learning, practice and technology. It demonstrates how to enhance learning and working with mobile technology by drawing on two perspectives: the ‘professional-plus’ and the ‘deliberate professional’.

In contemporary engineering domains, optimization and decision-making issues are crucial. Given the vast amounts of available data, processing times and memory usage can be substantial. Developing and implementing novel heuristic algorithms is time-consuming, yet even minor improvements in solutions can significantly reduce computational costs. In such scenarios, the creation of heuristics and metaheuristic algorithms has proven advantageous. The convergence of machine learning and metaheuristic algorithms offers a promising approach to address these challenges. Metaheuristic and Machine Learning Optimization Strategies for Complex Systems covers all areas of comprehensive information about hyper-heuristic models, hybrid meta-heuristic models, nature-inspired computing models, and meta-heuristic models. The key contribution of this book is the construction of a hyper-heuristic approach for any general problem domain from a meta-heuristic algorithm. Covering topics such as cloud computing, internet of things, and performance evaluation, this book is an essential resource for researchers, postgraduate students, educators, data scientists, machine learning engineers, software developers and engineers, policy makers, and more.

Bridge the Digital Divide with Research-Informed Technology Models Since the first edition of this bestselling resource many schools are still striving to close the digital divide and bridge the opportunity gap for historically marginalized students, including English learners. And the need for technology-infused lessons specifically aligned for English learners is even more critically needed. Building from significant developments in education policy, research, and remote learning innovations, this newly revised edition offers unique ways to bridge the digital divide that disproportionally affects culturally and linguistically diverse learners. Designed to support equitable access to engaging and enriching digital-age education opportunities for English learners, this book includes Research-informed and evidence-based technology integration models and instructional strategies Sample lesson ideas, including learning targets for activating students’ prior knowledge while promoting engagement and collaboration Tips for fostering collaborative practices with colleagues Vignettes from educators incorporating technology in creative ways Targeted questions to facilitate discussions about English language development methodology Complete with supplementary tools and resources, this guide provides all of the methodology resources needed to bridge the digital divide and promote learning success for all students.

Quality accreditation in higher education institutions (HEIs) is currently a buzzword. The need to maintain high-quality education standards is a critical requirement for HEIs to remain competitive in the market and for government and regulatory bodies to ensure the quality standards of programs offered. From being an implicit requirement that is internally addressed, quality assurance activities become an explicit requirement that is regularly audited and appraised by national and international accreditation agencies. HEIs are voluntarily integrating quality management systems (QMS), institutional and program-specific, in response to the political and competitive environment in which it exists. Through its higher education department or by creating non-profitable accreditation bodies, many governments have implemented a quality framework for licensing HEIs and invigilates its adherence based on which accreditation statuses are granted for HEIs. Global Perspectives on Quality Assurance and Accreditation in Higher Education Institutions provides a comprehensive framework for HEIs to address quality assurance and quality accreditation requirements and serves as a practical tool to develop and deploy well-defined quality management systems in higher education. The book focuses on the critical aspects of quality assurance; the need to develop a concise and agile vision, mission, values, and graduate attributes; and to develop a system that effectively aligns the various activities of the HEI to the attainment of the strategic priorities listed in the institutional plans. The chapters each cover the various facets of the quality assurance framework and accreditation agencies' requirements with practical examples of each. This book is useful for HEI administrators, quality assurance specialists in HEIs, heads of academic departments, internal auditors, external auditors, and other practitioners of quality, along with stakeholders, researchers, academicians, and students interested in quality assurance and accreditation in higher education.

This book brings together new ideas about how communities, creative producers, and visitors can productively engage with competing notions of experience and authenticity in the tourist environment. It investigates how community interests intersect the desire for more intimate engagements with cultural experiences. Focusing on the way in which communities and visitors ‘perform’ new forms of cultural tourism, Performing Cultural Tourism is aimed at undergraduate students, researchers, academics, and a diverse range of professionals at both private and government levels that are seeking to develop policies and business plans that recognize and respond to new interests in contemporary tourism.

Armstrong's Handbook of Human Resource Management Practice is the definitive resource for HRM students and professionals, helping readers understand and implement HR to align with business needs. This book provides detailed coverage of all areas essential to the HR function such as employment law, employee relations, learning and development, performance management and reward management. It also covers the HR skills needed to ensure professional success, including leadership, managing conflict, interviewing and using statistics. It is illustrated throughout in full colour and has a range of pedagogical features to consolidate learning such as source review boxes, key learning points and case studies from international organizations such as IBM, HSBC and Johnson and Johnson. This fully updated 16th edition includes new chapters on managing remote workers and developments in digital human resource management practices. There are also updates to reflect the changes throughout the HR function, such as performance leadership, 'smart' reward and employee wellbeing. Armstrong's Handbook of Human Resource Management Practice is suited to both professionals and students of undergraduate and postgraduate degrees. It is also aligned with the Chartered Institute of Personnel and Development (CIPD) profession map so can be used by those studying the Associate Level 5 and Advanced Level 7 qualifications. Online supporting resources include comprehensive handbooks for lecturers and students, lecture slides, all figures and tables, toolkits, and a literature review, glossary and bibliography.

The second edition of University Teaching in Focus distils the knowledge and insights of internationally acclaimed experts in university teaching. It empowers university teachers and contributes to their career success by developing their teaching skills, strategies and knowledge. Written in a clear and accessible style, it provides a sharp focus on student learning through the lens of four sections: Focus on subject and curriculum design Focus on subject teaching and learning Focus on students Focus on your career Each of the 15 chapters targets a key teaching and learning issue referencing seminal works, current resources and practical applications using real-world cases. The ‘Your thoughts’ sections encourage reflection and offer opportunities to adapt international evidence about best practice to local contexts and disciplines. This edition will be a key resource for foundational teaching development programs in higher education institutions or as a self-help manual by early career and experienced teachers who wish to enhance their students’ learning.

With the recent advances in remote sensing technologies for Earth observation, many different remote sensors are collecting data with distinctive properties. The obtained data are so large and complex that analyzing them manually becomes impractical or even impossible. Therefore, understanding remote sensing images effectively, in connection with physics, has been the primary concern of the remote sensing research community in recent years. For this purpose, machine learning is thought to be a promising technique because it can make the system learn to improve itself. With this distinctive characteristic, the algorithms will be more adaptive, automatic, and intelligent. This book introduces some of the most challenging issues of machine learning in the field of remote sensing, and the latest advanced technologies developed for different applications. It integrates with multi-source/multi-temporal/multi-scale data, and mainly focuses on learning to understand remote sensing images. Particularly, it presents many more effective techniques based on the popular concepts of deep learning and big data to reach new heights of data understanding. Through reporting recent advances in the machine learning approaches towards analyzing and understanding remote sensing images, this book can help readers become more familiar with knowledge frontier and foster an increased interest in this field.