Help students take the lead on reaching their own personal highest level of success by shifting from the current paradigm of education to create a more meaningful and inclusive learning ecosystem. This essential guide offers the landscape model and its three elements: understanding what students bring to the ecosystem, defining the horizon, and charting the pathway. Access practical strategies for drawing on students’ experiences and strengths to create a more meaningful and inclusive educational ecosystem. Educators committed to lifelong learning, diversity, equity, and inclusion will: Retire the inadequate goal of access and move education toward the higher and more urgent, equitable goal of helping every student reach their highest possible level of individual success Embrace the concept of inclusive prosperity, which goes beyond diversity to accepting and supporting all students—their experiences, gifts, and challenges—to build communities where all students belong Receive practical, research-based strategies for developing agency and engagement so that students become the protagonists of their journey through the learning ecosystem Design systems for student protagonism by implementing student-centered strategies for cognitive and cultural inclusion Obtain reproducible tools to deepen understanding and implementation of the material Learn how to successfully implement the model despite common hurdles and potential challenges, such as traditional academic contexts and economically disenfranchised schools Contents: Introduction Part 1: Understanding the Landscape Model Chapter 1: The Landscape Model’s Three Elements Chapter 2: Eight Guiding Principles Part 2: Implementing the Landscape Model Chapter 3: Element One: The Ecosystem Chapter 4: Element Two: The Horizon Chapter 5: Element Three: The Pathway Part 3: Leading the Landscape Model Chapter 6: Student Growth Assessment on the Landscape Chapter 7: Challenges of Implementation Chapter 8: Landscape Model Implementation for Long-Term Success Chapter 9: Opportunities for the Future Epilogue: Why This Work Matters Appendix References and Resources Index

"This handbook investigates a variety of ePortfolio uses through case studies, the technology that supports the case studies, and it also explains the conceptual thinking behind current uses as well as potential uses"--Provided by publisher.

Reliable predictions of how changing climate and disturbance regimes will affect forest ecosystems are crucial for effective forest management. Current fire and climate research in forest ecosystem and community ecology offers data and methods that can inform such predictions. However, research in these fields occurs at different scales, with disparate goals, methods, and context. Often results are not readily comparable among studies and defy integration. We discuss the strengths and weaknesses of three modeling paradigms: empirical gradient models, mechanistic ecosystem models, and stochastic landscape disturbance models. We then propose a synthetic approach to multi-scale analysis of the effects of climatic change and disturbance on forest ecosystems. Empirical gradient models provide an anchor and spatial template for stand-level forest ecosystem models by quantifying key parameters for individual species and accounting for broad-scale geographic variation among them. Gradient imputation transfers predictions of fine-scale forest composition and structure across geographic space. Mechanistic ecosystem dynamic models predict the responses of biological variables to specific environmental drivers and facilitate understanding of temporal dynamics and disequilibrium. Stochastic landscape dynamics models predict frequency, extent, and severity of broad-scale disturbance. A robust linkage of these three modeling paradigms will facilitate prediction of the effects of altered fire and other disturbance regimes on forest ecosystems at multiple scales and in the context of climatic variability and change.

This book constitutes the refereed proceedings of the Third International Workshop on Learning Technology for Education in Cloud, LTEC 2014, held in Santiago, Chile, in September 2014. The 20 revised full papers presented were carefully reviewed and selected from 31 submissions. The papers are organized in topical sections on MOOC for learning; learning technologies; learning in higher education; case study in learning.

The whole landscape of space use is undergoing a radical transformation. In the workplace a period of unprecedented change has created a mix of responses with one overriding outcome observable worldwide: the rise of distributed space. In the learning environment the social, political, economic and technological changes responsible for this shift have been further compounded by constantly developing theories of learning and teaching, and a wide acceptance of the importance of learning as the core of the community, resulting in the blending of all aspects of learning into one seamless experience. This book attempts to look at all the forces driving the provision and pedagogic performance of the many spaces, real and virtual, that now accommodate the experience of learning and provide pointers towards the creation and design of learning-centred communities. Part 1 looks at the entire learning universe as it now stands, tracks the way in which its constituent parts came to occupy their role, assesses how they have responded to a complex of drivers and gauges their success in dealing with renewed pressures to perform. It shows that what is required is innovation within the spaces and integration between them. Part 2 finds many examples of innovation in evidence across the world – in schools, the higher and further education campus and in business and cultural spaces – but an almost total absence of integration. Part 3 offers a model that redefines the learning landscape in terms of learning outcomes, mapping spatial requirements and activities into a detailed mechanism that will achieve the best outcome at the most appropriate scale. By encouraging stakeholders to creating an events-based rather than space-based identity, the book hopes to point the way to a fully-integrated learning landscape: a learning community.

The International Handbook of Research in Professional and Practice-based Learning discusses what constitutes professionalism, examines the concepts and practices of professional and practice-based learning, including associated research traditions and educational provisions. It also explores professional learning in institutions of higher and vocational education as well the practice settings where professionals work and learn, focusing on both initial and ongoing development and how that learning is assessed. The Handbook features research from expert contributors in education, studies of the professions, and accounts of research methodologies from a range of informing disciplines. It is organized in two parts. The first part sets out conceptions of professionalism at work, how professions, work and learning can be understood, and examines the kinds of institutional practices organized for developing occupational capacities. The second part focuses on procedural issues associated with learning for and through professional practice, and how assessment of professional capacities might progress. The key premise of this Handbook is that during both initial and ongoing professional development, individual learning processes are influenced and shaped through their professional environment and practices. Moreover, in turn, the practice and processes of learning through practice are shaped by their development, all of which are required to be understood through a range of research orientations, methods and findings. This Handbook will appeal to academics working in fields of professional practice, including those who are concerned about developing these capacities in their students. In addition, students and research students will also find this Handbook a key reference resource to the field.

One of the most striking features of Coordination Dynamics is its interdisciplinary character. The problems we are trying to solve in this field range from behavioral phenomena of interlimb coordination and coordination between stimuli and movements (perception-action tasks) through neural activation patterns that can be observed during these tasks to clinical applications and social behavior. It is not surprising that close collaboration among scientists from different fields as psychology, kinesiology, neurology and even physics are imperative to deal with the enormous difficulties we are facing when we try to understand a system as complex as the human brain. The chapters in this volume are not simply write-ups of the lectures given by the experts at the meeting but are written in a way that they give sufficient introductory information to be comprehensible and useful for all interested scientists and students.

The ?eld of applied nonlinear dynamics has attracted scientists and engineers across many different disciplines to develop innovative ideas and methods to study c- plex behavior exhibited by relatively simple systems. Examples include: population dynamics, ?uidization processes, applied optics, stochastic resonance, ?ocking and ?ightformations,lasers,andmechanicalandelectricaloscillators. Acommontheme among these and many other examples is the underlying universal laws of nonl- ear science that govern the behavior, in space and time, of a given system. These laws are universal in the sense that they transcend the model-speci?c features of a system and so they can be readily applied to explain and predict the behavior of a wide ranging phenomena, natural and arti?cial ones. Thus the emphasis in the past decades has been in explaining nonlinear phenomena with signi?cantly less att- tion paid to exploiting the rich behavior of nonlinear systems to design and fabricate new devices that can operate more ef?ciently. Recently, there has been a series of meetings on topics such as Experimental Chaos, Neural Coding, and Stochastic Resonance, which have brought together many researchers in the ?eld of nonlinear dynamics to discuss, mainly, theoretical ideas that may have the potential for further implementation. In contrast, the goal of the 2007 ICAND (International Conference on Applied Nonlinear Dynamics) was focused more sharply on the implementation of theoretical ideas into actual - vices and systems.

Complex systems in nature are those with many interacting parts, all capable of influencing global system outcomes. There is a growing body of research that has modeled sport performance from a complexity sciences perspective, studying the behavior of individual athletes and sports teams as emergent phenomena which self-organise under interacting constraints. This book is the first to bring together experts studying complex systems in the context of sport from across the world to collate core theoretical ideas, current methodologies and existing data into one comprehensive resource. It offers new methods of analysis for investigating representative complex sport movements and actions at an individual and team level, exploring the application of methodologies from the complexity sciences in the context of sports performance and the organization of sport practice. Complex Systems in Sport is important reading for any advanced student or researcher working in sport and exercise science, sports coaching, kinesiology or human movement.

Environmental Soil-Landscape Modeling: Geographic Information Technologies and Pedometrics presents the latest methodological developments in soil-landscape modeling. It analyzes many recently developed measurement tools, and explains computer-related and pedometric techniques that are invaluable in the modeling process. This volume provi