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Dynamic Learning is about a revolutionary new approach to learning and teaching. The authors present leading edge methods and techniques that improve the ability to learn in a variety of areas, offering stimulating exercises and step-by-step procedures that help you to make better use of the most valuable resource you have-your brain.
Writing for general managers, the authors go beyond manufacturing structural decisions to actually changing the infrastructure of a manufacturing company--the leadership and vision, the policies and practices that are vital to creating superior factories and a dynamic learning continuum.
A textbook covering data-science and machine learning methods for modelling and control in engineering and science, with Python and MATLAB®.
This volume tackles issues arising from today’s high reliance on learning from visualizations in general and dynamic visualizations in particular at all levels of education. It reflects recent changes in educational practice through which text no longer occupies its traditionally dominant role as the prime means of presenting to-be-learned information to learners. Specifically, the book targets the dynamic visual components of multimedia educational resources and singles out how they can influence learning in their own right. It aims to help bridge the increasing gap between pervasive adoption of dynamic visualizations in educational practice and our limited understanding of the role that these representations can play in learning. The volume has recruited international leaders in the field to provide diverse perspectives on the dynamic visualizations and learning. It is the first comprehensive book on the topic that brings together contributions from both renowned researchers and expert practitioners. Rather than aiming to present a broad general overview of the field, it focuses on innovative work that is at the cutting edge. As well as further developing and complementing existing approaches, the contributions emphasize fresh ideas that may challenge existing orthodoxies and point towards future directions for the field. They seek to stimulate further new developments in the design and use of dynamic visualizations for learning as well as the rigorous, systematic investigation of their educational effectiveness.the volume="" sheds="" light="" on="" the="" complex="" and="" highly="" demanding="" processes="" of="" conceptualizing,="" developing="" implementing="" dynamic="" visualizations="" in="" practice="" as="" well="" challenges="" relating="" research="" application="" perspectives.
From household appliances to applications in robotics, engineered systems involving complex dynamics can only be as effective as the algorithms that control them. While Dynamic Programming (DP) has provided researchers with a way to optimally solve decision and control problems involving complex dynamic systems, its practical value was limited by algorithms that lacked the capacity to scale up to realistic problems. However, in recent years, dramatic developments in Reinforcement Learning (RL), the model-free counterpart of DP, changed our understanding of what is possible. Those developments led to the creation of reliable methods that can be applied even when a mathematical model of the system is unavailable, allowing researchers to solve challenging control problems in engineering, as well as in a variety of other disciplines, including economics, medicine, and artificial intelligence. Reinforcement Learning and Dynamic Programming Using Function Approximators provides a comprehensive and unparalleled exploration of the field of RL and DP. With a focus on continuous-variable problems, this seminal text details essential developments that have substantially altered the field over the past decade. In its pages, pioneering experts provide a concise introduction to classical RL and DP, followed by an extensive presentation of the state-of-the-art and novel methods in RL and DP with approximation. Combining algorithm development with theoretical guarantees, they elaborate on their work with illustrative examples and insightful comparisons. Three individual chapters are dedicated to representative algorithms from each of the major classes of techniques: value iteration, policy iteration, and policy search. The features and performance of these algorithms are highlighted in extensive experimental studies on a range of control applications. The recent development of applications involving complex systems has led to a surge of interest in RL and DP methods and the subsequent need for a quality resource on the subject. For graduate students and others new to the field, this book offers a thorough introduction to both the basics and emerging methods. And for those researchers and practitioners working in the fields of optimal and adaptive control, machine learning, artificial intelligence, and operations research, this resource offers a combination of practical algorithms, theoretical analysis, and comprehensive examples that they will be able to adapt and apply to their own work. Access the authors' website at www.dcsc.tudelft.nl/rlbook/ for additional material, including computer code used in the studies and information concerning new developments.
This volume discusses the need for a major paradigm shift in educational practice in the current digital and globalized world. It establishes a bridge between theory and praxis and revisits the objectives of learning and its modalities within the context of a rapidly evolving global world order. This volume includes perspectives from different countries on creating a dynamic and adaptive education system that encourages creativity, leadership, flexibility, and working in virtual as well as inclusive environments. The four sections include chapters that discuss creating meaningful learning environments, preparing teachers for new age classrooms, the digital learning space, fostering change in classrooms, and importantly also includes cases and experiments from schools. The authors are teacher educators, teachers and researchers, and each chapter, while being deeply rooted in theory, is juxtaposed with informed practice, making the suggestions easy to implement in different settings. This is an important resource for researchers and practitioners associated with education systems in creating engaging, meaningful and future-ready education practices.
Say goodbye to boring lectures and tired, one-and-done activities! In Blended Learning with Google, bestselling author and experienced educator Kasey Bell shows you how to use Google tools to design and support dynamic blended learning experiences whether you're teaching in-person, online classes, or both! With so much of life and learning happening online, we have to think differently about lessons and assignments. We can't rely on worksheets or one-and-done activities. They don't cut it anymore! To better serve our students, we must go beyond traditional methods-and beyond the walls of our classrooms. We need Dynamic Learning, and Google's powerful and easy-to-use suite of tools can help! Kasey Bell is your personal Google guide, but don't let the southern charm fool you. She packs this book with practical ideas and meaningful strategies that you can implement right away. Here is a peek at what you'll find in Blended Learning with Google A practical framework for meaningful Blended Learning Digital learning strategies for every classroom Google templates, lesson plans, pro tips, remote learning tips, and more! This book is not about Google; it's about how to use Google tools to support Dynamic Learning for your students every day! Shake Up Learning with Google tools to design Dynamic Blended Learning experiences in your classroom!
This book comes at the right time with answers for teachers, principals, and schools who want to be on the cutting edge of the effective use of technology, the internet, and teacher pedagogy.
This resource explains how to merge the essential skills of embedding culturally responsive teaching practices into online and in person learning settings. The Dynamic Equitable Learning Environments (DELE) framework assists in building the knowledge, awareness, skills, and dispositions to pivot instruction to facilitate equitable, inclusive, and anti-racist learning experiences that transcend cultural, social, and linguistic backgrounds--regardless of student environments.
