In this book you will read stories told by faculty who have redesigned their university courses using the Decision-Based Learning pedagogy and the impact this powerful strategy can have on student learning. It should be of use to anyone teaching and designing curricula in higher education settings.

"Gathering data and using it to inform instruction is a requirement for many schools, yet educators are not necessarily formally trained in how to do it. This book helps bridge the gap between classroom practice and the principles of educational psychology. Teachers will find cutting-edge advances in research and theory on human learning and teaching in an easily understood and transferable format. The text's integrated model shows teachers, school leaders, and district administrators how to establish a data culture and transform quantitative and qualitative data into actionable knowledge based on: assessment; statistics; instructional and differentiated psychology; classroom management."--Publisher's description.

In a context where schools are held more and more accountable for the education they provide, data-based decision making has become increasingly important. This book brings together scholars from several countries to examine data-based decision making. Data-based decision making in this book refers to making decisions based on a broad range of evidence, such as scores on students’ assessments, classroom observations etc. This book supports policy-makers, people working with schools, researchers and school leaders and teachers in the use of data, by bringing together the current research conducted on data use across multiple countries into a single volume. Some of these studies are ‘best practice’ studies, where effective data use has led to improvements in student learning. Others provide insight into challenges in both policy and practice environments. Each of them draws on research and literature in the field.

This book, jointly authored by two distinguished philosophers and two prominent social scientists, has an ambitious aim: to improve decision-making in education policy. First they dive into the goals of education policy and explain the terms "educational goods" and "childhood goods," adding precision and clarity to the discussion of the distributive values that are essential for good decision-making about education. Then they provide a framework for individual decision-makers that enables them to combine values and evidence in the evaluation of educational policy options. Finally they delve into the particular policy issues of school finance, school accountability, and school choice, and they show how decision makers might approach them in the light of this decision-making framework. The authors are not advocated particular policy choices, however. The focus instead is a smart framework that will make it easier for policymakers (and readers) to identify and think through what they disagree with others about.

In this book you will read stories told by faculty who have redesigned their university courses using the Decision-Based Learning pedagogy and the impact this powerful strategy can have on student learning. It should be of use to anyone teaching and designing curricula in higher education settings.

Reinforcement and Systemic Machine Learning for Decision Making There are always difficulties in making machines that learn from experience. Complete information is not always available—or it becomes available in bits and pieces over a period of time. With respect to systemic learning, there is a need to understand the impact of decisions and actions on a system over that period of time. This book takes a holistic approach to addressing that need and presents a new paradigm—creating new learning applications and, ultimately, more intelligent machines. The first book of its kind in this new and growing field, Reinforcement and Systemic Machine Learning for Decision Making focuses on the specialized research area of machine learning and systemic machine learning. It addresses reinforcement learning and its applications, incremental machine learning, repetitive failure-correction mechanisms, and multiperspective decision making. Chapters include: Introduction to Reinforcement and Systemic Machine Learning Fundamentals of Whole-System, Systemic, and Multiperspective Machine Learning Systemic Machine Learning and Model Inference and Information Integration Adaptive Learning Incremental Learning and Knowledge Representation Knowledge Augmentation: A Machine Learning Perspective Building a Learning System With the potential of this paradigm to become one of the more utilized in its field, professionals in the area of machine and systemic learning will find this book to be a valuable resource.

This book is written for anyone who has been inspired by the idea of Team-Based Learning (TBL) through his or her reading, a workshop, or a colleague’s enthusiasm, and then asks the inevitable question: how do I start?Written by five authors who use TBL in their teaching and who are internationally recognized as mentors and trainers of faculty making the switch to TBL, the book also presents the tips and insights of 46 faculty members from around the world who have adopted this teaching method.TBL is a uniquely powerful form of small group learning. It harnesses the power of teams and social learning with accountability structures and instructional sequences. This book provides the guidance, from first principles to examples of practice, together with concrete advice, suggestions, and tips to help you succeed in the TBL classroom. This book will help you understand what TBL is and why it is so powerful. You will find what you need to plan, build, implement, and use TBL effectively. This book will appeal to both the novice and the expert TBL teacher.

The chief executive officer of a corporation is not much different from a public school administrator. While CEOs base many of their decisions on data, for school administrators, this type of research may conjure up miserable memories of searching for information to meet a graduate school requirement. However, the value of data-based decision making will continue to escalate and the school community—students, teachers, parents and the general public—expect this information to come from their administrators. Administrators are called on to be accountable, but few are capable of presenting the mountain of data that they collect in a cohesive and strategic manner. Most statistical books are focused on statistical theory versus application, but Statistics Made Simple for School Leaders presents statistics in a simple, practical, conceptual, and immediately applicable manner. It enables administrators to take their data and manage it into strategic information so the results can be used for action plans that benefit the school system. The approach is 'user friendly' and leaves the reader with a confident can-do attitude to communicate results and plans to staff and the community.

Join Luffy as he tries to become the king of the pirates and find the legendary treasure, One Piece As a child, Monkey D. Luffy dreamed of becoming King of the Pirates. But his life changed when he accidentally gained the power to stretch like rubber...at the cost of never being able to swim again Years, later, Luffy sets off in search of the "One Piece," said to be the greatest treasure in the world... The Straw Hat crew are the only ones standing in the way of the New Fish-Man pirates taking complete control over Fish-Man Island. And when Hody puts his diabolical plan into action, only Luffy can stop him. Luffy may have become much more powerful thanks to his training, but how can he hope to defeat a Fish-Man at the bottom of the ocean? Reads R to L (Japanese Style) for teen audiences.