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This work explains that equilibrium is the long-run outcome of a process in which non-fully rational players search for optimality over time. The models they e×plore provide a foundation for equilibrium theory and suggest ways for economists to evaluate and modify traditional equilibrium concepts.
In recent years, there has been growing interest in the use of digital games to enhance teaching and learning at all educational levels, from early years through to lifelong learning, in formal and informal settings. The study of games and learning, however, takes a broader view of the relationship between games and learning, and has a diverse multi-disciplinary background. Digital Games and Learning: Research and Theory provides a clear and concise critical theoretical overview of the field of digital games and learning from a cross-disciplinary perspective. Taking into account research and theory from areas as varied as computer science, psychology, education, neuroscience, and game design, this book aims to synthesise work that is relevant to the study of games and learning. It focuses on four aspects of digital games: games as active learning environments, games as motivational tools, games as playgrounds, and games as learning technologies, and explores each of these areas in detail. This book is an essential guide for researchers, designers, teachers, practitioners, and policy makers who want to better understand the relationship between games and learning.
The video game market continues to increase, reaching millions of users on a variety of platforms and revealing how engaging and pervasive gaming can be. Games create engagement and offer both entertainment and a powerful way to understand and interact with the world. It is natural that educators see the potential of games as a learning tool that can support students who have difficulties learning and also reinvent it. Practical Perspectives on Educational Theory and Game Development is a critical scholarly resource that combines educational scenarios and game fundamentals in order to improve the way people learn and evolve. The book supports professionals with the creation of strategies for using gamification and game-based learning theory with effectiveness and measured results. Featuring a wide range of topics such as entrepreneurship, gamification, and traditional learning, this book is ideal for academicians, education professionals, curriculum designers, educational game developers, researchers, and students.
Game Theory 101: The Complete Textbook is a no-nonsense, games-centered introduction to strategic form (matrix) and extensive form (game tree) games. From the first lesson to the last, this textbook introduces games of increasing complexity and then teaches the game theoretical tools necessary to solve them. Quick, efficient, and to the point, Game Theory 101: The Complete Textbook is perfect for introductory game theory, intermediate microeconomics, and political science.
Now in full color, the 10th anniversary edition of this classic book takes you deep into the influences that underlie modern video games, and examines the elements they share with traditional games such as checkers. At the heart of his exploration, veteran game designer Raph Koster takes a close look at the concept of fun and why it’s the most vital element in any game. Why do some games become boring quickly, while others remain fun for years? How do games serve as fundamental and powerful learning tools? Whether you’re a game developer, dedicated gamer, or curious observer, this illustrated, fully updated edition helps you understand what drives this major cultural force, and inspires you to take it further. You’ll discover that: Games play into our innate ability to seek patterns and solve puzzles Most successful games are built upon the same elements Slightly more females than males now play games Many games still teach primitive survival skills Fictional dressing for modern games is more developed than the conceptual elements Truly creative designers seldom use other games for inspiration Games are beginning to evolve beyond their prehistoric origins
Discusses the essential elements in creating a successful game, how playing games and learning are connected, and what makes a game boring or fun.
There is a growing recognition in the learning sciences that video games can no longer be seen as impediments to education, but rather, they can be developed to enhance learning. Educational and developmental psychologists, education researchers, media psychologists, and cognitive psychologists are now joining game designers and developers in seeking out new ways to use video game play in the classroom. In Learning by Playing, a diverse group of contributors provide perspectives on the most current thinking concerning the ramifications of leisure video game play for academic classroom learning. The first section of the text provides foundational understanding of the cognitive skills and content knowledge that children and adolescents acquire and refine during video game play. The second section explores game features that captivate and promote skills development among game players. The subsequent sections discuss children and adolescents' learning in the context of different types of games and the factors that contribute to transfer of learning from video game play to the classroom. These chapters then form the basis for the concluding section of the text: a specification of the most appropriate research agenda to investigate the academic potential of video game play, particularly using those games that child and adolescent players find most compelling. Contributors include researchers in education, learning sciences, and cognitive and developmental psychology, as well as instructional design researchers.
At a time when digital games are becoming much more commonly used in classrooms, Game-Based Learning: Theory, Strategies, and Performance Outcomes provides a much-needed guide to different forms and applications of digital game-based learning. This book brings together researchers and practitioners from around the world who share their theories, strategies, findings of case studies, and practical approaches to support better performance and learning outcomes when learning with digital games. This book is intended to provide readers with three main parts of information. One is a clear and practical understanding of theory and research-based principles of game-based learning. This first section of the book includes fresh perspectives and an overview of existing and emerging theories in game-based learning, which are also presented in the form of case study findings and implications. The second section of this book gives readers the "how to" information needed to turn the understanding of intellectual grounding into effective practices of digital games for classroom use. The third part of this book also includes some practical approaches for evaluating different aspects of learning within the game-based learning context. This information about practical approaches is presented through chapters on achievements and performance outcomes. Game-Based Learning: Theory, Strategies, and Performance Outcomes synthesizes arguments, practices, and research findings on the effectiveness of different designs and approaches within game-based learning practices. But, a major message of this book is that the joint influence of implementation, context, and learner characteristics interacting with digital games is what determines learning and achievement outcomes. This book is intended for researchers, practitioners, designers, policy makers, and current and future teachers. The teacher/-educator will benefit from topics such as practical strategies to improve student performance, while researchers can use the findings from the case studies presented in this book as a foundation for future explorations and research studies.
A comprehensive introduction to the latest research and theory on learning and instruction with computer games. This book offers a comprehensive introduction to the latest research on learning and instruction with computer games. Unlike other books on the topic, which emphasize game development or best practices, Handbook of Game-Based Learning is based on empirical findings and grounded in psychological and learning sciences theory. The contributors, all leading researchers in the field, offer a range of perspectives, including cognitive, motivational, affective, and sociocultural. They explore research on whether (and how) computer games can help students learn educational content and academic skills; which game features (including feedback, incentives, adaptivity, narrative theme, and game mechanics) can improve the instructional effectiveness of these games; and applications, including games for learning in STEM disciplines, for training cognitive skills, for workforce learning, and for assessment. The Handbook offers an indispensable reference both for readers with practical interests in designing or selecting effective game-based learning environments and for scholars who conduct or evaluate research in the field. It can also be used in courses related to play, cognition, motivation, affect, instruction, and technology. Contributors Roger Azevedo, Ryan S. Baker, Daphne Bavelier, Amanda E. Bradbury, Ruth C. Clark, Michele D. Dickey, Hamadi Henderson, Bruce D. Homer, Fengfeng Ke, Younsu Kim, Charles E. Kinzer, Eric Klopfer, James C. Lester, Kristina Loderer, Richard E. Mayer, Bradford W. Mott, Nicholas V. Mudrick, Brian Nelson, Frank Nguyen, V. Elizabeth Owen, Shashank Pawar, Reinhard Pekrun, Jan L. Plass, Charles Raffale, Jonathon Reinhardt, C. Scott Rigby, Jonathan P. Rowe, Richard M. Ryan, Ruth N. Schwartz, Quinnipiac Valerie J. Shute, Randall D. Spain, Constance Steinkuehler, Frankie Tam, Michelle Taub, Meredith Thompson, Steven L. Thorne, A. M. Tsaasan
This important text and reference for researchers and students in machine learning, game theory, statistics and information theory offers a comprehensive treatment of the problem of predicting individual sequences. Unlike standard statistical approaches to forecasting, prediction of individual sequences does not impose any probabilistic assumption on the data-generating mechanism. Yet, prediction algorithms can be constructed that work well for all possible sequences, in the sense that their performance is always nearly as good as the best forecasting strategy in a given reference class. The central theme is the model of prediction using expert advice, a general framework within which many related problems can be cast and discussed. Repeated game playing, adaptive data compression, sequential investment in the stock market, sequential pattern analysis, and several other problems are viewed as instances of the experts' framework and analyzed from a common nonstochastic standpoint that often reveals new and intriguing connections.