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LEARNING AND BEHAVIOR, Seventh Edition, is stimulating and filled with high-interest queries and examples. Based on the theme that learning is a biological mechanism that aids survival, this book embraces a scientific approach to behavior but is written in clear, engaging, and easy-to-understand language.
Students thrive when educators commit to proactively meeting their behavioral as well as academic needs. This book will help teachers and school leaders transform the research on behavior, response to intervention, and professional learning communities into practical strategies they can use to create a school culture and classroom climates in which learning is primed to occur.
This popular text gives students a comprehensive and readable introduction to contemporary issues in learning and behaviour, while providing balanced coverage of classical and instrumental conditioning.
Explains sensory motor development and provides activities and games for use in the classroom and at home.
Research on fundamental learning processes continues to tell an important and interesting story. In the Second Edition of his textbook, Mark Bouton recounts that story, providing an in-depth but highly readable review of modern learning and behavior theory that is informed by the history of the field. The text reflects the author's conviction that the study of animal learning has a central place in psychology, and that understanding its principles and theories is important for students, psychologists, and scientists in related disciplines (e.g., behavioral neuroscience and clinical psychology). Lively and current, Learning and Behavior: A Contemporary Synthesis, Second Edition engages students while illustrating the interconnectedness of topics within the field and the excitement of modern research. What's New in This Edition Over 50 new chapter-end Discussion Questions engage the student in reviewing and integrating the chapter material. In addition to new figures, all of the art has been digitally enhanced and updated to full colour. New and expanded coverage of topics such as metacognition in animals, behavioral economics, hybrid attention theory, consolidation and reconsolidation, the motivational control of instrumental behavior, and action and habit learning. More illustrative studies that focus on human participants. All material has been thoroughly updated, with 279 new references cited.
This volume provides research-based, practical information on managing the challenges that Asperger syndrome (AS) presents in everyday life and in the classroom. Current knowledge is reviewed on the core learning, behavioral, emotional, social, and communication difficulties associated with this complex disorder. Hurdles facing children with AS and their parents and teachers are clearly identified, and effective assessment and intervention approaches described. Special features include firsthand accounts from an adult with AS and a teacher with extensive experience in the area, as well as numerous illustrative vignettes and classroom examples. While written primarily for professionals, the volume will also be of interest to many parents.
This book has been replaced by Developing a Schoolwide Framework to Prevent and Manage Learning and Behavior Problems, Second Edition, ISBN 978-1-4625-4173-7.
Behavior Analysis with Machine Learning Using R introduces machine learning and deep learning concepts and algorithms applied to a diverse set of behavior analysis problems. It focuses on the practical aspects of solving such problems based on data collected from sensors or stored in electronic records. The included examples demonstrate how to perform common data analysis tasks such as: data exploration, visualization, preprocessing, data representation, model training and evaluation. All of this, using the R programming language and real-life behavioral data. Even though the examples focus on behavior analysis tasks, the covered underlying concepts and methods can be applied in any other domain. No prior knowledge in machine learning is assumed. Basic experience with R and basic knowledge in statistics and high school level mathematics are beneficial. Features: Build supervised machine learning models to predict indoor locations based on WiFi signals, recognize physical activities from smartphone sensors and 3D skeleton data, detect hand gestures from accelerometer signals, and so on. Program your own ensemble learning methods and use Multi-View Stacking to fuse signals from heterogeneous data sources. Use unsupervised learning algorithms to discover criminal behavioral patterns. Build deep learning neural networks with TensorFlow and Keras to classify muscle activity from electromyography signals and Convolutional Neural Networks to detect smiles in images. Evaluate the performance of your models in traditional and multi-user settings. Build anomaly detection models such as Isolation Forests and autoencoders to detect abnormal fish behaviors. This book is intended for undergraduate/graduate students and researchers from ubiquitous computing, behavioral ecology, psychology, e-health, and other disciplines who want to learn the basics of machine learning and deep learning and for the more experienced individuals who want to apply machine learning to analyze behavioral data.
INTRODUCTION TO LEARNING AND BEHAVIOR, 5th Edition provides you with a clear introduction to the basic principles of behavior presented in an accessible, engaging manner. Using examples derived from both animals and humans, the text vividly illustrates the relevance of behavioral principles to understanding and improving human behavior. The authors demonstrate the application of behavioral principles to such relevant issues as improving your study behavior, reducing procrastination, raising children, and managing relationships. To help you maximize your learning, the text is packed with innovative study and review tools to further your understanding of key concepts.
This book reviews how people and animals learn and how their behaviors are later changed as a result of this learning. Nearly all of our behaviors are influenced by prior learning experiences in some way. This book describes some of the most important principles, theories, controversies, and experiments that pertain to learning and behavior that are applicable to many different species and many different learning situations. Many real-world examples and analogies make the concepts and theories more concrete and relevant to the students. In addition, most of the chapters include sections that describe how the theories and principles have been used in the applied field of behavior modification. Each chapter in the seventh edition was updated with new studies and new references that reflect recent developments in the field. The book includes a number of learning aids for students, including a list of learning objectives at the beginning of each chapter, practices quizzes and review questions, and a glossary for all important terms. Learning & Behavior covers topics such as classical and operant conditioning, reinforcement schedules, avoidance and punishment, stimulus control, comparative cognition, observational learning, motor skill learning, and choice. Both the classic studies and the most recent developments and trends in the field are explored. Although the behavioral approach is emphasized, many cognitive theories are covered as well along with a chapter on comparative cognition. Upon completing this book readers will be able to:understand the field of learning and discuss real-world applications of learning principles.