Brings together a diversity of research on goal-driven learning to establish a broad, interdisciplinary framework that describes the goal-driven learning process. In cognitive science, artificial intelligence, psychology, and education, a growing body of research supports the view that the learning process is strongly influenced by the learner's goals. The fundamental tenet of goal-driven learning is that learning is largely an active and strategic process in which the learner, human or machine, attempts to identify and satisfy its information needs in the context of its tasks and goals, its prior knowledge, its capabilities, and environmental opportunities for learning. This book brings together a diversity of research on goal-driven learning to establish a broad, interdisciplinary framework that describes the goal-driven learning process. It collects and solidifies existing results on this important issue in machine and human learning and presents a theoretical framework for future investigations. The book opens with an an overview of goal-driven learning research and computational and cognitive models of the goal-driven learning process. This introduction is followed by a collection of fourteen recent research articles addressing fundamental issues of the field, including psychological and functional arguments for modeling learning as a deliberative, planful process; experimental evaluation of the benefits of utility-based analysis to guide decisions about what to learn; case studies of computational models in which learning is driven by reasoning about learning goals; psychological evidence for human goal-driven learning; and the ramifications of goal-driven learning in educational contexts. The second part of the book presents six position papers reflecting ongoing research and current issues in goal-driven learning. Issues discussed include methods for pursuing psychological studies of goal-driven learning, frameworks for the design of active and multistrategy learning systems, and methods for selecting and balancing the goals that drive learning. A Bradford Book

This resource provides an action plan for understanding what a student knows and how to build from it. It shows teachers how to integrate formative assessment, student metacognition, and motivational strategies to make goal setting an integral instructional strategy. It weaves research and case studies with practical strategies to demonstrate how goal setting, with clear learning intentions and scaffolded teacher support, can lead to high learning growth and student agency.

This book is more than a collection of activities or ready-made lesson plans to add to a teaching repertoire. Instead, Goal-Driven Lesson Planning is intended to empower teachers and help them create a principled framework for their teaching—a framework that will shape the varied activities of the ESL classroom into a coherent teaching and learning partnership. After reading this book, teachers and prospective teachers will be able to articulate their individual teaching philosophies. Goal-Driven Lesson Planning shows readers how to take any piece from English language materials—an assigned text, a random newspaper article, an ESL activity from a website, etc.—and use it to teach students something about language. Readers are walked through the process of reflecting on their role in diagnosing what that “something” is—what students really need—and planning how to get them there and how to know when they got there in a goal-driven principled manner. This book has chapters on the theory of setting specific language goals for students; how to analyze learner needs (including an initial diagnostic and needs-analysis); templates to use when planning goal-driven English language lessons; explicit instruction on giving corrective feedback; how to recognize and assess student progress; and the mechanics and logistics that facilitate the goal-driven language classroom.

Knowledge-based approaches to planning and control offer benefits over classical techniques in applications that involve large yet structured state spaces. However, knowledge bases are time consuming and costly to construct. In this dissertation I introduce a framework for analytical learning that enables the agent to acquire generalizable, domain-specific procedural knowledge in the form of goal-indexed hierarchical task networks by observing a small number of successful demonstrations of goal-driven tasks. I discuss how, in contrast with most algorithms for learning by observation, my approach can learn from unannotated input demonstrations by automatically inferring the purpose of each solution step using the background knowledge about the domain. I discuss the role of hierarchical structure, distributed applicability conditions, and goals in the generalizability of the acquired knowledge. I also introduce an approach for adaptively determining the structure of the acquired knowledge that strikes a balance between generality and operationality, and for making the algorithm robust to changes in the structure of background knowledge. This involves resolving interdependencies among goals using temporal information. I present experimental studies on a number of domains which demonstrate that the quality of acquired knowledge is comparable to handcrafted content in terms of both coverage and complexity. In closing, I review related work and directions for future research.

Goal-Directed Decision Making: Computations and Neural Circuits examines the role of goal-directed choice. It begins with an examination of the computations performed by associated circuits, but then moves on to in-depth examinations on how goal-directed learning interacts with other forms of choice and response selection. This is the only book that embraces the multidisciplinary nature of this area of decision-making, integrating our knowledge of goal-directed decision-making from basic, computational, clinical, and ethology research into a single resource that is invaluable for neuroscientists, psychologists and computer scientists alike. The book presents discussions on the broader field of decision-making and how it has expanded to incorporate ideas related to flexible behaviors, such as cognitive control, economic choice, and Bayesian inference, as well as the influences that motivation, context and cues have on behavior and decision-making. - Details the neural circuits functionally involved in goal-directed decision-making and the computations these circuits perform - Discusses changes in goal-directed decision-making spurred by development and disorders, and within real-world applications, including social contexts and addiction - Synthesizes neuroscience, psychology and computer science research to offer a unique perspective on the central and emerging issues in goal-directed decision-making

The #1 New York Times bestseller. Over 20 million copies sold! Translated into 60+ languages! Tiny Changes, Remarkable Results No matter your goals, Atomic Habits offers a proven framework for improving--every day. James Clear, one of the world's leading experts on habit formation, reveals practical strategies that will teach you exactly how to form good habits, break bad ones, and master the tiny behaviors that lead to remarkable results. If you're having trouble changing your habits, the problem isn't you. The problem is your system. Bad habits repeat themselves again and again not because you don't want to change, but because you have the wrong system for change. You do not rise to the level of your goals. You fall to the level of your systems. Here, you'll get a proven system that can take you to new heights. Clear is known for his ability to distill complex topics into simple behaviors that can be easily applied to daily life and work. Here, he draws on the most proven ideas from biology, psychology, and neuroscience to create an easy-to-understand guide for making good habits inevitable and bad habits impossible. Along the way, readers will be inspired and entertained with true stories from Olympic gold medalists, award-winning artists, business leaders, life-saving physicians, and star comedians who have used the science of small habits to master their craft and vault to the top of their field. Learn how to: make time for new habits (even when life gets crazy); overcome a lack of motivation and willpower; design your environment to make success easier; get back on track when you fall off course; ...and much more. Atomic Habits will reshape the way you think about progress and success, and give you the tools and strategies you need to transform your habits--whether you are a team looking to win a championship, an organization hoping to redefine an industry, or simply an individual who wishes to quit smoking, lose weight, reduce stress, or achieve any other goal.

Praise for How Learning Works "How Learning Works is the perfect title for this excellent book. Drawing upon new research in psychology, education, and cognitive science, the authors have demystified a complex topic into clear explanations of seven powerful learning principles. Full of great ideas and practical suggestions, all based on solid research evidence, this book is essential reading for instructors at all levels who wish to improve their students' learning." —Barbara Gross Davis, assistant vice chancellor for educational development, University of California, Berkeley, and author, Tools for Teaching "This book is a must-read for every instructor, new or experienced. Although I have been teaching for almost thirty years, as I read this book I found myself resonating with many of its ideas, and I discovered new ways of thinking about teaching." —Eugenia T. Paulus, professor of chemistry, North Hennepin Community College, and 2008 U.S. Community Colleges Professor of the Year from The Carnegie Foundation for the Advancement of Teaching and the Council for Advancement and Support of Education "Thank you Carnegie Mellon for making accessible what has previously been inaccessible to those of us who are not learning scientists. Your focus on the essence of learning combined with concrete examples of the daily challenges of teaching and clear tactical strategies for faculty to consider is a welcome work. I will recommend this book to all my colleagues." —Catherine M. Casserly, senior partner, The Carnegie Foundation for the Advancement of Teaching "As you read about each of the seven basic learning principles in this book, you will find advice that is grounded in learning theory, based on research evidence, relevant to college teaching, and easy to understand. The authors have extensive knowledge and experience in applying the science of learning to college teaching, and they graciously share it with you in this organized and readable book." —From the Foreword by Richard E. Mayer, professor of psychology, University of California, Santa Barbara; coauthor, e-Learning and the Science of Instruction; and author, Multimedia Learning