Goal-driven Learning

Goal-driven Learning PDF Author: Ashwin Ram
Publisher: MIT Press
ISBN: 9780262181655
Category : Computers
Languages : en
Pages : 548

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Book Description
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

Goal-driven Learning

Goal-driven Learning PDF Author: Ashwin Ram
Publisher: MIT Press
ISBN: 9780262181655
Category : Computers
Languages : en
Pages : 548

Get Book Here

Book Description
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

Step Into Student Goal Setting

Step Into Student Goal Setting PDF Author: Chase Nordengren
Publisher: Corwin Press
ISBN: 1071867067
Category : Education
Languages : en
Pages : 145

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Book Description
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.

Atomic Habits

Atomic Habits PDF Author: James Clear
Publisher: Penguin
ISBN: 0735211299
Category : Business & Economics
Languages : en
Pages : 321

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Book Description
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.

Fundamentals of Artificial Intelligence Research

Fundamentals of Artificial Intelligence Research PDF Author: Jozef Kelemen
Publisher: Springer Science & Business Media
ISBN: 9783540545071
Category : Computers
Languages : en
Pages : 276

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Book Description
This volume contains 6 invited lectures and 13 submitted contributions to the scientific programme of the international workshop Fundamentals of Artificial Intelligence Research, FAIR '91, held at Smolenice Castle, Czechoslovakia, September 8-12, 1991, under the sponsorship of the European Coordinating Committee for Artificial Intelligence, ECCAI. FAIR'91, the first of an intended series of international workshops, addresses issues which belong to the theoretical foundations of artificial intelligence considered as a discipline focused on concise theoretical description of some aspects of intelligence by toolsand methods adopted from mathematics, logic, and theoretical computer science. The intended goal of the FAIR workshops is to provide a forum for the exchange of ideas and results in a domain where theoretical models play an essential role. It is felt that such theoretical studies, their development and their relations to AI experiments and applications have to be promoted in the AI research community.

Handbook of Research on Improving Learning and Motivation through Educational Games: Multidisciplinary Approaches

Handbook of Research on Improving Learning and Motivation through Educational Games: Multidisciplinary Approaches PDF Author: Felicia, Patrick
Publisher: IGI Global
ISBN: 1609604962
Category : Education
Languages : en
Pages : 1374

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Book Description
"This book provides relevant theoretical frameworks and the latest empirical research findings on game-based learning to help readers who want to improve their understanding of the important roles and applications of educational games in terms of teaching strategies, instructional design, educational psychology and game design"--Provided by publisher.

Artificial Neural Networks and Machine Learning – ICANN 2021

Artificial Neural Networks and Machine Learning – ICANN 2021 PDF Author: Igor Farkaš
Publisher: Springer Nature
ISBN: 3030863808
Category : Computers
Languages : en
Pages : 703

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Book Description
The proceedings set LNCS 12891, LNCS 12892, LNCS 12893, LNCS 12894 and LNCS 12895 constitute the proceedings of the 30th International Conference on Artificial Neural Networks, ICANN 2021, held in Bratislava, Slovakia, in September 2021.* The total of 265 full papers presented in these proceedings was carefully reviewed and selected from 496 submissions, and organized in 5 volumes. In this volume, the papers focus on topics such as model compression, multi-task and multi-label learning, neural network theory, normalization and regularization methods, person re-identification, recurrent neural networks, and reinforcement learning. *The conference was held online 2021 due to the COVID-19 pandemic.

Measurement Methodologies to Assess the Effectiveness of Global Online Learning

Measurement Methodologies to Assess the Effectiveness of Global Online Learning PDF Author: Isaias, Pedro
Publisher: IGI Global
ISBN: 1799886638
Category : Education
Languages : en
Pages : 366

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Book Description
While online learning was an existing practice, the COVID-19 pandemic greatly accelerated its capabilities and forced educational organizations to swiftly introduce online learning for all units. Though schools will not always be faced with forced online learning, it is apparent that there are clear advantages and disadvantages to this teaching method, with its usage in the future cemented. As such, it is imperative that methods for measuring and assessing the effectiveness of online and blended learning are examined in order to improve outcomes and future practices. Measurement Methodologies to Assess the Effectiveness of Global Online Learning aims to assess the effectiveness of online teaching and learning in normal and pandemic situations by addressing challenges and opportunities of adoption of online platforms as well as effective learning strategies, investigating the best pedagogical practices in digital learning, questioning how to improve student motivation and performance, and managing and measuring academic workloads online. Covering a wide range of topics such as the future of education and digital literacy, it is ideal for teachers, instructional designers, curriculum developers, educational software developers, academics, researchers, and students.

College Success

College Success PDF Author: Amy Baldwin
Publisher:
ISBN: 9781951693169
Category :
Languages : en
Pages :

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Book Description


Intrinsically Motivated Learning in Natural and Artificial Systems

Intrinsically Motivated Learning in Natural and Artificial Systems PDF Author: Gianluca Baldassarre
Publisher: Springer Science & Business Media
ISBN: 3642323758
Category : Computers
Languages : en
Pages : 453

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Book Description
It has become clear to researchers in robotics and adaptive behaviour that current approaches are yielding systems with limited autonomy and capacity for self-improvement. To learn autonomously and in a cumulative fashion is one of the hallmarks of intelligence, and we know that higher mammals engage in exploratory activities that are not directed to pursue goals of immediate relevance for survival and reproduction but are instead driven by intrinsic motivations such as curiosity, interest in novel stimuli or surprising events, and interest in learning new behaviours. The adaptive value of such intrinsically motivated activities lies in the fact that they allow the cumulative acquisition of knowledge and skills that can be used later to accomplish fitness-enhancing goals. Intrinsic motivations continue during adulthood, and in humans they underlie lifelong learning, artistic creativity, and scientific discovery, while they are also the basis for processes that strongly affect human well-being, such as the sense of competence, self-determination, and self-esteem. This book has two aims: to present the state of the art in research on intrinsically motivated learning, and to identify the related scientific and technological open challenges and most promising research directions. The book introduces the concept of intrinsic motivation in artificial systems, reviews the relevant literature, offers insights from the neural and behavioural sciences, and presents novel tools for research. The book is organized into six parts: the chapters in Part I give general overviews on the concept of intrinsic motivations, their function, and possible mechanisms for implementing them; Parts II, III, and IV focus on three classes of intrinsic motivation mechanisms, those based on predictors, on novelty, and on competence; Part V discusses mechanisms that are complementary to intrinsic motivations; and Part VI introduces tools and experimental frameworks for investigating intrinsic motivations. The contributing authors are among the pioneers carrying out fundamental work on this topic, drawn from related disciplines such as artificial intelligence, robotics, artificial life, evolution, machine learning, developmental psychology, cognitive science, and neuroscience. The book will be of value to graduate students and academic researchers in these domains, and to engineers engaged with the design of autonomous, adaptive robots. The contributing authors are among the pioneers carrying out fundamental work on this topic, drawn from related disciplines such as artificial intelligence, robotics, artificial life, evolution, machine learning, developmental psychology, cognitive science, and neuroscience. The book will be of value to graduate students and academic researchers in these domains, and to engineers engaged with the design of autonomous, adaptive robots.

How People Learn II

How People Learn II PDF Author: National Academies of Sciences, Engineering, and Medicine
Publisher: National Academies Press
ISBN: 0309459672
Category : Education
Languages : en
Pages : 347

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Book Description
There are many reasons to be curious about the way people learn, and the past several decades have seen an explosion of research that has important implications for individual learning, schooling, workforce training, and policy. In 2000, How People Learn: Brain, Mind, Experience, and School: Expanded Edition was published and its influence has been wide and deep. The report summarized insights on the nature of learning in school-aged children; described principles for the design of effective learning environments; and provided examples of how that could be implemented in the classroom. Since then, researchers have continued to investigate the nature of learning and have generated new findings related to the neurological processes involved in learning, individual and cultural variability related to learning, and educational technologies. In addition to expanding scientific understanding of the mechanisms of learning and how the brain adapts throughout the lifespan, there have been important discoveries about influences on learning, particularly sociocultural factors and the structure of learning environments. How People Learn II: Learners, Contexts, and Cultures provides a much-needed update incorporating insights gained from this research over the past decade. The book expands on the foundation laid out in the 2000 report and takes an in-depth look at the constellation of influences that affect individual learning. How People Learn II will become an indispensable resource to understand learning throughout the lifespan for educators of students and adults.