Learning from Demonstration (LfD) explores techniques for learning a task policy from examples provided by a human teacher. The field of LfD has grown into an extensive body of literature over the past 30 years, with a wide variety of approaches for encoding human demonstrations and modeling skills and tasks. Additionally, we have recently seen a focus on gathering data from non-expert human teachers (i.e., domain experts but not robotics experts). In this book, we provide an introduction to the field with a focus on the unique technical challenges associated with designing robots that learn from naive human teachers. We begin, in the introduction, with a unification of the various terminology seen in the literature as well as an outline of the design choices one has in designing an LfD system. Chapter 2 gives a brief survey of the psychology literature that provides insights from human social learning that are relevant to designing robotic social learners. Chapter 3 walks through an LfD interaction, surveying the design choices one makes and state of the art approaches in prior work. First, is the choice of input, how the human teacher interacts with the robot to provide demonstrations. Next, is the choice of modeling technique. Currently, there is a dichotomy in the field between approaches that model low-level motor skills and those that model high-level tasks composed of primitive actions. We devote a chapter to each of these. Chapter 7 is devoted to interactive and active learning approaches that allow the robot to refine an existing task model. And finally, Chapter 8 provides best practices for evaluation of LfD systems, with a focus on how to approach experiments with human subjects in this domain.
Learning from Demonstration (LfD) explores techniques for learning a task policy from examples provided by a human teacher. The field of LfD has grown into an extensive body of literature over the past 30 years, with a wide variety of approaches for encoding human demonstrations and modeling skills and tasks. Additionally, we have recently seen a focus on gathering data from non-expert human teachers (i.e., domain experts but not robotics experts). In this book, we provide an introduction to the field with a focus on the unique technical challenges associated with designing robots that learn from naive human teachers. We begin, in the introduction, with a unification of the various terminology seen in the literature as well as an outline of the design choices one has in designing an LfD system. Chapter 2 gives a brief survey of the psychology literature that provides insights from human social learning that are relevant to designing robotic social learners. Chapter 3 walks through an LfD interaction, surveying the design choices one makes and state of the art approaches in prior work. First, is the choice of input, how the human teacher interacts with the robot to provide demonstrations. Next, is the choice of modeling technique. Currently, there is a dichotomy in the field between approaches that model low-level motor skills and those that model high-level tasks composed of primitive actions. We devote a chapter to each of these. Chapter 7 is devoted to interactive and active learning approaches that allow the robot to refine an existing task model. And finally, Chapter 8 provides best practices for evaluation of LfD systems, with a focus on how to approach experiments with human subjects in this domain.
As the number of deployed robots grows, there will be an increasing need for humans to teach robots new skills that were not pre-programmed, without requiring these users to have any experience with programming or artificial intelligent systems. To enable this, we need to better understand how people want to teach and to support the ways in which people want to teach. To learn from human teachers, we consider the case where a human could provide online evaluative feedback, or design a sequence of tasks for the agent to learn on. With respect to learning from evaluative feedback, this dissertation demonstrates that learning algorithms that treat human feedback as a complex, discrete mode of communication can be better suited to learning from human trainers, rather than simply a numeric utility function to be optimized. Our empirical results indicate that humans, when teaching agents, deliver discrete feedback and follow different training strategies. We develop a novel model of evaluative feedback that captures knowledge about a teacher's training strategy. Based on this model, we develop two Bayesian learning algorithms that can learn from real users more efficiently than previous approaches that interpret feedback as numeric. To address limited evaluative feedback, we design a new representation of the learning agent. We demonstrate empirically that by changing the speed of the agent according to its confidence level, human trainers can be implicitly motivated to provide more explicit feedback when the learner has more uncertainty about how to act. We believe this can potentially be an effective way for the agent to interact with end-users, when taking into account human factors such as frustration. Finally, we consider the case where a human could design a sequence of tasks for the agent to learn on. We investigate how non-experts design curricula and how we can adapt machine-learning algorithms to better take advantage of this non-expert guidance. We empirically show that non-experts can design curricula that result in better overall agent performance than learning from scratch. We also demonstrate that by leveraging some principles people use when designing curricula, we can significantly improve our curriculum-learning algorithm.
Even on good days, teaching is a challenging profession. One way to make the job of college instructors easier, however, is to know more about the ways students learn. How Humans Learn aims to do just that by peering behind the curtain and surveying research in fields as diverse as developmental psychology, anthropology, and cognitive neuroscience for insight into the science behind learning. The result is a story that ranges from investigations of the evolutionary record to studies of infants discovering the world for the first time, and from a look into how our brains respond to fear to a reckoning with the importance of gestures and language. Joshua R. Eyler identifies five broad themes running through recent scientific inquiry--curiosity, sociality, emotion, authenticity, and failure--devoting a chapter to each and providing practical takeaways for busy teachers. He also interviews and observes college instructors across the country, placing theoretical insight in dialogue with classroom experience.
In this revolutionary book, a renowned computer scientist explains the importance of teaching children the basics of computing and how it can prepare them to succeed in the ever-evolving tech world. Computers have completely changed the way we teach children. We have Mindstorms to thank for that. In this book, pioneering computer scientist Seymour Papert uses the invention of LOGO, the first child-friendly programming language, to make the case for the value of teaching children with computers. Papert argues that children are more than capable of mastering computers, and that teaching computational processes like de-bugging in the classroom can change the way we learn everything else. He also shows that schools saturated with technology can actually improve socialization and interaction among students and between students and teachers. Technology changes every day, but the basic ways that computers can help us learn remain. For thousands of teachers and parents who have sought creative ways to help children learn with computers, Mindstorms is their bible.
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
In an age where the quality of teacher education programs has been called into question, it is more important than ever that teachers have a fundamental understanding of the principles of human learning, motivation, and development. Theory to Practice: Educational Psychology for Teachers and Teaching is a series for those who teach educational psychology in teacher education programs. At a time when educational psychology is at risk of becoming marginalized, it is imperative that we, as educators, “walk our talk” in serving as models of what effective instruction looks like. Each volume in the series draws upon the latest research to help instructors model fundamental principles of learning, motivation, and development to best prepare their students for the diverse, multidimensional, uncertain, and socially-embedded environments in which these future educators will teach. The inaugural volume, Teaching on Assessment, is centered on the role of assessment in teaching and learning. Each chapter translates current research on critical topics in assessment for educational psychology instructors and teacher educators to consider in their teaching of future teachers. Written for practitioners, the aim is to present contemporary issues and ideas that would help teachers engage in meaningful assessment practice. This volume is important not only because of the dwindling presence of assessment-related instructional content in teacher preparation programs, but also because the policy changes in the last two decades have transformed the meaning and use of assessment in K-12 classrooms. Praise for Teaching on Assessment "This thought-provoking book brings together perspectives from educational psychology and teacher education to examine how assessment can best support student motivation, engagement, and learning. In the volume, editors Nichols and Varier present a set of chapters written by leaders in the field to examine critical questions about how to best prepare teachers to make instructional decisions, understand assessment within the context of learning and motivation theory, and draw on assessment in ways which can meet the needs of diverse learners. Written in a highly accessible language and style, each chapter contains clear takeaway messages designed for educational psychologists, teacher educators, teachers, and pre-service teachers. This book is essential reading for anyone involved in teaching or developing our future teaching professionals." Lois R. Harris, Australian Catholic University "This impressive book provides a wealth of contemporary and engaging resources, ideas and perspectives that educational psychology instructors will find relevant for helping students understand the complexity of assessment decision-making as an essential component of instruction. Traditional assessment principles are integrated with contemporary educational psychology research that will enhance prospective teachers’ decision-making about classroom assessments that promote all students’ learning and motivation. It is unique in showing how to best leverage both formative and summative assessment to boost student engagement and achievement, enabling students to understand how to integrate practical classroom constraints and realities with current knowledge about self-regulation, intrinsic motivation, and other psychological constructs that assessment needs to consider. The chapters are written by established experts who are able to effectively balance presentation of research and theory with practical applications. Notably, the volume includes very important topics rarely emphasized in other assessment texts, including assessment literacy frameworks, diversity, equity, assessment strategies for students with special needs, and data-driven decision making. The book will be an excellent supplement for educational psychology classes or for assessment courses, introducing students to current thinking about how to effectively integrate assessment with instruction." James McMillan, Virginia Commonwealth University.
First released in the Spring of 1999, How People Learn has been expanded to show how the theories and insights from the original book can translate into actions and practice, now making a real connection between classroom activities and learning behavior. This edition includes far-reaching suggestions for research that could increase the impact that classroom teaching has on actual learning. Like the original edition, this book offers exciting new research about the mind and the brain that provides answers to a number of compelling questions. When do infants begin to learn? How do experts learn and how is this different from non-experts? What can teachers and schools do-with curricula, classroom settings, and teaching methodsâ€"to help children learn most effectively? New evidence from many branches of science has significantly added to our understanding of what it means to know, from the neural processes that occur during learning to the influence of culture on what people see and absorb. How People Learn examines these findings and their implications for what we teach, how we teach it, and how we assess what our children learn. The book uses exemplary teaching to illustrate how approaches based on what we now know result in in-depth learning. This new knowledge calls into question concepts and practices firmly entrenched in our current education system. Topics include: How learning actually changes the physical structure of the brain. How existing knowledge affects what people notice and how they learn. What the thought processes of experts tell us about how to teach. The amazing learning potential of infants. The relationship of classroom learning and everyday settings of community and workplace. Learning needs and opportunities for teachers. A realistic look at the role of technology in education.
A surprisingly simple way for students to master any subject--based on one of the world's most popular online courses and the bestselling book A Mind for Numbers A Mind for Numbers and its wildly popular online companion course "Learning How to Learn" have empowered more than two million learners of all ages from around the world to master subjects that they once struggled with. Fans often wish they'd discovered these learning strategies earlier and ask how they can help their kids master these skills as well. Now in this new book for kids and teens, the authors reveal how to make the most of time spent studying. We all have the tools to learn what might not seem to come naturally to us at first--the secret is to understand how the brain works so we can unlock its power. This book explains: Why sometimes letting your mind wander is an important part of the learning process How to avoid "rut think" in order to think outside the box Why having a poor memory can be a good thing The value of metaphors in developing understanding A simple, yet powerful, way to stop procrastinating Filled with illustrations, application questions, and exercises, this book makes learning easy and fun.
