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Motor control and learning 5th edition pdf

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Motor Learning and Performance

From Principles to Application

Fifth Edition

Richard A. Schmidt

Timothy D. Lee

Human Kinetics

3

Library of Congress Cataloging-in-Publication Data

Schmidt, Richard A., 1941- author.

Motor learning and performance : from principles to application / Richard A. Schmidt, Timothy D. Lee. -- Fifth edition.

p. ; cm.

Includes bibliographical references and index.

I. Lee, Timothy Donald, 1955- author. II. Title.

[DNLM: 1. Learning. 2. Motor Activity. 3. Kinesthesis. 4. Psychomotor Performance. BF 295]

BF295

152.3'34--dc23

2013014793

ISBN-10: 1-4504-4361-3 (print)

ISBN-13: 978-1-4504-4361-6 (print)

Copyright © 2014 by Richard A. Schmidt and Timothy D. Lee

Copyright © 2008, 2004, 2000 by Richard A. Schmidt and Craig A. Wrisberg

Copyright © 1991 by Richard A. Schmidt

All rights reserved. Except for use in a review, the reproduction or utilization of this work in any form or by any electronic, mechanical, or other means, now known or hereafter invented, including xerography, photocopying, and recording, and in any information storage and retrieval system, is forbidden without the written permission of the publisher.

Permission notices for material reprinted in this book from other sources can be found on page xvii.

The web addresses cited in this text were current as of June 19, 2013, unless otherwise noted.

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Check Out the Web Study Guide! You will notice a reference throughout this version of Motor Learning and Performance, Fifth Edition to a web study guide. This resource is available to supplement your e-book.

The web study guide offers interactive activities to reinforce key concepts and principles-to-application exercises that allow you to apply concepts to real-world scenarios.

Follow these steps to purchase access to the web study guide:

1. Visit http://tinyurl.com/BuySchmidt5EWebStudyGuide. 2. Click the Add to Cart button and complete the purchase process. 3. After you have successfully completed your purchase, visit the book’s

website at www.HumanKinetics.com/MotorLearningAndPerformance. 4. Click the fifth edition link next to the corresponding fifth edition book

cover. 5. Click the Sign In link on the left or top of the page and enter the e-mail

address and password that you used during the purchase process. Once you sign in, your online product will appear in the Ancillary Items box. Click on the title of the web study guide to access it.

6. Once purchased, a link to your product will permanently appear in the menu on the left. All you need to do to access your web study guide on subsequent visits is sign in to www.HumanKinetics.com/MotorLearningAndPerformance and follow the link!

Click the Need Help? button on the textbook’s website if you need assistance along the way.

6

http://www.HumanKinetics.com/MotorLearningAndPerformance
http://www.HumanKinetics.com/MotorLearningAndPerformance
Dedication Jack A. Adams (1922-2010) was a giant in motor learning research. His passing marks a sad personal loss for us as well as a huge professional loss to motor learning research across the world. This book is dedicated to Jack’s memory in appreciation for all he taught us.

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Contents Dedication

Preface

Student and Instructor Resources

Acknowledgments

Credits

Chapter 1: Introduction to Motor Learning and Performance Why Study Motor Skills? The Science of Motor Learning and Performance Defining Skills Components of Skills Classifying Skills Understanding Performance and Learning Summary

Part I: Principles of Human Skilled Performance

Chapter 2: Processing Information and Making Decisions The Information-Processing Approach Reaction Time and Decision Making Memory Systems Summary

Chapter 3: Attention and Performance What Is Attention? Limitations in Stimulus Identification Limitations in Response Selection Limitations in Movement Programming Decision Making Under Stress Summary

Chapter 4: Sensory Contributions to Skilled Performance

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Sources of Sensory Information Processing Sensory Information Principles of Visual Control Audition and Motor Control Summary

Chapter 5: Motor Programs Motor Program Theory Evidence for Motor Programs Motor Programs and the Conceptual Model Problems in Motor Program Theory: The Novelty and Storage Problems Generalized Motor Program Theory Summary

Chapter 6: Principles of Speed, Accuracy, and Coordination Speed–Accuracy Trade-Offs Sources of Error in Rapid Movements Exceptions to the Speed–Accuracy Trade-Off Analyzing a Rapid Movement: Baseball Batting Accuracy in Coordinated Actions Summary

Chapter 7: Individual Differences The Study of Individual Differences Abilities Versus Skills Is There a General Motor Ability? Abilities and the Production of Skills Prediction and Selection Based on Ability Summary

Part II: Principles of Skill Learning

Chapter 8: Introduction to Motor Learning Motor Learning Defined How Is Motor Learning Measured? Distinguishing Learning From Performance Transfer of Learning Summary

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Chapter 9: Skill Acquisition, Retention, and Transfer Skill Acquisition Skill Retention Skill Transfer Summary

Chapter 10: Organizing and Scheduling Practice Off-Task Practice Considerations Organizing Practice and Rest Variable Versus Constant Practice Blocked Versus Random Practice Summary

Chapter 11: Augmented Feedback Feedback Classifications Functions of Augmented Feedback How Much Feedback to Give When to Give Feedback Summary

Glossary

References

About the Authors

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Preface Most of us feel tremendous excitement, pleasure, and perhaps envy when we watch a close race, match, or performance, focusing on the complex, well- controlled skills evidenced by the players or musicians. In these situations, we marvel at those who must succeed in executing their skill “on the spot”—at how the person with high-level skills is able to excel, sometimes under extreme “pressure” to do so.

This book was written for people who appreciate high-level skilled activity and for those who would like to learn more about how such incredible performances occur. Thus, readers in fields related directly to kinesiology and physical education (such as teaching and coaching) will benefit from the knowledge provided here. But the material extends far beyond these fields and should be relevant for those who study rehabilitation in physical and occupational therapy, as well as for instructors and facilitators of many other areas in which motor skills play an important role, such as music, ergonomics, and the military. The text is intended for beginners in the study of skill and requires little knowledge of physiology, psychology, or statistical methodologies.

The level of analysis of the text focuses on motor behavior—the overt, observable production of skilled movements. Of course, there are many scientific areas or fields of study involved in the understanding of this overt skilled behavior. Any skill is the outcome of processes studied in many different fields, such as neurology, anatomy, biomechanics, biochemistry, and social and experimental psychology; and this text could have focused on any number of these fundamental fields. But the focus of the text is broader than the fundamental fields that support it. The focus is behavioral, with the major emphasis on humans performing skills of various kinds. To be sure, we will talk about these other levels of analysis from time to time throughout the book in an attempt to explain what processes or events occur to support these high-level skills. Therefore this text should be appropriate for courses in elementary motor learning and motor performance in a relatively wide group of scientific areas.

Throughout the text, we construct a conceptual model of human performance. The term “model” is used in a variety of ways in many

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branches of science, and models are found frequently. A model typically consists of a system of parts that are familiar to us; when assembled in a certain way, these parts mimic certain aspects of the system we are trying to understand. One example is the pump-and-pipe model of our circulatory system, in which the heart is represented by a pump and the arteries and veins are pipes of various diameters and lengths. One could actually construct the model (although some models are purely conceptual); such a model could be used in classroom demonstrations or “experiments” on the effects of blood pressure on capillaries of the “hand.”

Our first goal in writing this text was to build a strong, general, conceptual understanding (an overview) of skills. We believe that instructors, coaches, therapists, and trainers, as well as others dealing with the learning or teaching of skills, will profit greatly from such a high-level conceptual understanding of skilled behavior. In striving toward this goal, we have adopted (assumed) the idea that skills can be understood, for the most part, through the use of concepts concerning information and its processing. We set about to build a conceptual model that would capture (or explain) many of the intricacies of skilled motor performance. We begin this process by considering the human as a very simple input–output system; then gradually, as we introduce new topics in the text, we expand the model by adding these new concepts. Gradually, by building on knowledge and concepts presented in earlier parts of the text, we add increasing complexity to the conceptual model. Simply presenting the finished conceptual model would make it very difficult for students to understand, and we hope that the systematic process of constructing the model, assembled with parts as they are presented in the text, forms a logical basis for increasing the model’s complexity. This construction process should make the final version of the model maximally understandable.

Our second goal was to organize the book in the best way to aid student understanding based on our many years of teaching experience. The text is divided into two parts. After the introduction to the study of motor skills in chapter 1, part I, examines how the motor system works by investigating the major principles of human performance and progressively developing a conceptual model of human actions. The focus is mainly on human performance as based on an information-processing perspective; but motor learning cannot be ignored, so it is mentioned briefly in various places. Chapter 2 discusses the nature of information processing, decision making, and movement planning. Chapter 3 considers the concepts of attention and

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memory. Chapter 4 concerns the information received from various sensory sources that is relevant to movement. Chapter 5 examines the processes underlying the production of movement, with particular attention to the role of motor programs. Chapter 6 considers the basic principles of performance that form the “building blocks” of skilled performance—analogous to the fundamental laws of physics. Finally, in chapter 7, the concern shifts to the differences in movement abilities among people and how these differences allow the prediction of success in new situations; differences among components in the conceptual model help in understanding these differences among people. On completion of part I, the student should have a reasonably coherent view of the conceptual and functional properties of the motor system. These principles seem appropriate for maximizing the performance of already learned skills. Part II of the text uses the conceptual model to impart an understanding of human motor learning processes. Much of this discussion uses the terms and concepts introduced in part I. This method works well in our own teaching, probably because motor learning is usually inferred from changes in motor behavior; therefore, it is easy to discuss these changes in terms of the behavioral principles from part I. In this second part, chapter 8 treats some methodological problems unique to the study of learning, such as how and when to measure performance, which also have application to measuring performance in analogous teaching situations. Chapter 9 considers broad issues of learning, retention, and transfer, such as the important role of practice. Chapter 10 concerns the issue of how and when to practice, dealing with the many factors that instructors can control directly to make practice more effective. Finally, chapter 11 deals with the critical topic of feedback, examining what kinds of movement information students need for effective learning, when it should be given, and so on. By the end of the text, readers will have a progressive accumulation of knowledge that, in our experience, provides a consistent view of how skills are performed and learned.

Many real-world examples of motor performance and learning principles are discussed in the main body of the text. In addition, we’ve included Focus on Application sections set off from the main textual materials. Strategically located directly after pertinent discussions of principles, these sections indicate applications to real-world teaching, coaching, or therapy. We wanted to write a text that could be used by performers, teachers, coaches, physical therapists, and other instructors in various fields to enhance human performance in real-world settings. To meet this goal, we have worked to focus the text on the topics most relevant to practical

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application.

As a third goal, we wanted a presentation style that would be simple, straightforward, and highly readable for those without extensive backgrounds in the motor performance area. As a result, the main content does not stress the research and data that contribute to our knowledge of motor skill acquisition and performance. Important points are occasionally illustrated by data from a critical experiment, but the emphasis is on an integrated conceptual knowledge of how the motor system works and how it learns. However, for those who desire a tighter link to the basic data, we have included sections called Focus on Research, which are set off from the main text and describe the important experiments and concepts in detail.

Finally, we demanded that the principles discussed should be faithful to the empirical data and thought in the study area. From decades in doing basic research in motor learning and motor performance, we have developed what we believe to be defensible, coherent, personal viewpoints (conceptual models, if you will) about how skills are performed and learned, and our aim was to present this model to the reader to facilitate understanding. Our viewpoints are based on a large literature of theoretical ideas and empirical data, together with much thought about competing ideas and apparently contradictory research findings. We have tried to write from this perspective as we would tell a story. Every part of the story can be defended empirically, or it would not have been included. Our goal has been to write “the truth,” at least as we currently understand it and as it can be understood with the current level of knowledge. We have included a brief section at the end of each chapter describing additional readings that provide competing viewpoints and additional scientific justifications.

Students will find a range of learning aids within each chapter, including chapter-opening outlines, objectives, and lists of key terms, as well as an end-chapter summary of the activities in the accompanying web study guide and “Check Your Understanding” and “Apply Your Knowledge” questions. Instructors using this text in their courses will find a wealth of updated ancillary materials at www.HumanKinetics.com/MotorLearningAndPerformance, including a presentation package and image bank, instructor guide, and test package.

This fifth edition of Motor Learning and Performance extends the approach used in the previous four editions. As with the previous editions, we have tried to integrate the latest new findings together with the research

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http://http://www.HumanKinetics.com/MotorLearningAndPerformance
and findings that have remained relevant for longer periods of time. But this edition could also be considered quite different as well. In many ways, this fifth edition returns to the approach adopted in the first edition, of providing a theoretical and conceptual basis for motor performance and learning that could be applied as broadly as possible. Since motor learning and performance are probably the most widespread activities that humans from all walks of life experience on a daily basis, our goal was to touch on as many of these applications as possible. The generality and limitations of these principles represent a core of human existence, and we hope that our treatment of them in this book resonates well with each person who reads it.

Richard A. Schmidt

Human Performance Research

Marina del Rey, California

Timothy D. Lee

Department of Kinesiology

McMaster University, Hamilton, Ontario

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Student and Instructor Resources Student Resources

Students, visit the free web study guide, available at www.HumanKinetics.com/MotorLearningAndPerformance. The web study guide has been fully revised for the fifth edition to offer a more focused and interactive set of activities to aid learning. The activities in this study guide will help you to assess and build your understanding of concepts from each chapter of the text as you study.

In each chapter of the web study guide, you will be presented with a series of two to four interactive activities that test your understanding of important concepts. These include matching, multiple-choice, and diagram-based activities. For each chapter, you will be also be presented with a principles-to-application exercise that prompts you to take your knowledge beyond the classroom by using principles of motor control and learning to analyze an activity. There is no single right answer for the principles-to- application problems, but it is important to provide evidence and reasoning to support your ideas. Each principles-to-application exercise includes sample student answers and critiques of those answers to guide you as you develop your analysis. By completing the exercises included in this study guide, you will build your knowledge of important concepts from the textbook and learn to apply that knowledge to real-world situations.

Instructor Resources

The instructor guide, test package, chapter quizzes, presentation package, and image bank are free to course adopters and are accessed at www.HumanKinetics.com/MotorLearningAndPerformance.

Instructor Guide

The instructor guide includes chapter summary notes for preparing lectures and ideas for presenting topics and engaging students in class discussions, as well as practical laboratory activities.

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http://http://www.HumanKinetics.com/MotorLearningAndPerformance
http://http://www.HumanKinetics.com/MotorLearningAndPerformance
Test Package

The test package includes more than 230 true-or-false, multiple-choice, fill- in-the-blank, and short-answer questions that can be used to create exams. The test package is available for download in Respondus and LMS formats as well as in Rich Text Format (.rtf) for use with word processing software.

Chapter Quizzes

New for the fifth edition, these ready-to-use 10-question quizzes help assess students’ comprehension of the most important concepts in each chapter. Chapter quizzes can be imported into learning management systems or be used in RTF format by instructors who prefer to offer a written quiz.

Presentation Package

The presentation package includes more than 230 PowerPoint text slides that highlight material from the text for use in lectures and class discussions. The slides can be used directly in PowerPoint or can be printed to make transparencies or handouts for distribution to students. Instructors can easily add, modify, and rearrange the order of the slides as well as search for images based on key words.

Image Bank

The image bank, included with the presentation package, includes most of the figures, content photos, and tables from the text, sorted by chapter, which can be used to develop a customized presentation.

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Acknowledgments This edition of Motor Learning and Performance owes a debt of gratitude to many people. It was Rainer Martens who first conceptualized the idea, and his encouragement led to the publication of the first edition (Schmidt, 1991). Sincere thanks go to Craig Wrisberg, who coauthored the next three editions (Schmidt & Wrisberg, 2000, 2004, 2008). Over the years the authors have worked with many wonderful editors at Human Kinetics, who made the sometimes tedious process much more enjoyable, for which we are very grateful. For this edition we would especially like to thank Myles Schrag and Kate Maurer for their efforts in seeing this project through to completion. We also thank Liz Sanli for her hard work on the book’s ancillaries and Jasmine Caveness, Marilyn Lomeli, and Dianne Hopkins for their contributions to the task of copyediting and several other efforts. And lastly, we thank our wives, Gwen Gordon and Laurie Wishart, for their understanding and support of the work that went into not only producing this book, but all of our various endeavors.

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Credits Figures

Figure 2.6 Reprinted, by permission, from R.A. Schmidt and T.D. Lee, 2011, Motor control and learning: A behavioral emphasis, 5th ed. (Champaign, IL: Human Kinetics). 65; Data from Merkel 1885.

Figure 2.7 Reprinted, by permission, from R.A. Schmidt and T.D. Lee, 2011, Motor control and learning: A behavioral emphasis, 5th ed. (Champaign, IL: Human Kinetics). 65; Data from Merkel 1885.

Figure 2.8 Reprinted, by permission, from R.A. Schmidt and T.D. Lee, 2011, Motor control and learning: A behavioral emphasis, 5th ed. (Champaign, IL: Human Kinetics). 70.

Figure 2.9 Reprinted, by permission, from J.A. Adams and S. Dijkstra, 1966, “Short-term memory for motor responses,” Journal of Experimental Psychology 71: 317.

Figure 3.3 Reprinted from D.J. Simons and C.F. Chabis, 1999, “Gorillas in our midst: Sustained inattentional blindness for dynamic events,” Perception 28: 1059-1074. By permission of D.J. Simons and C.F. Chabis.

Figure 3.5 Part a reprinted, by permission, from R.A. Schmidt and T.D. Lee, 2011, Motor control and learning: A behavioral emphasis, 5th ed. (Champaign, IL: Human Kinetics), 108; part b reprinted, by permission, from R.A. Schmidt and T.D. Lee, 2011, Motor control and learning: A behavioral emphasis, 5th ed. (Champaign, IL: Human Kinetics), 110; Data from Davis 1959.

Figure 3.7 Reprinted from M.I. Posner and S.W. Keele, 1969, Attentional demands of movement. In Proceedings of the 16th Congress of applied physiology (Amsterdam, Amsterdam: Swets and Zeitlinger). By permission of M.I. Posner.

Figure 3.8 Reprinted, by permission, from R.A. Schmidt and T.D. Lee,

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2011, Motor control and learning: A behavioral emphasis, 5th edition. (Champaign, IL: Human Kinetics). Data from Weinberg and Ragan 1978.

Figure 4.7 Reprinted, by permission, from D.N. Lee and E. Aronson, 1974, “Visual proprioceptive control of standing in human infants,” Perception & Psychophysics 15: 529-532.

Figure 4.11 Reprinted, by permission, from T.J. Ayres, R.A. Schmidt et al., 1995, Visibility and judgment in car-truck night accidents. In Safety engineering and risk analysis--1995, edited by D.W. Pratt (New York: The American Society of Mechanical Engineers), 43-50.

Figure 5.3 Reprinted with permission from Research Quarterly for Exercise and Sport, Vol.24, 22-32, Copyright 1953 by the American Alliance for Health, Physical Education, Recreation and Dance, 1900 Association Drive, Reston, VA 20191.

Figure 5.4 Reprinted, by permission, from R.A. Schmidt and T.D. Lee, 2011, Motor control and learning: A behavioral emphasis, 5th edition. (Champaign, IL: Human Kinetics), 183.

Figure 5.5 Part a reprinted, by permission, from R.A. Schmidt and T.D. Lee, 2011, Motor control and learning: A behavioral emphasis, 5th edition. (Champaign, IL: Human Kinetics), 195; part b reprinted, by permission, from R.A. Schmidt and T.D. Lee, 2011, Motor control and learning: A behavioral emphasis, 5th edition. (Champaign, IL: Human Kinetics), 195; Data from Slater-Hammel 1960.

Figure 5.6 Reprinted from W.J. Wadman, 1979, “Control of fast goal- directed arm movements,” Journal of Human Movement Studies 5: 10. By permission of W.J. Wadman.

Figure 5.8 Adapted from T.R. Armstrong, 1970, Training for the production of memorized movement patterns: Technical report no. 26 (Ann Arbor, MI: University of Michigan, Human Performance Center), 35. By permission of the Department of Psychology, University of Michigan.

Figure 5.9a and b Reprinted, by permission, from R.A. Schmidt and T.D. Lee, 2011, Motor control and learning: A behavioral emphasis, 5th edition. (Champaign, IL: Human Kinetics), 212.

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Figure 5.10a and b Reprinted, by permission, from D.C. Shapiro et al., 1981, “Evidence for generalized motor programs using gait-pattern analysis,” Journal of Motor Behavior 13: 38.

Figure 5.11 Adapted, by permission, from J.M. Hollerbach, 1978, A study of human motor control through analysis and synthesis of handwriting. Doctoral dissertation, (Cambridge, MA: Massachusetts Institute of Technology).

Figure 5.12 Reprinted from M.H. Raibert, 1977, Motor control and learning by the state-space model: Technical report no. A1-TR-439 (Cambridge, MA: Artificial Intelligence Laboratory, Massachusetts Institute of Technology), 50. By permission of M.H. Raibert.

Figure 6.1 Adapted from Categories of human learning, A.W. Melton (Ed.), P.M. Fitts, Perceptual-motor skills learning, categories of human learning pg. 258.

Figure 6.2 Reprinted, by permission, from R.A. Schmidt and T.D. Lee, 2011, Motor control and learning: A behavioral emphasis, 5th ed. (Champaign, IL: Human Kinetics), 226. Data from Fitts 1954.

Figure 6.3a and b Adapted from P.M. Fitts, 1954, “The information capacity of the human motor system in controlling the amplitude of movement,” Journal of Experimental Psychology 47: 381-391.

Figure 6.4 Reprinted, by permission, from R.A. Schmidt et al., 1979, “Motor-output variability: A theory for the accuracy of rapid motor acts,” Psychological Review 86: 425. Copyright © 1979 by the American Psychological Association.

Figure 6.5 Reprinted, by permission, from R.A. Schmidt et al., 1979, “Motor-output variability: A theory for the accuracy of rapid motor acts,” Psychological Review 86: 425. Copyright © 1979 by the American Psychological Association.

Figure 6.8 Reprinted, by permission, from R.A. Schmidt and D.E. Sherwood, 1982, “An inverted-U relation between spatial error and force requirements in rapid limb movements: Further evidence for the impulse- variability model,” Journal of Experimental Psychology: Human Perception and Performance 8: 165. Copyright © 1982 by the American

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Psychological Association.

Figure 6.9 Reprinted, by permission, from R.A. Schmidt and T.D. Lee, 2011, Motor control and learning: A behavioral emphasis, 5th ed. (Champaign, IL: Human Kinetics), 238.

Figure 6.12 Reprinted, by permission, from P.A. Bender, 1987, Extended practice and patterns of bimanual interference. Unpublished doctoral dissertation (Los Angeles, CA: University of Southern California).

Figure 6.13a and b Reprinted, by permission, from T.D. Lee et al., 2008, “Do expert golfers really keep their heads still while putting?” Annual Review of Golf Coaching 2: 135-143.

Figure 6.14 Reprinted from Physics Letters A, Vol.118, J.A.S. Kelso, J.P. Scholz, and G. Schöner, “Nonequilibrium phase transitions in coordinated biological motion: Critical fluctuations,” pg. 281, copyright 1986, with kind permission of Elsevier.

Table 7.2 by permission, from J.N. Drowatzky and F.C. Zuccato, 1967, “Interrelationships between selected measures of static and dynamic balance,” Research Quarterly 38: 509-510.

Figure 7.4 Reprinted, by permission, from E.A. Fleishman and W.E. Hempel, 1955, “The relation between abilities and improvement with practice in a visual discrimination task,” Journal of Experimental Psychology 49: 301-312. Copyright © 1955 by the American Psychological Association.

Figure 8.2 Reprinted, by permission, from J.A. Adams, 1952, “Warm up decrement in performance on the pursuit-rotor,” American Journal of Psychology 65(3): 404-414.

Figure 8.3 Reprinted, by permission, from C.J. Winstein and R.A. Schmidt, 1990, “Reduced frequency of knowledge of results enhances motor skill learning,” Journal of Experimental Psychology: Learning, Memory and Cognition 16: 677-691. Copyright © 1990 by the American Psychological Association.

Figure 8.4 Adapted, by permission, from H.P. Bahrick, P.M. Fitts, and G.E. Briggs, 1957, “Learning curves—facts or artifacts?” Psychological

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Bulletin 54: 256- 268. Copyright © 1957 by the American Psychological Association.

Figure 9.3 Adapted, by permission, from R.A. Schmidt and T.D. Lee, 2011, Motor control and learning: A behavioral emphasis, 5th ed. (Champaign, IL: Human Kinetics), 451; Adapted from MacKay, 1976, personal communication.

Figure 9.4 Reprinted, by permission, from E. Neumann and R.B. Ammons, 1957, “Acquisition and long term retention of a simple serial perception motor skill,” Journal of Experimental Psychology 53: 160. Copyright © 2011 by the American Psychological Association.

Figure 9.5 Reprinted from E.A. Fleishman and J.F. Parker, 1962, “Factors in the retention and relearning of perceptual motor skill,” Journal of Experimental Psychology 64: 218. Copyright © 1962 by the American Psychological Association.

Figure 10.1 Adapted, by permission, from B.A. Boyce, 1992, “Effects of assigned versus participant-set goals on skill acquisition and retention of a selected shooting task,” Journal of Teaching in Physical Education 11(2): 227.

Figure 10.2 Reprinted, by permission, from R. Lewthwaite and G. Wulf, 2010, “Social-comparative feedback affects motor skill learning,” Quarterly Journal of Experimental Psychology 63: 738-749.

Figure 10.3 Reprinted, by permission, from G. Wulf, 2003, “Attentional focus on supra-postural tasks affects balance learning,”Quarterly Journal of Experimental Psychology 56A: 1191-1211.

Figure 10.4 Reprinted, by permission, from D.M. Ste-Marie et al., 2012, “Observation interventions for motor skill learning and performance: An applied model for the use of observation,” International Review of Sport and Exercise Psychology 5(2): 145-176.

Figure 10.6 Reprinted, by permission, from R.A. Schmidt and T.D. Lee, 2011, Motor control and learning: A behavioral emphasis, 5th ed. (Champaign, IL: Human Kinetics), 365. Data from Baddeley and Longman 1978.

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Figure 10.7 Reprinted from L.E. Bourne and E.J. Archer, 1956, “Time continuously on target as a function of distribution of practice,” Journal of Experimental Psychology 51: 27.

Figure 10.10 Reprinted, by permission, from K.M. Keetch, R.A. Schmidt, T.D. Lee, and D.E. Young, 2005, “Especial skills: Their emergence with massive amounts of practice,” Journal of Experimental Psychology: Human Perception and Performance 31: 970-978. Copyright © 2005 by the American Psychological Association.

Figure 10.11 Adapted, by permission, from J.B. Shea and R.L. Morgan, 1979, “Contextual interference effects on the acquisition, retention, and transfer of a motor skill,” Journal of Experimental Psychology: Human Learning and Memory 5: 179-187. Copyright © 1979 by the American Psychological Association.

Figure 10.12 Reprinted with permission from Research Quarterly for Exercise and Sport, vol. 68, pg. 103. Copyright 1997 by the American Alliance for Health, Physical Education, Recreation and Dance, 1900 Association Drive, Reston, VA 20191.

Figure 11.3 Reprinted with permission from Research Quarterly for Exercise and Sport, Vol. 78, pg. 43, Copyright 2007 by the American Alliance for Health, Physical Education, Recreation and Dance, 1900 Association Drive, Reston, VA 20191.

Figure 11.4 Adapted by permission. ©Bob Scavetta. Any adaptation or reproduction of the “1.5 Seconds of Thought” is forbidden without the written permission of the copyright holder.

Figure 11.5 Reprinted, by permission, from R.A. Schmidt and T.D. Lee, 2011, Motor control and learning: A behavioral emphasis, 5th ed. (Champaign, IL: Human Kinetics), 401; Data from Kernodle and Carlton 1992.

Figure 11.6 Reprinted, by permission, from C.J. Winstein and R.A. Schmidt, 1990, “Reduced frequency of knowledge of results enhances motor skill learning,” Journal of Experimental Psychology: Learning, Memory, and Cognition 16: 910. Copyright © 1990 by the American Psychological Association.

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Figure 11.8 Reprinted from Human Movement Science, Vol 9, R.A. Schmidt, C. Lange, and D.E. Young, “Optimizing summary knowledge of results for skill learning,” p. 334, copyright 1990, with permission of Elsevier.

Figure 11.9 Reprinted, by permission, from W. Yao, M.G. Fischman, and Y.T. Wang, 1994, “Motor skill acquisition and retention as a function of average feedback, summary feedback, and performance variability,” Journal of Motor Behavior 26: 273-282.

Figure 11.12 Adapted, by permission, from Schmidt and Lee, 2011, Motor control and learning: A behavioral emphasis, 5th ed. (Champaign, IL: Human Kinetics), 387. Adapted from Armstrong 1970.

Figure 11.13 Reprinted, by permission, from S.P. Swinnen et al., 1990, “Information feedback for skill acquisition: instantaneous knowledge of results degrades learning,” Journal of Experimental Psychology: Learning, Memory, and Cognition 16: 712. Copyright © 2011 by the American Psychological Association.

Figure 11.14 Reprinted from M.A. Guadagnoli and R.M. Kohl, 2001, “Knowledge of results for motor learning: Relationship between error estimation and knowledge of results frequency,” Journal of Motor Behavior, 33: 217-224.

Photos

Dedication photo Courtesy of Jack Adams

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Chapter 1 dec. photo 1 © Jerome Brunet/ZUMA Press

Focus on Research 1.1 Reprinted, by permission, from Weinberg, R.S., and Gould, D. 12003, Foundations of Sport and Exercise Psychology, Champaign, IL: Human Kinetics, 10.

Chapter 1 dec. photo 2 © Lee Mills/Action Images/Icon SMI

Chapter 1 dec. photo 3 © Human Kinetics/J. Wiseman, reefpix.org

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Chapter 2 opening page © Cliff Welch/Icon SMI

Chapter 2 dec. photo 3 © Chris Ison/PA Archive/Press Association Images

Figure 3.3 Reprinted from D.J. Simons and C.F. Chabis, 1999, "Gorillas in our midst: Sustained inattentional blindness for dynamic events," _Perception_ 28: 1059-1074. By permission of D.J. Simons and C.F. Chabis.

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Chapter 3 dec. photo 3 © Jim West/Age Fotostock

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Figure 4.7 Reprinted from D.N. Lee and E. Aronson, 1974, "Visual proprioceptive control of standing in human infants," _Perception & Psychophysics_ 15: 529-532. By permission of D.N. Lee.

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Chapter 9 opening page Courtesy Timothy D. Lee.

Chapter 9 dec. photo 3 © George Shelley/Age Fotostock

Chapter 9 dec. photo 4 Courtesy Richard A. Schmidt

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Chapter 1 Introduction to Motor Learning

and Performance

How Skills Are Studied

Chapter Outline Why Study Motor Skills?

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The Science of Motor Learning and Performance Defining Skills Components of Skills Classifying Skills Understanding Performance and Learning Summary

Chapter Objectives Chapter 1 provides an overview of research in human motor skills with particular reference to their study in motor learning and performance. This chapter will help you to understand

the scientific method in skills research, different taxonomies used to classify skills, common variables used to measure motor performance, and the rationale for developing a conceptual model of motor performance.

Key Terms absolute constant error (|CE|) absolute error (AE) closed skill constant error (CE) continuous skill discrete skill open skill root-mean-square error (RMSE) serial skill skill tracking variable error (VE)

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In 2012, a petite American girl named Gabrielle (“Gabby”) Douglas captivated the sport world with her feats in women's gymnastics at the London Olympic Games, and, almost instantly, she became a role model for many young girls who suddenly wanted to learn gymnastics. The “flying squirrel,” as she is fondly called by her teammates, won the gold medal in the women’s all-around competition—arguably the pinnacle in women’s gymnastics. In the 1980s Jim Knaub, who had lost the use of his legs in an accident, won several important marathons in the wheelchair division, earning our heartfelt respect. From the 1970s into the ’90s, David Kiley earned the title “King of Wheelchair Sports” by (a) winning five gold medals in the 1976 Paralympic Games in Canada; (b) climbing the highest mountain in Texas; (c) playing on the United States men's wheelchair basketball team five times; and (d) competing at the highest level in tennis, racquetball, and skiing. And, since the Woodstock music festival in 1969, Johnny Winter, who is arguably (at least according to the second author) the world’s best guitarist, continues to amaze audiences with his skills and versatility. These and countless other examples indicate that skills are a critical part of human existence. How people can perform at such high levels, how such skills are developed, and how you can develop some approximation of these skills in yourself, your children, or your students— all of these questions generate fascination, encouraging further learning about human movement.

A description of the study of motor performance and learning starts here. The overview presented in this chapter introduces the concept of skill and discusses various features of its definition. The chapter then gives examples of skill classification schemes important for later applications. Finally, to help you understand skills effectively using this book, the logic behind the book’s organization is described: first, the principles and processes underlying skilled performance, followed by how such capabilities can be developed with practice.

The remarkable human capability to perform skills is a critical feature of our very existence. It is almost uniquely human, although various animals relatively high on the evolutionary scale can be trained to produce what you might call skilled behaviors (e.g., circus dogs doing somersaults, bears riding bicycles). Without the capacity for skilled performance, we could not type the page we are preparing now and you could not read it. And for students involved in physical education and kinesiology, coaching, physical (or speech or occupational) therapy, chiropractic, medicine, or human

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factors and ergonomics, here is the opportunity to learn about the fundamentals of a wide variety of sports and athletic endeavors, music, and simply ordinary everyday actions that are so strongly fascinating and exciting. Human skills take many forms, of course—from those that emphasize the control and coordination of our largest muscle groups in relatively forceful activities like soccer or tumbling, to those in which the smallest muscle groups must be tuned precisely, as in typing or repairing a watch. This text generally focuses on the full range of skilled behavior because it is useful to understand that many common features underlie the performance of skills associated with industrial and military settings, sport, the reacquisition of movement capabilities lost through injuries or stroke, or simply the everyday activities of most people.

Most humans are born with the capability to produce many skills, and only some maturation and experience is necessary in order to produce them in nearly complete form. Walking and running, chewing, balancing, and avoiding painful stimuli are some examples of these relatively innate behaviors. But imagine what simple and uninteresting creatures we would be if these inherited actions were all that we could ever do. All biological organisms have the remarkable facility to profit from their experiences, to learn to detect important environmental features (and to ignore others), and to produce behaviors that were not a part of their original capabilities. Humans seem to have the most flexibility of all, which allows gains in proficiency for occupations as chemists or computer programmers, for competition in music or athletics, or simply for conducting daily lives more efficiently. Thus, producing skilled behaviors and the learning that leads to their development are tightly intertwined in human experience. This book is about both of these aspects of skills—skilled human performance and human learning.

This book is not about skills in which the degree of success is determined by deciding which of many already learned actions the performer is to do. When the laboratory rat learns to press a bar at the presentation of a sound, the rat is not learning how to press the bar; rather, the animal is learning when to make this already learned bar-pressing action. As another example, in the card game of poker, it does not matter in what fashion the various cards are played (i.e., moved). What matters is cognitive decision making about which card to play and when to do it. The study of these kinds of decision-making processes falls mainly into fields such as experimental psychology and cognitive neuroscience, and these processes are

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deliberately not included here.

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Johnny Winter, who is (according to this book’s second author) the world’s best guitarist, demonstrating just one of his nearly unlimited variety of motor

skills.

Why Study Motor Skills? Because skills make up such a large part of human life, scientists and educators have been trying for centuries to understand the determinants of skills and the factors that affect their performance. The knowledge gained is applicable to numerous aspects of life. Important points apply to the instruction of skills, where methods for efficient teaching and effective carryover to life situations are primary concerns. There is also considerable applicability for improving high-level performances, such as sport, music, and surgical skills. Of course, much of what coaches and music and physical education teachers do during their professional activities involves, in one way or another, skills instruction. The practitioners who understand these skill-related processes most effectively undoubtedly have an advantage when their “subjects” begin their trained-for activities.

Other application areas can be emphasized as well. There are many applications in training skills for industry, where effective job skills can mean success in the workplace and can be major determinants of satisfaction both with the job and with life in general. Teaching job skills most effectively, and determining which of a large number of individuals are best suited to particular occupations, are common situations in which knowledge about skills can be useful in industry. Usually these applications

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are considered within human factors (ergonomics).The principles also apply to physical therapy and occupational therapy settings as well, where the concern is for the (re)learning and production of movements that have been lost through head or spinal cord injury, stroke, birth defects, and the like. Although all these areas may be different and the physical capabilities of the learners may vary widely, the principles that lead to successful application are generally the same.

The Science of Motor Learning and Performance

It is not uncommon that as an area of interest grows, the systematic study of the principles involved also develops. Motor learning and performance is no different, in that a science has emerged that allows the formalization of terms and concepts for others to use. When we use the word “science,” what do we mean?

The concept of a science implies several things: (a) the active use of theory and hypothesis testing to further our knowledge; (b) a certain “infrastructure” that involves books and journals, scientific organizations that deal with both the fundamental aspects of the science and ways to apply the knowledge to real-world situations, and granting agencies to provide funds for research; and, of course, (c) the existence of courses of study of the area in universities and colleges.

Theories and Hypotheses

Certainly at the heart of every science are theories that purport to explain how things work. A theory is a human-made structure whose purpose is to explain how various phenomena occur. The theorist conjures up what are called hypothetical constructs—imaginary elements, or pieces, that interact in various ways in the theory. The theorist then describes the ways in which the hypothetical constructs interact with each other so as to explain some empirical phenomenon. Then, using logical deduction, scientists determine certain predictions that the theory makes in its current form. These predictions form the basis of hypotheses that can be tested, typically in the laboratory. These hypotheses take the form of statements such as “If I ask learners to practice under condition x, then learning should be enhanced.”

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Theories are typically tested by doing experiments, which determine whether or not the hypothesis predicts what happens. In the field of motor learning and performance, these experiments typically take the form of having at least two groups of subjects randomly assigned to experimental treatments, with one group performing a task under condition x (as in the example just mentioned) and the other group performing under some other conditions that are reasonably well understood (sometimes called a “control condition”). If, in this example, the group practicing under condition x outperforms the group in the control condition, then we say that the hypothesis is supported. However, a given theory might predict an outcome that would make sense for several different theories, so an experiment that supports a hypothesis is not always the strongest type of evidence. What is usually far stronger is if the results come out contrary to the prediction; this leads to the logical inference that the theory must be incorrect, allowing us to reject one of the possible theories. This is so because a theory cannot “survive” for long if something predicted from it turns out not to be the case. Because of this difference in the power of the ways in which hypotheses are tested, scientists tend to search out predictions from a theory that might not hold if tested in the laboratory.

What Kinds of Skills Have Been Studied?

The science of motor learning and performance has been used to study many varieties of skills. In the very beginning (research and writing done in the early 1900s, or perhaps slightly before), two types of investigations can be identified: (a) investigations of relatively complex, high-level skills such as telegraphy and typing (e.g., Bryan & Harter, 1897, 1899), and (b) studies by biologists and physiologists concerning the fundamental mechanisms of neural control of muscle, muscle force production (Fullerton & Cattell, 1892), and the study of nerves and the nervous system (Fritsch & Hitzig, 1870; Sherrington, 1906).

Focus on Research 1.1

Franklin M. Henry, Father of Motor Behavior Research

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Franklin M. Henry (1904-1993)

Before World War II and during the 1950s and 1960s when much effort was directed at military skills such as pilotry, most of the research in movement behavior and learning was done by experimental psychologists using relatively fine motor skills. Little effort was devoted to the gross motor skills that would be applicable to many sports. Franklin M. Henry, trained in experimental psychology but working in the Department of Physical Education, at the University of California Berkley, was filling this gap with a new tradition of laboratory experimentation that started an important new direction in research on movement skills. He studied gross motor skills, with performances intentionally representative of those seen on the playing fields and in gymnasiums. But he used laboratory tasks——that enabled the rigorous study of these skills employing methods analogous to those used in experimental psychology. He examined a number of research problems, such as the differences among people, practice scheduling, the mathematical shapes of performance curves, and the roles of fatigue and rest in performance.

Henry’s influence on the fields of physical education and kinesiology was widespread by the 1970s and 1980s.

Defining Skills As widely represented and diverse as skills are, it is difficult to define them

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in a way that applies to all cases. Guthrie (1952) provided a definition that captures most of the critical features of skills that we emphasize here. He defined skill as “the ability to bring about some end result with maximum certainty and minimum outlay of energy, or of time and energy” (p. 136). Next, we consider some of the important components (or features) of this definition.

First, performing skills implies some desired environmental goal, such as holding a handstand in gymnastics or being able to walk again after a stroke. Skills are usually thought of as different from movements, which do not necessarily have any particular environmental goal, such as idly wiggling one’s little finger. Of course, skills consist of movements because the performer could not achieve an environmental goal without making at least one movement.

Second, to be skilled implies meeting this performance goal, this “end result,” with maximum certainty. For example, while playing darts a player makes a bull's-eye. But this by itself does not ensure that he is a skilled darts player, because this result was achieved without very much certainty. Such an outcome could have been the result of one lucky throw in the midst of hundreds of others that were not so lucky. To be considered “skilled” requires that a person produce the skill reliably, on demand, without luck playing a very large role. This is one reason why people value so greatly the champion athlete who, with but one chance and only seconds remaining at the end of a game, makes the goal that allows the team to win.

Third, a major feature in many skills is the minimization, and thus conservation, of the energy required for performance. For some skills this is clearly not the goal, as in the shot put, where the only goal is to throw the maximum distance. But for many other skills the minimization of energy expenditure is critical, allowing the marathon runner to hold an efficient pace or allowing the wrestler to save strength for the last few minutes of the match. We evolved to walk as we do, in part, because our walking style minimizes energy expenditure for walking a given distance. This minimum- energy notion applies not only to the physiological energy costs but also to the psychological, or mental, energy required for performance. Many skills have been learned so well that the performers hardly have to pay attention to them, freeing their cognitive processes for other features of the activity, such as strategy in basketball or expressiveness in dance. A major contributor to the efficiency of skilled performance is, of course, practice, with learning

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and experience leading to the relatively effortless performances so admired in highly skilled people.

Finally, another feature of many skills is for highly proficient performers to achieve their goals in minimum time. Many skills have this as the only goal, such as a swimming race. Minimizing time can interact with the other skill features mentioned, however. Surgeons who conduct invasive surgery need to work quickly to minimize the opportunity for infections to enter the body. Yet surgeons obviously need to work carefully, too. Speeding up performance often results in imprecise movements that have less certainty in terms of achieving their environmental goals. Also, increased speed generates movements for which the energy costs are sometimes higher. Thus, understanding skills involves optimizing and balancing several skill aspects that are important to different extents in different settings. In sum, skills generally involve achieving some well-defined environmental goal by

maximizing the certainty of goal achievement, minimizing the physical- and mental-energy costs of performance, and minimizing the time used.

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To be skilled implies that a person can produce an end result with a high degree of certainty. For example, an expert darts player can consistently

throw the dart close to his target.

Components of Skills The elegant performance of the skilled dancer and the artistic talents of an expert sculptor may appear simple, but the performance goals actually were realized through a complex combination of interacting mental and motor processes. For example, many skills involve considerable emphasis on sensory–perceptual factors, such as detecting that a tennis opponent is going to hit a shot to your left or that you are rapidly approaching a car that has suddenly stopped on the road ahead of you. Often, sensory factors require the split-second analysis of patterns of sensory input, such as discerning that the combined movements of an entire football team indicate that the play will be a running play to the left side. These perceptual events lead to decisions about what to do, how to do it, and when to do it. These decisions are often a major determinant of success. Finally, of course, skills typically depend on the quality of movement generated as a result of these decisions. Even if the situation is correctly perceived and the response decisions are appropriate, the performer will not be effective in meeting the environmental goal if she executes the actions poorly.

These three elements are critical to almost any skill:

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Perceiving the relevant environmental features Deciding what to do and where and when to do it to achieve the goal Producing organized muscular activity to generate movements that achieve the goal

The movements have several recognizable parts. Postural components support the actions; for instance, the arms and hands of a surgeon need to be supported by a stable “platform” in order to perform accurately. Body transport, or locomotion, components move the body toward the point where the skill will take place, as in carrying a package of shingles up a ladder to place on the roof of a house.

It is interesting, but perhaps unfortunate, that each of these skill components seems to be recognized and studied in isolation from the others. For example, sensory factors in perception are studied by cognitive psychologists, scientists interested in (among other things) the complex information-processing activities involved in seeing, hearing, and feeling. Sometimes these factors are in the realm of psychophysics, the branch of psychology that examines the relationship between objective physical stimuli (e.g., vibration intensity) and the subjective sensations these stimuli create when perceived (loudness). Factors in the control of the movement itself are typically studied by scientists in the neurosciences, cognitive psychology, biomechanics, and physiology. Skill learning is studied by yet another group of scientists in kinesiology and physical education, in experimental or educational psychology, or in the field of human factors and ergonomics. A major problem for the study of skills, therefore, is the fact that the several components of skill are studied by widely different groups of scientists, often with little overlap and communication among them.

All of these various processes are present in almost all motor skills. Even so, we should not get the idea that all skills are fundamentally the same. In fact, the principles of human performance and learning depend to some extent on the kind of movement skill to be performed. So, the ways in which skills have been classified are discussed next.

Classifying Skills There are several skill classification systems that help organize the research findings and make application somewhat more straightforward. These are

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presented in the following sections.

Open and Closed Skills

One way to classify movement skills concerns the extent to which the environment is stable and predictable throughout performance. An open skill is one for which the environment is variable and unpredictable during the action. Examples include most team sports and driving a car in traffic where it is difficult to predict the future moves of other people. A closed skill, on the other hand, is one for which the environment is stable and predictable. Examples include swimming in an empty lane in a pool and drilling a hole in a block of wood. These “open” and “closed” designations actually mark only the end points of a continuum, with the skills lying in between having varying degrees of environmental predictability or variability (see Gentile, 2000, for a fuller discussion).

This classification points out a critical feature for skills, defining the performer's need to respond to moment-to-moment variations in the environment. It thus brings in the subprocesses associated with perception, pattern recognition, and decision making (usually with the need to perform these processes quickly) so the action can be tailored to the environment. These processes are arguably minimized in closed skills, where the performer can evaluate the environmental demands in advance without time pressure, organize the movement in advance, and carry it out without needing to make rapid modifications as the movement unfolds. These features are summarized in table 1.1.

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Discrete, Continuous, and Serial Skills

A second scheme for classifying skills concerns the extent to which the movement is an ongoing stream of behavior, as opposed to a brief, well- defined action. At one end of this dimension is a discrete skill, which usually has an easily defined beginning and end, often with a very brief duration of movement, such as throwing a ball, firing a rifle, or turning on a light switch. Discrete skills are particularly important in both sport and daily actions, especially considering the large number of discrete hitting, kicking, and throwing skills that make up many sport activities, as well as everyday skills of fastening buttons, writing your signature, and tying your shoelaces. Discrete skills often result in a measured outcome score, which can be combined with other scores to result in several types of “error” scores, discussed in Focus on Research 1.2 and 1.3.

At the other end of this dimension is a continuous skill , which has no particular beginning or end, the behavior flowing on for many minutes, such as swimming and knitting. As discussed later, discrete and continuous skills can be quite different, requiring different processes for performance and demanding that they be taught somewhat differently as a result.

One particularly important continuous skill is tracking, in which the performer's limb movements control a lever, a wheel, a handle, or some other device to follow the movements of some target-track. Steering a car involves tracking, with steering wheel movements made so the car follows the track, defined by the roadway. Tracking movements are very common in real-world skills situations, and much research has been directed to their performance and learning. Tracking tasks are sometimes scored using a particular error score, called root-mean-square error (RMSE) presented in detail in Focus on Research 1.3, “Error Scores in Continuous Tasks.”

Between the polar ends of the discrete-continuous-skill continuum is the serial skill, which is often thought of as a group of discrete skills strung together to make up a new, more complicated skilled action. See table 1.2

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for a comparison summary. Here the word “serial” implies that the order of the elements is usually critical for successful performance. Shifting car gears is a serial skill, with three discrete shift lever action elements (along with accelerator and clutch elements) connected in sequence to create a larger action. Other examples include performing a gymnastics routine and most types of cooking. Serial skills differ from discrete skills in that the movement durations tend to be somewhat longer, yet each component retains a discrete beginning and end. One view of learning serial skills suggests that the individual skill elements present in early learning are somehow combined to form one larger, single element that the performer controls almost as if it were truly discrete in nature (e.g., the smooth, rapid way a gymnast shifts from one maneuver to another on the rings).

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Swimming in an empty pool lane is an example of a closed, continuous skill.

Focus on Research 1.2

Error Scores in Discrete Tasks

Quite frequently in research, we are called on to generate a method for computing an accuracy score for a given subject who was attempting a series of trials on a test requiring accuracy, often involving discrete tasks. As we shall see here, there are various ways to do it.

Assume that you are testing subjects on a throwing task, in which subjects have to throw a ball exactly 50 ft away from where they are standing. Two hypothetical subjects perform this task for five trials, and the following are the results:

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Which of these two subjects was more skillful in this task? The problem here is to generate a single number that accurately reflects their skill in the task (a throwing accuracy “score”), based on those five throwing trials. Several candidate measures are possible.

Constant Error (CE)

The most obvious way to determine which subject was more accurate is to compute the error deviation of each throw, relative to the target, and then calculate the average of these error deviations. For example, on trial 1, Chester’s error score was -4 (his throw was 46 ft, and thus, 4 ft short of the target). The error score on the second trial was +2 (his 52-ft throw as 2 ft too far). After the error scores for each trial are computed the mean can then be calculated to determine the average error deviation. This is termed the subjects’ average constant error. The interpretation is that Chester tended to overthrow the 50 ft target by 0.4 ft; John-Lee tended to underthrow the target by 2.6 ft.

The formula for constant error is

CE = [Σ (X i − T) / N]

where: Σ = the “sum of,” i = trial number, X i = score for the ith trial, T = the target distance, and N = the number of trials.

Absolute Error (AE)

Another relatively obvious way to combine the scores into a single number is to consider the absolute value (i.e., with the sign ignored or removed) of the error on each trial, and take the average of those error scores for the various trials. For example, for Chester the first trial has an error of −4 ft; when we take the absolute value, the first trial has an absolute error of 4 ft; the second trial has an error of +2

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ft, whose absolute value is 2. If we do this procedure for the remainder of the trials for Chester, and all the trials for John-Lee, the computed average absolute error for Chester is 6.4; for John-Lee it is 4.2. Here, with the direction of the errors being disregarded, the interpretation is that Chester was off-target more than was John-Lee.

The formula for average absolute error (AE) is

AE = [Σ (|X i − T|) / N]

where: Σ, i, X, T, and N are defined as before for constant error, and the vertical bars (|) mean “absolute value of.”

Variable error (VE)

The third measure of skill is actually a measure of the subject’s inconsistency—that is, how different each individual score was in comparison to his average (CE) score. To compute variable error (VE), we square the difference between each trial’s error score and the subject’s own constant error [(X i − CE)

2], sum those over all of the trials, and divide by N. Now, since these are squared values, we return them to their original state by computing the square root of this value.

In this example, for Chester’s first trial, the difference between X 1 and Chester’s average CE (which was +0.4) is [(-4 – (+0.4)] = -4.4 ft, which, when squared, is 19.36 ft. For the second trial, the difference between X 2 and Chester’s average CE is [(+2) – (+0.4)] = 1.6 ft, which, when squared, is 2.56 ft. Now do the same thing for trials 3, 4, and 5; add up all five squared differences; divide this number by N = 5; then take the square root of that number; and you finally have VE. The score is interpreted as the inconsistency in responding, that is, how variable the performance is about the subject’s own CE. Of course when computing the value for John- Lee, we would use his CE (which was -2.6) in the computations. The computed VE score for Chester was 7.3 ft, and for John-Lee the VE was 4.5 ft. The interpretation is that even though Chester’s average throw was closer to the goal than was John-Lee’s average throw, Chester was more inconsistent in those throws than was

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John-Lee.

The formula for variable error is

VE = √ [Σ (X i − CE) 2 / N]

where Σ, X, i, CE, and N are defined as before, and √ is the square root.

AE was employed as a measure of error very frequently until investigators Schutz and Roy (1973) pointed out some statistical difficulties with it. Today, investigators tend to use CE (as a measure of average bias, or directional error) and VE (as a measure of inconsistency). Sometimes investigators use a statistic called absolute constant error (abbreviated |CE|) instead of CE for a subject’s measure of bias. The |CE| is simply the average absolute value of the computed CE score as defined previously. The advantage is that |CE| retains the magnitude of average deviation from the target, but prevents two scores from “canceling out” when subjects are averaged together to present a group score. Much more on these error scores is presented in chapter 2 of Schmidt and Lee (2011).

Focus on Research 1.3

Error Scores in Continuous Tasks

Continuous tasks, like tracking, are capable of producing many error scores on a single trial. Consider figure 1.1 as an example of a portion of a single trial of a tracking task for one subject. The blue track represents the stimulus goal, such as a highway lane along which a driver might navigate a car. The red line represents the exact (unmarked) center of the track from edge to edge. The dotted line represents a subject’s tracking behavior, in this case, how close to the center of the road the car is maintained. How can skill be measured in this single trial of a continuous performance?

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A common method used by researchers who study tracking tasks is to compute a measure called root-mean-square error (RMSE). One does this by computing the distance of the subject’s tracking response from the target line at set distance-points along the track (e.g., every 10 ft of highway traveled) or, more commonly, at a constant interval of time along the track (e.g., every 100 ms). This method effectively “slices” the movement into equal intervals of tracking behavior, from start to finish.

With each “slice” of the track, the researcher then computes how far the subject’s tracking position is from the target. Since the red line in figure 1.1 represents the center of the track, it is convenient to define the red line as the “zero” position. Therefore, if the subject is to the right of the target, the measure is given a positive error value; if the tracking position is to the left of the target, the measure gets a negative value. The root-mean-square error score is computed by first calculating the squared deviations for each measured position along the track, then taking the square root of the sum of those scores.

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Figure 1.1 Measuring RMSE in a tracking task. The blue area represents the “track” (such as a highway lane); the red (solid) line represents the unmarked center of the lane, and can be considered

the subject’s goal track. The blue (dotted) line represents the subject’s performance in attempting to follow the red line.

The RMSE is a more complex measure of performance than any of the error scores for discrete tasks, because it represents two components of behavior. The RMSE reflects both the subject’s bias tendency (e.g., on average, to drive closer to the right edge of the lane than the left edge) as well as inconsistency in the tracking behavior (how variable the performance tends to be). It is well recognized as a very good measure of how effectively the person tracked.

Understanding Performance and Learning In some ways, skilled performance and motor learning are interrelated concepts that cannot be easily separated for analysis. Even so, a temporary separation of these areas is necessary for presentation and making eventual understanding much easier. Many of the terms, principles, and processes that scientists use to describe the improvements with practice and learning (the subfield of motor learning) actually come from the literature on the underlying processes in the production of skilled motor performance (the subfield of human performance; the field of motor behavior often includes both motor learning and human performance). Therefore, whereas at first glance it might seem most logical to treat motor learning before motor performance (a person has to learn before performing), it turns out to be awkward to present information on learning without first having provided this background performance information.

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For this reason this book is organized into two parts, the first of which introduces the terminology, concepts, and principles related to skilled human performance without very much reference to processes associated with learning. The principles here probably apply most strongly to the performance of already skilled actions. Having examined the principles of how the motor system produces skills, the discussion turns to how these processes can be altered, facilitated, and trained through practice. This involves motor learning, whose principles apply most strongly to the instruction of motor skills.

When studying motor-skill performance and learning, it is helpful to understand where each concept fits into the complex process of performing a skill. For this reason, and to help apply skills information to a variety of settings, this book develops a conceptual model. This model represents the big picture of motor performance; and as new topics are introduced, they are added to the model, tying together most of the major processes and events that occur as performers produce skills. Models of this type are critical in teaching and in science because they embrace many seemingly unrelated facts and concepts, linking real-world knowledge with the concepts being discussed.

Models can be of many types, of course, such as the plumbing-and-pump model of the human circulatory system and the variety of balls that model the structure of atoms, the solar system, and molecules in chemistry. For skills, a useful conceptualization is an information-flow model, which considers how information of various kinds is used in producing and learning a skilled action. The first portions of the text build this model, first considering how the sensory information that enters the system through the receptors is processed, transformed, and stored. Then, to this is added how this sensory information leads to other processes associated with decision making and planning action. To the emerging conceptual model are then added features of the initiation of action as well as the activities involved while the action is unfolding, such as controlling muscular contractions and detecting and correcting errors; this is highly related to the performer’s analysis of the sensations produced as a result of performing the action— processes related to feedback. In the second portion of the text, which deals with learning, the model provides an effective understanding of the processes that are, and are not, influenced by practice.

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Summary People regard skills as an important, fascinating aspect of life. Knowledge about skills has come from a variety of scientific disciplines and can be applied to many settings, such as sport, teaching, coaching, industry, and physical therapy.

Skill is usually defined as the capability to bring about some desired end result with maximum certainty and minimum time and energy. Many different components are involved; major categories are perceptual or sensory processes, decision making, and movement output. Skills may be classified along numerous dimensions, such as open versus closed skills, and discrete, continuous, and serial skills. These classifications are important because the principles of skills and their learning often differ for different skill categories.

The text's particular organization of materials should facilitate an understanding of skills. After this introduction, the remainder of part I treats the principles of human skilled performance and the underlying processes, focusing on how the various parts of the motor system act to produce skilled actions. Part II examines how to modify these various processes by practice and motor learning. Understanding how all of these components can operate together is facilitated by a conceptual model of human performance that is developed throughout the text.

Web Study Guide Activities

The student web study guide, available at www.HumanKinetics.com/MotorLearningAndPerformance, offers these activities to help you build and apply your knowledge of the concepts in this chapter.

Interactive Learning

Activity 1.1: Classify skills as discrete, serial, or continuous in nature by selecting the appropriate category for each of five examples. Activity 1.2: Review the types of error measured in motor learning research by matching various error measures with their definitions.

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http://www.HumanKinetics.com/MotorLearningAndPerformance
http://courses.humankinetics.com/shell.cfm?siteCourseID=655&pageid=30104
http://courses.humankinetics.com/shell.cfm?siteCourseID=655&pageid=30105
Principles-to-Application Exercise

Activity 1.3: The principles-to-application exercise for this chapter applies the concepts in this chapter to your own experience by asking you to analyze a motor skill that you have learned in the past or are currently learning. You’ll describe the skill as open or closed and as discrete, continuous, or serial and identify the goals of the skill and the factors that contribute to your success when performing it.

Check Your Understanding

1. Define a skill and indicate why each of the following terms is important to that definition.

Environmental goal Maximum certainty Minimum energy costs Minimum time

2. Distinguish between open and closed skills and between discrete, serial, and continuous skills. Give one example of each.

3. List and describe three elements critical to almost any skill. 4. Define a theory and describe how scientists use theories to design

experiments.

Apply Your Knowledge

1. List three motor skills that you have learned, either recently or when you were younger (e.g., swinging a baseball bat, tying your shoelaces, or playing a chord on the piano). Classify each of the skills you have listed, distinguishing between open and closed and between discrete, serial, and continuous skills. Are maximum certainty, minimum energy costs, and minimum time equally important for each of the tasks you have listed? Why or why not?

Suggestions for Further Reading

Historical reviews of motor skills research were conducted by Irion (1966), Adams (1987), and Schmidt and Lee (2011). The first edition of Motor Control and Learning (Schmidt, 1982) contains a chapter devoted to the scientific study of motor skills. Snyder and Abernethy (1992) devoted a

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http://courses.humankinetics.com/shell.cfm?siteCourseID=655&pageid=30106
chapter to the early stages of the career of Franklin Henry. Skills classification systems are reviewed in Poulton (1957), Gentile (1972), and Farrell (1975). See the reference list for these additional resources.

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Part I Principles of Human Skilled

Performance Chapter 1 introduced just a few of the types of motor performance that fascinate us—from the powerful movements of elite athletes to virtuoso musical performances. We now begin a two-part exploration of such skilled motor performances. In part I, we emphasize the research-based principles of how such motor performances can occur. As we introduce the various concepts concerning motor performance, we “build” a conceptual model of human skilled performance throughout the first part of the book. This model contains and summarizes many of the major factors that underlie such performances and is useful as a guide for understanding how motor skills are performed. In part I, the focus is mainly on the factors that allow skilled motor performances to occur, without much reference to practice and learning of skills. After we explain the terminology and fundamental concepts of human performance in part I, we turn in part II to some of the principles governing how certain components outlined in part I are acquired with practice and experience.

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Chapter 2 Processing Information and

Making Decisions

The Mental Side of Human Performance

Chapter Outline 57

The Information-Processing Approach Reaction Time and Decision Making Memory Systems Summary

Chapter Objectives Chapter 2 describes a conceptualization of how decisions are made in the performance of motor skills. This chapter will help you to understand

the information-processing approach to understanding motor performance, the stages that occur during information processing, various factors that influence the speed of information processing, the role of anticipation in hastening the speed of responding, and memory systems and their roles in motor performance.

Key Terms choice reaction time foreperiod Hick’s Law information-processing approach long-term memory (LTM)

memory

movement time (MT) population stereotypes reaction time (RT) response time

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short-term memory (STM) short-term sensory store (STSS) simple RT spatial anticipation temporal anticipation

The batter was ready this time. The pitcher had just thrown three slow curveballs in a row. Although the batter had two strikes against him, he felt confident because he thought the next pitch would be a fastball, and he was prepared for it. As the pitch was coming toward him, he strode forward and began to swing the bat to meet the ball, but he soon realized this was another curve. He could not modify his swing in time, and the bat crossed the plate long before the ball arrived. The pitcher had beaten him again.

How did the batter's faulty anticipation interfere with his performance? What processes were required to amend the action? To what extent did the stress of the game interfere? Certainly a major concern for the skilled performer is the evaluation of information, leading to decision making about future action. But what information was the batter reflecting on while the pitch was coming toward the plate—the spin of the ball? its velocity? its location? the type, speed, and location of previous pitches? how fast to swing the bat? where to try to hit the ball? Processing all, or even some, of this information would surely have affected the batter’s success in hitting the ball.

Without a doubt, one of the most important features of skilled performance is deciding what to do (and what not to do) in situations in which these decisions are needed quickly and predictably. After all, the most beautifully executed baseball throw to first base is ineffective if the throw should have been directed somewhere else instead. This chapter considers factors contributing to these decision-making capabilities, including processing environmental information, and some of the factors that contribute to the actual decision. We begin with a general approach for understanding how the motor system uses information, which will form the basis of the conceptual model of human performance.

The Information-Processing Approach Researchers have found it useful to think of the human being as a processor

59

of information very much like a computer. Information is presented to the human as input; various processing stages within the human motor system generate a series of operations on this information; and the eventual output is skilled movement. This simple information-processing approach is shown in figure 2.1.

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Figure 2.1 A simplified information-processing approach to thinking about human performance.

A major goal of researchers interested in the performance of motor skills is to understand the specific nature of the processes in the box labeled “Human” in figure 2.1. There are many ways to approach this problem; a particularly useful one assumes that there are separable information- processing stages through which the information must pass on the way from input to output. For our purposes, here are three of these stages:

Stimulus identification Response selection Movement programming

This stage analysis of performance generally assumes that peripheral information enters the system and is processed in the first stage. When, and only when, this stage has completed its operations, the result is passed on to the second stage whose processing is completed, and then the Stage-2 result is passed to the third stage, and so on. A critical assumption is that the stages are nonoverlapping—meaning that all of the processing in a given stage is completed before the product of classification is passed to the next stage; that is, processing in two different stages cannot occur at the same time. This process finally results in an output—the action. What occurs in these stages of processing?

Stimulus Identification Stage

During this first stage the system's problem is to decide whether a stimulus has been presented and, if so, what it is. Thus, stimulus identification is primarily a sensory stage, analyzing environmental information from a variety of sources, such as vision, audition, touch, kinesthesis, and smell. The components, or separate dimensions of these stimuli, are thought to be “assembled” in this stage, such as the combination of edges and colors that

61

form a representation of a car in traffic. Patterns of movement are also detected, such as whether other objects are moving, in what direction and how quickly they are moving, and so on, as would be necessary for driving a car in heavy traffic. The result of this stage is thought to be some representation of the stimulus, with this information being passed on to the next stage—response selection.

Response Selection Stage

The activities of the response selection stage begin after the stimulus identification stage provides information about the nature of the environmental stimulus. This stage has the task of deciding what response to make, given the nature of the situation and environment. In the driving example, the choice from available responses might be to overtake another vehicle, to slow the car, or to make an avoidance maneuver. Thus, this stage requires a kind of transition process between sensory input and movement output.

Movement Programming Stage

This final stage begins its processing upon receiving the decision about what movement to make as determined by the response selection stage. The movement programming stage has the task of organizing the motor system to make the desired movement. Before producing a movement, the system must ready the lower-level mechanisms in the brainstem and spinal cord for action, and it must retrieve and organize a motor program that will eventually control the movement. In the driving example, if the response- selection stage determined that a braking response was required, then the organization of the motor program responsible for executing a braking action would occur in the movement-programming stage.

Expanding the Conceptual Model

Figure 2.2 adds some detail to the simple notion of information processing described in figure 2.1 by including the stages of processing just described. This elaboration is the first revision of our conceptual model, which will be expanded throughout the text as we introduce more fundamental ideas of human performance.

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Figure 2.2 An expanded information-processing model, highlighting three critical processing stages in thinking about human performance.

Clearly, these stages are all included within the human information system and are not directly observable under usual circumstances. However, several laboratory methods allow scientists to learn about these stages. Reaction time (abbreviated RT) is one of the most important tools that researchers have used for many decades to learn about these stages. We will examine RT in much more detail to understand how information processing operates.

Reaction Time and Decision Making An important performance measure indicating the speed and effectiveness of decision making is the RT interval—the interval of time that elapses following a suddenly presented, often unanticipated stimulus until the beginning of the response. The concept and assessment of RT are important because it represents a part of some everyday events, such as braking rapidly in response to an unanticipated traffic event; responding to catch a glass that has been accidentally tipped over; and, in sport, in such events as sprint races, where an auditory tone serves as a stimulus to begin a race.

An old saying is that a picture is worth a thousand words. This is certainly borne out by the redrawn photo of a long-ago sprint race (figure 2.3) reprinted from Scripture (1905). The starter on the left side of the photo has

63

already fired his gun, perhaps a couple of hundred or so milliseconds earlier, as you can see by the position of the smoke from the pistol rising above the starter. And yet the runners are all still in their ready positions, and are only now just beginning to move. The photo illustrates nicely the substantial delay involved in RT. Being able to minimize RT in such a situation is critical to getting the movement under way as rapidly as possible. Because RT is a fundamental component of many skills, it is not surprising that much research attention has been directed toward it.

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Figure 2.3 Illustration of the RT delay in a sprint start; the starting gun has been fired, yet the athletes are still on their marks because of the delay in processing the signal from the starting gun (the delay is contained in the

reaction-time interval).

But RT has important theoretical meaning as well, which is the major reason it has attracted so much research attention. However, sometimes there is confusion about what RT is and how it is measured. To review, researchers define the RT interval very carefully; it is the period of time beginning when the stimulus is first presented and ending when the movement response starts. Note that the RT interval does not include the time that is taken to complete the movement, as illustrated in figure 2.4. That period of time, from the end of RT until the completion of the movement, is typically called the “movement time” (or simply MT). Hence, terms like “brake RT” used to describe the time it takes a person to press the brake pedal in a car are technically incorrect, as the time taken to press the brake includes the time for the foot’s movement from the accelerator to depress the brake, which occurs after the reaction interval. What many refer to as brake RT is actually the total of RT plus MT—what is called response time.

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Figure 2.4 Measuring reaction time, movement time, and response time for pressing the brake pedal in a car.

The RT interval is a measure of the accumulated durations of the three sequential and nonoverlapping stages of processing seen in figure 2.2. Any factor that increases the duration of one or more of these stages will thus lengthen RT. For this reason, scientists interested in information processing have used RT as a measure of the speeds of processing in these stages. Next is a discussion of how changes in RT can inform us about the stages of processing.

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