Online Discussion Behaviorism Theory

Learning Theories An Educational Perspective

Sixth Edition

Dale H. Schunk The University of North Carolina at Greensboro

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Library of Congress Cataloguing in Publication Data

Schunk, Dale H. Learning theories : an educational perspective / Dale H. Schunk.—6th ed.

p. cm. Includes bibliographical references and index. ISBN-13: 978-0-13-707195-1 ISBN-10: 0-13-707195-7 1. Learning. 2. Cognition. 3. Learning, Psychology of. I. Title. LB1060.S37 2012 370.15’23—dc22

2010048468

10 9 8 7 6 5 4 3 2 1

ISBN-10: 0-13-707195-7

ISBN-13: 978-0-13-707195-1

Dedication

To Barry Zimmerman, mentor, colleague, and friend

Brief Contents

1 Introduction to the Study of Learning 1

2 Neuroscience of Learning 29

3 Behaviorism 71

4 Social Cognitive Theory 117

5 Information Processing Theory 163

6 Constructivism 228

7 Cognitive Learning Processes 278

8 Motivation 345

9 Self-Regulation 399

10 Development 444

Glossary 489

References 501

Author Index 539

Subject Index 550

iv

Contents

v

1 Introduction to the Study of Learning 1

Learning Defined 3

Precursors of Modern Learning Theories 4

Learning Theory and Philosophy 5 Beginnings of the Psychological Study of

Learning 7 Structuralism and Functionalism 8

Learning Theory and Research 10

Functions of Theory 10 Conducting Research 11

Assessment of Learning 14 Direct Observations 14 Written Responses 15 Oral Responses 16 Ratings by Others 16 Self-reports 18

Relation of Learning and Instruction 18

Historical Perspective 18 Instructional Commonalities 19 Integration of Theory and Practice 20

Critical Issues for Learning Theories 21

How Does Learning Occur? 22 What is the Role of Memory? 23 What is the Role of Motivation? 23 How Does Transfer Occur? 24 Which Processes are Involved in

Self-regulation? 24 What are the Implications for

Instruction? 25

Three Learning Scenarios 25 Kathy Stone’s Third-grade Class 25 Jim Marshall’s U.S. History Class 26 Gina Brown’s Educational Psychology

Class 26

Summary 27

Further Reading 28

2 Neuroscience of Learning 29

Organization and Structures 31 Neural Organization 32 Brain Structures 33 Localization and Interconnections 37 Brain Research Methods 39

Neurophysiology of Learning 43 Information Processing System 43 Memory Networks 46 Language Learning 49

Brain Development 50 Influential Factors 50 Phases of Development 51 Critical Periods 52 Language Development 55

Motivation and Emotions 58 Motivation 58 Emotions 60

Instructional Applications 62 Relevance of Brain Research 62 Educational Issues 63 Brain-based Educational Practices 64

Summary 67

Further Reading 70

3 Behaviorism 71 Connectionism 73

Trial-and-error Learning 73 Laws of Exercise and Effect 74 Other Principles 75 Revisions to Thorndike’s Theory 75 Thorndike and Education 76

Classical Conditioning 78 Basic Processes 79 Informational Variables 81 Biological Influences 81 Conditioned Emotional Reactions 82

Contiguous Conditioning 84 Acts and Movements 84 Associative Strength 84 Rewards and Punishments 85 Habit Formation and Change 85

Operant Conditioning 88 Conceptual Framework 89 Basic Processes 89 Behavioral Change 98 Behavior Modification 100 Self-regulation 102

Instructional Applications 102 Behavioral Objectives 103 Learning Time 105 Mastery Learning 107 Programmed Instruction 109 Contingency Contracts 112

Summary 114

Further Reading 116

4 Social Cognitive Theory 117 Conceptual Framework for Learning 119

Reciprocal Interactions 119 Enactive and Vicarious Learning 119 Learning and Performance 122 Self-regulation 122

Modeling Processes 123 Theories of Imitation 123 Functions of Modeling 125 Cognitive Skill Learning 129 Motor Skill Learning 131

Influences on Learning and Performance 133

Developmental Status of Learners 133 Model Prestige and Competence 134 Vicarious Consequences to

Models 135

Motivational Processes 138 Goals 138 Outcome Expectations 143 Values 145

Self-Efficacy 146 Conceptual Overview 146 Self-efficacy in Achievement

Situations 147 Models and Self-efficacy 149 Motor Skills 152 Instructional Self-efficacy 153 Health and Therapeutic Activities 154

Instructional Applications 156 Models 157 Self-efficacy 157 Worked Examples 158 Tutoring and Mentoring 158

Summary 159

Further Reading 162

5 Information Processing Theory 163

Information Processing System 165 Assumptions 165 Two-store (dual) Memory Model 165 Alternatives to the Two-store Model 168

Attention 171 Theories of Attention 171 Attention and Learning 172 Attention and Reading 174

vi Contents

Perception 175 Gestalt Theory 175 Sensory Registers 178 LTM Comparisons 179

Two-Store Memory Model 180 Verbal Learning 181 Short-term (working) Memory 183 Long-term Memory 184 Influences on Encoding 187

Long-Term Memory: Storage 191 Propositions 191 Storage of Knowledge 191 Production Systems and Connectionist

Models 196

Long-Term Memory: Retrieval and Forgetting 200

Retrieval 200 Language Comprehension 204 Forgetting 209

Mental Imagery 213 Representation of Spatial Information 213 Imagery in LTM 216 Individual Differences 217

Instructional Applications 217 Advance Organizers 218 Conditions of Learning 219 Cognitive Load 223

Summary 224

Further Reading 227

6 Constructivism 228 Constructivism: Assumptions and Perspectives 230

Overview 230 Perspectives 232 Situated Cognition 233 Contributions and Applications 234

Piaget’s Theory of Cognitive Development 236

Developmental Processes 236 Implications for Instruction 239

Vygotsky’s Sociocultural Theory 240 Background 241 Basic Principles 242 Zone of Proximal Development 243 Applications 245 Critique 247

Private Speech and Socially Mediated Learning 248

Private Speech 248 Verbalization and Achievement 249 Socially Mediated Learning 251 Self-regulation 252

Motivation 254 Contextual Factors 254 Implicit Theories 256 Teachers’ Expectations 258

Constructivist Learning Environments 261

Key Features 261 APA Learner-Centered Principles 263

Instructional Applications 265 Discovery Learning 266 Inquiry Teaching 268 Peer-assisted Learning 269 Discussions and Debates 271 Reflective Teaching 271

Summary 274

Further Reading 276

7 Cognitive Learning Processes 278

Skill Acquisition 280 General and Specific Skills 280 Novice-to-expert Research

Methodology 281 Expert-novice Differences in

Science 283

Conditional Knowledge and Metacognition 284

Conditional Knowledge 285 Metacognition and Learning 286

Contents vii

viii Contents

Variables Influencing Metacognition 288

Metacognition and Behavior 289 Metacognition and Reading 290

Concept Learning 292 The Nature of Concepts 292 Concept Attainment 294 Teaching of Concepts 295 Motivational Processes 298

Problem Solving 299 Historical Influences 299 Heuristics 302 Problem-Solving Strategies 304 Problem Solving and Learning 309 Experts and Novices 310 Reasoning 311 Implications for Instruction 315

Transfer 317 Historical Views 317 Activation of Knowledge in

Memory 318 Types of Transfer 319 Strategy Transfer 321 Teaching for Transfer 322

Technology and Instruction 324 Computer-based Learning

Environments 325 Distance Learning 328 Future Directions 330

Instructional Applications 332 Worked Examples 332 Writing 334 Mathematics 337

Summary 342

Further Reading 344

8 Motivation 345 Historical Perspectives 347

Drive Theory 347 Conditioning Theory 348

Cognitive Consistency Theory 349 Humanistic Theory 351

Model of Motivated Learning 356 Pretask 357 During Task 357 Posttask 358

Achievement Motivation 358 Expectancy-value Theory 359 Familial Influences 361 Contemporary Model of Achievement

Motivation 362 Self-worth Theory 364 Task and Ego Involvement 366

Attribution Theory 366 Locus of Control 367 Naïve Analysis of Action 367 Attribution Theory of

Achievement 368

Social Cognitive Theory 371 Goals and Expectations 372 Social Comparison 372

Goal Theory 374 Goal Orientations 376 Conceptions of Ability 379

Perceived Control 380 Control Beliefs 380 Learned Helplessness 381 Students with Learning Problems 382

Self-Concept 383 Dimensions and Development 383 Self-concept and Learning 385

Intrinsic motivation 386 Theoretical Perspectives 386 Overjustification and Reward 389

Instructional Applications 392 Achievement Motivation Training 392 Attribution Change Programs 393 Goal Orientations 395

Summary 397

Further Reading 398

9 Self-Regulation 399 Behavioral Theory 401

Self-monitoring 401 Self-instruction 404 Self-reinforcement 405

Social Cognitive Theory 405 Conceptual Framework 405 Social Cognitive Processes 407 Cyclical Nature of Self-regulation 411 Social and Self Influences 414

Information Processing Theory 415 Model of Self-regulation 415 Learning Strategies 417

Constructivist Theory 427 Sociocultural Influences 428 Implicit Theories 430

Motivation and Self-Regulation 431 Volition 432 Values 434 Self-schemas 434 Help Seeking 435

Instructional Applications 436 Academic Studying 436 Writing 436 Mathematics 439

Summary 441

Further Reading 443

10 Development 444 Beginnings of the Scientific Study of Development 446

Historical Foundations 446 Philosophical Foundations 446 The Child Study Movement 447

Perspectives on Development 449 Issues Relevant to Learning 450 Types of Developmental Theories 452 Structural Theories 455

Bruner’s Theory of Cognitive Growth 457

Knowledge Representation 457 Spiral Curriculum 458

Contemporary Developmental Themes 460

Developmental Changes 460 Developmentally Appropriate

Instruction 461 Transitions in Schooling 463

Family Influences 465 Socioeconomic Status 465 Home Environment 468 Parental Involvement 469 Electronic Media 472

Motivation and Development 474 Developmental Changes 475 Implications 476

Instructional Applications 477 Learning Styles 478 Case’s Instructional Model 482 Teacher-student Interactions 483

Summary 486

Further Reading 487

Glossary 489

References 501

Author Index 539

Subject Index 550

Contents ix

Preface The study of human learning continues to develop and expand. As researchers from var- ious theoretical traditions test their ideas and hypotheses in basic and applied settings, their research findings give rise to improvements in teaching and learning by students of all ages. Especially noteworthy is how topics once seen as not intimately connected with learning—such as motivation, technology, and self-regulation—are increasingly being addressed by researchers and practitioners.

Although the field of learning is ever changing, the primary objectives of this sixth edition remain the same as those of the previous editions: (a) to inform students of learn- ing theoretical principles, concepts, and research findings, especially as they relate to education and (b) to provide applications of principles and concepts in settings where teaching and learning occur. The text continues to focus on cognition, although behav- iorism also is discussed. This cognitive focus is consistent with the contemporary con- structivist emphasis on active learners who seek, form, and modify their knowledge, skills, strategies, and beliefs.

STRUCTURE OF THIS TEXT The text’s 10 chapters are organized as follows. The introductory chapter discusses learn- ing theory, research, and issues, as well as historical foundations of the study of learning and the relation of learning to instruction. At the end of this chapter are three scenarios involving elementary, secondary, and university settings. Throughout the text, these three settings are used to demonstrate applications of principles of learning, motivation, and self-regulation. Chapter 2 discusses the neuroscience of learning. Presenting this material early in the text is beneficial so that readers better understand subsequent links made be- tween brain functions and cognitive and constructivist learning principles. Behaviorism, which dominated the field of learning for many years, is addressed in Chapter 3. Current cognitive and constructivist views of learning are covered in the next four chapters: social cognitive theory; information processing theory; constructivism; and cognitive learning processes. The final three chapters cover topics relevant to and closely integrated with learning theories: motivation; self-regulation; and development.

NEW TO THIS EDITION Readers familiar with prior editions will notice many content and organizational changes in this edition, which reflect evolving theoretical and research emphases. Self-regulation, which in recent editions was covered in other chapters, now is a chapter on its own. This chapter highlights the importance of self-regulation in learning and reflects the increasing

x

emphasis on self-regulation by researchers and practitioners. Given the prevalence of tech- nology in schools and homes, the text includes new sections on learning from electronic media and in computer-based learning environments. In prior editions, content-area learn- ing and instructional models were covered in separate chapters. In this sixth edition, this material is integrated into other chapters at appropriate places, which provides better co- herence and connection between learning and content instruction. Some chapters have been reordered in the text, and some topics have been shifted within chapters to provide a better flow. The continued growth of research relevant to academic learning led to new terms incorporated into the glossary and to more than 140 new references.

This edition continues to provide many examples of learning concepts and principles applied to settings where learning occurs. Each chapter after the introductory chapter contains a new section on instructional applications. Chapters open with vignettes that il- lustrate some of the principles discussed in the chapters and also contain many informal examples and detailed applications. Many of the latter are set in the scenarios described in Chapter 1. Most of the applications in the chapters pertain to K-12 learners, but appli- cations also address younger and older students and learning in out-of-school settings.

The text is intended for use by graduate students in education or related disciplines, as well as by upper-level undergraduates interested in education. It is assumed that most students have taken a prior course in education or psychology and currently work in an educational capacity or anticipate pursuing an educational career. In addition to courses on learning, the text is appropriate for any course that covers learning in some depth, such as courses on motivation, educational psychology, human development, and in- structional design.

ACKNOWLEDGMENTS I gratefully acknowledge several individuals for their assistance with this project. Throughout my career, many colleagues have enriched my thinking about learning processes and applications, including Albert Bandura, Curt Bonk, James Chapman, Herb Clark, Lyn Corno, Peg Ertmer, Doreen Ferko, the late Nate Gage, Marilyn Haring, Carolyn Jagacinski, Mark Lepper, Dave Lohman, Judith Meece, Sam Miller, Carol Mullen, the late John Nicholls, the late Frank Pajares, the late Paul Pintrich, Don Rice, Ellen Usher, Claire Ellen Weinstein, Allan Wigfield, Phil Winne, and Barry Zimmerman. I continue to benefit from activities with members of professional organizations, especially the Motivation in Education Special Interest Group of the American Educational Research Association, and Division 15 (Educational Psychology) of the American Psychological Association. My learning has been broadened by many outstanding students, teachers, counselors, ad- ministrators, and superintendents with whom I have worked. Sincere thanks go to gradu- ate and undergraduate student collaborators for their assistance on research projects.

For many years, my editor at Pearson Education was Kevin Davis. I am so thankful for all the guidance and support provided by Kevin, which has served to strengthen and improve this text. With this edition, Paul Smith assumed the editorial responsibilities, and he has done a fantastic job. It has been a pleasure working with Paul. Special thanks also are due to Matt Buchholz and Cynthia Parsons at Pearson for their editorial assistance. I

Preface xi

wish to thank the following reviewers of the fifth edition: Ronald A. Beghetto, University of Oregon; Denise Ward Hood, Northern Arizona University; and Sherri Horner, Bowling Green State University. At the University of North Carolina at Greensboro, I appreciate the assistance with administrative tasks provided by Tomi Register, Liz Meeks, and Melissa Edmonds-Kruep.

I am ever grateful for the love and encouragement from my parents, the late Mil and Al Schunk, and for the ways that friends Bill Gattis, Rob Eyman, Doug Curyea, and the late Jim Tozer have helped me keep life’s priorities straight. I express deep gratitude to Caryl and Laura Schunk for their understanding, support, encouragement, and love since the first edition of this text appeared in 1991. Caryl assisted with many of the examples and applications based on her experiences in K-12 education. Laura, who was a baby when the first edition was published and today is poised to graduate from college, is an intelligent, motivated, and sociable young woman. The impact of learning in her life con- tinually brings this text close to home.

xii Preface

1 Introduction to the Study of Learning

Russ Nyland teaches an education course for graduate students on cognitive instruction and learning. It is toward the end of the semester, and, as class finishes one day, three students approach him: Jeri Kendall, Matt Bowers, and Trisha Pascella.

Russ: What’s up? Wasn’t I clear today?

Jeri: Dr. Nyland, can we talk with you? We’ve been talking, and it’s late in the course and we’re still confused.

Russ: About what?

Jeri: Well, we’ve been studying all these theorists. It seems like they’re saying different things, but maybe not. Bandura, Bruner, Anderson, Vygotsky, and the others. They make different points, but then some of what they say seems to overlap what others say.

Matt: Yeah, I’m so confused. I read these theorists and think like, yeah, I agree with that. But then it seems like I agree with everything. I thought you were supposed to have one theory, to believe one way and not others. But it seems like there’s a lot of overlap between theories.

Russ: You’re right Matt, there is. Most of what we’ve studied in this course are cognitive theories, and they are alike because they say that learning involves changes in cognitions—knowledge, skills, beliefs. Most theorists also say that learners construct their knowledge and beliefs; they don’t automatically adopt what somebody tells them. So yes, there is much overlap.

Trisha: So then what are we to do? Am I supposed to be something like an information processing theorist, a social cognitive theorist, a constructivist? That’s what I’m confused about.

Russ: No, you don’t have to be one or the other. There may be one theory that you like better than the others, but maybe that theory doesn’t address everything you want it to. So then you can borrow from other theories. For example, when I was in grad school I worked with a professor whose specialty was cognitive learning. There was another professor who did

Chapter

1

2 Chapter 1

developmental research. I really liked her research, probably because I had been a teacher and was interested in development, especially the changes in kids from elementary to middle school. So I was a learning theorist who borrowed from the developmental literature and still do. It’s ok to do that!

Jeri: Well that makes me feel better. But it’s late in the course, and I guess I want to know what I should be doing next.

Russ: Tell you what—next class I’ll spend some time on this. A good place to start is not to decide which type of theorist you are, but rather determine what you believe about learning and what types of learning you’re interested in. Then you can see which theory matches up well to your beliefs and assumptions and maybe do as I did—borrow from others.

Matt: Isn’t that what you call being eclectic?

Russ: Perhaps, but you may still have one preferred theory that you then adapt as needed. That’s okay to do. In fact, that’s how theories are improved—by incorporating ideas that weren’t in them originally.

Trisha: Thanks Dr. Nyland. This is really helpful.

Learning involves acquiring and modifying knowledge, skills, strategies, beliefs, attitudes, and behaviors. People learn cognitive, linguis- tic, motor, and social skills, and these can take many forms. At a simple level, children learn to solve 2 � 2 � ?, to recognize y in the word daddy, to tie their shoes, and to play with other children. At a more complex level, stu- dents learn to solve long-division problems, write term papers, ride a bicycle, and work co- operatively on a group project.

This book is about how human learning occurs, which factors influence it, and how learning principles apply in various educational contexts. Animal learning is de-emphasized, which is not intended to downgrade its impor- tance because we have gained much knowl- edge about learning from animal research. But human learning is fundamentally different from animal learning because human learning is more complex, elaborate, rapid, and typically involves language.

This chapter provides an overview of the study of learning. Initially, learning is defined and examined in settings where it occurs. An

overview is given of some important philo- sophical and psychological precursors of con- temporary theories that helped to establish the groundwork for the application of learn- ing theories to education. The roles of learn- ing theory and research are discussed, and methods commonly used to assess learning are described. The links between learning theories and instruction are explained, after which critical issues in the study of learning are presented.

At the end of this chapter are three scenar- ios that involve learning with elementary, sec- ondary, and college students. Background in- formation is given about the learners, teachers, instruction, content, setting, and other features. In subsequent chapters, these scenarios will be used to exemplify the operation of learning principles. Readers will benefit from seeing how different learning principles are applied in an integrated fashion in the same settings.

The opening scenario describes a situation that happens to many students when they take a course in learning, instruction, or motivation and are exposed to different theories. Students

Introduction to the Study of Learning 3

often think that they are supposed to believe in one theory and adopt the views of those theorists. They often are confused by the per- ceived overlap between theories.

As Russ says, that is normal. Although the- ories differ in many ways, including their gen- eral assumptions and guiding principles, many rest on a common foundation. This text focuses on cognitive views of learning, which contend that learning involves changes in learners’ cognitions—their thoughts, beliefs, skills, and the like. These theories differ in how they predict that learning occurs—in the processes of learning—and in what aspects of learning they stress. Thus, some theories are oriented more toward basic learning and others toward applied learning (and, within that, in different content areas); some stress the role of development, others are strongly linked with instruction; and some emphasize motivation.

Russ advises his students to examine their beliefs and assumptions about learning rather than decide which type of theorist they are. This is good advice. Once it is clear in our minds where we stand on learning in general, then the theoretical perspective or perspectives that are most relevant will emerge. As you study this text, it will help if you reflect on your beliefs and assumptions about learning and decide how these align with the theories.

This chapter should help to prepare you for an in-depth study of learning by providing a framework for understanding learning and some background material against which to view contemporary theories. When you finish studying this chapter, you should be able to do the following:

■ Define learning and identify instances of learned and unlearned phenomena.

■ Distinguish between rationalism and em- piricism and explain the major tenets of each.

■ Discuss how the work of Wundt, Ebbinghaus, the Structuralists, and the Functionalists helped to establish psychol- ogy as a science.

■ Describe the major features of different research paradigms.

■ Discuss the central features of different methods of assessing learning.

■ State some instructional principles com- mon to many learning theories.

■ Explicate the ways that learning theory and educational practice complement and refine one another.

■ Explain differences between behavioral and cognitive theories with respect to var- ious issues in the study of learning.

LEARNING DEFINED People agree that learning is important, but they hold different views on the causes, processes, and consequences of learning. There is no one definition of learning that is universally accepted by theorists, researchers, and practitioners (Shuell, 1986). Although people disagree about the precise nature of learning, the following is a general definition of learning that is consistent with this book’s cognitive focus and that captures the crite- ria most educational professionals consider central to learning.

Learning is an enduring change in behavior, or in the capacity to behave in a given fashion, which results from practice or other forms of experience.

4 Chapter 1

Let us examine this definition in depth to identify three criteria for learning (Table 1.1). One criterion is that learning involves change—in behavior or in the capacity for be-

havior. People learn when they become capable of doing something differently. At the same time, we must remember that learning is inferential. We do not observe learning di- rectly but rather its products or outcomes. Learning is assessed based on what people say, write, and do. But we also add that learning involves a changed capacity to behave in a given fashion because it is not uncommon for people to learn skills, knowledge, beliefs, or behaviors without demonstrating them at the time learning occurs (Chapter 4).

A second criterion is that learning endures over time. This excludes temporary behav- ioral changes (e.g., slurred speech) brought about by such factors as drugs, alcohol, and fatigue. Such changes are temporary because when the cause is removed, the behavior re- turns to its original state. But learning may not last forever because forgetting occurs. It is debatable how long changes must last to be classified as learned, but most people agree that changes of brief duration (e.g., a few seconds) do not qualify as learning.

A third criterion is that learning occurs through experience (e.g., practice, observation of others). This criterion excludes behavioral changes that are primarily determined by heredity, such as maturational changes in children (e.g., crawling, standing). Nonetheless, the distinction between maturation and learning often is not clear-cut. People may be ge- netically predisposed to act in given ways, but the actual development of the particular behaviors depends on the environment. Language offers a good example. As the human vocal apparatus matures, it becomes able to produce language; but the actual words pro- duced are learned from interactions with others. Although genetics are critical for chil- dren’s language acquisition, teaching and social interactions with parents, teachers, and peers exert a strong influence on children’s language achievements (Mashburn, Justice, Downer, & Pianta, 2009). In similar fashion, with normal development children crawl and stand, but the environment must be responsive and allow these behaviors to occur. Children whose movements are forcibly restrained do not develop normally.

PRECURSORS OF MODERN LEARNING THEORIES The roots of contemporary theories of learning extend far into the past. Many of the is- sues addressed and questions asked by modern researchers are not new but rather reflect a desire for people to understand themselves, others, and the world about them.

This section traces the origins of contemporary learning theories, beginning with a discussion of philosophical positions on the origin of knowledge and its relation to the environment and concluding with some early psychological views on learning. This re- view is selective and includes historical material relevant to learning in educational set- tings. Readers interested in a comprehensive discussion should consult other sources (Bower & Hilgard, 1981; Heidbreder, 1933; Hunt, 1993).

Table 1.1 Criteria of learning. ■ Learning involves change

■ Learning endures over time

■ Learning occurs through experience

Introduction to the Study of Learning 5

Learning Theory and Philosophy From a philosophical perspective, learning can be discussed under the heading of epistemology, which refers to the study of the origin, nature, limits, and methods of knowl- edge. How can we know? How can we learn something new? What is the source of knowledge? The complexity of how humans learn is illustrated in this excerpt from Plato’s Meno (427?–347? B.C.):

I know, Meno, what you mean . . . You argue that a man cannot enquire (sic) either about that which he knows, or about that which he does not know; for if he knows, he has no need to enquire (sic); and if not, he cannot; for he does not know the very subject about which he is to enquire (sic). (1965, p. 16)

Two positions on the origin of knowledge and its relationship to the environment are rationalism and empiricism. These positions are recognizable in current learning theories.

Rationalism. Rationalism refers to the idea that knowledge derives from reason without recourse to the senses. The distinction between mind and matter, which figures promi- nently in rationalist views of human knowledge, can be traced to Plato, who distinguished knowledge acquired via the senses from that gained by reason. Plato believed that things (e.g., houses, trees) are revealed to people via the senses, whereas individuals acquire ideas by reasoning or thinking about what they know. People have ideas about the world, and they learn (discover) these ideas by reflecting upon them. Reason is the highest men- tal faculty because through reason people learn abstract ideas. The true nature of houses and trees can be known only by reflecting upon the ideas of houses and trees.

Plato escaped the dilemma in Meno by assuming that true knowledge, or the knowl- edge of ideas, is innate and is brought into awareness through reflection. Learning is re- calling what exists in the mind. Information acquired with the senses by observing, lis- tening, tasting, smelling, or touching constitutes raw materials rather than ideas. The mind is innately structured to reason and provide meaning to incoming sensory information.

The rationalist doctrine also is evident in the writings of René Descartes (1596–1650), a French philosopher and mathematician. Descartes employed doubt as a method of in- quiry. By doubting, he arrived at conclusions that were absolute truths and not subject to doubt. The fact that he could doubt led him to believe that the mind (thought) exists, as reflected in his dictum, “I think, therefore I am.” Through deductive reasoning from gen- eral premises to specific instances, he proved that God exists and concluded that ideas ar- rived at through reason must be true.

Like Plato, Descartes established a mind–matter dualism; however, for Descartes the ex- ternal world was mechanical, as were the actions of animals. People are distinguished by their ability to reason. The human soul, or the capacity for thought, influences the body’s mechanical actions, but the body acts on the mind by bringing in sensory experiences. Although Descartes postulated dualism, he also hypothesized mind–matter interaction.

The rationalist perspective was extended by the German philosopher Immanuel Kant (1724–1804). In his Critique of Pure Reason (1781), Kant addressed mind–matter dualism and noted that the external world is disordered but is perceived as orderly because order is imposed by the mind. The mind takes in the external world through the senses and al- ters it according to subjective, innate laws. The world never can be known as it exists but

6 Chapter 1

only as it is perceived. People’s perceptions give the world its order. Kant reaffirmed the role of reason as a source of knowledge, but contended that reason operates within the realm of experience. Absolute knowledge untouched by the external world does not exist. Rather, knowledge is empirical in the sense that information is taken in from the world and interpreted by the mind.

In summary, rationalism is the doctrine that knowledge arises through the mind. Although there is an external world from which people acquire sensory information, ideas originate from the workings of the mind. Descartes and Kant believed that reason acts upon information acquired from the world; Plato thought that knowledge can be ab- solute and acquired by pure reason.

Empiricism. In contrast to rationalism, empiricism refers to the idea that experience is the only source of knowledge. This position derives from Aristotle (384–322 B.C.), who was Plato’s student and successor. Aristotle drew no sharp distinction between mind and mat- ter. The external world is the basis for human sense impressions, which, in turn, are in- terpreted as lawful (consistent, unchanging) by the mind. The laws of nature cannot be discovered through sensory impressions, but rather through reason as the mind takes in data from the environment. Unlike Plato, Aristotle believed that ideas do not exist inde- pendently of the external world. The latter is the source of all knowledge.

Aristotle contributed to psychology with his principles of association as applied to mem- ory. The recall of an object or idea triggers recall of other objects or ideas similar to, differ- ent from, or experienced close, in time or space, to the original object or idea. The more that two objects or ideas are associated, the more likely that recall of one will trigger recall of the other. The notion of associative learning is prominent in many learning theories.

Another influential figure was British philosopher John Locke (1632–1704), who de- veloped a school of thought that was empirical but that stopped short of being truly ex- perimental (Heidbreder, 1933). In his Essay Concerning Human Understanding (1690), Locke noted that there are no innate ideas; all knowledge derives from two types of ex- perience: sensory impressions of the external world and personal awareness. At birth the mind is a tabula rasa (blank tablet). Ideas are acquired from sensory impressions and personal reflections on these impressions. Nothing can be in the mind that does not originate in the senses. The mind is composed of ideas that have been combined in different ways. The mind can be understood only by breaking down ideas into simple units. This atomistic notion of thought is associationist; complex ideas are collections of simple ones.

The issues Locke raised were debated by such profound thinkers as George Berkeley (1685–1753), David Hume (1711–1776), and John Stuart Mill (1806–1873). Berkeley believed that mind is the only reality. He was an empiricist because he be- lieved that ideas derive from experiences. Hume agreed that people never can be certain about external reality, but he also believed that people cannot be certain about their own ideas. Individuals experience external reality through their ideas, which constitute the only reality. At the same time, Hume accepted the empiricist doctrine that ideas de- rive from experience and become associated with one another. Mill was an empiricist and associationist, but he rejected the idea that simple ideas combine in orderly ways to form complex ones. Mill argued that simple ideas generate complex ideas, but that the

Introduction to the Study of Learning 7

latter need not be composed of the former. Simple ideas can produce a complex thought that might bear little obvious relation to the ideas of which it is composed. Mill’s beliefs reflect the notion that the whole is greater than the sum of its parts, which is an integral assumption of Gestalt psychology (Chapter 5).

In summary, empiricism holds that experience is the only form of knowledge. Beginning with Aristotle, empiricists have contended that the external world serves as the basis for people’s impressions. Most accept the notion that objects or ideas associate to form complex stimuli or mental patterns. Locke, Berkeley, Hume, and Mill are among the better-known philosophers who espoused empiricist views.

Although philosophical positions and learning theories do not neatly map onto one another, conditioning theories (Chapter 3) typically are empiricist whereas cognitive the- ories (Chapters 4–6) are more rationalistic. Overlap often is evident; for example, most theories agree that much learning occurs through association. Cognitive theories stress as- sociation between cognitions and beliefs; conditioning theories emphasize the association of stimuli with responses and consequences.

Beginnings of the Psychological Study of Learning The formal beginning of psychology as a science is difficult to pinpoint (Mueller, 1979), although systematic psychological research began to appear in the latter part of the nine- teenth century. Two persons who had a significant impact on learning theory are Wundt and Ebbinghaus.

Wundt’s Psychological Laboratory. The first psychological laboratory was opened by Wilhelm Wundt (1832–1920) in Leipzig, Germany, in 1879, although William James had started a teaching laboratory at Harvard University four years earlier (Dewsbury, 2000). Wundt wanted to establish psychology as a new science. His laboratory acquired an inter- national reputation with an impressive group of visitors, and he founded a journal to re- port psychological research. The first research laboratory in the United States was opened in 1883 by G. Stanley Hall (Dewsbury, 2000; see Chapter 10).

Establishing a psychological laboratory was particularly significant because it marked the transition from formal philosophical theorizing to an emphasis on experimentation and instrumentation (Evans, 2000). The laboratory was a collection of scholars who con- ducted research aimed at scientifically explaining phenomena (Benjamin, 2000). In his book Principles of Physiological Psychology (1873), Wundt contended that psychology is the study of the mind. The psychological method should be patterned after the physio- logical method; that is, the process being studied should be experimentally investigated in terms of controlled stimuli and measured responses.

Wundt’s laboratory attracted a cadre of researchers to investigate such phenomena as sensation, perception, reaction times, verbal associations, attention, feelings, and emo- tions. Wundt also was a mentor for many psychologists who subsequently opened labo- ratories in the United States (Benjamin, Durkin, Link, Vestal, & Acord, 1992). Although Wundt’s laboratory produced no great psychological discoveries or critical experiments, it established psychology as a discipline and experimentation as the method of acquiring and refining knowledge.

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Ebbinghaus’s Verbal Learning. Hermann Ebbinghaus (1850–1909) was a German psy- chologist who was not connected with Wundt’s laboratory but who also helped to val- idate the experimental method and establish psychology as a science. Ebbinghaus in- vestigated higher mental processes by conducting research on memory. He accepted the principles of association and believed that learning and the recall of learned infor- mation depend on the frequency of exposure to the material. Properly testing this hy- pothesis required using material with which participants were unfamiliar. Ebbinghaus invented nonsense syllables, which are three-letter consonant-vowel-consonant combi- nations (e.g., cew, tij).

Ebbinghaus was an avid researcher who often used himself as the subject of study. In a typical experiment, he would devise a list of nonsense syllables, look at each syllable briefly, pause, and then look at the next syllable. He determined how many times through the list (trials) it took to him learn the entire list. He made fewer errors with re- peated study of the list, needed more trials to learn more syllables, forgot rapidly at first but then more gradually, and required fewer trials to relearn syllables than to learn them the first time. He also studied a list of syllables some time after original learning and cal- culated a savings score, defined as the time or trials necessary for relearning as a percent- age of the time or trials required for original learning. He memorized some meaningful passages and found that meaningfulness made learning easier. Ebbinghaus compiled the results of his research in the book Memory (1885/1964).

Although important historically, there are concerns about this research. Ebbinghaus typically employed only one participant (himself), and it is unlikely he was unbiased or a typical learner. We also might question how well results for learning nonsense syllables generalize to meaningful learning (e.g., text passages). Nonetheless, he was a careful re- searcher, and many of his findings later were validated experimentally. He was a pioneer in bringing higher mental processes into the experimental laboratory.

Structuralism and Functionalism The work by Wundt and Ebbinghaus was systematic but confined to particular locations and of limited influence on psychological theory. The turn of the century marked the be- ginning of more widespread schools of psychological thought. Two perspectives that emerged were structuralism and functionalism. Although neither exists as a unified doc- trine today, their early proponents were influential in the history of psychology as it re- lates to learning.

Structuralism. Edward B. Titchener (1867–1927) was Wundt’s student in Leipzig. In 1892 he became the director of the psychology laboratory at Cornell University. He imported Wundt’s experimental methods into U.S. psychology.

Titchener’s psychology, which eventually became known as structuralism, repre- sented a combination of associationism with the experimental method. Structuralists be- lieved that human consciousness is a legitimate area of scientific investigation, and they studied the structure or makeup of mental processes. They postulated that the mind is composed of associations of ideas and that to study the complexities of the mind, one must break down these associations into single ideas (Titchener, 1909).

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The experimental method used often by Wundt, Titchener, and other structuralists was introspection, which is a type of self-analysis. Titchener noted that scientists rely on observation of phenomena and that introspection is a form of observation. Participants in introspection studies verbally reported their immediate experiences fol- lowing exposure to objects or events. For example, if shown a table they might report their perceptions of shape, size, color, and texture. They were told not to label or re- port their knowledge about the object or the meanings of their perceptions. Thus, if they verbalized “table” while viewing a table, they were attending to the stimulus rather than to their conscious processes.

Introspection was a uniquely psychological process and helped to demarcate psy- chology from the other sciences. It was a professional method that required training in its use so that an introspectionist could determine when individuals were examining their own conscious processes rather than their interpretations of phenomena.

Unfortunately, introspection often was problematic and unreliable. It is difficult and unrealistic to expect people to ignore meanings and labels. When shown a table, it is nat- ural that people say “table,” think of uses, and draw on related knowledge. The mind is not structured to compartmentalize information so neatly, so by ignoring meanings intro- spectionists disregarded a central aspect of the mind. Watson (Chapter 3) decried the use of introspection, and its problems helped to rally support for an objective psychology that studied only observable behavior (Heidbreder, 1933). Edward L. Thorndike, a prominent psychologist (Chapter 3), contended that education should be based on scientific facts, not opinions (Popkewitz, 1998). The ensuing emphasis on behavioral psychology domi- nated U.S. psychology for the first half of the twentieth century.

Another problem was that structuralists studied associations of ideas, but they had little to say about how these associations are acquired. Further, it was not clear that intro- spection was the appropriate method to study such higher mental processes as reasoning and problem solving, which are removed from immediate sensation and perception.

Functionalism. While Titchener was at Cornell, developments in other locales challenged the validity of structuralism. Among these was work by the functionalists. Functionalism is the view that mental processes and behaviors of living organisms help them adapt to their environments (Heidbreder, 1933). This school of thought flourished at the University of Chicago with John Dewey (1867–1949) and James Angell (1869–1949). An especially prominent functionalist was William James (1842–1910). Functionalism was the dominant American psychological perspective from the 1890s until World War I (Green, 2009).

James’s principal work was the two-volume series, The Principles of Psychology (1890), which is considered one of the greatest psychology texts ever written (Hall, 2003). An abridged version was published for classroom use (James, 1892). James was an em- piricist who believed that experience is the starting point for examining thought, but he was not an associationist. He thought that simple ideas are not passive copies of environ- mental inputs but rather are the product of abstract thought and study (Pajares, 2003).

James (1890) postulated that consciousness is a continuous process rather than a col- lection of discrete bits of information. One’s “stream of thought” changes as experiences change. “Consciousness, from our natal day, is of a teeming multiplicity of objects and re- lations, and what we call simple sensations are results of discriminative attention, pushed

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often to a very high degree” (Vol. I, p. 224). James described the purpose of conscious- ness as helping individuals adapt to their environments.

Functionalists incorporated James’s ideas into their doctrine. Dewey (1896) argued that psychological processes could not be broken into discrete parts and that consciousness must be viewed holistically. “Stimulus” and “response” describe the roles played by objects or events, but these roles could not be separated from the overall reality (Bredo, 2003). Dewey cited an example from James (1890) about a baby who sees a candle burning, reaches out to grasp it, and experiences burned fingers. From a stimulus–response perspective, the sight of the candle is a stimulus and reaching is a response; getting burned (pain) is a stimulus for the response of withdrawing the hand. Dewey argued that this sequence is better viewed as one large coordinated act in which seeing and reaching influence each other.

Functionalists were influenced by Darwin’s writings on evolution and studied the utility of mental processes in helping organisms adapt to their environments and survive (Bredo, 2003; Green, 2009). Functional factors were bodily structures, consciousness, and such cog- nitive processes as thinking, feeling, and judging. Functionalists were interested in how men- tal processes operate, what they accomplish, and how they vary with environmental condi- tions. They also saw the mind and body as interacting rather than existing separately.

Functionalists opposed the introspection method, not because it studied consciousness but rather because of how it studied consciousness. Introspection attempted to reduce con- sciousness to discrete elements, which functionalists believed was not possible. Studying a phenomenon in isolation does not reveal how it contributes to an organism’s survival.

Dewey (1900) argued that the results of psychological experiments should be appli- cable to education and daily life. Although this goal was laudable, it also was problematic because the research agenda of functionalism was too broad to offer a clear focus. This weakness paved the way for the rise of behaviorism as the dominant force in U.S. psy- chology (Chapter 3). Behaviorism used experimental methods, and it was psychology’s emphasis on experimentation and observable phenomena that helped to firmly secure its standing as a science (Asher, 2003; Tweney & Budzynski, 2000).

LEARNING THEORY AND RESEARCH Theory and research are integral to the study of learning. This section discusses some general functions of theory, along with key aspects of the research process.

Functions of Theory A theory is a scientifically acceptable set of principles offered to explain a phenomenon. Theories provide frameworks for interpreting environmental observations and serve as bridges between research and education (Suppes, 1974). Research findings can be orga- nized and systematically linked to theories. Without theories, people could view research findings as disorganized collections of data, because researchers and practitioners would have no overarching frameworks to which the data could be linked. Even when researchers obtain findings that do not seem to be directly linked to theories, they still must attempt to make sense of data and determine whether the data support theoretical predictions.

Introduction to the Study of Learning 11

Theories reflect environmental phenomena and generate new research through hypotheses, or assumptions, that can be empirically tested. Hypotheses often can be stated as if-then statements: “If I do X, then Y should occur,” where X and Y might be such events as “praise students for their progress in learning” and “raise their self-confidence and achievement,” respectively. Thus, we might test the hypothesis, “If we praise students when they make progress in learning, then they should display higher self-confidence and achievement than students who are not praised for their progress.” A theory is strengthened when hypotheses are supported by data. Theories may require revision if data do not support hypotheses.

Researchers often explore areas where there is little theory to guide them. In that case they formulate research objectives or questions to be answered. Regardless of whether researchers are testing hypotheses or exploring questions, they need to specify the research conditions as precisely as possible. Because research forms the basis for the- ory development and has important implications for teaching, the next section examines types of research and the process of conducting research.

Conducting Research To specify the research conditions, we need to answer such questions as: Who will par- ticipate? Where will the study be conducted? What procedures will be employed? What are the variables and outcomes to be assessed?

We must define precisely the phenomena we are studying. We provide conceptual definitions of phenomena and also define them operationally, or in terms of the opera- tions, instruments, and procedures we use to measure the phenomena. For example, we might define self-efficacy (covered in Chapter 4) conceptually as one’s perceived capabil- ities for learning or performing a task and operationally by specifying how we assess self-efficacy in our study (e.g., one’s score on a 30-item questionnaire). In addition to defining operationally the phenomena we study, we also must be precise about the procedure we follow. Ideally, we specify conditions so precisely that, after reading the description, another researcher could replicate our study.

Research studies that explore learning employ various types of paradigms (models). The following paragraphs describe the correlational, experimental, and qualitative para- digms, followed by a discussion of laboratory and field studies (Table 1.2).

Table 1.2 Learning research paradigms.

Type Qualities

Correlational Examines relations between variables

Experimental One or more variables are altered and effects on other variables are assessed

Qualitative Concerned with description of events and interpretation of meanings

Laboratory Project conducted in a controlled setting

Field Project conducted in a natural setting (e.g., school, home, work)

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Correlational Research. Correlational research deals with exploring relations that exist be- tween variables. A researcher might hypothesize that self-efficacy is positively correlated with (related to) achievement such that the higher the students’ self-efficacy, the higher they achieve. To test this relation, the researcher might measure students’ self-efficacy for solving mathematical problems and then assess how well they actually solve the problems. The re- searcher could statistically correlate the self-efficacy and achievement scores to determine the direction of the relation (positive, negative) and its strength (high, medium, low).

Correlational research helps to clarify relations among variables. Correlational find- ings often suggest directions for further research. If the researcher were to obtain a high positive correlation between self-efficacy and achievement, the next study might be an experiment that attempts to raise students’ self-efficacy for learning and determine whether such an increase produces higher achievement.

A limitation of correlational research is that it cannot identify cause and effect. A pos- itive correlation between self-efficacy and achievement could mean that (a) self-efficacy influences achievement, (b) achievement influences self-efficacy, (c) self-efficacy and achievement influence each other, or (d) self-efficacy and achievement are influenced by other, nonmeasured variables (e.g., parents, teachers). To determine cause and effect, an experimental study is necessary.

Experimental Research. In experimental research the researcher changes one or more (in- dependent) variables and determines the effects on other (dependent) variables. The ex- perimental researcher could form two groups of students, systematically raise self-efficacy beliefs among students in one group and not among students in the other group, and as- sess achievement in the two groups. If the first group performs better, the researcher might conclude that self-efficacy influences achievement. While the researcher alters vari- ables to determine their effects on outcomes, she or he must hold constant other variables that potentially can affect outcomes (e.g., learning conditions).

Experimental research can clarify cause-effect relations, which helps us understand the nature of learning. At the same time, experimental research often is narrow in scope. Researchers typically study only a few variables and try to minimize effects of others, which is difficult to do and often unrealistic. Classrooms and other learning settings are complex places where many factors operate at once. To say that one or two variables cause outcomes may overemphasize their importance. It is necessary to replicate experi- ments and examine other variables to better understand effects.

Qualitative Research. The qualitative research paradigm is characterized by intensive study, descriptions of events, and interpretation of meanings. The theories and methods used are referred to under various labels including qualitative, ethnographic, participant observation, phenomenological, constructivist, and interpretative (Erickson, 1986).

Qualitative research is especially useful when researchers are interested in the struc- ture of events rather than their overall distributions, when the meanings and perspectives of individuals are important, when actual experiments are impractical or unethical, and when there is a desire to search for new potential causal linkages that have not been dis- covered by experimental methods (Erickson, 1986). Research is varied and can range from analyses of verbal and nonverbal interactions within single lessons to in-depth

Introduction to the Study of Learning 13

observations and interviews over longer periods. Methods may include observations, use of existing records, interviews, and think-aloud protocols (i.e., participants talk aloud while performing tasks). It is not the choice of method that characterizes this approach— all of the aforementioned methods could be used in correlational or experimental stud- ies—but rather the depth and quality of data analysis and interpretation.

The qualitative researcher might be curious about how self-efficacy contributes to the development of skills over time. She or he might work with a small group of students for several months. Through observations, interviews, and other forms of data collection, the researcher might examine how students’ self-efficacy for learning changes in relation to skill refinement in reading, writing, and mathematics.

Qualitative research yields rich sources of data, which are more intensive and thorough than those typically obtained in correlational or experimental research. This model also can raise new questions and fresh perspectives on old questions that often are missed by traditional methods. A potential limitation is that qualitative studies typ- ically include only a few participants, who may not be representative of a larger pop- ulation of students or teachers. This limits generalization of findings beyond the research context. Another limitation is that data collection, analysis, and interpretation can be time consuming and therefore impractical for students wanting to graduate and professors wanting to build their publication records! Nonetheless, as a research model, this paradigm offers a useful approach for obtaining data typically not col- lected with other methods.

Laboratory and Field Research. Laboratory research is conducted in controlled settings, whereas field research is conducted where participants live, work, or attend school. During the first half of the twentieth century, most learning research was conducted on animals in laboratories. Today most learning research is conducted with people, and much is done in field settings. Any of the preceding research models (experimental, cor- relational, qualitative) can be applied in the laboratory or the field.

Laboratories offer a high degree of control over extraneous factors that can affect re- sults, such as phones ringing, people talking, windows to look out of, and other persons in the room who are not part of the study. Light, sound, and temperature can be regu- lated. Laboratories also allow researchers to leave their equipment set up over lengthy periods and have all materials at their immediate disposal.

Such control is not possible in the field. Schools are noisy, and often it is difficult to find space to work. There are numerous distractions: Students and teachers walk by, bells ring, public announcements are made, and fire drills are held. Rooms may be too bright or dark, cold or warm, and used for other purposes so researchers have to set up equipment each time they work. Interpreting results in light of these distractions can be a problem.

An advantage of field research is that results are highly generalizable to other similar settings because studies are conducted where people typically learn. In contrast, general- ization of laboratory findings to the field is done with less confidence. Laboratory re- search has yielded many important insights on learning, and researchers often attempt to replicate laboratory findings in the field.

Whether we choose the laboratory or the field depends on such factors as the pur- pose of the research, availability of participants, costs, and how we will use the results. If

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we choose the laboratory, we gain control but lose some generalizability, and vice versa if we choose the field. In the field, researchers try to minimize extraneous influences so that they can be more confident that their results are due to the factors they are studying.

ASSESSMENT OF LEARNING We know that learning is inferential; we do not observe it directly but rather through its products and outcomes. Researchers and practitioners who work with students may be- lieve that students have learned, but the only way to know is to assess learning’s products and outcomes.

Assessment involves “a formal attempt to determine students’ status with respect to ed- ucational variables of interest” (Popham, 2008, p. 6). In school, the educational variable of interest most often is student achievement in such areas as reading, writing, mathematics, science, and social studies. Although student achievement always has been critical, its im- portance was underscored by the federal government’s No Child Left Behind Act of 2001 (Shaul & Ganson, 2005). This act has many provisions (Popham, 2008). Among the most significant are the requirements for annual testing of students in grades 3 through 8 and again in high school in reading and mathematics and for school systems to show increases in students making adequate yearly progress in these subjects.

Two points are noteworthy with respect to this text. Although accountability often leads to testing being the means of assessment, the latter includes many measurement procedures besides testing (described below). Researchers and practitioners want to know whether learning has occurred, and there may be procedures other than testing that provide evidence of student learning. Second, students’ skills in content areas often are the learning outcome assessed, but researchers and practitioners may also be inter- ested in other forms of learning. For example, they may want to know whether students have learned new attitudes or self-regulation strategies or whether students’ interests, val- ues, self-efficacy, and motivation have changed as a result of content learning.

This section covers ways to assess the products or outcomes of learning. These methods include direct observations, written responses, oral responses, ratings by others, and self-reports (Table 1.3).

Direct Observations Direct observations are instances of student behavior that we observe to assess whether learning has occurred. Teachers employ direct observations frequently. A chemistry teacher wants students to learn laboratory procedures. The teacher observes students in the laboratory to determine whether they are implementing the proper procedures. A physical education instructor observes students dribble a basketball to assess how well they have learned the skill. An elementary teacher gauges how well students have learned the classroom rules based on their class behavior.

Direct observations are valid indexes of learning if they are straightforward and involve little inference by observers. They work best when the behaviors can be specified and then the students can be observed to ascertain whether their behaviors match the standard.

Introduction to the Study of Learning 15

A problem with direct observations is that they focus only on what can be observed and therefore bypass the cognitive and affective processes that underlie actions. For example, the chemistry teacher knows that students have learned laboratory procedures but she or he does not know what the students are thinking about while they are per- forming the procedures or how confident they are about performing well.

A second problem is that, although directly observing a behavior indicates that learn- ing has occurred, the absence of appropriate behavior does not mean that learning has not occurred. Learning is not the same as performance. Many factors other than learning can affect performance. Students may not perform learned actions because they are not motivated, are ill, or are busy doing other things. We have to rule out these other factors to conclude from the absence of performance that learning has not occurred. That re- quires making the assumption—which at times may be unwarranted—that since students usually try to do their best, if they do not perform, they have not learned.

Written Responses Learning often is assessed based on students’ written responses on tests, quizzes, home- work, term papers, and reports. Based on the level of mastery indicated in the responses, teachers decide whether adequate learning has taken place or whether additional in- struction is needed because students do not fully comprehend the material. For example, assume that a teacher is planning a unit on the geography of Hawaii. Initially the teacher assumes that students know little about this topic. A pretest given prior to the start of in- struction will support the teacher’s belief if the students score poorly. The teacher retests students following the instructional unit. Gains in test scores lead the teacher to conclude that learners have acquired some knowledge.

Table 1.3 Methods of assessing learning.

Category Definition

Direct observations Instances of behavior that demonstrate learning

Written responses Written performances on tests, quizzes, homework, papers, and projects

Oral responses Verbalized questions, comments, and responses during learning

Ratings by others Observers’ judgments of learners on attributes indicative of learning

Self-reports People’s judgments of themselves

■ Questionnaires Written ratings of items or answers to questions

■ Interviews Oral responses to questions

■ Stimulated recalls Recall of thoughts accompanying one’s performances at given times

■ Think-alouds Verbalizing aloud one’s thoughts, actions, and feelings while performing a task

■ Dialogues Conversations between two or more persons

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Their relative ease of use and capacity for covering a wide variety of material makes written responses desirable indicators of learning. We assume that written responses re- flect learning, but many factors can affect performance of behavior even when students have learned. Written responses require us to believe that students are trying their best and that no extraneous factors (e.g., fatigue, illness, cheating) are operating such that their written work does not represent what they have learned. We must try to identify ex- traneous factors that can affect performance and cloud assessments of learning.

Oral Responses Oral responses are an integral part of the school culture. Teachers call on students to an- swer questions and assess learning based on what they say. Students also ask questions during lessons. If their questions indicate a lack of understanding, this is a signal that proper learning has not occurred.

Like written responses, we assume that oral responses are valid reflections of what stu- dents know, which may not always be true. Further, verbalization is a task, and there may be problems translating what one knows into its oral expression due to unfamiliar termi- nology, anxiety about speaking, or language difficulties. Teachers may rephrase what stu- dents say, but such rephrasing may not accurately reflect the nature of students’ thoughts.

Ratings by Others Another way to assess learning is for individuals (e.g., teachers, parents, administrators, researchers, peers) to rate students on the quantity or quality of their learning. These ratings by others (e.g., “How well can Timmy solve problems of the type 52 � 36 � ?” “How much progress has Alicia made in her printing skills in the past 6 months?”) provide useful data and can help to identify students with exceptional needs (e.g., “How often does Matt need extra time to learn?” “How quickly does Jenny finish her work?”).

An advantage of ratings by others is that observers may be more objective about stu- dents than students are about themselves (self-reports, discussed next). Ratings also can be made for learning processes that underlie actions (e.g., comprehension, motivation, at- titudes) and thereby provide data not attainable through direct observations; for example, “How well does Seth comprehend the causes of World War II?” But ratings by others re- quire more inference than do direct observations. It may be problematic to accurately rate students’ ease of learning, depth of understanding, or attitudes. Further, ratings require observers to remember what students do and will be distorted when raters selectively re- member only positive or negative behaviors.

Self-Reports Self-reports are people’s assessments of and statements about themselves. Self-reports take various forms: questionnaires, interviews, stimulated recalls, think-alouds, and dialogues.

Questionnaires present respondents with items or questions asking about their thoughts and actions. Respondents may record the types of activities they engage in, rate their perceived levels of competence, and judge how often or how long they engage in

Introduction to the Study of Learning 17

them (e.g., “How long have you been studying Spanish?” “How difficult is it for you to learn geometric theorems?”). Many self-report instruments ask respondents to record rat- ings on numerical scales (“On a 10-point scale, where 1 � low and 10 � high, rate how good you are at reducing fractions.”).

Interviews are a type of questionnaire in which an interviewer presents the questions or points to discuss and the respondent answers orally. Interviews typically are conducted individually, although groups can be interviewed. A researcher might describe a learning context and ask students how they typically learn in that setting (e.g., “When the French teacher begins a lesson, what are your thoughts? How well do you think you will do?”). Interviewers may need to prompt respondents if replies are too brief or not forthcoming.

In the stimulated recall procedure, people work on a task and afterward recall their thoughts at various points during the task. Interviewers query them (e.g., “What were you thinking about when you got stuck here?”). If the performance was videotaped, respon- dents subsequently watch it and recollect, especially when interviewers stop the record- ing and ask questions. It is imperative that the recall procedure be accomplished soon after the performance so that participants do not forget their thoughts.

Think-alouds are procedures in which students verbalize their thoughts, actions, and feelings while working on a task. Verbalizations may be recorded by observers and subse- quently scored for level of understanding. Think-alouds require that respondents verbalize; many students are not used to talking aloud while working in school. Talking aloud may seem awkward to some, and they may feel self-conscious or otherwise have difficulty ex- pressing their thoughts. Investigators may have to prompt students if they do not verbalize.

Another type of self-report is the dialogue, which is a conversation between two or more persons while engaged in a learning task. Like think-alouds, dialogues can be recorded and analyzed for statements indicating learning and factors that seem to affect learning in the setting. Although dialogues use actual interactions while students are working on a task, their analysis requires interpretation that may go beyond the actual el- ements in the situation.

The choice of self-report measure should match the purpose of the assessment. Questionnaires can cover a lot of material; interviews are better for exploring a few issues in depth. Stimulated recalls ask respondents to recall their thoughts at the time actions took place; think-alouds examine present thoughts. Dialogues allow for investigation of social interaction patterns.

Self-report instruments typically are easy to develop and administer; questionnaires are usually easy to complete and score. A problem can arise when inferences have to be drawn about students’ responses. It is essential to have a reliable scoring system. Other concerns about self-reports are whether students are giving socially acceptable answers that do not match their beliefs, whether self-reported information corresponds to actual behavior, and whether young children are capable of self-reporting accurately. By guar- anteeing that data are confidential, researchers can help promote truthful answering. A good means of validating self-reports is to use multiple assessments (e.g., self-reports, di- rect observations, oral and written responses). There is evidence that beginning around the third grade self-reports are valid and reliable indicators of the beliefs and actions they are designed to assess (Assor & Connell, 1992), but researchers need to use self-reports cautiously to minimize potential problems.

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RELATION OF LEARNING AND INSTRUCTION Historical Perspective We have seen how theories and research findings help to advance the field of learning. Their ultimate contribution, however, must be to improve teaching that promotes learn- ing. Although it may seem odd, historically there was little overlap between the fields of learning and instruction (Shuell, 1988). One reason for this lack of integration may have been that these fields traditionally were dominated by persons with different interests. Most learning theorists and researchers have been psychologists. Much early learning re- search used nonhuman species. Animal research has benefits, but animals do not allow for proper exploration of instructional processes. In contrast, instruction was the domain of educators, who were primarily concerned with directly applying teaching methods to classrooms and other learning settings. This applied focus has not always lent itself well to exploring how learning processes are affected by instructional variations.

A second reason for lack of integration of learning with instruction derives from the common belief that teaching is an art and not a science like psychology. As Highet (1950) wrote: “[This book] is called The Art of Teaching because I believe that teaching is an art, not a science. It seems to me very dangerous to apply the aims and methods of science to human beings as individuals” (p. vii). Highet stated, however, that teaching is insepa- rable from learning. Good teachers continue to learn about their subject areas and ways to encourage student learning.

Gage (1978) noted that the use of “art” in reference to teaching is a metaphor. As a way to understand and improve teaching, the “art of teaching” has received inadequate attention. Teaching as an art can become the object of the same type of scrutiny and sci- entific investigation as any other type of art, including drawing, painting, and musical composition. Thus, teaching can be improved through scientific study.

A third possible reason stems from the idea that different theoretical principles may govern the two domains. Sternberg (1986) contended that cognition (or learning) and in- struction require separate theories. This may be true for learning and instruction by them- selves, but as Shuell (1988) noted: “Learning from instruction differs from traditional con- ceptions of learning and teaching considered separately” (p. 282). Learning from instruction involves an interaction between learners and contexts (e.g., teachers, materi- als, setting), whereas much psychological learning research is less context dependent. Sequencing of material, for example, affects learners’ cognitive organizations and devel- opment of memory structures. In turn, how these structures develop affects what teachers do. Teachers who realize that their instruction is not being comprehended will alter their approach; conversely, when students understand material that is being presented, teachers are apt to continue with their present approach.

Fourth, traditional research methods may be inadequate to study instruction and learning simultaneously. Process–product research conducted in the 1970s and 1980s re- lated changes in teaching processes (such as number and type of questions asked, amount of warmth and enthusiasm displayed) to student products or outcomes (e.g., achievement, attitudes; Pianta & Hamre, 2009). Although this research paradigm pro- duced many useful results, it neglected the important roles of teacher and student

Introduction to the Study of Learning 19

■ Learners progress through stages/phases

■ Material should be organized and presented in small steps

■ Learners require practice, feedback, and review

■ Social models facilitate learning and motivation

■ Motivational and contextual factors influence learning

thoughts. Thus, we might know which type of questions produce higher student achieve- ment, but not why they do so (i.e., how questions change students’ thinking). Process–product research also focused primarily on student achievement at the expense of other outcomes relevant to learning (e.g., expectations, values). In short, a process–product model is not well designed to examine how students learn.

At the same time, much learning research has used experimental methods in which some conditions are varied and changes in outcomes are determined. Teaching methods often are held constant across changes in variables, which negates the potential effects of the former.

Fortunately, the situation has changed. Researchers increasingly are viewing teach- ing as the creation of learning environments that assist students in executing the cogni- tive activities necessary to develop skills and reasoning abilities (Floden, 2001). Researchers are examining student learning by observing teaching during content in- struction, especially in schools and other places where people typically learn (Pellegrino, Baxter, & Glaser, 1999; Pianta & Hamre, 2009). Researchers today are more concerned with analyzing teaching patterns rather than discrete teaching behaviors (Seidel & Shavelson, 2007). Children’s learning has received increased attention (Siegler, 2000, 2005), and more research is being devoted to how what is learned in school is re- lated to what skills are important outside of school (Anderson, Reder, & Simon, 1996). Researchers of different traditions accept the idea that instruction and learning interact and are best studied in concert. Instructional research can have a profound impact on learning theories and their applications to promote student learning (Glaser, 1990; Glaser & Bassok, 1989; Pianta & Hamre, 2009).

Instructional Commonalities Regardless of perspective, most learning theories share principles that are predicted to enhance learning from instruction (Table 1.4). One principle is that learners progress through stages or phases of learning that can be distinguished in various ways, such as in terms of progressive skill levels: novice, advanced beginner, competent, proficient, expert (Shuell, 1990). Processes and behaviors often used in such classifications include speed and type of cognitive processing, ability to recognize problem formats, proficiency in dealing with problems that arise, organization and depth of knowledge structures, and ability to monitor performance and select strategies depending on personal and contex- tual factors.

Table 1.4 Instructional principles common to diverse learning theories.

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