Experimental Psychology [1 ed.] 9788120345164, 8120345169

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EXPERIMENTAL PSYCHOLOGY

Hardeep Kaur Shergill Consultant Counsellor and Psychotherapist and Former Faculty, Trinity College Jalandhar, Punjab

Delhi-110092 2012

EXPERIMENTAL PSYCHOLOGY Hardeep Kaur Shergill © 2012 by PHI Learning Private Limited, Delhi. All rights reserved. No part of this book may be reproduced in any form, by mimeograph or any other means, without permission in writing from the publisher. ISBN-978-81-203-4516-4 The export rights of this book are vested solely with the publisher. Published by Asoke K. Ghosh, PHI Learning Private Limited, 111, Patparganj Industrial Estate, Delhi110092 and Printed by Raj Press, New Delhi-110012.

To My father S. Balbir Singh Shergill and My daughter Harnoor Shergill with love

Contents PREFACE...........XIII ACKNOWLEDGEMENTS............XV

PART A 1. EXPERIMENTAL METHOD............3 – 25 Introduction..........3 1.1 Brief History of Experimental Psychology..........3 1.2 Early Experimental Psychology..........7 1.2.1 The 20th Century Scenario..........8 1.2.2 Methodology..........9 1.2.3 Experiments..........9 1.2.4 Other Methods..........9 1.2.5 Criticism..........10

1.3 The Experimental Method..........10 1.3.1 Some Definitions of an Experiment..........10 1.3.2 Variable..........12 1.3.3 Experimental and Controlled Conditions or Groups..........14 1.3.4 Control of Variables..........15 1.3.5 Confounding Variables..........16 1.3.6 Advantages of the Experimental Method..........17 1.3.7 Disadvantages of the Experimental Method..........17

1.4 S—O—R Framework..........17 Questions..........19 References..........20 2. VARIABLES............26 – 33

Introduction..........26 2.1 Some Definitions of a Variable..........26 2.2 Types of Variables..........27 2.2.1 Stimulus Variables or Input or Independent Variables (IVs)..........27 2.2.2 Organismic Variables or O-variables or Throughput or Intervening Variables..........27 2.2.3 Response Variables or Output Variables or Behaviour Variables or Dependent Variables..........28

2.3 Process of Experimentation..........29 2.4 Research or Experimental Designs..........30 2.4.1 Single-group or Within-subjects Experimental Design..........30 2.4.2 Separate Group or Between Subjects Experimental Design..........31

Questions..........31 References..........32 3. SENSATION............34 –79 Introduction..........34 3.1 Some Definitions of Sensation..........34 3.2 Nature of Sensation or Characteristics of Sensation..........37 3.3 Attributes of Sensations..........37 3.4 Types of Sensation..........38 3.4.1 Organic or Bodily Sensations..........38 3.4.2 Special Sensations..........39 3.4.3 Visual Sensation or the Sensation of Vision or Sight..........40 3.4.4 Auditory Sensation..........49 3.4.5 The Cutaneous Sensation..........55 3.4.6 The Olfactory Sensation or Sensation of Smell..........59 3.4.7 Gustatory Sensation or Sensation of Taste..........64

3.5 Beyond Our Five Senses..........70 Questions..........70 References..........73 4. PERCEPTUAL PROCESSES............80 –142 Introduction..........80 4.1 Sensation and Perception..........81 4.2 Some Definitions of Perception..........82 4.3 Characteristics of Perception..........83 4.4 Selective Perception/Attention..........85 4.5 The Role of Attention in Perceptual Processing or Selective Attention..........87 4.6 Factors Affecting Perception or Psychological and Cultural

Determinants of Perception..........89 4.6.1 Psychological or Internal Factors..........89 4.6.2 Cultural Factors..........94

4.7 Laws of Perception or Gestalt Grouping Principles..........97 4.7.1 Limitations of Gestalt Laws of Organisation..........100

4.8 Perception of Form..........100 4.8.1 Figure–Ground Differentiation in Perception..........101 4.8.2 Gestalt Grouping Principles..........102

4.9 Perceptual Set..........105 4.9.1 Factors Affecting Set..........106

4.10 Perception of Movement..........108 4.10.1 Image–Retina and Eye–Head Movement System..........108 4.10.2 Apparent Movement..........108 4.10.3 Induced Movement..........109 4.10.4 Auto-kinetic Movement..........110

4.11 Perception of Space..........110 4.11.1 Monocular and Binocular Cues for Space Perception..........111

4.12 Perceptual Constancies—Lightness, Size, and Shape..........118 4.12.1 Lightness Constancy..........119 4.12.2 Size Constancy..........120 4.12.3 Shape Constancy..........121

4.13 Illusions—Types, Causes, and Theories..........123 4.13.1 Types of Illusions..........124

Questions..........131 References..........133 5. STATISTICS............143 –174 Introduction..........143 5.1 Normal Probability Curve (NPC) or Normal Curve or Normal Distribution Curve or Bell Curve..........143 5.1.1 Basic Principles of Normal Probability Curve (NPC)..........145 5.1.2 Properties or Characteristics of the Normal Probability Curve (NPC)..........147 5.1.3 Causes of Divergence from Normality..........149 5.1.4 Measuring Divergence from Normality..........150 5.1.5 Applications of the Normal Probability Curve (NPC)..........151

5.2 Correlation or Coefficient of Correlation..........157 5.2.1 Some Definitions of Correlation..........158 5.2.2 Characteristics or Properties of Correlation..........160 5.2.3 Methods of Correlation..........162

Questions..........170 References..........174

PART B 6. PSYCHOPHYSICS............177–194 Introduction..........177 6.1 Some Definitions of Psychophysics..........178 6.2 The Threshold..........178 6.3 Psychophysical Methods..........182 6.3.1 Method of Limits..........182 6.3.2 Method of Constant Stimuli..........186 6.3.3 Method of Average Error..........190

Questions..........192 References..........194 7. LEARNING ............ 195 – 227 Introduction..........195 7.1 Some Definitions of Learning..........195 7.2 Characteristics Features of the Learning Process..........196 7.3 Factors Affecting Learning..........198 7.4 Conditioning..........199 7.4.1 Factors Affecting Conditioning..........199 7.4.2 Classical Conditioning or Pavlovian or Simple or Respondent Conditioning..........200 7.4.3 Instrumental or Operant Conditioning..........206 7.4.4 Types of Reinforcement..........210 7.4.5 Reinforcement Schedules or Schedules of Reinforcement..........211 7.4.6 Classical and Operant Conditioning: A Comparison..........212

7.5 Transfer of Training..........214 7.5.1 Types of Transfer of Training..........214

7.6 Skill Learning..........215 7.6.1 Types of Skills..........215 7.6.2 Fitts and Posner’s Theory..........216 7.6.3 Schmidt’s Schema Theory..........216 7.6.4 Adam’s Closed Loop Theory..........216

7.7 Transfer of Learning..........217 7.7.1 Effects of Transfer of Learning..........217 7.7.2 How do We Assess Skill Performance?..........217 7.7.3 How are Faults Caused?..........218 7.7.4 Strategies and Tactics..........218

7.8 Learning Skills: 3 Key Theories..........218 7.8.1 Classical Conditioning..........219 7.8.2 Operant Conditioning..........219 7.8.3 Vicarious Learning or Modelling..........220

Questions..........221

References..........223 8. MEMORY ............ 228 – 286 Introduction..........228 8.1 Some Definitions of Memory..........229 8.2 The Process of Memorising or the Three Stages of Memory..........230 8.3 Types of Memory..........233 8.3.1 Sensory or Immediate Memory or Sensory Register or Sensory Stores..........233 8.3.2 Short-term and Long-term Memory..........234 8.3.3 Models of Memory..........238 8.3.4 Classification by Information Type..........240 8.3.5 Classification by Temporal Direction..........241 8.3.6 Physiology..........241

8.4 Concept of Mnemonics or Techniques of Improving Memory..........242 8.4.1 Method of Loci..........243 8.4.2 Key Word Method..........245 8.4.3 Use of Imagery or Forming Mental Images or Pictures in Our Minds..........245 8.4.4 Organisational Device..........246 8.4.5 First Letter Technique or Acronym Method..........246 8.4.6 Narrative Technique..........246 8.4.7 Method of PQRST..........247 8.4.8 The SQ3R Method..........247 8.4.9 Schemas..........248

8.5 Reconstructive Memory..........249 8.6 Explicit Memory and Implicit Memory: Definitions..........251 8.6.1 The Differentiation..........252

8.7 Eyewitness Memory or Testimony..........256 8.7.1 Fragility of Memory..........257 8.7.2 Leading Questions..........257 8.7.3 Hypnosis..........258 8.7.4 Confirmation Bias..........258 8.7.5 Violence..........258 8.7.6 Psychological Factors..........258

8.8 Methods of Retention..........262 8.8.1 Paired-associate Learning..........262 8.8.2 Serial Learning..........262 8.8.3 Free Recall..........262 8.8.4 Recognition..........263

8.9 Forgetting..........263 8.9.1 Some Definitions of Forgetting..........263 8.9.2 Types of Forgetting..........264 8.9.3 Reasons for Forgetting..........264 8.9.4 Factors Affecting Forgetting..........268

8.10 Motivated Forgetting or Repression..........269

8.11 Tips for Memory Improvements..........269 8.11.1 Brain Exercises..........270 8.11.2 General Guidelines to Improve Memory..........270 8.11.3 Healthy Habits to Improve Memory..........271 8.11.4 Nutrition and Memory Improvement..........271

Questions..........272 References..........275 9. THINKING AND PROBLEM-SOLVING............287–347 Introduction..........287 9.1 Some Definitions of Thinking..........287 9.2 Characteristics of Thinking..........290 9.3 Types of Thinking..........291 9.4 Tools or Elements of Thought or Thinking..........292 9.5 Characteristics of Creative Thinkers..........293 9.6 Problem..........296 9.6.1 Problem Types..........297 9.6.2 Characteristics of Difficult Problems..........299

9.7 Problem-solving..........300 9.7.1 Some Definitions of Problem-solving..........301 9.7.2 Strategies Technique for Effective Problem-solving..........305 9.7.3 Barriers to Effective Problem-solving..........308 9.7.4 Overcoming Barriers with Creative Problem-solving..........311 9.7.5 Phases in Problem-solving..........312 9.7.6 Steps in Problem-solving..........314 9.7.7 Stages in Problem-solving..........314 9.7.8 Steps of Creative Problem-solving Process..........316 9.7.9 Factors Affecting Problem-solving..........317 9.7.10 Tips on Becoming a Better Problem Solver..........322

9.8 Concept Attainment..........323 9.9 Reasoning..........324 9.9.1 Some Definitions of Reasoning..........325 9.9.2 Deductive Reasoning..........325 9.9.3 Inductive Reasoning..........328

9.10 Language and Thinking..........331 Questions..........333 References..........336 SYLLABUS OF B.A AND T.D.C. PART II..........349 – 351 INDEX............353 – 360

Preface Experimental psychology is a methodological approach rather than a subject and encompasses varied fields within psychology. Experimental psychologists have traditionally conducted research, published articles, and taught classes on neuroscience, developmental psychology, sensation, perception, attention, consciousness, learning, memory, thinking, and language. Recently, however, the experimental approach has extended to motivation, emotion, and social psychology. Experimental psychology is the study of psychological issues that uses experimental procedures. The concern of experimental psychology is discovering the processes underlying behaviour and cognition. Experimental psychologists conduct research with the help of experimental methods. This book is divided into two parts and the subject matter has been organised in nine chapters. The contents of various chapters are based on the researches in the area of Experimental Psychology. Starting with an introduction to the meaning, nature, and methods of Experimental Psychology, the book goes on to explore the various aspects of human behaviour in the outlook of experimental psychology. A greater focus is on the nature and theories of sensation, perception, learning, psychophysics, memory and forgetting, and transfer of training. The importance of cognitive aspect of human behaviour is also highlighted through discussions on topics related to thinking, reasoning, and problem-solving. The text provides an essential knowledge and skill for the use of statistics in organising data and computing statistics like computation of correlation using rank difference and

product moment methods and dealing with the concept of Normal Probability Curve for its analysis. I have worked to present the contents in a simple, clear, easy-tounderstand, and illustrative manner. The text is adequately illustrated with examples, figures, and tables for helping the readers in their understanding of the topics. All topics covered in the text are informed and supplemented by the most recent information available. The goal of this book has been to produce the most accessible and comprehensive textbook. For those who wish to make an advanced study of the subject, I have compiled references at the end of each chapter. I earnestly hope that this book will be of great use to all students who want to venture into the field of Experimental Psychology. However, it may be particularly useful for the students of B.A. / T.D.C. Part II of Guru Nanak Dev University and other universities. The contents of the book take full account of the syllabus of B.A. / T.D.C. Part II of Guru Nanak Dev University, Amritsar, and also includes Questions. The questions provided in the question-sections are frequently asked in the examinations conducted by the Guru Nanak Dev University. A knowledge of the answers to these questions can help the students to achieve success in the examination. I wish the very best to the readers. Hardeep Kaur Shergill

Acknowledgements This book is very affectionately dedicated to my daughter Harnoor Shergill and my father S. Balbir Singh Shergill, without whose inspiration, this work would not have been possible. I am greatly indebted to my near and dear ones for their enormous encouragement and support. I would like to extend special thanks to PHI Learning, New Delhi for publishing this book. Hardeep Kaur Shergill

PART A Chapter 1: Experimental Method Chapter 2: Variables Chapter 3: Sensation Chapter 4: Perceptual Processes Chapter 5: Statistics

1 Experimental Method INTRODUCTION Experimental psychology is a methodological approach rather than a subject and encompasses varied fields within psychology. Experimental psychologists have traditionally conducted research, published articles, and taught classes on neuroscience, developmental psychology, sensation, perception, attention, consciousness, learning, memory, thinking, and language. Recently, however, the experimental approach has extended to motivation, emotion, and social psychology. Experimental psychology is the study of psychological issues that uses experimental procedures. The concern of experimental psychology is discovering the processes underlying behaviour and cognition. Experimental psychologists conduct research with the help of experimental methods.

1.1 BRIEF HISTORY OF EXPERIMENTAL PSYCHOLOGY Experimental Psychology can well be understood by studying the history of those who were the forerunners in this field.

Ernst Heinrich Weber (1795–1878)

Ernst Heinrich Weber, the German anatomist (physiologist) and a psychologist. He is considered the founder of experimental psychology, and also called the founder of sensation, physiology, and psychophysics. Weber is best known for his work on sensory response to weight, temperature, and pressure. In 1834, he conducted research on the lifting of weights. From his researches, he discovered that the experience of the differences in the intensity of sensations depends on percentage differences in the stimuli rather than absolute differences. This is known as the just-noticeable difference (j.n.d), difference threshold or limen. He formulated the first principle of psychophysics and named it “Just Noticeable Difference (JND)”. He explained the qualitative relationship between stimulus and response, called Weber’s law. The work was published in Der Tastsinn Und das Gemingefuhl (1851; The Sense of Touch and the Common Sensibility) and was given mathematical expression by Weber’s student Gustav Theodor Fechner as the Weber-Fechner law.

Gustav Theodor Fechner (1801–1887)

Gustav Theodor Fechner (April 19, 1801-November 28, 1887) was a German experimental psychologist. An early pioneer in experimental psychology and founder of psychophysics, he inspired many 20th century scientists and philosophers. He is also credited with demonstrating the nonlinear relationship between psychological sensation and the physical intensity of a stimulus. He had found out what amount of physical energy can create different intensity of sensation. Fechner did excellent work in the field of psychophysics. He modified Weber’s experiments. He “rediscovered” Weber’s notion of differential threshold. He formalised Weber’s law and saw it as a way to unite body and mind (sensation and perception), bringing together the day view and the night view, reconciling them.

Hermann Von Helmholtz (1821–1894)

Hermann Von Helmholtz was a German physicist and a physiologist who made significant contributions to several widely varied areas of modern science. He did most prestigious work in the field of the physiological psychology of sensation. In physiology and psychology, he is known for his mathematics of the eye, theories of vision, ideas on the visual perception of space, colour vision research, and on the sensation of tone, perception of sound, and empiricism. As a philosopher, he is known philosophy of science, ideas on the relation between the laws of perception and the laws of nature, the science of aesthetics, and ideas on the civilising power of science. He measured the rate of the nervous impulse. He had modified the ThomasYoung’s theory of colour vision, which is today known as “YoungHelmholtz” colour vision theory. Thomas Young in 1801 proposed theory of colour vision called Trichromatic theory. According to this theory, there are basically three colours—Red, Green, and Blue. Thomas Young, an English physicist, concluded that mixing of three lights Red, Green, and Blue is enough to produce all combinations of colours visible to a normal human eye. German physiologist Hermann Von Helmholtz elaborated Young’s theory with certain modifications and re-propounded or re-proposed it in 1852. Helmholtz proposed that our eye possesses three types of cones in retina responding to the three primary colours which, according to this theory are Red, Green, and Blue. These cones are labeled as R-cones, G-cones, and B-cones respectively. According to this theory, colour blindness is the weakening or complete absence of these three types of cones.

Sir Francis Galton (1822–1911)

The development of Experimental Psychology particularly in the field of individual differences started with the contribution of Sir Francis Galton. His main contribution was in the methodology of Psychology. He was the first psychologist who had constructed psychological tests for measuring intelligence and mental abilities. He had also formulated the first test laboratory in London in 1882, and invented the scattergram (precedent for the coefficient of correlation, which his friend, Karl Pearson developed) as a way to express the relationship between two dimensions. He was the first psychologist who applied questionnaire method for studying psychological traits. His main contribution was the application of Normal Probability Curve (NPC) in the analysis of psychological data, and he was the first to apply the normal curve to human traits. He studied the normal curve extensively using a device he invented, called the quincunx. Hereditary Genius (1869) is his best known work. He suggested that fingerprints be used for personal identification and devised a test called Galton’s Word Association Test. He also conducted study of mental imagery.

Wilhelm Wundt (1832–1920)

Wilhelm Wundt was a psychologist, a physiologist, and a psychophysicist. He is called the Founder or Father of Modern Psychology and the first man who without reservation is properly called a psychologist (Boring, 1969). In

his first world recognised Experimental laboratory at Leipzig (Germany) in 1879, he did experiments on sensations, emotions, reaction time, feelings, ideas, psychophysics, etc. His main contribution in psychology was recognition of psychology as a science and he did work scientifically in his laboratory and studied several psychological problems experimentally. He wrote the first Psychology textbook, “Principles of Physiological Psychology” in 1874.

Hermann Ebbinghaus (1850–1909)

Hermann Ebbinghaus was the first social scientist to conduct first experimental study on memory and learning process. He did several experiments on himself at first by using the nonsense syllables. In fact, he was the first to introduce nonsense syllables in memory experiments. Even today, “Ebbinghaus Curve of Forgetting” is greatly considered.

James Mc Keen Cattell (1860–1944)

James Mc Keen Cattell did researches in the field of Reaction time and Associations. For the measurement of perception, he had invented an instrument called Tachistoscope. He constructed several tests for the measurement of individual differences (personality, intelligence, creativity, aptitudes, attitudes, and level of aspiration) and mental abilities. He had also worked in the field of sensation and psychophysics.

Oswald Kulpe (1862–1915)

Oswald Külpe (August 3, 1862–December 30, 1915) was one of the structural psychologists of the late 19th and early 20th century. He was the assistant and student of Wilhelm Wundt. He was influenced strongly by his mentor Wilhelm Wundt, but later disagreed with Wundt on the complexity of human consciousness that could be studied. In 1893, his first book was published entitled Outlines of Psychology. Kulpe and his associates (students) did experimental work on thinking, memory, and judgment. His main finding, known as imageless thought seemed to be that thoughts can occur without a particular sensory or imaginal content.

Ivan Petrovich Pavlov (1849–1936)

Ivan Pertrovich Pavlov conducted scientific research, first on the physiology of the digestive system (for which he was awarded Noble prize in 1904) and later on conditioned reflexes.

John Brodaeus Watson (1878–1958)

John Brodaeus Watson was the Founder or the Father of behaviourism school, and due to the publicity of this school, consciousness and introspection method had been eliminated from Psychology. Introspection had been labeled “superstitious” by John Watson, the founder of behaviourism. Watson, Edward C. Tolman (1886 –1959), Clark H. Hull (1884 –1952), Edward Lee Thorndike (1874 –1949), and B.F. Skinner (1904 –1990) had conducted several learning experiments in the field of animal psychology and formulated laws of learning. Karl S. Lashley (1890 –1958) conducted experimental studies on the structure of the brain.

In the history of Psychology, the year 1912 has been considered as a revolutionary year because it was in this year that Watson came with his behaviourism. Controversy between Structuralism (Wilhelm Wundt, 1832– 1920, Edward Bradford Titchener, 1867–1927) and Functionalism (William James) was resolved. Edward Lee Thorndike, and Ivan Petrovich Pavlov’s “Modern Associationism” attained popularity and a new era started in the field of psychoanalysis, due to the conflict between Sigmund Freud (1856– 1939) and his associates—Carl Gustav Jung (1875–1961) and Alfred Adler (1870–1937), the school of Gestalt psychology started.

Gestalt psychologists deserve a special consideration in the field of experimental psychology. Max Wertheimer (1880–1943), Wolfgang Kohler (1887–1967), Kurt Koffka (1886–1941) had formulated Insight theory in learning on the basis of their experimental studies in the field of Experimental Psychology. Wertheimer and Koffka had also conducted experimental studies in the field of perception.

Kurt Lewin (1890–1947) also belonged to this school and had significantly contributed in the field of experimental child psychology and on the basis of his experimental research, formulated “Field Theory”.

Kurt Lewin (1890–1947)

Jean Piaget was one of the most influential psychologists of the twentieth century. He published his first paper (a short note on an albino sparrow) at the age of 11. In 1920, he undertook research on intelligence testing, leading to fascination with the reasons for those children suggested for their answers to standard test items. This resulted in some 60 years’ ingenious research into the development of children’s thinking. In 1955, Piaget established the International Centre for Genetic Epistemology in Geneva.

Jean William Fritz Piaget (1896–1980)

1.2 EARLY EXPERIMENTAL PSYCHOLOGY Experimental psychology emerged as a modern academic discipline in the nineteenth century when Wilhelm Wundt introduced a mathematical and experimental approach to the field. Wundt founded the first psychology laboratory in Leipzig, Germany. Other early experimental psychologists, including Hermann Ebbinghaus and Edward Bradford Titchener, included introspection among their experimental methods.

George Trumbull Ladd (1842–1921)

Experimental psychology was introduced into the United States by George Trumbull Ladd, who founded Yale University psychological laboratory in 1879. In 1887, he published Elements of Physiological Psychology, the first American textbook to include a substantial amount of information on the new experimental form of the discipline. Between Ladd’s founding of the Yale

Laboratory and his textbook, the center of experimental psychology in the USA shifted to Johns Hopkins University, where George Hall and Charles Sanders Peirce was extending and qualifying the Wundt’s work.

Charles Sanders Peirce (1839–1914)

Joseph Jastrow (1863–1944)

With his student Joseph Jastrow (1863–1944), Charles Sanders Peirce randomly assigned volunteers to a blinded, repeated-measures design to evaluate their ability to discriminate weights. Peirce’s experiment inspired other researchers in psychology and education, which developed a research tradition of randomized experiments in laboratories and specialized textbooks in the eighteen-hundreds. The Peirce-Jastrow experiments were conducted as part of Peirce’s pragmatic program to understand human perception and other studies considered perception of light. While Peirce was making advances in experimental psychology and psychophysics, he was also developing a theory of statistical inference, which was published in Illustrations of the Logic of Science (1877–1878) and A Theory of Probable Inference (1883). Both publications emphasised the importance of randomisation-based inference in statistics. To Peirce and to experimental psychology belongs the honor of having invented randomised experiments, decades before the innovations of Jerzy Neyman (1894–1981) and Ronald Ayemer Fisher (1890–1962) in agriculture.

Peirce’s pragmaticist philosophy also included an extensive theory of mental representations and cognition, which he studied under the name of semiotics. Peirce’s student Joseph Jastrow continued to conduct randomised experiments throughout his distinguished career in experimental psychology, much of which would later be recognised as cognitive psychology. There has been a resurgence of interest in Peirce’s work in cognitive psychology. Another student of Peirce, John Dewey (1859–1952), conducted experiments on human cognition, particularly in schools, as part of his “experimental logic” and “public philosophy”.

1.2.1 The 20th Century Scenario In the middle of the twentieth century, behaviourism became a dominant paradigm within psychology, especially in the U.S. This led to some neglect of mental phenomena within experimental psychology. In Europe this was less the case, as European psychology was influenced by psychologists such as Sir Frederic Bartlett (1886–1969), Kenneth James Williams Craik (1914–1945), William Edmund Hick (1912–1974) and Donald Broadbent (1926–1993), who focused on topics such as thinking, memory and attention. This laid the foundations for the subsequent development of cognitive psychology.

In the latter half of the twentieth century, the phrase “experimental psychology” had shifted in meaning due to the expansion of psychology as a discipline and the growth in the size and number of its sub-disciplines. Experimental psychologists use a range of methods and do not confine themselves to a strictly experimental approach, partly because developments in the philosophy of science have had an impact on the exclusive prestige of experimentation. In contrast, an experimental method is now widely used in fields such as developmental and social psychology, which were not

previously part of experimental psychology. The phrase continues in use, however, in the titles of a number of well-established, high prestige learned societies and scientific journals, as well as some university courses of study in psychology.

1.2.2 Methodology Experimental psychologists study human behaviour in different contexts. Often, human participants are instructed to perform tasks in an experimental setup. Since the 1990s, various software packages have eased stimulus presentation and the measurement of behaviour in the laboratory. Apart from the measurement of response times and error rates, experimental psychologists often use surveys before, during, and after experimental intervention and observation methods.

1.2.3 Experiments The complexity of human behaviour and mental processes, the ambiguity with which they can be interpreted and the unconscious processes to which they are subject to gives rise to an emphasis on sound methodology within experimental psychology. Control of extraneous variables, minimising the potential for experimenter bias, counterbalancing the order of experimental tasks, adequate sample size, and the use of operational definitions which are both reliable and valid, and proper statistical analysis are central to experimental methods in psychology. As such, most undergraduate programmes in psychology include mandatory courses in research methods and statistics.

1.2.4 Other Methods While other methods of research—case study, corelational, interview, and naturalistic observation—are practiced within fields typically investigated by experimental psychologists, experimental evidence remains the gold standard for knowledge in psychology. Many experimental psychologists have gone further, and have treated all methods of investigation other than experimentation as suspect. In particular, experimental psychologists have been inclined to discount the case study and interview methods as they have been used in clinical psychology.

1.2.5 Criticism Critical and postmodernist psychologists conceive of humans and human nature as inseparably tied to the world around them, and claim that experimental psychology approaches human nature and the individual as entities independent of the cultural, economic, and historical context in which they exist. At most, they argue, experimental psychology treats these contexts simply as variables affecting a universal model of human mental processes and behaviour rather than the means by which these processes and behaviours are constructed. In so doing, critics assert, experimental psychologists paint an inaccurate portrait of human nature while lending tacit support to the prevailing social order. Three days before his death, radical behaviourist B.F. Skinner criticised experimental psychology in a speech at the American Psychological Association (APA) for becoming increasingly “mentalistic”—that is, focusing research on internal mental processes instead of observable behaviours. This criticism was leveled in the wake of the cognitive revolution wherein behaviourism fell from dominance within psychology and functions of the mind were given more credence. C.G. Jung criticised experimental psychology, maintaining that anyone who wants to know the human psyche will learn next to nothing from (it). He would be better advised to abandon exact science, put away his scholar’s gown, bid farewell to his study, and wander with human heart through the world. There in the horrors of prisons, lunatic asylums and hospitals, in drab suburban pubs, in brothels and gambling-hells, in the salons of the elegant, the Stock Exchanges, socialist meetings, churches, revivalist gatherings and ecstatic sects, through love and hate, through the experience of passion in every form in his own body, he would reap richer stores of knowledge than text-books a foot thick could give him, and he will know how to doctor the sick with a real knowledge of the human soul.

1.3 THE EXPERIMENTAL METHOD Experiment is an observation of behaviour done under controlled conditions. It is the most objective and scientific method. The word “experiment” is derived from the Latin word experimentum, which means ‘a trial’ or ‘test’.

1.3.1 Some Definitions of an Experiment According to Eysenck (1996) “An experiment is the planned manipulation of variables in which at least one of the variables that is the independent variable is altered under the predetermined conditions during the experiment.” According to Jahoda, “Experiment is a method of testing hypothesis.” According to Festinger and Katz, “The essence of experiment may be described as observing the effect of dependent variable after the manipulation of independent variable.” According to Bootzin (1991), “An experiment is a research method designed to control the factors that might affect a variable under study, thus allowing scientists to establish cause and effect.” In essence, any experiment is an arrangement of conditions or procedures for the purpose of testing some hypothesis. The critical aspect of any experiment is that there is control over the independent variables or IV (the antecedent conditions or treatments or experimental variables) such that cause-and-effect relationships can be discovered. The experimental method is the method of investigation most often used by psychologists. Experimental method allows us to study cause-and-effect relationship. An experiment is a controlled method of exploring the relationship between factors capable of change, called variables. A hypothesis tells what relationship a researcher expects to find between an independent variable (IV) and a dependent variable (IV) to study cause-andeffect relationship. The experiment is a research method designed to study or answer the questions about cause (independent variable IV) and effect (dependent variable DV), or to identify a cause-and-effect relationship. Its main advantage over other data gathering or collecting methods is that it permits the researcher to control the conditions and so rule out—to as large an extent as possible—all influences on subject’s behaviour except the factors or variables being examined. In an experiment, researchers systematically manipulate a variable Independent variable (IV) under controlled conditions and observe how the participants respond. For example, suppose researcher wants to study the effect of music on student’s accuracy in solving mathematical problems. Researchers manipulate one variable (IV, for example, presence or absence of

music) and they observe how the subjects or the participants respond (Dependent variable (DV), which is the number of mathematical problems correctly solved). They try to hold constant the other variables that are not being tested but they can exert their influence on the variable being studied (IV). Variables which need to be controlled include light in the room, noise, fatigue, and type of math problems being solved and so on. If the behaviour changes when only that manipulated variable is changed, then researcher can conclude that they have discovered a cause-and-effect relationship, for example, in this case between the presence of music and problem solving. In designing an experiment, the first step after framing of the problem is to state a hypothesis. “A hypothesis is a tentative set of beliefs about the nature of the world, a statement about what you expect to happen if certain conditions are true” (Halpern, 1989). It is a pre-supposed answer to a problem. A hypothesis can be stated in an “If _ _ _ _ _ _ then _ _ _ _ _ _’’ format. If certain conditions are true, then certain things will happen. For example, if music is present, then people solve a smaller number of math problems accurately.

1.3.2 Variable A variable, as the name implies, is something that which changes, that which is subject to increases and/or decreases over time—in short, that which varies. The term “variable” means that which can take up a number of values. Variable may be defined as those attributes, qualities, and characteristics of objects, events, things, and beings, which can be measured. In other words, variables are the characteristics or conditions that are manipulated, controlled or observed by the experimenter. Variable in a scientific investigation is any condition that may change in quantity and quality. Intelligence, anxiety, aptitude, income, education, authoritarianism, achievement, etc. are some examples of variables commonly employed or studied in Psychology, sociology, and education.

Some definitions According to Postman and Egan (1949), “A variable is a characteristic or attribute that can take a number of values.” According to D’Amato (2004), “Any measurable attribute of objects, things, or beings is called a variable.” The measurability attribute need not be

quantitative; it can be qualitative also such as race, sex, and religion.”

Independent and dependent variable Independent variable (IV) is also called the experimental variable, the controlled variable, and the treatment variable. Independent variable is the variable that is manipulated by the researcher to see how it affects the DV. It is the variable that the experimenter deliberately (wishfully) manipulates. Experimenter decides how much of that variable to present to the participant. The independent variable is described in the “if” part of the “if _ _ _ _ _ _ then _ _ _ _ _ _’’ statement of the hypothesis. In the example discussed earlier, the IV is whether or not the music is presented to the participants or subjects of the study. The independent variable is the one which is selected, manipulated, and measured by the experimenter or researcher for the purpose of producing observable changes in the behavioural measure (DV). In other words, it is the variable on the basis of which the prediction about the DV is made. Some definitions of the independent variable (IV) According to Kerlinger (1986), “An independent variable is the presumed cause of the dependant variable.” According to D’Amato (2004), Independent variable is “Any variable manipulated by experimenter either directly or through selection in order to determine its effect on a behavioral variable.” According to Townsend, “Independent variable is that variable which is manipulated by the experimenter in his attempt to ascertain its relationship to an observed phenomenon.” According to Ghorpade, “Independent variable is usually the cause whose effects are being studied. The experimenter changes or varies independent variable to find out what effects such change produced on dependent variable.” Independent variable is any variable the values of which are, in principle, independent of the changes in the values of other variables. Underwood (1966) refers to the IV as the stimulus variable. Independent variable is indeed a stimulus to which a response from the participant or subject is sought. In an experiment, IV is specifically manipulated by the experimenter and its effect is observed or examined upon the DV. Some experts, depending

upon the method of manipulation used have tried to divide the independent variable into Type-E independent variable and Type-S independent variable (D’Amato, 1970). Type-E independent variable is one which is directly or experimentally manipulated by the experimenter and Type-S independent variable is one which is not manipulated directly by the experimenter or researcher as these are difficult to be manipulated directly but manipulated through the process of selection only. A research or investigation which involves the manipulation of the Type-E independent variable is called experimentation, no matter whether it is done in a laboratory or in a natural setting. Likewise, a research which involves the manipulation of the Type-S independent variable is called correlation research. A research in which there are no independent variables is called observation. The independent variables thus classified, according to Underwood was on the basis of method of manipulation. The independent variables or the stimulus can also be classified on the basis of nature of the variables. The following categories are according to this classification: (i) Task variables: The “task variables” refer to those characteristics or features which are associated with a behavioural task presented to the subject or participant of the study. It includes the physical characteristics of the apparatus or instrument as well as many features of the task procedure or the method. The simplicity or the complexity of the apparatus or the instrument used in a research or study is likely to produce a change in behavioural measure or the behaviour of the subject or participant. (ii) Environmental variables: The “environmental variables” refer to those characteristics or features of the environment, which are not physical parts of the task as such, but they tend to produce changes in the behavioural measure or the behaviour of the subject. Examples of such variables include noise, temperature, levels of illumination, and time of the day when experiment was conducted or done. (iii) Subject variables: The “subject variables” refer to those characteristics or features of the subjects (humans or animals) which are likely to produce changes in the behavioural measures. Examples of such variables include age, sex, height, weight, intelligence, anxiety

level of the subject, and the like. Dependent variable (DV) or behavioural measure concerns the responses that the participants make. It is the measure of their behaviour. Behaviour of the person or the subject or the participant is the DV. Any measured behavioural variable of interest to the experimenter in a psychological investigation is the DV. The DV, which nearly always involves some form of behaviour, is what is expected to change when the IV is manipulated, provided the experimenter’s hypothesis is right. Changes in the DV depend on the changes in the IV. Dependent variable is any variable the values of which are, in principle, the result of changes in the values of one or more IVs. The behaviour of the subject under consideration is dependent upon the manipulation of some other factors. Some definitions of the dependent variable (DV) According to D’Amato, “Any measured behavioral variable of interest in the psychological investigation is dependent variable.” According to Townsend, “A dependent variable is that factor which appears, disappears, or varies as the experimenter introduces, or removes, or varies the independent variable.” According to Postman & Egan, “The ‘phenomenon’ with which we wish to explain and predict is dependent variable.” Dependent variable is the behaviour or response outcome that the researcher measures, which is hoped to have been affected by the IV. Dependent variable is described in the “then” part of the “if _ _ _ _ _ then _ _ _ _ _’’ statement or format of hypothesis. Underwood has referred to DV as the response variable. In the example that we are discussing, the DV is the problem solving of the participants or the subjects, which we could measure in terms of the number of the problems correctly solved in a specified time. An “if _ _ _ _ _ then _ _ _ _ _” statement stresses that a cause-and-effect relationship occurs in one direction only. Change in the independent variable causes change in the DV but not vice versa. Because an experiment provides a means of establishing causality, it is the data gathering method of choice for many psychologists.

1.3.3 Experimental and Controlled Conditions or Groups In an experiment, the researcher must arrange to test at least two conditions

or groups that are specified by the independent variable—control condition or group and the experimental condition or group. Control condition or group is a condition or group in an experiment that is as closely matched as possible to the experimental condition or group except that it is not exposed to the IV or variables under study. Experimental condition or group is a condition or group in an experiment that is exposed to the IV or variables under investigation. In the simple example of the music experiment, the researcher or the experimenter could test one group of subjects or participants of the study or research in a “no music condition’’ (controlled group) and the second group in a “music” condition (experimental group). An experimental group consists of those subjects who experience the experimental condition —”music”. The IV that is music here is introduced in the experimental group. The experimental condition is changed in some way. Most experiments also use a control group to provide a source of comparison. Control subjects experience all the conditions that the experimental subjects do except the key factor the psychologist or researcher is evaluating, that is the independent variable (music). The control condition is left unchanged. A particular variable is present in the experimental condition that is absent in the control condition (music is either present or absent).

1.3.4 Control of Variables A good research design should control the effects of extraneous variables which are more or less similar to IV or variables that have the capacity to influence the DV or variables. Control means the exercise of the scientific method whereby the various treatments in an experiment are regulated so that the causal factors may be unambiguously identified. Control is any method for dealing with extraneous variable that may affect your study. The experimenter seeks to eliminate the effects of irrelevant variables by ‘controlling’ them, leaving only the experimental variable or variables free to change. If left uncontrolled, such variables are called independent extraneous variables or simply extraneous variables. There are various ways to control the effects of extraneous variables. Of these ways, randomisation is considered by many as one of the best techniques of controlling the extraneous variables. Randomisation is a very popular technique of controlling extraneous variables. Randomisation refers to a technique in which each member of the population or universe at large

has an equal and independent chance of being selected in the groups. There are three basic phases in randomisation—random selection of subjects, random assignment of subjects into control and experimental groups, and random assignment of experimental treatments among different groups. Sometimes, it happens that for the researcher it is not possible to make random selection of subjects. In such situations, the researcher tries to randomly assign the selected subjects into different experimental groups. When this random assignment is not possible due to any reason, the researcher randomly assigns the different experimental treatments into experimental groups. Whatever the method may be, randomisation has proved very useful in controlling the extraneous variables. A research design which fully controls the extraneous variable or variables is considered to be the best design for the research. This increases the internal validity of the research. Randomisation helps in generalising the findings. Random assignment means that people are assigned to experimental group or groups using a system, such as slip system, coin tossing—which ensures that everyone has equal chance to be selected to any group or being assigned to any one group. Randomisation is used where the experimenter or the researcher assumes that some extraneous variables operate, but she or he cannot specify them and, therefore, cannot apply the other techniques of controlling extraneous variables. The technique is also applied where the extraneous variables are known but their effects can’t be controlled by known techniques. The importance of randomisation lies in the fact that this technique randomly distributes the extraneous effects over the experimental and control conditions. Such balancing occurs whether or not the experimenter has identified certain extraneous variables, because the effects of unknown or unspecified extraneous variables are said to be equally distributed across different conditions of the experiment when the experimenter randomly assigns subjects to the different groups or conditions. If the number of participants or subjects in the study is sufficiently large, then random assignment usually guarantees that the various groups will be reasonably similar with respects to important characteristics like age, gender, intelligence, personality, aptitude, and other psychological traits. The participants used in an experiment consist of one or more samples drawn from some larger population. If we want the findings from a sample to be true

of the population, then those included in the sample must be representative of the population. In more simple words, the sample must be true representative of the population. The best way to obtain a representative sample from that population would be to make use of random sampling. Another way of obtaining a representative sample is by using quota sampling, a sample that is chosen from a population so that the sample is similar to the population in certain ways, for example, proportion of females, proportion of graduates, and so on. Random sampling and quota sampling are often expensive and time consuming. Accordingly, opportunity sampling can be used, which means participants are selected on the basis of their availability rather than by any other method. The extraneous variables can be controlled in several ways. Extraneous variable is any variable other than the IV that may influence the DV in a specific way. Of these various ways, randomisation, balancing, and counterbalancing are relatively more popular. All experiments require some kind of comparison between conditions. If we have only one condition, we cannot draw conclusions about cause and effect. The music study could compare four conditions—no music (control condition) and three experimental conditions (low/soft, medium, and high/loud music).

1.3.5 Confounding Variables A confounding variable is any variable, other than the IV that is not equivalent in all conditions. These are variables that are mistakenly manipulated along with the IV. Confounding variables can lead researchers to draw incorrect conclusions. Researchers can guard against the confounding variables by the use of random assignment. Subjects are placed in either the experimental or the control group completely at random. According to the Dictionary of Psychology, “randomness” is a mathematical or statistical concept, and the term means simply that there is no detectable systematicity in the sequence of events observed. Strictly speaking, “random” refers not to a thing but to the lack of a thing, the lack of pattern or structure or regularity. The typical list of synonyms of the word random includes words or phrases like haphazard, by chance, occurring without voluntary control, aimless, purposeless, and so on. This is a way of compensating for the fact that experimenters cannot possibly control for everything about their subjects. When a sample is sufficiently large, random assignments tends to produce a

good shuffling, with regard to other factors that might otherwise bias experiment’s results. Consequently, any observed differences in the behaviour of the two groups are not likely to have been caused by inherent differences in the people who form these groups. If researchers use precautions such as random assignment to reduce the effect of the confounding variables, then they have a systematic, planned, précised, well organised, well controlled, and a scientific study. With a well controlled study, researcher or the experimenter feels more confident and sure about drawing cause-and-effect relationship and conclusions in an experiment. In experimental method, researchers manipulate a variable called independent variable and observe how the participants respond. If conditions in an experiment are carefully controlled and confounding variables are avoided, the researchers can conclude that a change in the IV actually caused or brought a change in the DV.

1.3.6 Advantages of the Experimental Method (i) Experimental method is the only method that allows the experimenter to infer cause-and-effect relationship. (ii) In experimental method, the experimenter can exercise control over other confounding variables. (iii) It helps in conducting a systematic, objective, précised, planned, wellorganised, and a well-controlled scientific study. (iv) This method makes any subject a science because a subject is a science not by “what” it studies but by “how” it studies. This method makes Psychology a science.

1.3.7 Disadvantages of the Experimental Method (i) Its control is its weakness. It makes the set up or the situation artificial. A situation in which all the variables are carefully controlled is not a normal, natural situation. As a result, the researcher or the experimenter may have difficulty generalising the findings from observations in an experiment to the real world (Christensen, 1992). For example, researcher may not be able to generalise from a study conducted that examinee’s memory for non-sense syllables presented on a computer screen in a psychological laboratory and draw conclusions about the

student’s learning about introductory Psychology in a college classroom. It is very difficult to know and control all the intervening variables. (ii) All the psychological phenomena can’t be studied by this method. (iii) The experimental method is costly in terms of money and time. A well established laboratory and trained personnel are needed to conduct experiments.

1.4 S—O—R FRAMEWORK (Stimulus—Organism—Response) In a psychological experiment, one obvious requirement is an organism to serve as subject by responding to stimuli. If we designate the stimulus (or stimulus complex or stimulating situation) by the letter S, and the subject’s response by the letter R, we can best designate the subject or organism by the letter O. It (O) was originally read “observer”, because the early experiments were largely in the field of sensation and perception, where the subject’s task was to report what she or he saw, heard, and the like. The letter E stands for the experimenter. A psychological experiment, then, can be symbolised by S—O—R which means E (understood) applies a certain stimulus (or situation) to O’s receptors (five sense organs—eyes, ears, nose, tongue, and skin) and observes O’s response. This formula suggests a class of experiments in which E’s aim is to discover what goes on in the organism between the stimulus and the motor response. Physiological recording instruments often reveal something of what is going on in the organism during emotion, and introspection can show something of the process of problem solution. E does not attempt to observe directly what goes on in O, but hopes to find out indirectly by varying the conditions and noting the resulting variation in response. Since O certainly responds differently to different stimuli, there must be stimulus variables, S—factors, affecting the response. Subject also responds differently to the same identical stimulus according to her or his own state and intentions at the moment. Different human beings may give different responses to same stimulus because of the differences in their personality, past experience, and learning. There are O variables, the O— factors affecting the response. At a certain moment, the organism makes a

response. The response depends on the stimuli acting at that moment and on factors present in the organism at that moment. This general statement can be put in the form of an equation: R = f(S, O) which reads that the response is a function of S—factors or variables and O— factors or variables. Or it can be read that R—variables or responses or behaviour of the subject or organism depend on S—variables and O— variables. In any particular experiment, some particular S—factor or O— factor is selected as the experimental variable (Independent variable or variable whose effect an experimenter wants to study in an experiment) and some particular R—variable is observed. As to the control of these variables, stimuli can be controlled far as they come from the environment, for E (experimenter) can manage the immediate environment consisting of the experimental room and the apparatus. But controlling the O—variables is difficult. For example, hunger, a much used variable in animal experiments can be controlled by regulating the feeding schedule. What directly controls is “hours since last feeding” prior to the actual test or “trial” when a stimulus is applied and the response observed. Time since feeding is thus an antecedent variable, an A—variable, and the experimenter may find it more helpful and “operational” (able to function) to speak of, A—rather than O—variables and give our equation this modified form: R = f(S, A) Of course, the A—variables have no effect on the response experiments as they affect O’s state during the test. The O—variables are the real factors in the response.

QUESTIONS Section A Answer the following in five lines or 50 words: 1. Define Experimental Psychology * 2. Wilhelm Wundt * 3. Define experimental method.

4. 5. 6. 7. 8. 9. 10. 11. 12. 13. 14. 15. 16. 17.

Define an experiment. Stimulus Response Variable Experimental group What is Independent Variable? What is Dependent Variable? Response variables Stimulus variables Counter balancing method Manipulation What do you understand by the term ‘experimental group’? Control and experimental groups. Placebo effect

Section B Answer the following questions up to two pages or in 500 words: 1. Write a note on Experimental method. 2. Define the experimental method and give its merits and demerits. or Elaborate on the merits and demerits of the experimental method. or Briefly explain the procedure involved in the experimental method and give its merits and demerits. 3. Trace out the history of experimental psychology with special reference to Wundt and Fechner. 4. How is Psychology a Science?

Section C Answer the following questions up to five pages or in 1000 words: 1. Trace the history of Experimental Psychology and also explain its role towards raising the status of Psychology to that of a ‘Science’.

2. Describe history of Psychology. 3. Explain the contributions of Wundt and Titchener to Experimental Psychology. 4. Define Experimental Psychology and trace its origin from the historical background. 5. What is Experimental Psychology? Discuss its scope in detail. 6. Explain the nature and scope of Experimental Psychology. 7. Discuss an experiment and its steps with the help of an example. 8. What is Experimental Method? Critically evaluate it. 9. Give the steps of the Experimental Method and also explain its merits and demerits. 10. Write brief notes on the contributions of the following to Psychology: (i) Weber and Fechner (ii) Watson (iii) Kohler and Koffka (iv) Woodworth (v) Freud (vi) Jung and Adler 11. 11. Write short notes on the following: (i) S-O-R connection (ii) Organism and Environment

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University, New York, 1914. Thorndike, E.L., Human Learning, Cornell University, New York, 1931. Thorndike, E.L., Human Learning, Holt, New York, 1965. Titchener, E.B., “Experimental psychology: A retrospect” American Journal of Psychology, 36, pp. 313–323, 1925. Tolman, E.C., “A new formula for behaviorism”, Psychological Review, 29, pp. 44–53, 1922. [available at http://psychclassics.yorku.ca/Tolman/formula.htm]. Tolman, E.C., Purposive Behavior in Animals and Men, Appleton-CenturyCrofts, New York, 1932. Tolman, E.C., Drives Towards War, Appleton-Century-Crofts, New York, 1942. Tolman, E.C., “Cognitive maps in rats and men”, Psychological Review, 55, pp. 189–208, 1948. Underwood, B.J., Experimental Psychology, Appleton, New York, 1966. Watson, J.B., “Psychology as a behaviorist views it”, Psychological Review, 20, 1913. Watson, J.B., Psychology from the Stand-point of a Behaviourist, Lippincott, Philadelphia, 1919. Watson, J.B., Behaviourism, Kegan Paul, London, 1930. Watson, J.B., Behaviourism, Norton, New York, 1970. Weber, E.H., Leipzig Physiologist, JAMA 199 (4), pp. 272–3, 1967, Jan 23, doi:10.1001/jama.199.4.272, PMID 5334161 Wertheimer, M., “Psychomotor co-ordination of audotory-visual space at birth”, Science, 134, 1962. Wundt, W., Fundamental of Physiological Psychology, 1874. Young, C., Emotions and Emotional Intelligence, Cornell University, Retrieved April 1999, from http: //trochim. human. cornell. edu/gallery/young/emotion. HTM. Young, P.T., Emotion in Men and Animal (2nd ed.), Huntington, Krieger, New York, 1973.

2 Variables INTRODUCTION Variable is any measurable attribute of objects, things, or beings. Anything which varies or which takes up a number of values is a variable. A variable can take several or many values across a range. Variable is a symbol to which numbers are assigned, and a factor which can be measured or is related to those objects which have the features of quantitative measurement. A variable can be controlled or observed in a study.

2.1 SOME DEFINITIONS OF A VARIABLE According to D’Amato, “By variable we mean any measurement or attribute of those objects, events or things which have quantitative relationship.” According to Postman and Egan, “Variable is an attribute that can take up number of values.” Thus, by variable, we mean anything we can observe and which can be measured quantitatively. For example, extrasensory perception is thought by some to be an attribute of human beings, but as it is apparently incapable of reliable measurement (Hansel, 1966), we would not call it a variable. An attribute is a specific value on a variable. For instance, the variable sex or gender has two attributes: male and female; or a variable agreement having five attributes such as 1 = strongly disagree

2 = disagree 3 = neutral 4 = agree 5 = strongly agree The measurability required of an attribute need not be quantitative. Race, sex, and religion, for example, are variables that are only “qualitatively” measurable.

2.2 TYPES OF VARIABLES According to Spence (1948): (i) Stimulus variables (ii) Organismic variables (iii) Response variables According to Mc Guigan (1969): (i) Stimulus variable or “Input” (ii) Organismic variable or “Throughput” (iii) Response variable or “Output”

2.2.1 Stimulus Variables or Input or Independent Variables (IVs) Elementary stimuli differ in “modality” or type or kind, being visual (seeing), auditory (hearing), olfactory (smelling), gustatory (tasting), cutaneous (feeling) and so on according to the sense which they stimulate. In every modality, stimuli vary in intensity or strength and duration. Stimuli of light and sound also vary in the dimension of wavelength or frequency, corresponding to colour and pitch. Odour or smell stimuli differ chemically one from another, and so do taste stimuli. Area or extent is a variable in the cases of light and skin stimuli. An experimenter always plans to hold all factors constant or stable except those she or he wishes to investigate. A large share of the experimenter’s preliminary planning and labour (effort that he put in planning) is directed towards avoiding irrelevant causes of variability. If the experimenter’s interest lies in a stimulus variable, she or he must neutralise or hold constant such as O (Organismic) variables as drive and habit strength.

Not only elementary stimuli but also stimulus combinations or complexes are covered by the S (Subject) in the formula. Spatial perception of the distance, direction, size, and shape of an object depends on the subject’s ability to utilise a combination of stimuli.

2.2.2 Organismic Variables or O-variables or Throughput or Intervening Variables A valuable analysis of what are called O-factors was offered by Clark Hull (1943, 1951). Some of his O-factors are the following: (i) Habit strength (SHR): It is the strength of association between a certain S and a certain R, based on previous learning which is an Avariables or combination of A-variables. Hull uses the symbol, SHR, for habit strength. (ii) Drive, such as hunger, thirst, etc. (iii) Incentive, the reward or punishment expected. (iv) Inhibition is a factor or combination of factors tending to diminish the momentary readiness for a response. Examples are fatigue, satiation, distraction, fear, and caution. (v) Oscillation is an uncontrollable variation in O’s readiness to act, dependent probably on a multitude of small internal causes, but not beyond measurement and prediction since an individual usually varies only within limits. (vi) Individual differences and differences due to age, health, and organic state. (vii) Goal-set: In a typical human experiment, E (Experimenter) gives O (Organism) certain “instructions”, assigning the task to be performed, and human subject’s willingness to cooperate by following instructions and performing the task quite eagerly. Verbal instructions are not necessary when, as in animal experiments, the situation is so arranged as to guarantee that a certain goal will be striven for by the subject.

2.2.3 Response Variables or Output Variables or Behaviour Variables or Dependent Variables Dependent variable is the response or behaviour of the organism or an

individual. Dependent variable is called so because its value depends upon the value of the Independent variable. According to Townsend, “Dependent variable is the factor which appears, disappears, or varies as the experimenter introduces, removes, or varies the Independent variable.” Some of the response variables are: (i) Accuracy: In many experiments on perception, O’s task is to observe and report the stimulus as accurately as possible, and his errors are measured or counted by the experimenter. More errors mean less accuracy and fewer errors mean more accuracy. Any measure of accuracy is almost inevitably a measure of errors. (ii) Speed or quickness: Speed or quickness is a reaction time of a single response or by the total time consumed in a complex performance. When the task is composed of many similar units, such as columns of numbers to be added, the test is conducted according to either of two plans: (a) Time limit: How much is done in the same time allowed? (b) Amount limit: How long does it take to do the assigned amount? These are both speed tests. (iii) Difficulty level: A type of measurement often adopted in intelligence testing so as to avoid overemphasis on speed. It can be used as a response measure or variable when the experimenter is provided with a scale of tasks graded in difficulty. (iv) Probability or frequency: When a particular response occurs sometimes but not on every trial, a stimulus just at the “threshold” will be noticed about 50 per cent of the time. A partially learned response will perhaps be made in 6 out of 10 trials, so that its probability is 60 per cent at that stage of learning. If there are two or more competing responses to the same stimulus or situation, the probability of each competitor can be determined in a series of trials. (v) Strength or energy of response: Through sometimes a useful Rvariable, the relation of muscular output to excellence of performance is far from simple. It cannot be said that the stronger the muscular response, the better, for often intelligent training gets rid of a lot of superfluous muscular effort. The less energy consumed in attaining a

certain result, the greater the efficiency. The student of learning is concerned with the “strength” of an S—R connection, SHR, which is very different from muscular strength.

2.3 PROCESS OF EXPERIMENTATION The sine qua non (something that you must have or which must exist, for something else to be possible) of most sciences, including Psychology, is experimentation. Even astronomy (the study of stars and planets and their movements) which relies heavily on co-relational research, owes much of its viability to the improvement in observational techniques and apparatus constantly emerging from experimentation in allied sciences. In an ideal experiment, the investigator or experimenter controls and directly manipulates the important variables of interest to her or him. Through careful manipulation of variables, the experimenter is able to show that changes in A (for example, music—IV) result in (cause) changes in B (for example, problem-solving—DV) concomitance or accompanying is replaced by causeand-effect (DV—problem-solving) relations. Since the variables with which the experimenter deals are usually within his province or reach of direct manipulation, he is able to achieve a measure of control over relevant experimental factors not easily obtained otherwise, a control which enables experimenter to disentangle and isolate from nature’s complexity the particular effects of specific variables. The major criterion, then, for experimentation, is that the variables of interest are subject to direct manipulation as contrasted with manipulation through selecting procedures. A few examples of variables related to the experimental situation and to the experimental task that allow for direct manipulation are temperature, humidity, lighting, task instructions, materials and procedures. Many subject or organismic variables also permit direct manipulation, such as anxiety level (when manipulated through the application of such aversive stimuli as shocks), hunger and thirst drives, states induced through the use of drugs and variations in (limited) previous experience brought about by different training procedures. The cardinal or most important feature of experimentation is that the variables under study are directly manipulated by the researcher or experimenter. And it may be stated as a general principle that the more

directly the researcher can manipulate her or his variables of interest, the more reliable and precise her or his results are likely to be. Direct manipulation of variables possesses several advantages over manipulation by the selection. (i) The dangers of concomitant or accompanying manipulation of relevant but extraneous variables are considerably less potent or effective with direct manipulation. (ii) There is generally less error of manipulation involved when variables are directly manipulated. By “error”, we refer to the discrepancy between the value of the variable assumed by manipulation and its actual or “true” value. (iii) Certain powerful research techniques, such as single-group designs, are possible with many variables that are manipulated directly. But are possible with few variables that are manipulated by selection. In singlegroup (within-subjects) designs, a single group of subjects serves in all conditions of the research, in separate-groups (between-subjects) designs; a separate group of subjects serves under each of the conditions of the research. The research designs are discussed later in this chapter. The progress from natural observation to laboratory experimentation is characterised by the researcher’s winning increasing control over the events with which she or he is concerned. Experimentation, however, is not limited to a laboratory setting; it is, in some disciplines, most often practiced within a natural setting. Similarly, co-relational research may be conducted within a laboratory or natural setting.

2.4 RESEARCH OR EXPERIMENTAL DESIGNS Research or experimental designs may be single group or separate group as explained in the following.

2.4.1 Single-group or Within-subjects Experimental Design Single-group or within-subjects design is a technique in which each subject serves as his own control. This single group of subjects serves under all values or levels or conditions of the research or the independent variable, that is the variable under study. For example, the experimenter wants to determine whether nicotine (found in tobacco) has a deleterious or harmful or damaging

effect on motor coordination. One powerful means of studying this problem is as follows: the experimenter would choose a group of subjects and submit them to a series of motor coordination tests, one test daily. Before some of the tests, the subjects would be given a dose of nicotine, and before others they would receive a placebo, an innocuous or harmless substance administered in the same way as the drug (nicotine) and no-drug conditions. Placebo is a harmless substance given as medicine, especially to humor a patient. If the drug has a harmful effect on motor coordination, experimenter should observe that, in general, the performance of subjects is poorer when tested under the drug (nicotine) than when tested after receiving the placebo. Because each subject is tested under both conditions, the experimenter need not concern herself or himself with individual differences in motor coordination ability. Single-group design or within-subjects design produce quite representative results possible to generalise.

2.4.2 Separate Group or Between Subjects Experimental Design If the only way in which the experimenter could obtain subjects with different amounts of nicotine in them was to choose smokers and nonsmokers from the general population then he would be forced to use a separate-groups (or between-subjects) design; that is, one group of subjects (non-smokers) would be tested under the no-drug condition. With separategroups (between-subjects) designs, a separate group of subjects serves under each of the conditions of the research. By comparing the performance of the two groups of subjects, the experimenter can evaluate the effect of nicotine on motor coordination. The situation with respect to individual differences in motor coordination ability is drastically changed. The experimenter is now importantly interested in any dimension of individual differences that might significantly affect motor coordination, such as age, sex, and occupation. Obviously, he would want the smokers (nicotine group) and non-smokers (no drug group or placebo group) to be well-equated with respect to such individual characteristics. However, such precautions are not necessary with a single-group design because every subject is tested under all conditions of the research and each subject serves as his own control. In single-group designs, a single group of Ss (subjects) serves under all

values or levels of the independent variable; in separate-groups designs, a separate group of Ss serves under each of the values or levels of the independent variable. The earlier definitions, introduced before the development of the concept of variables, however, made reference to serving under “conditions of the research” rather than under “values of the independent variable”.

QUESTIONS Section A Answer the following in five lines or 50 words: 1. 2. 3. 4. 5. 6. 7. 8. 9. 10.

Define Independent and Dependent variables * Response variables Stimulus variables Organismic variables * Continuous variables Counter balancing method Manipulation Matched-group technique Hypothesis and its types Randomised group technique

Section B Answer the following questions up to two pages or 500 words: 1. Explain the experimental method used in psychology pointing out its merits and demerits. 2. Write an essay on variables of an experimental method. 3. Differentiate between control and manipulation of variables. 4. How can we control the extraneous variables? 5. Differentiate within and between experimental designs. 6. Define variables and give the various techniques of control of variables. 7. Name the different kinds of variables and elaborate on the techniques

of controlling the interfering variables. 8. What is objective observation? Examine its merits and limitations. 9. Illustrate an experimental design. Explain experimental and controlled conditions.

Section C Answer the following questions up to five pages or in 1000 words: 1. Define controls. Give various methods of controlling variables. 2. Differentiate between various types of variables. 3. What is control of variables? What are the different methods of controlling the variables? 4. Discuss the nature and classification of variables in Experimental Psychology. 5. Discuss the characteristics of experimental method in Psychology. Illustrate your answer with experimental designs. 6. What do you understand by independent and dependent variables? What is relevant variable in psychological experiment?

REFERENCES D’Amato, M.R., Experimental Psychology, Tata McGraw-Hill, New Delhi, 2004. Hansel, C.E.M., ESP: A Scientific Evaluation, Scribner’s, New York, pp. 186–189, 1966. Hull, C.L., Principles of Behavior, Appleton-Century-Crofts, New York, 1943. Hull, C.L., Essentials of Behavior, CT: Yale University Press, New Haven, 1951. Mc Guigan, F.J., Thinking: Studies of Covert Language Process, AppletonCentury-Crofts, New York, 1966. Mc Guigan, F.J., “Covert oral behavior during the silent performance of language”, Psychological Bulletin, 74, pp. 309–326, 1970. Mc Guigan, F.J., Cognitive Psychophysiology: Principles of Covert Behavior,

Prentice-Hall, Inc., Englewood Cliffs, 1978. Postman, L. and Egan, J.P., Experimental Psychology: An Introduction, Harper and Row, New York, 1949. Spence, Kenneth W., “The postulates and methods of behaviorism”, Psychological Review, 55, pp. 67–69, 1948.

3 Sensation INTRODUCTION Sensation is the first response of the organism to the stimuli. The study of sensation is concerned with the initial contact between organisms and their physical environment. Sensation is the first step in processing information. The word refers to the activation of receptors (receptor cells or sense organs) and sensations can be viewed as the basic building blocks of perception. Receptor cells are those cells which receive physical stimulation from the environment and start the process of adjustment of the organism to her or his environment. Perception is the process of organising and attempting to understand the sensory stimulation we receive. Sensation focuses on describing the relationship between various forms of sensory stimulation (including light waves, sound waves, pressure and so on) and how these inputs are registered by our sense organs—the eyes, ears, nose, tongue, and skin (Baron, 2003). Sense organs are our windows, which help us in gathering information from the external world in which we live. They are our first contacts with the physical world. Sense organs are also called sensory systems or informationgathering systems. Each sense organ is tuned to receive specific physical energy, such as light for the eyes, sound waves for the ears and so on. This physical stimulus which alone can stimulate the sense organ is called its adequate stimulus. Thus, light or light waves is an adequate stimulus for the eyes and sound waves for the ears, etc.

Sensations (the basic immediate experiences that a stimulus such as a sound or a touch elicits in a sense organ such as the ears or the sensory receptors in the skin) provide an important input of sensory organs only partly explains our behavioural responses to stimuli.

3.1 SOME DEFINITIONS OF SENSATION Sensation is “awareness of sense stimulation.” According to Jalota, “Sensation is primary cognitive experience.” According to Woodworth, “Sensation is first step of our knowledge.” According to James, “Sensations are the first things in the way of consciousness.” Edward Bradford Titchener (1867–1927) defined sensation as “An elementary process which constituted of atleast four attributes—quality, intensity, clearness, and duration.” Quality of sensation (i) Quality means nature of sensation, that is, whether visual, auditory, olfactory, gustatory, or tactual. For example, taste can be sweet or bitter; colour can be red or green and so on. (ii) Intensity or strength means the strength of the sensation. For example, sound can be loud, moderate, or mild. Greater the intensity, stronger is the sensation. (iii) Clearness means the degree to which perceived objects appear definite, distinct and with well-defined boundaries. A clear sensation or a clear image was one which was in the centre of attention and stood out vividly from the background. For example, colour can be deep or pale. Clearness plays a major role in Figure-Ground differentiation. More clear the stimulus, the better is the sensation of objects. (iv) Duration means the subjective, unanalysable attribute of a sensation which was regarded as the basis for the experience of the passage of time. For example, an advertisement can be of one minute or two minutes. Longer the duration, stronger is the sensation. Eysenck et al. (1972) defined sensation as “A psychic phenomenon incapable of further division and is produced by external stimuli on the sensory organ; in its intensity it depends on the strength of the stimuli and in its quality on the nature of the sense organ.” According to Bootzin (1991), “The activation of sensory receptors and

processing and transmission of these signals to higher centers in the brain is called sensation.” According to Baron (1995), “Sensation is concerned with the initial contact between organism and their physical environment. It focuses on describing the relationship between various forms of sensory stimulation and how their inputs are registered by our sense organs.” According to Feldman (1996), “Sensation is the process by which an organism responds to physical stimulation from the environment.” According to Rathus (1996), “The stimulation of sensory receptors and the transmission of sensory information to the central nervous system (CNS) is called the sensation.” Stimulus is necessary to activate a receptor and without a stimulus, there cannot be a sensation. It stirs certain receptor cells into activity. A particular stimulus must be strong enough to produce a sensation 50 per cent of the times in the minimum. It must be above the threshold or absolute limen. Those stimuli which are too weak to produce a sensation remain below the threshold and hence are called subliminal (below the level of conscious awareness). In such cases, they fail to elicit or give a sensation. When the receptors are stimulated, information can be transmitted to the brain, more specifically the cerebral cortex. Brain performs two major functions: (i) It controls the movements of the muscles, producing useful behaviours, and (ii) It regulates the body’s internal environment. To perform both these tasks and functions, the brain must be informed about what is happening both in the external environment and within the body. Such information is received by the sensory systems. Transmission of neural impulses to the brain is not however, enough to give us an understanding and awareness of our surroundings. If the receptors do not receive stimulation from the environment or are unable to process, the information is transmitted to the brain and perception does not occur (Dennett and Kinsbourne, 1992). The sensory organ, for example the eye, receives the physical energy, for example, the light waves and converts the physical energy into electrochemical form or what we call neural impulses. The process of converting

one form of energy into another kind by our sense organs is technically called transduction. It is also called encoding because the incoming information is encoded by the receptors (sense organs—eyes, ears, nose, tongue and skin) for transmission to the specialised area in the cerebral cortex. In the cortex, the encoded information is decoded and interpreted. Neurons operate on the basis of changes in electrical charge and the release of chemical substances which are called neurotransmitters. In order for the brain to function adequately, neurons or excited nerve cells, need to be able to communicate effectively from the axon of one neuron to the dendrites or cell body of another neuron, called as the synapse or synaptic cleft—a tiny filled space between neurons. These interneuronal or transsynaptic transmissions are accomplished by these chemicals that are released into the synaptic cleft by the presynaptic neuron when a nerve impulse occurs. There are many different kinds of neurotransmitters. There is also a likelihood that the postsynaptic neuron will “fire” (produce an impulse), while others inhibit the impulse. Whether the neural message is successfully transmitted to the postsynaptic neuron depends, among other things, on the concentration of certain neurotransmitters within the synaptic cleft. The belief that neurotransmitter imbalances in the brain can result in abnormal behaviour is one of the basic tenets of biological perspective today. Sometimes stress can bring on neurotransmitter imbalances. The following three types or kinds of neurotransmitters have been most extensively studied in relationship to psychopathology: (i) Norepinephrine (schizophrenia) (ii) Dopamine (anxiety, depression, suicide) (iii) GABA—Gamma aminobutryic acid (anxiety) We receive information about the environment from sensory receptors— specialised neurons that detect a variety of physical events. Stimuli impinge on the receptors and, through various processes, alter their membrane potentials. This process is known as sensory transduction because sensory events are transduced (“transferred”) into changes which are called the receptor potentials. Somehow, the physical energies of light and sound waves and those of odour and taste molecules must be changed into electrochemical forms which the nervous system can process. This process of converting the stimulation

received by the receptors into electrochemical energy that can be used by the nervous system is called transduction. Continued presentation of the same stimulus, however, causes the receptors to become less sensitive to that particular stimulus. This process, known as adaptation, occurs very rapidly when odours and tastes are involved. Sensation involves neurological events that occur within the nervous system as neural messages are first generated at the level of sensory receptors, in response to external stimuli, and then transmitted to various regions within the brain that process specific sensory inputs.

3.2 NATURE OF SENSATION OR CHARACTERISTICS OF SENSATION (i) Sensation is comparatively a passive state of consciousness. (ii) Sensation is partly subjective and partly objective. (iii) Sensations differ in quality. (iv) Sensations differ in quality regarding intensity, duration, and extensity. “Intensity” refers to the strength of the stimuli. “Duration” depends on the persistence of the stimuli. As the persistence differs, so does the duration and with it the quantity of the sensation. “Extensity”, that is volume-ness depends upon the sensitive surface attended. As the affected surface increases so does the extensity, thereby making a difference in the quality of different sensations. (v) Sensations have different traits like organs, spatial and motor sensations, distinguishing them from each other. (vi) Sensations are localised in the external world. So, they can be easily distinguished from each other. (vii) Sensations have relativity. According to Harald Hoffding (18431931), “From the moment of its first coming into being, the existence and properties of a sensation are determined by its relation to other sensations.”

3.3 ATTRIBUTES OF SENSATIONS (i) Quality: Sensations received through different sense organs differ in quality. Again, sensations received through the same sense organ also

differ in quality. Different types of colour and taste exemplify this fact. (ii) Intensity or strength: The strength or different degree of strength or intensity depends upon the (a) objective strength of the stimulus. (b) mental state of the individual. (iii) Duration: The duration of a sensation depends on the continuity of the stimulus or of its effect. More the continuity and persistence, the greater or longer the duration. (iv) Extensity: “Extensity” means volume-ness or spread-out-ness of sensation. It is a spatial characteristic. As this increases, the sensation appears to be bigger. (v) Local sign: Different sensations are distinguished according to the spot stimulated. This is local sign. It is because different local signs that one can distinguish among the sensations having the same quality and same quantity that is intensity, duration, and extensity. Thus, one can distinguish between two pin pricks simply because they are felt as two. To survive and adjust in this world, we must get accurate information from our environment. This information is gathered by our sense organs, called information-gathering system, ten in all. Eight of the sense organs are those that collect information from the external world—eyes (visual, seeing), ears (auditory, hearing), nose (olfactory, smell), tongue (gustatory, taste), and skin (cutaneous, touch, warmth, cold, pressure, and pain). Two are termed as deep senses; these sense organs help us in maintaining body equilibrium or balance and provide important information about body position and movement of body parts relative to each other—vestibular and kinesthetic.

3.4 TYPES OF SENSATION Sensation is the first response of the organism to the stimulus and is a step in the direction of perception. Sensation is not separate from perception (because Perception = Sensation + its Meaning). According to James Ward (1843–1925), “Pure sensation is a psychological myth.” Sensations are felt through five sense organs—eyes, ears, nose, tongue, and skin. Sensations can be generally divided into the following two categories:

3.4.1 Organic or Bodily Sensations Sensations which arise from the conditions of the internal organs are called organic sensations. They do not need any external stimulation. Hunger creates organic sensation caused by the contraction of the walls of the stomach. Thirst creates organic sensation which results from the drying up of the throat or the membrane located at the back of the neck. These sensations indicate the internal conditions of the body and do not convey any knowledge of the outside world. The distinction between organic sensations based on their location, they are classified into three types: (i) Sensations whose location can be determined, like cutting, burning, blistering and so on in the tissues. The location is fixed. (ii) Sensations whose location is undetermined: The position of comfort and restlessness are spread over the entire body and no particular part of the body can be assigned to them. (iii) Sensations whose location is vague: We have a hazy or unclear idea of the general location of some sensations like hunger, thirst, pain, though we do not know the exact location minutely. Organic sensations play an important role in the affective and motivational aspects of life.

3.4.2 Special Sensations Special sensations are caused by the specific sense organs—eyes, ears, nose, tongue, and skin. These can be clearly distinguished from one another. They originate from external stimuli like the light, air and so on. Organic sensations and special sensations are different from each other (see Table 3.1). Table 3.1 Differences between organic and special sensations Organic sensations

Special sensations

Source is internal

Source is external

No specific organ

Specific organs for special sensations like eyes, ears, nose, tongue, and skin

No knowledge of the outside world

Give knowledge of the outside world

Cannot be retained easily

Can be recollected with ease

Cannot be distinguished clearly from one another

Can be distinguished clearly from one another

Location is not possible or they cannot be located

Location is possible or they can be located

Are not intense in quality and quantity

Are comparatively more intense in quality and quantity than organic and motor sensations

The sense of gustation (taste) or olfaction (smell) differs from the other senses in that they respond to chemicals rather than to energy in the environment. The chemical senses tell us about the things we eat, drink, and breathe. For knowing adequate stimuli and sense organ associated with different senses (see Table 3.2). Table 3.2 Adequate stimuli and sense organ associated with different senses Sense

Adequate stimuli/ Physical energy

Sense organ

Sensation

Vision (Seeing)

Light waves 400–700 nm; (nanometers)

Eyes

Colours, shapes, textures

Audition (Hearing)

Sound waves 20–20,000 Hz (hertz)

Ears

Tones, sounds

Olfaction (Smell)

Chemical molecules or odour molecules

Nose

Odours, aroma

Gustation (Taste)

Soluble chemical substances

Cutaneous (Touch)

External contact (pressure)

Vestibular

Mechanical and gravitational forces

Kinesthetic

Motor activities

Tongue Skin

Flavours (sweet, sour, bitter, salty) Touch, warmth, cold, pain, and pressure

Inner ear

Body position and orientation, head orientation, movement

Joints, muscles, and tendons

Body position and movement of body parts, relative to each other

Out of the eight external senses, vision is the highly developed, most complex, and important sense in human beings. It is being used by us about 80 per cent of the time while transacting with the external world, followed by audition. Our brain has more neurons devoted to vision than to hearing, taste, or smell (Restak, 1994). Vision and hearing are sense modalities which we use most to explore our environments, and are of more general significance in everyday life. There is much evidence that the visual sense is the dominant one for most purposes. Other senses also contribute in enriching the information we gather from the external world.

3.4.3 Visual Sensation or the Sensation of Vision or Sight

Of all the senses, the sensation of sight is the most urgent for survival. It is at the same time, the most precious possession of human beings. Of all the senses, vision is the most extensively studied sense modality.

The physical stimulus for vision Our eyes detect the presence of light. Light, in the form of energy from the sun, is part of the fuel that drives the engine of life on earth. We possess remarkably adapted organs for detecting this stimulus: our eyes. Indeed, for most of us, sight is the most important way of gathering information about the world. When we speak of light as the stimulus for vision, we are referring more accurately to a range of electromagnetic radiation wavelengths called visible light, between 400 and 700 nm (nanometers: one nm is equal to one-billionth of a meter). For humans, light is a narrow band of electromagnetic radiation. Electromagnetic radiation with a wavelength of between 380 and 760 nm is visible to us. The narrow band that remains is the continuum or spectrum of wavelengths from bluish-violet (around 400 nm) to reddish (about 700 nm) in appearance is best seen in a rainbow. Our sensations shift from violet through blue (shorter wavelengths), green, yellow, orange (medium wavelengths), and finally red (longer wavelengths). The perceived colour of light is determined by three different dimensions: hue, saturation, and brightness (intensity). Light travels at a constant speed of approximately 300,000 kilometers (186,000 miles) per second. Slower oscillations lead to longer wavelengths, and faster ones lead to shorter wavelengths. Wavelengths, the distance between successive peaks and valleys of light energy, determine the first of the three perceptual dimensions of light: Hue or colour. The visible spectrum displays the range of hues that our eyes can detect. Violet 400 nm

Blue

Blue green

Green 500 nm

Yellow orange

Yellow 600 nm

Orange

Red 700 nm

Light can also vary in intensity that is the amount of energy it contains, which corresponds to the second perceptual dimension of light: Brightness. If the intensity of the electromagnetic radiation is increased, the apparent brightness increases, too.

The third dimension, Saturation, refers to the relative purity of the light that is being perceived; the extent to which light contains only one wavelength, rather than many. If all the radiation is of one wavelength, the perceived colour is pure or fully saturated. Conversely, if the radiation contains all wavelengths, it produces no sensation of hue—it appears white. Colours with intermediate amounts of saturation consist of different mixtures of wavelength. For example, deep red colour of an apple is highly saturated and is more pure colour appears, whereas the pale pink colour is low in saturation. Vision starts with the sequence of events that begins when patterns of light entering the eye that stimulate visual receptors. The information received by the eye is preprocessed and the encoded message is transmitted through the visual pathways leading to occipital lobe in the cerebral cortex. Our eye occupies the first place among the sense organs, and it is the “queen of the senses”. The human eye is the most complex sense organ. Each eye is about 25 mm in diameter and weighs about 7 gm. In certain respects the eye can be compared with a camera. The physical sensations of light from the environment are collected by the visual receptors located in the eye. Our eye consists of the following parts: (i) Socket: It is the case that lodges the eye. It is oval in shape (see Figure 3.1). This indeed protects the eyeball from external injuries and blows. It is lined with fatty tissues which provide cushion to the eyeball and allow its free movement.

Figure 3.1 Human eye.

(ii) Eye-lids and eye lashes: The eye opens in order to receive the light in. Nature has designed the eye-lids to protect the eyeball from any injury

and so they act as covers to the eyeballs. Eye-lids are made of thin skin and certain nerve structures. At the end of the eye-lids, there are long hairs called eye-lashes (see Figure 3.1). The function of the eye-lashes is to protect the eyeballs from the entry of any external material. (iii) The eyeball: The eyeball is oval in shape and hollow in structure (see Figure 3.2). Its diameter is about an inch. In the front, it is transparent. The eyeball consists of three layers or coats, such as the following:

Figure 3.2 Front view of human eye.

(a) Outer layer: The entire eyeball is covered by two coats. The outer layer coat is called the Sclerotic Coat. The sclerotic coat is hard in texture and whitish in colour (see Figures 3.2 and 3.3). It gives protection to the inner structure of the eye and maintains its shape. Light Cornea Sclerotic coat Choroid Pupil

Figure 3.3 Anatomy of human eye.

Cornea (the eye’s transparent outer coating): It is the hard transparent area situated at the front of the eye that allows the light to pass into the eye. It can be seen and touched from outside. It does not have blood vessels and so it does not get the nutrition from lymph (blood). Light rays first pass through this transparent protective structure and then enter the eye through the pupil. Pupil is an opening in the eye; just behind the cornea, through which light rays enter the eye (see Figures 3.2 and 3.3). Rods and cones or the visual receptor cells: The retina consists of millions of sensitive cells called Rods and Cones scattered unevenly in the Retina (see Figure 3.3). Rods and cones efficiently perform two of the major tasks that we require of our visual system. Rods: These cells assist in the vision where the light is dim because rods’ sensitivity increases with the decrease in the intensity or strength of light. The rods are very sensitive to even very faint or dim light. Hence, our vision of dim light is rodvision and not cone-vision. Rods are extremely sensitive to light, and are approximately 500 times more sensitive to light than cones (Eysenck, 1999). The sensitivity of rods means that movement in the periphery of vision can be detected very readily. Rods, however, are colour blind. Being colourless, rod cells work when the cones do not and that is when object is colourless. The change over to rod-vision due to fall in intensity or strength of light is called Purkinge-phenomenon. There are 120 million rods located in the retina of the eye. The Retina is a postage stamp-sized structure that contains two types of light sensitive receptor cells (rods and cones) about 5 million cones and about 120 million rods (Coren, Ward and Enns, 1999). The rods are most densely present in the outer part of the retina. Rods are visual receptor cells that are important for night vision. They are better for night vision because they are much more sensitive than cones. Cones: Cones are more highly developed cells than the rods. They provide us with colour vision and help us to make fine

discriminations. Cones are mostly located in the central part of the retina. Cones (approximately 120 million), located primarily in the center of the retina, an area called Fovea (see Figures 3.3, 3.4, 3.5 and 3.6), function best in bright light and play a key role both in colour vision and in our ability to notice fine details. Cones are visual receptor cells that are important in daylight vision and colour vision. The colour of an object can be clearly seen only when the rays of light fall upon the Fovea, where only cones are present, and not when they fall on the outermost areas of the Retina, where only rods are present. This shows that colour vision is cone-vision and not rod-vision. Colour vision is possible because there are three types of cones, each possessing different photo-pigments. One type of cone is maximally sensitive to light from the short-wavelength area of the spectrum; a second type of cone responds most to mediumwavelength light; and the third type responds maximally to longwavelength light. Perceived colour, however, is not affected only by the wavelength of the light reflected from an object. Colour blindness is usually caused by deficiencies in cone pigment in the retina of the eye. Once stimulated, the rods and cones transmit neural information to other neurons called Bipolar Cells. These cells, in turn, stimulate other neurons, called Ganglion Cells. Axons from the Ganglion Cells converge to form the optic nerve (see Figures 3.3 and 3.4) and carry visual information to the brain (cerebral cortex). No receptors (rods and cones) are present where this nerve exits the eye, so there is a “Blind Spot” at this point of our visual field (see Figure 3.3). (b) Middle layer: The middle coat is black in colour is called the Choroid (see Figure 3.3). It is surrounded or lined with a thick dark coating, designed to absorb the surplus or excessive rays of light which could otherwise cause blurred or vague vision. The Choroid contains a network of blood vessels which supply blood to the eye. It is continued in front by a muscular curtain which supplies blood to the eye. It is continued in front by a muscular

curtain called the Iris (see Figures 3.2 and 3.3). Iris is visible through the Cornea as the coloured portion of the eye. Iris adjusts the amount of light that enters by constricting or dilating the pupil. In the centre of the Iris, there is a hole or opening called the Pupil (see Figures 3.2 and 3.3), which can increase or decrease in size because the Iris is capable of contraction and expansion. Pupil is the opening at the center of the iris which controls the amount of light entering the eye, dilates and constricts. There is a transparent Biconvex Lens just behind the pupil. Lens is the transparent structure that focuses light onto the retina (see Figure 3.3). It is a curved structure behind the pupil that bends light rays, focusing them on the retina. It focuses automatically—not by coming forwards or moving inwards, but by altering its surfaces or curvatures by means of the contraction and expansion of the Ciliary Muscles. The Ciliary Muscles are attached to the sclerotic layer just where it merges into the Cornea (see Figure 3.3). (c) Innermost layer: The retina is the innermost coat of the eye (see Figures 3.3 and 3.4). Retina is the surface at the back of the eye containing the rods and cones. Retina is the innermost membrane of the eye that receives information about light using rods and cones. The functioning of the retina is similar to the spinal cord—both act as highway for information to travel on. It has the shape of the cup. The space enclosed by the retinal cup contains a transparent jellylike fluid called the Vitreous Humour (see Figure 3.3). Vitreous Humour gives shape and firmness to the eye and keeps the Retina in contact with the other two coats—the middle coat and the innermost coat. Similarly, the space between the lens and the cornea is filled with a clear watery fluid called the Aqueous Humour.

Figure 3.4 The retina.

Cornea

Pupil and lens

Retina

Optic nerve

Occipital lobe (cerebral cortex) The light rays enter the eye through the cornea, and pass through the pupil and the lens, and then, reach the retina. From the retina, the optic nerve carries the impression to the brain, where it gives rise to the sensation of vision or sight. Optic nerve is a bundle of nerve fibers at the back of the eye which carry visual information to the brain (see Figures 3.3 and 3.4). The optic nerve enters the back of the eyeball. In the centre of this place, is a point called the Blind Spot (see Figure 3.3). Whenever the light rays fall on this spot, no sensation of sight or vision takes place. This spot is at the back of the retina through which the optic nerve exits the eye. This exit point contains no rods or cones and is therefore insensitive to light. At the centre of the back of the eyeball, exactly opposite to the pupil and very near to the blind spot, is another round spot called the Yellow Spot or the Fovea (see Figures 3.3, 3.4, 3.5 and 3.6). Fovea is a tiny spot in the centre of the retina that contains only cones or where cones are highly concentrated. Visual acuity is best here. So, when you need to focus on something, you attempt to bring the image into the fovea.

Figure 3.5 Simple diagram of human fovea.

Figure 3.6 Human fovea.

This is the point of the clearest vision. If we want to see the object clearly, we move our eyeball so that the light from the object we want to see clearly, passing through the centre of the lens, may fall on the fovea.

Theories of colour vision Various theories of colour vision have been proposed for many years—long before it was possible to disprove or validate them by physiological means.

Thomas Young (1773–1829)

Young-Helmholtz’s theory of colour vision or trichromatic or tristimulus theory of colour vision: In 1802, Thomas Young, a British physicist and physician proposed that the eye detected different colours because it

contained three types of receptors, each sensitive to a single hue. His theory was referred to as the Trichromatic (three colours) theory. It was suggested by the fact that for a human observer, any colour can be reproduced by mixing various quantities of three colours judiciously selected from different points along the spectrum.

Hermann Von Helmholtz (1821–1894)

Young-Helmholtz’s theory of colour vision or Trichromatic or Tristimulus theory of colour vision suggests that we have three different types of cones (colour-sensitive cells) in our ultra range of light wavelengths in our retina— a range roughly corresponding to Blue (400–500 nm), Green (475–600 nm), or Red (490–650 nm). This theory indicates that we can receive three types of colours (red, green, and blue) and that cones vary the ratio of neural activity. Careful study of the human retina suggests that we do possess three types of receptors although, there is a great deal of overlap among the three types’ sensitivity range (De Valois and De Valois, 1975; Rushton, 1975). According to the trichromatic theory, the ability to perceive colours results from the joint action of the three receptor cells. Thus, light of a particular wavelength produces differential stimulation of each receptor type, and it is the overall pattern of stimulation that produces our rich sense of colour. This differential sensitivity may be due to genes that direct different cones to produce pigments sensitive to Blue, Green, or Red (Natvans, Thomas, and Hogness, 1986). Trichromatic theory however, fails to account for certain aspects of colour vision, such as the occurrence of negative afterimages—sensations of complimentary colours that occur after one stares at a stimulus of a given colour. For example, after you stared at a red object, if you shift your gaze or focus to a neutral background or white surface, sensations of green may follow. Similarly, after you stare at a yellow stimulus, sensations of blue may occur.

Opponent-process theory or Ewald Hering’s theory of colour vision: Hering disagreed with the leading theory developed mostly by Thomas Young and Hermann Von Helmholtz (Turner, 1994). Hering looked more at qualitative aspects of colour and said there were six primary colours, coupled in three pairs: red-green, yellow-blue and white-black. Any receptor that was turned off by one of these colours was excited by its coupled colour. This results in six different receptors. It also explained afterimages. His theory was rehabilitated in the 1970s when Edwin Herbert Land developed the Retinas theory that stated that whereas Helmholtz’s colours hold for the eye, in the brain the three colours are translated into six.

Karl Ewald Konstantin Hering (1834–1918)

According to this theory, colour perception depends on the reception of antagonist colours. Each receptor can only work with one colour at a time. So, the opponent colour in the pair is blocked out. The pairs are red-green; blue-yellow; black-white (light-dark). The opponent-process theory suggests that we possess specialised cells that play a role in sensations of colour (De Valois and De Valois, 1975). Two of these cells, for example, are red and green (complimentary colours). One is stimulated by red light and inhibited by green light, whereas the other is stimulated by green light and inhibited by red. This is where the phrase opponent-process originates. Two additional types of cells handle yellow and blue: one is stimulated by yellow and inhibited by blue, while the other shows the opposite pattern. The remaining two types handle black and white—again, in an opponent-process manner. Opponent-process theory can help explain the occurrence of negative afterimages (Jameson and Hurvich, 1989). The idea is that when stimulation of the cell in an opponent pair is terminated, the other is also automatically activated. Thus, if the original stimulus viewed was yellow, the after-image seen would be blue. Each opponent pair is stimulated in different patterns by the three types of cones. It is the overall pattern of such stimulation that

yields our complex and eloquent or powerful or impressive sensation of colour. Although these theories (Young-Helmholtz or Trichromatic or Tristimulus theory and opponent-process theory) competed for many years, both are necessary to explain our impressive ability to respond to colour. Trichromatic or Tristimulus theory explains how colour coding occurs in the cones of the retina, whereas opponent-process theory by Hering accounts for processing in higher-order cells (Coren, Ward, and Enns, 1999; Hurvich, 1981; Matlin and Foley, 1997). Evolutionary theory of colour vision: In contrast to the prevailing threecolour and opponent-colour explanations of colour vision, Christine LaddFranklin (1847–1930) developed an evolutionary theory that posited three stages in the development of colour vision. While studying in Germany in 1891–1892, she developed the Ladd-Franklin theory, which emphasized the evolutionary development of increased differentiation in colour vision and assumed a photochemical model for the visual system. She is probably best-known for her work on colour vision. Presenting her work at the International Congress of Psychology in London in 1892, she argued that black-white vision was the most primitive stage, since it occurs under the greatest variety of conditions, including under very low illumination and at the extreme edges of the visual field. The colour white, she theorised, later became differentiated into blue and yellow, with yellow ultimately differentiated into red-green vision. Her theory, which criticised the views of Hermann von Helmholtz and Ewald Hering, was widely accepted. Ladd-Franklin’s theory was well-received and remained influential for some years, and its emphasis on evolution is still valid today.

Christine Ladd-Franklin (1847–1930)

She published an influential paper on the visual phenomenon known as “Blue Arcs” in 1926, when she was in her late seventies, and in 1929, a year before her death, a collection of her papers on vision was published under the title Color and Color Theories. The Ladd-Franklin theory of colour vision stressed increasing colour differentiation with evolution and assumed a photochemical model for the visual system. Her principal works are The Algebra of Logic (1883), The Nature of Color Sensation (1925), and Color and Color Theories (1929). Ladd-Franklin’s theory of colour vision was based on evolutionary theory. She noted that some animals are colour blind and assumed that achromatic vision appeared first in evolution and colour vision later. She assumed further that the human eye carries vestiges of its earlier evolutionary development. She observed that the most highly evolved part of the eye is the fovea, where at least in daylight, visual acuity and colour sensitivity are greatest. Moving from the fovea to the periphery of the retina, acuity is reduced and the ability to distinguish colour is lost. However, in the periphery of the retina, night vision and movement perception are better than in the fovea. Ladd-Franklin assumed that peripheral vision (provided by the rods of the retina) was more powerful than foveal vision (provided by the cones of the retina) because night vision and movement detection are crucial for survival but if colour vision evolved later than achromatic vision, was it possible that colour vision itself evolved in progressive stages? After carefully studying the established colour zones on the retina and the facts of colour blindness, Ladd-Franklin concluded that colour vision evolved in three stages. Achromatic vision came first, then blue-yellow sensitivity, and finally red-green sensitivity. The assumption that the last to evolve would be the most fragile explains prevalence of red-green colour blindness. Blue-green colour blindness is less frequent because it evolved earlier and is less likely to be defective. Achromatic vision is the oldest and therefore the most difficult to disrupt. Ladd-Franklin, of course, was aware of Helmholtz’s and Hering’s theories, and although she preferred Hering’s theory, her theory was not offered in opposition to either. Rather, she attempted to explain in evolutionary terms the origins of the anatomy of the eye and its visual abilities.

After initial popularity, Ladd-Franklin’s theory fell into neglect, perhaps because she did not have adequate research facilities available to her. Some believe, however, that her analysis of colour vision still has validity (Hurvich, 1971).

3.4.4 Auditory Sensation Next to vision, audition or hearing is the second important sense. Like vision, hearing also provides reliable spatial information. Ear is the organ for receiving the auditory sensation. The auditory system is reasonably complex (shown here in Figure 3.7). In the outside world, any physical movement disturbs the surrounding medium (usually air) and pushes molecules of air back and forth (vibrations in the air). This results in changes in pressure spread outward in the form of sound waves travelling at a rate of about 1100 ft (feet) per second. When these sound waves strike our ears, they initiate or start a set of further changes that ultimately trigger the auditory receptors. It has been experimentally determined and verified that human ear (child and young adult) is sensitive to sound waves within a definite range of frequency, that is between 20 Hz (hertz) to about 20,000 Hz cycle per second. Older adults progressively lose sensitivity. Nature the human ear is most sensitive to sounds with frequencies between 1,000 and 5,000 Hz (Coren, Ward, and Enns, 1999). The waves of frequencies below 20 Hz and those above 20,000 Hz are technically referred to as Parasonic rays and Ultrasonic rays, respectively.

Figure 3.7 Structure of human ear.

Physical characteristics of sound (i) Amplitude (Physical strength) (ii) Wavelength (iii) Frequency Sound waves can vary in amplitude as well as in wavelength. Amplitude refers to the height of a wave crest and is a measure of physical strength of sound wave (see Figure 3.8). The wavelength is the distance between successive crests. Sound waves are generally described by their frequency (see Figure 3.9). The human ear can perceive frequencies from 16 cycles per second, which is a very deep bass, to 28,000 cycles per second, which is a very high pitch. The human ear can detect pitch changes as small as 3 hundredths of one per cent of the original frequency in some frequency ranges. Some people have “perfect pitch”, which is the ability to map a tone precisely on the musical scale without reference to an external standard.

Figure 3.8 Amplitude.

Figure 3.9 Frequency.

Sound waves travel in same waves and have three properties: loudness, pitch, and timbre. Sound waves enter through the pinna or auricle (outer ear) and strike the tympanic membrane (the eardrum, from which sound waves travel to the ossicles; layer of skin) or eardrum and in turn activate three bones of the middle ear known as the ossicles—malleus (hammer bone), incus (anvil bone), and stapes (stirrup bone) (see Figures 3.7, 3.10 and 3.11). From the ossicles (three bones in the ear between the tympanic membrane and the fenestra ovalis), information passes to the fenestra ovalis, which is an opening in the bone that surrounds the inner ear (see Figure 3.13). From there, information passes to the cochlea (see Figures 3.7, 3.10, 3.12 and 3.13), which is a coiled tube filled with liquid. The vibrations give energy to the cochlea, located in the inner ear (see Figure 3.12). There are two cochleas, one on each side of the head. Inside each cochlea there are hair cells between two membranes to move and thus the hair cells. This in turn produces action potentials in the auditory nerve (see Figures 3.7, 3.10 and 3.13). The neural impulses from the cochlea leave through auditory nerve and reach medial gemculate nucleus in the thalamus. Information from each cochlea passes to both sides of the brain, as well as to sub-cortical areas. The

process is like this: Pinna Auditory canal Eardrum Hammer bone bone Cochlea Medial gemculate nucleus

Anvil bone

Stirrup

Structure of the ear Our ear is made of three parts: the outer or the external ear, the middle ear and the inner ear. Let us study in detail the structure of the ear: (i) Outer or External ear: This is the external part of the ear which we can see outwardly. It consists of the following: (a) Pinna or Auricle: Pinna is the technical term for the visible part of our hearing organ, the ear (see Figures 3.7 and 3.10). Outer or external ear comprises of Pinna or Auricle (see Figure 3.7). However, this is only a small part of the entire ear. The outer ear protrudes away from the head and is shaped like a cup to direct sounds toward the tympanic membrane. Inside the ear is an intricate system of membranes, small bones and receptor cells that transform sound waves into neural information for the brain.

Figure 3.10 Structure of the whole ear.

(b) Eardrum: Eardrum is a thin piece of tissue just inside the ear (see Figures 3.7 and 3.10), moves ever so slightly in response to sound waves striking it.

(ii) Middle ear: When eardrum moves, it causes three tiny bones (the malleus, incus and stapes; Hammer, Anvil, and Stirrup) within middle ear to vibrate (see Figures 3.7, 3.10, 3.11 and 3.13). The third of these bones that is stirrup bone or stapes is attached to the oval-window, which covers a fluid-filled, spiral-shaped structure called Cochlea (see Figures 3.7, 3.10, 3.12 and 3.13).

Figure 3.11 Middle ear.

(iii) Inner ear: The inner ear or cochlea (see Figures 3.7, 3.10, 3.12 and 3.13), is a spiral-shaped chamber covered internally by nerve fibers that react to the vibrations and transmit impulses to the brain via the auditory nerve (see Figures 3.7, 3.10 and 3.13). The brain combines the input of our two ears to determine the direction and distance of sounds.

Figure 3.12 Inner ear-cochlea.

Hair like receptor cells are contained in the corti (sensory receptor in the cochlea that transduces sound waves into coded neural impulses). Vibration in the cochlea fluid set the basilar membrane in motion. This movement, in turn, moves the organ of corti and stimulates the receptor cells that it contains. These receptor cells transducers the sound waves in the cochlear fluid into coded neural impulses that are sent to the brain. Vibration of the oval window causes movements of the fluid in the cochlea. Finally, the movement of fluid bends tiny hair cells, the true sensory receptors of the sound. The neural messages they (tiny hair cells) create are then transmitted to the brain via the auditory nerve. The inner ear has a vestibular system formed by three semicircular canals (see Figure 3.10) that are approximately at right angles to each other and which are responsible for the sense of balance and spatial orientation. The inner ear has chambers filled with a viscous fluid and small particles (otoliths) containing calcium carbonate. The movement of these particles over small hair cells in the inner ear sends signals to the brain that are interpreted as motion and acceleration. (a) Fenestra ovalis: Fenestra ovalis is a part of the ear involved in auditory perception; more specifically, an opening in the bone which surrounds the inner ear (see Figure 3.13).

Figure 3.13 Fenestra ovalis.

Theories of hearing Historically, there have been two competing theories of hearing, the Resonance or Place theory and the Frequency theory. Crude forms of the resonance theory can be found as far back as 1605, but the beginning of the modern resonance theory can be attributed to Helmholtz in 1857. The frequency theory can be dated back to Rinne in 1865 and Rutherford in 1880. These theories underwent a continuous process of modification through to the middle of the 20th century. An overview of the development of these theories can be found in Wever (1965) and Gulick (1971). Low sounds Frequency theory High sounds Place theory Middle range (500–4,000) Both theories Table 3.3 illustrates the physical and perceptual dimensions of sound. Table 3.3 Physical and perceptual dimensions of sound Physical dimension

Perceptual dimension

Amplitude (Intensity) Frequency Complexity

Loudness Pitch Timbre

Loud Low Simple

Soft High Complex

The resonance or place theory: The place theory is usually attributed to Hermann Helmholtz, though it was widely believed much earlier. This theory of hearing states that our perception of sound depends on where each component frequency produces vibrations along the basilar membrane. By this theory, the pitch of a musical tone is determined by the places where the

membrane vibrates. Place theory (also called the Travelling wave theory) suggests that sounds of different frequencies cause different places among the basilar membrane (the floor or base of the cochlea) to vibrate. The vibrations, in turn, stimulate the hair cells—the sensory receptors for sound. Actual observations have shown that sound does produce pressure waves and that these waves peak or produce maximal displacement, at various distances along the Basilar Membrane, depending on the frequency of the sound (Bekesy, 1960). High-frequency sounds cause maximum displacement at the narrow end of the basilar membrane near the oval window, whereas lower frequencies cause maximal displacement toward the wider, farther end of the basilar membrane. Unfortunately, place theory does not explain our ability to discriminate among very low-frequency sounds—sounds of only a few hundred cycles per second—because displacement on the basilar membrane is nearly identical for these sounds. Another problem is that place theory does not account for our ability to discriminate among sounds whose frequencies differ by as little as 1 or 2 Hz for these sounds; and, basilar membrane displacement is nearly identical. It is known through certain investigations that the deafness of high pitch is due to some defect in the ground sphere or floor of the basilar membrane and the deafness of low pitch are due to some defect in the apex of the basilar membrane. It is thus clear that different pitches are connected to different portions of the basilar membrane. Forbes and Gregg (1915) ascertained through their experiments that the decision about the pitch of some sound waves depends on those fibers which are disturbed or moved by it and send the greatest number of nervous impulses to the brain. The place theory, in its most modern form, states that the inner ear acts as a tuned resonator which extracts a spectral representation of the incoming sounds which it passes via the auditory nerve to the brainstem and the auditory cortex. This process involves a tuned resonating membrane, the basilar membrane, with frequency place-mapping. Frequency theory: Rutherford was the first to present in 1886 the frequency theory about the auditory sensation but in 1918, Wrightson explained it in detail and presented in a scientific way. Frequency theory suggests that sounds of different pitch cause different rates of neural firing. Thus, high-pitched sounds produce high rates of

activity in the auditory nerve, whereas low-pitched sounds produce lower rates. Frequency theory seems to be accurate up to sounds of about 1,000 Hz —the maximum rate of firing for individual neurons. Above that level (1,001 Hz to 20,000 Hz), the theory must be modified to include the Volley Principle—the assumption that sound receptors for other neurons begin to sound with a frequency of 5,000 Hz might generate a pattern of activity in which each of five groups of neurons fires 1,000 times in rapid succession— that is, in volleys. Our daily activities regularly expose us to sounds of many frequencies, and so both theories are needed to explain our ability to respond to this wide range of stimuli. Frequency theory explains how low-frequency sounds are registered whereas place theory explains how high-frequency sounds are registered. In the middle ranges, between 50 and 4,000 Hz, the range that we use for most daily activities, both theories apply.

3.4.5 The Cutaneous Sensation The sense of touch is distributed throughout the body. Nerve endings in the skin and other parts of the body transmit sensations to the brain. Some parts of the body have a larger number of nerve endings (see Figure 3.14) and, therefore, are more sensitive.

Figure 3.14 Structure of skin.

The skin is capable of picking up a number of different kinds of sensory information. The skin can detect pressure, temperature (cold and warmth), and pain. Although the skin can detect only three kinds of sensory information, there are atleast four different general types of receptors in the skin: the free nerve endings, the basket cells around areas the base of hairs, the tactile discs, and the specialised end bulbs. It appears that all four play a role in the sense of touch (pressure), with the specialised end bulbs important in sexual pleasure. The free nerve endings are the primary receptors for temperature and pain (Groves & Rebec, 1988; Hole, 1990). Each square inch of the layers of our skin contains nearly 20 million cells, including many sense receptors. The tips of the fingers contain many cutaneous receptors for touch or pressure. Some of the skin receptors have free nerve endings, while some have some sort of small covering over them. We call these latter cells encapsulated nerve endings, of which there are many different types. It is our skin that gives rise to our psychological experience of touch or pressure and of warmth and cold. It would be very convenient if each of the different types of receptor cells within the layers of our skin independently produced a different type of psychological sensation, but such is not the case. Indeed, one of the problems in studying the skin senses or cutaneous senses is trying to determine which cells in the skin give rise to the different sensations of pressure and temperature. There are different receptors in the skin responsible for each different sensation. Unfortunately, this proposal is not supported by the fact. Hairs on the skin magnify the sensitivity and act as an early warning system for the body. The fingertips and the sexual organs have the greatest concentration of nerve endings. The sexual organs have “erogenous zones” which when stimulated start a series of endocrine reactions and motor responses resulting in orgasm. By carefully stimulating very small areas of the skin, we can locate areas that are particularly sensitive to temperature. Warm and cold temperatures each stimulate different locations on the skin. Even so, there is no consistent pattern of receptor cells found at these locations, or temperature spots. That is, we have not yet located specific receptor cells for cold or hot. As a matter of fact, our experience of hot seems to come from the simultaneous

stimulation of both warm and cold spots. Touch sensations can be of the following types: (i) Pressure: The skin is amazingly sensitive to pressure, but sensitivity differs considerably from one region of the skin to another depending on how many skin receptors are present. In the most sensitive regions—the fingertips, the lips, and the genitals—a pressure that pushes in the skin less than 0.001 mm can be felt, but sensitivity in other areas is considerably less (Schiffman, 1976). Perhaps, the most striking example of the sensitivity of the skin is its ability to “read” and that too by blind people. Many blind people can read books using the Braille alphabet, patterns of small raised dots that stand for the letters of the alphabet. An experienced Braille user can read up to 300 words per minute using the sensitive skin of the fingertips. (ii) Temperature: The entire surface of the skin is able to detect temperature that is whether the air outside is hot or cold, but we actually sense skin temperature only through sensory receptors (free nerve endings) located in rather widely spaced “spots” on the skin. One set of spots detects warmth and one detects coldness. The information sent to the brain by these spots creates the feeling of temperature across the entire skin surface. (iii) Pain: Pain is said to be an aversive motive. It refers to avoidance drive. Any stimulus that is painful to the organism, invites avoidance or aversion tendency for it. Loud voices, electric shocks, pricking of pin, and the like give pain to the individual. So, they are usually avoided. When pain is prolonged and continuous, and can be escaped by developing appropriate action, it proves to be most effective and useful. Many bad habits are unlearned and good habits are learned by useful application of a painful stimulus. Chronic pain can also impair the immune system (Page, et al., 1993). Pain is unpleasant and we all want to avoid it. Pain alerts us to problems occurring somewhere within our bodies. Our feelings of pain are private sensations—they are difficult to share or describe to others (Verillo, 1975). Many stimuli can cause pain. Very intense stimulation of virtually any sense receptor can produce pain. Too much light, very strong pressure on the skin, excessive temperatures, very loud sounds, and even too many “hot” spices

can all result in our experiencing pain. The stimulus for pain need not be intense. Under the right circumstances, even a light pin prick can be very painful. Our skin seems to have many receptors for pain, but pain receptors can also be found deep inside our bodies—consider stomach aches, lower back pain, headaches. Pain is experienced in our brains; it is the only “sense” for which we can find no one specific centre in the cerebral cortex. The sensation of pain is transmitted along two different nerve pathways in the spinal cord—rapid and slow neural pathways. This is why we often experience “first and second pain” (Melzack and Wall, 1983; Sternbach, 1978). A theory of pain that still attracts attention from researchers is Melzack & Wall’s Gate-control theory (Melzack, 1973). Melzack believes that pain signals are allowed in or blocked from the brain by neural “gates” in the spinal cord and brainstem. It suggests that our experience of pain happens not so much at the level of the receptor (say, in the skin), but within the central nervous system. The theory proposes that a gate like structure in the spinal cord responds to stimulation from a particular type of nerve—one that “opens the gate” and allows for the sensation of pain by letting impulses on up to the brain. Other nerve fibers can offset the activity of the pain-carrying fibers and “close the gate” so that pain messages are cut off and never make it to the brain. The sensation of pain is transmitted along two different nerve pathways in the spinal cord—rapid and slow neural pathways. This is why we often experience “first and second pain” (Melzack and Wall, 1983; Sternbach, 1978). The “first pain” is clear, localised feeling that does not “hurt” much, but it tells us that what part of the body have been hurt and what kind of injury has occurred. It can be described as quick and sharp—the kind of pain we experience when we receive a cut. The “second pain” is more diffuse, dull and throbbing, a long-lasting pain that hurts in the emotional sense like the pain we experience from a sore muscle or an injured body part. There are two reasons that we experience these two somewhat separate pain sensations in sequence: (i) The first type of pain seems to be transmitted through large myelinated sensory nerve fibers (Campbell and La Motte, 1983). Impulses travel

faster along myelinated fibers, and so it makes sense that sharp sensations of pain are carried via these fiber types. In contrast, dull pain is carried by smaller unmyelinated nerve fibers, which conduct neural impluse more slowly. (ii) The reason that we experience first and second pain is that the two neural pathways travel to different parts of the brain. The rapid pathways travel through the thalamus to the somatosensory area. This is the part of the parietal lobe of the cerebral cortex that receives and interprets sensory information from the skin and body. When the information transmitted to this area on the rapid pathway is interpreted, we know what has happened and where it has happened, but the somatosensory area does not process the emotional aspects of the experience of “pain”. Information that travels on the slower second pathway is routed through the thalamus to the limbic system. It is here in the brain system that mediated emotion, that the “ouch” part of the experience of pain is processed. Pain involves more than the transmission of pain messages to the brain, however. There is not a direct relationship between the pain stimulus and the amount of pain experienced. Under certain circumstances, pain messages can ever be blocked out of the brain. For example, a football player whose attention is focused on a big game may not notice a painful cut until after the game is over. The pain receptors transmit the pain messages during the game, but the message is not fully processed by the brain until the player is no longer concentrating on the game. There are several situations in which this theory of opening and closing a gate to pain seems reasonable. One of the things that happen when we are exposed to persistent pain is that certain neurotransmitters—endorphins—are released in the brain (Hughes et al., 1975; Terenius, 1982). Endorphins (plural because there may be a number of them) naturally reduce our sense of pain and generally make us feel good. When their effects are blocked, pain seems usually severe. Endorphins stimulate nerve fibers that go to the spinal cord and effectively close the gate that monitors the passage of impulses from pain receptors. One situation that seems to fit the gate-control theory is abnormally persistent pain. Some patients who have received a trauma to some part of

their body, for example through accident or surgery continue to experience pain even after the initial wound is completely healed. Abnormal pain is also found in the so-called “phantom limb” pain experienced by some (about 10 per cent) of amputees. Phantom limb means ability to feel pain, pressure, temperature and many other types of sensations including pain in a limb that does not exist (either amputated or born without). These patients continue to feel pain in an arm or leg, even after that limb is no longer there. Recent thinking is that severe trauma of amputation overloads and destroys the function of important cells in the spinal cord that normally act to close the gate for pain messages, leaving the pain circuits uninhibited (Gracely, Lynch, and Bennett, 1992; Laird and Bennett, 1991). Think of some of the other mechanisms that are useful in moderating the experience of pain. Hypnosis and cognitive self-control (just trying very hard to convince yourself that the pain you are experiencing is not that bad and will go away) are effective (Litt, 1988; Melzack, 1973). That pain can be controlled to some extent by cognitive training is clear from the success of many classes aimed at reducing the pain of childbirth. The theory is that psychological processes influence the gate-control centre in the spinal cord. We also have ample evidence that placebos (an inactive substance that works because a person has to come to believe that it will be effective) can be effective in treating pain. A placebo is a substance (perhaps in pill or tablet form) that a person believes will be effective in treating some symptoms, when, infact there is no active pain-relieving ingredient in the substance (placebo). When subjects are given a placebo that they genuinely believe will alleviate pain, endorphins are released in the brain which, again, help to close the gate to pain-carrying impulses (Levine et al., 1979). Another process that works to ease the feeling or experience of pain, particularly pain from or near the surface of the skin, is called counterritation. The idea here is to stimulate forcefully (not painfully, of course) an area of the body near the location of the pain. Dentists have discovered that rubbing the gum near where a novocaine needle is to be inserted significantly reduces the patient’s experience of the pain of the needle. Again, as you might have guessed, the logic is that all the stimulation from the rubbing action in nearby area serves to close the pain gate so that needle has little effect. And speaking of needles, the ancient oriental practice of acupuncture can also be tied to the gate-control theory of pain. There also

is evidence that acupuncture releases endorphins in the brain. Perhaps, each or all of these functions serve the major purpose of controlling pain by closing off impulses to the brain.

3.4.6 The Olfactory Sensation or Sensation of Smell The nose is the organ responsible for the sense of smell (see Figure 3.15). The cavity of the nose is lined with mucous membranes that have smell receptors connected to the olfactory nerve. The smells themselves consist of vapours of various substances. The smell receptors interact with the molecules of these vapours and transmit the sensations to the brain. The nose also has a structure called the vomeronasal organ whose function has not been determined, but which is suspected of being sensitive to pheromones that influence the reproductive cycle. The smell receptors are sensitive to seven types of sensations that can be characterised as camphor, musk, flower, mint, ether, acrid, or putrid. The sense of smell is sometimes temporarily lost when a person has a cold. Dogs have a sense of smell that is many times more sensitive than human beings.

Figure 3.15 Structure of human nose.

The stimulus for sensations of smell consists of molecules of various substances (odorants) contained in the air. Such molecules enter the nasal passages, where they dissolve in moist nasal tissues. This brings them in contact with receptor cells contained in the olfactory epithelium, which lie at the extreme top of the nasal passages. “Olfactory epithelium” is the dimesized mucous coated sheet or membrane of receptor cells at the top of the

nasal cavity. Receptor cells for the olfactory sensation are located in the nose at its apex. Human beings possess only about 50 million of these receptors. (Dogs, in contrast, possess more than 200 million receptors; four times of human beings). Nevertheless, our ability to detect smells is impressive. Chemicals in the air we breathe pass by the olfactory receptors on their way to the lungs. Our 50 million olfactory receptor cells reside within two patches of mucous membrane (the olfactory epithelium), each having an average of about one square inch. In mammals, the olfactory receptors are located high in the nasal cavity. The yellow-pigmented olfactory membrane in humans covers about 2.5 cm2 (0.4 sq in.) on each side of the inner nose. Less than 10 per cent of the air that enters the nostrils reaches the olfactory epithelium; a sniff is needed to sweep air upward into the nasal cavity so that it reaches the olfactory receptors. As only a part of the breath reaches the receptor cells, it is necessary to draw a deeper breath in order to smell an odour. The odour carrying air or air which carries odour, when drawn in, activates these cells by touching them. The sensation is carried to the brain and odour is felt. Our olfactory senses are restricted, however, in terms of the range of stimuli to which they are sensitive. Just as the visual system can detect only a small portion of the total electromagnetic spectrum (400–700 nm), human olfactory receptors can detect only substances with molecular weights—the sum of the atomic weights of all atoms in an odorous molecule—between 15 and 300 (Carlson, 1998). This explains why we can smell the alcohol contained in a mixed drink, with a molecular weight of 46, but cannot smell table sugar, with a molecular weight of 342. As with taste, we seem to be able to smell only a limited number of primary odours. The first scientist to make a serious effort to classify odours was the Swedish botanist Linnaeus (1756). He distinguished 7 classes of odours, namely: (i) Aromatic as carnation (ii) Fragrant as lily (iii) Ambrosial as musk (iv) Alliaceous as garlic (v) Hircine as valerian

(vi) Repulsive as certain bugs (vii) Nauseous as carrion Zwaardemaker (1895, 1925) added two classes to it—the ethereal and the empyreumatic. Henning (1915–16, 1924) made a radical revision of Zwaardemaker’s arrangement, ending up with the following six classes: (i) Fragrant (ii) Ethereal (fruity) (iii) Resinous (iv) Spicy (v) Putrid (rotten, stinking) (vi) Empyreumatic (burnt) There is less agreement among psychologists about primary odours than about primary tastes, but one widely used system of classifying odours divides all of the complex aromas and odours of life into combinations of seven primary qualities (Ackerman, 1991; Amoore, Johnston, and Rubin, 1964): (i) Resinous (camphor) (ii) Floral (roses) (iii) Minty (peppermint) (iv) Ethereal (fruits; pears) (v) Musky (musk oil) (vi) Acrid (vinegar) (vii) Putrid (rotten eggs) For many years, recognition of specific odours had been an enigma. Humans can recognise up to ten thousand different odourants, and other animals can probably recognise even more of them (Shepherd, 1994). However, professionals who create perfumes and other aromas distinguish 146 distinct odours (Dravnicks, 1983). Interestingly, nearly all of the chemicals that humans can detect as odours are organic compounds, meaning they come from living things. In contrast, we can smell very few inorganic compounds—the sniff that rocks and sand are made of. Thus, our noses are useful tools for sensing the qualities of plants and animals—necessarily among other things, to distinguish between poisonous and edible things

(Cain, 1988). Although, we can only smell compounds derived from living things, chemists have long known how to create these organic compounds in test tubes. This means that any aroma can be custom created to order and no longer has to be painstakingly extracted from flower petal and spices.

Odorous substances To be odorous, a substance must be sufficiently volatile for its molecules to be given off and carried into the nostrils by air currents. The solubility of the substance also seems to play a role; chemicals that are soluble in water or fat tend to be strong odorants, although many of them are inodorous. No unique chemical or physical property that can be said to elicit the experience of odour has yet been defined. Only seven of the chemical elements are odorous: (i) Flourine (ii) Chlorine (iii) Bromine (iv) Iodine (v) Oxygen (as ozone) (vi) Phosphorous and (vii) Arsenic Most odorous substances are organic (carbon-containing) compounds in which both the arrangement of atoms within the molecule as well as the particular chemical groups that comprise the molecule that influence odour. Stereoisomers (that is, different spatial arrangements of the same molecular components) may have different odours. On the other hand, a series of different molecules that derive from benzene all have a similar odour. It is of historic interest that the first benzene derivatives studied by chemists were found in pleasant-smelling substances from plants (such as oil of wintergreen or oil of anise), and so the entire class of these compounds was labeled aromatic. Subsequently, other so-called aromatic compounds were identified that have less attractive odours.

Odour stimuli Inspite of the relative inaccessibility of the human olfactory receptor cells,

odour stimuli can be detected at extremely low concentrations. Olfaction is said to be 10,000 times more sensitive than taste. A human threshold value for such a well-known odorant as ethyl mercaptan (found in rotten meat) has been cited in the range of 1/400,000,000th of a milligram per litre of air. Temperature influences the strength of an odour by affecting the volatility and hence the emission of odorous particles from the source, humidity also affects odours for the same reasons.

Theories of smell Several theories have been proposed for how smell messages are interpreted by the brain. Stereochemical theory: Stereochemical theory suggests that substances differ in smell because they have different molecular shapes (Amoore, 1970). According to the stereochemical theory, the complex molecules responsible for each of these primary odours have a specific shape that will “fit” into only one type of receptor cell, like a key into a lock. Only when molecules of a particular shape are present well the corresponding olfactory receptor sends its distinctive message to the brain (Cohen, 1988). Unfortunately, support for this theory has been mixed in nearly identical molecules can have extremely different fragrances, whereas substances with very different chemical structures can produce very similar odours (Engen, 1982; Wright, 1982). Other theories have focused on isolating “primary odours”, similar to the basic hues in colour vision. But these efforts have been unsuccessful, because different individuals’ perceptions of even the most basic smells often disagree. One additional intriguing or interesting possibility is that the brain’s ability to recognise odours may be based on the overall pattern of activity produced by the olfactory receptors; olfactory epithelium (Sicard and Holey, 1984). According to this view, humans possess many different types of olfactory receptors, each one of which is stimulated to varying degrees by a particular odourant. Different patterns of stimulation may, in turn, result in different patterns of output that the brain recognises as specific odours. How the brain accomplishes this task is not yet known. Actually, although our ability to identify specific odours is limited, our memory of them is impressive (Schab, 1991). Once exposed to a specific

odour, we can recognise it a month later (Engen and Ross, 1973; Rabin and Cain, 1984). This may be due, in part, to the fact that our memory for odours is often coded as part of memories of a more complex and significant life event (Richardson and Zucco, 1989). Practitioners of a field called aromatherapy claim that they can successfully treat a wide range of psychological problems and physical ailments by means of specific fragrances (Tisserand, 1977). Aroma therapists claim, for example, that fragrances such as lemon, peppermint, and basil lead to increased alertness and energy, whereas lavender and cedar promote relaxation and reduce tension after high-stress work periods (Iwahashi, 1992). The sense of smell is important in and of it; of course, sometimes bringing joyous messages of sweet perfumes to the brain and other times warning us of dangerous and foul odours. But the sense of smell contributes to the sense of taste as well. Not only do we smell foods as they pass beneath our noses on the way to our mouths, but odours do rise into the nasal passage as we chew. We are usually unaware of the grand impact of smell, on the sense of taste, until a head cold or flu makes everything taste like paste. The contribution of smell to taste is important partly because of the greater sensitivity of the sense of smell. The nose can detect the smell of cherry pie in the air that is 1/25,000th of the amount that is acquired for the taste buds to identify (Ackerman, 1991).

Measures of olfactory sensation Following are some measures of olfactory sensation: (i) The dilution technique: Plaffmann (1951) (ii) Olfactometer: Zwardemaker (1887) (iii) Blast injection method: Elsberg & Levy (1935–1936) (iv) Camera Inodorate (v) Constant flow method: Le Magnen (1942–1945)

3.4.7 Gustatory Sensation or Sensation of Taste Gustation means the sense of taste. The tongue is the sense organ of gustatory sensation or it is the tongue which acquires these sensations. Taste is a chemical sense which is detected by special structures called taste buds, of which we all have about 10,000, mainly on the tongue with a few at the

back of the throat and on the palate. Taste buds surround pores within the protuberances on the tongue’s surface and elsewhere. There are four types of taste buds: these are sensitive to sweet, salty, sour and bitter chemicals. All tastes are formed from a mixture of these basic elements. The sensory structures for taste in human beings are the taste buds, the clusters of cells contained in goblet-shaped structures (papillae) that open by a small pore to the mouth cavity. The receptors for taste called taste buds (see Figure 3.16), are situated chiefly in the tongue, but they are also located in the roof of the mouth and near the pharynx. Human beings possess about 10,000 taste buds. We are able to taste food and other things because of the 10,000 taste buds on the tongue. Babies have the most taste buds and are the most sensitive to tastes.

Figure 3.16 Structure of tongue.

Each taste bud contains approximately a dozen sensory receptors called taste cells, bag-like structures, that are grouped together much like the segments of an orange. Taste cells are the sensory receptor cells for gustation located in the taste buds. These taste cells are also the taste receptors. The sensation of taste passes through the taste pores and reaches the taste bud where the sensation is transferred to the brain. The result is the experience of taste. It is the taste cells that are sensitive to chemicals in our food and drink (Bartoshuk, 1988). A single bud contains about 50 to 75 slender cells, all arranged in a bananalike cluster pointed toward the gustatory pore. These are the taste receptor cells, which differentiate from the surrounding epithelium, grow to mature form, and then die out, to be replaced by new cells in a turnover period as short as seven to ten days. The various types of cells in the taste bud appear to be at different stages in this turnover process. Slender nerve fibers entwine or entangle among and make contact

usually with many cells. The process can be simply explained as follows: Tongue Pores Taste buds (taste cells) Brain Experience of taste At the base of each taste bud there is a nerve that sends the sensations to the brain. The sense of taste functions in coordination with the sense of smell. The number of taste buds varies substantially from individual to individual, but greater numbers increase sensitivity. Women, in general, have a greater number of taste buds than men. As in the case of colour blindness, some people are insensitive to some tastes. The taste buds are further bunched together in bumps on the tongue called papillae that can be easily seen on the tongue. There are many papillae on the tongue. Mostly, there are taste pores in these papillae. In human beings and other mammals, taste buds are located primarily in fungiform (mushroomshaped), foliate, and circumvallate (walled-around) papillae of the tongue or in adjacent structures of the palate and throat. Many gustatory receptors in small papillae on the soft palate and back roof of the mouth in human adults are particularly sensitive to sour and bitter, whereas the tongue receptors are relatively more sensitive to sweet and salt. Some loss of taste sensitivity suffered among wearers of false teeth may be traceable to mechanical interference of the denture with taste receptors on the roof of the tongue. There are numerous filiform papillae, which seem to have about the same function as the nonskid thread on tyres. The three remaining types serve the sense of taste. The mushroom-shaped fungiform papillae are scattered over the tongue, the leaf-like foliate papillae are at the sides, and the large circumvallate papillae are arranged in a chevron (a V-shaped symbol) near the base. Each gustatory papilla contains one or more taste buds, which also are found elsewhere in the mouth, especially during childhood. In a typical taste bud there are several spinal-shaped receptor cells, each with a hair like end projecting through the pore of the bud into the mouth cavity. These hair cells (taste cells) are the receptors for taste; they connect with nerve fibers which run to the brain stem by the VIIth and IXth cranial nerves but are united in their further course to the somesthetic cortex.

Nerve supply In human beings, the anterior (front) two-thirds of the tongue is supplied by one nerve (the lingual nerve), the back of the tongue by another (the

glossopharyngeal nerve), and the throat and larynx by certain branches of a third (the vagus nerve), all of which subserve touch, temperature, and pain sensitivity in the tongue as well as taste. The gustatory fibers of the anterior tongue leave the lingual nerve to form a slender nerve (the chorda tympani) that traverses the eardrum on the way to the brain stem. When the chorda tympani at one ear is cut or damaged (by injury to the eardrum), taste buds begin to disappear and gustatory sensitivity is lost on the anterior two-thirds of the tongue on the same side. Impulses have been recorded from the human chords tympani, and good correlations have been found between the reports people give of their sensations of taste and of the occurrences of the different nerve discharge. The taste fibers from all the sensory nerves from the mouth come together in the brainstem (medulla oblongata). Here and at all levels of the brain, gustatory fibers run in distinct and separate pathways, lying close to the pathways for other modalities from the tongue and mouth cavity. From the brain’s medulla, the gustatory fibers second by a pathway to a small cluster of cells in the thalamus and hence to a taste-receiving area in the anterior cerebral cortex.

Taste qualities For a long time, there has been general agreement on just four primary taste qualities: salt, sour, sweet, and bitter. Alkaline is probably a combination of several tastes (Hahn, Kuckulies, and Taeger, 1938). The taste buds are responsive to thousands of chemicals but interestingly all of our sensations of taste appear to result from four basic sensations of taste; sweetness (mostly to sugars), sourness (mostly to acids), saltiness (mostly to salts), and bitterness (to a variety of other chemicals most of which either have no food value or are toxic) (Bertoshuk, 1988). Every flavour that we experience is made up of combinations of these four basic qualities. However, our perception of food also includes sensations from the surfaces of the tongue and mouth: touch (food texture), temperature (cold tea tastes very different from hot tea) and pain. The sight and aroma of food also greatly affect our perception of food. Theorists of taste sensitivity classically posited only four basic or primary types of human taste receptors, one for each gustatory quality: salty, sour, bitter, and sweet. Mixed sensitivity may be only partly attributed to multiple branches of taste nerve endings.

Tastes (i) Sweet Sugar (ii) Salt Common table salt—NaCl (Sodium chloride) (iii) Sour Vinegar, imli—HCl (Hydrogen chloride) (iv) Bitter Quinine A few drops of the fungiform papillae (scattered all over the tongue) respond only to sweet, others only to acid, and still others to salt, but none of them seem specialized for bitter. Different parts of the tongue are differentially sensitive (see Figure 3.17). Bitter is most effective at the back, near the circumvallate papillae, and along the back portions of the edges. Sweet is just the opposite, stimulating the tip and front edges. Sour reaches its maximum effectiveness about the middle of the edges and salt is best sensed in the forward part of the tongue. The central part of the top surface of the tongue is quite insensitive. The central portion of the tongue cannot receive sensations of different tastes. Our gustatory (and olfactory) chemistry is a baffling or inexplicable subject and not far advanced at most points. Although each taste bud seems to be primarily responsive to one of the four primary qualities, each responds to some extent to some or all of the other qualities as well (Arvidson and Friberg, 1980). Interestingly, the taste buds that are most sensitive to the four primary tastes are not evenly distributed over the tongue. They are bunched in different areas. This means that different parts of the tongue are sensitive to different tastes. We usually do not notice this because of the differences in sensitivity are not great and because our food usually reaches all parts of the tongue during the chewing process anyway. But if you ever have to swallow a truly bitter pill, try it in the exact middle of the tongue, where there are no taste receptors at all.

Figure 3.17 Areas where different types of tastes are detected.

(i) Sweet: Generally, the taste buds close to the tip of the tongue are sensitive to sweet tastes. The tip of the tongue acquires the sweet taste. Unfortunately, we cannot tie down the chemical property of a substance that makes it sweet. Sucrose (cane or beet sugar) is a carbohydrate, and so are glucose, which is less sweet, and starch which is not sweet at all. The alcohols are sweet but so are saccharine, decidedly, though very different in chemical composition; and so again are the poisonous salt, “sugar of lead”, which is anything but a sugar except in taste. Except for some salts of lead or beryllium, the sweet taste is associated with organic compounds (such as alcohols, glycols, sugars, and sugar derivates). Human sensitivity to synthetic sweetness (for example, saccharine) is especially remarkable; the taste of saccharine can be detected in a dilution 700 times weaker than that required for cane sugar. The stereochemical (spatial) arrangement of atoms within a molecule may affect its taste; thus, slight changes within a sweet molecule will make it bitter or tasteless. Several theorists have proposed that the common feature of all of sweet stimuli is the presence in the molecules of a so-called proton acceptor such as the OH (hydroxyl) components of carbohydrates (for example, sugars) and many other sweet tasting compounds. It has also been theorized that such molecules will not taste sweet unless they are of appropriate size. It was formerly thought that the sweet taste is one of the four taste receptors in the tongue and was thought to be located on the tip of the tongue. This myth has since been debunked, as we now know all tastes can be experienced in all parts of the tongue.

(ii) Salty: The taste buds on top and on the side of the tongue are sensitive to salty taste. Sodium chloride or NaCl or common salt is apparently the only substance which gives a purely salt taste. The typical salty substances are compounds of one of these cations—Sodium, Calcium, Lithium, Potassium—with one of the following anions—chloride, bromine, iodine, SO4, NO3, CO3. Both anion and cation seem to be important in generating the salty taste. Perhaps, the only one of these salty substances that has been widely used to substitute for NaCl (Sodium chloride) as table salt is lithium chloride; in large quantities it seems to cause illness (Hanlon et al., 1949). Although, the salty taste is often associated with water-soluble salts, most such compounds (except Sodium chloride) have complex tastes such as bitter-salt or sour-salts. Salts of low molecular weight are predominantly salty, while those of higher molecular weight tend to be bitter. The salts of heavy metals such as mercury have a metallic taste, although some of the salts of lead (especially lead acetate) and beryllium are sweet. Both parts of molecule (for example, lead and acetate) contribute to taste quality and to stimulating efficiency. In human beings, the following series for degree of saltiness, in decreasing order, is found: ammonium (most salty), potassium, calcium, sodium, lithium, and magnesium salts (least salty). It was formerly thought that the salty taste is one of four taste receptors in the tongue, most common in the tip and upper front portion of the tongue. We now know this to be false as all kinds of taste can be experienced in all parts of the tongue. (iii) Sour: The taste buds on top and on the side of the tongue are sensitive to sour taste. The edges or sides of the tongue acquire the sour taste. All the dilute acids that yield or give a fairly pure sour taste have one characteristic in common: When they are in solution, their molecules dissociate into two parts the hydrogen cation; positively charged ion (H ion) and an anion; negatively charged ion. Thus, hydrochloric acid (HCl) breaks into H+ and Cl–. The H ion seems to be the stimulus for sour. The hydrogen ions of acids (for example, hydrochloric acid, Hcl or HCl) are largely responsible for the sour taste; but, although a stimulus

grows more sour as its hydrogen ion (H+) concentration increases, this factor alone does not determine sourness. Weak organic acids (for example, the acetic acid in vinegar) taste more sour than would be predicted from their hydrogen ion concentration alone; apparently the rest of the acid molecule affects the efficiency with which hydrogen ions stimulate. It was formerly thought that the sour taste is one of the four taste receptors in the tongue and that they occur primarily along the sides of the tongue and is stimulated mainly by acids. We now know this is not the case as all tastes can be experienced by all parts of the tongue. (iv) Bitter: Taste buds in the back of the tongue are sensitive to bitter tastes. The most typical bitter substances are the vegetable alkaloids— such as quinine, but some metallic salts also are bitter. There are even some substances, as phenyl-thio-carbamide, which are extremely bitter to some people and almost tasteless to others (Blakeslee & Salmon, 1935; Cohen and Ogdon, 1949; Rikimaru, 1937). Bitter and sweet substances are in some cases very similar in chemical composition. The experience of a bitter taste is elicited by many classes of chemical compounds and often is found in association with sweet and other gustatory qualities. Among the best known bitter substances are such alkaloids (often toxic) as quinine, caffeine, and strychnine. Most of these substances have extremely low taste thresholds and are detectable in very weak concentrations. The size of such molecules in theoretically held to account for whether or not they will taste bitter. An increase in molecular weight of inorganic salts or an increase in length of chains of carbon atoms in organic molecules tends to be associated with increased bitterness. It used to be thought that the bitter taste is one of four taste receptors in the tongue, and that they are located toward the back of the tongue. We now know this is false as all parts of the tongue experience all kinds of taste. Bitter tastes are stimulated by a variety of chemical substances, most of which are organic compounds, although some inorganic salts of magnesium and calcium produce bitter sensations too.

Methods of stimulation

There are three methods of applying stimuli to the tongue. (i) Slip method: The simplest method may be called the slip method. An experimenter hands over the organism a small glass of a specified solution, lets her or him taste it, and then report. This method yields the lowest thresholds, since large areas of the tongue are involved. Care must be taken to clear the mouth between trials by spitting out the solution and rinsing. Further, it is necessary to train organism to sip and spit in a standardised manner to insure uniform trials. Atleast a half minute is advisable between trials to avoid adaptation effects (Mac Leod, 1952). (ii) Drop method: In studying single areas, the drop method may be used. A brush, dropper, pipette (a slender tube for transferring or measuring small amounts of liquid), or syringe places a fixed amount of solution where it is desired. (iii) Gusto meter: Still better is the gusto meter used by Hahn & Gunther (1932). This is essentially a U-tube, laid on the tongue. A hole opening downward at the bend of the U is placed over the desired portion of the tongue so that the stimulating solution washes over the area as it comes in one arm and goes out the other. Alternative supply tubes make it possible to shift rapidly from one solution to another.

Adaptability One of the most striking facts about taste is the rapid rate at which it adapts. A drink which tastes sweet or sour at the first sip often seems almost neutral by the end of the glass. Contrast is equally prominent; a pickle say mango pickle would taste very sour after an ice-cream. Elaborate series of experiments was carried out by Hahn (1932), using the gustometer. There was complete adaptation to even the 15 per cent solution within thirty seconds. Adaptation to a sugar solution was almost equally rapid. It would be a mistake, however, to generalise from this experiment to everyday experience. Substances are rarely applied regularly or uniformly to the same small area of the tongue; usually we move them around, varying the area and intensity of stimulation from second to second, and so preventing rapid adaptation.

3.5 BEYOND OUR FIVE SENSES

In addition to sight, smell, taste, touch, and hearing, humans also have awareness of balance, pressure, temperature, pain, and motion all of which may involve the coordinated use of multiple sensory organs. The sense of balance is maintained by a complex interaction of visual inputs, the proprioceptive sensors (which are affected by gravity and stretch sensors found in muscles, skin, and joints), the inner ear vestibular system, and the central nervous system. Disturbances occurring in any part of the balance system, or even within the brain’s integration of inputs, can cause the feeling of dizziness or unsteadiness.

QUESTIONS Section A Answer the following in five lines or 50 words: 1. 2. 3. 4. 5. 6. 7. 8. 9. 10. 11. 12. 13. 14. 15. 16. 17. 18. 19. 20.

Sensation Functions of the blind spot Importance of Young-Helmholtz Theory of colour vision Colour blindness Olfactory sensation Retina Transduction process Potential energy Five traditional senses Skin senses Cone system Receptors Visible spectrum Iris Blue paint + Yellow paint = Green paint. Explain. Rhodopsin Adaptation Synapse or Synaptic cleft Basilar membrane Sense organs and specific receptors for five kinds of sensation

21. 22. 23. 24. 25. 26. 27. 28. 29.

Rods and cones Process of visual sensation Fovea Write about the receptors of gustatory sensation After sensation Surface colours Visual adaptation Gustatory sensation Primary colours

Section B Answer the following in up to two pages or 500 words: 1. Define sensation. Give its characteristics. 2. What are the attributes of sensation? 3. What is sensation? Illustrate its types, corresponding receptor organs and stimuli objects. 4. Write a short note on the process of Seeing. 5. Explain Place Theory of Ear (with diagram). 6. Discuss the theories of colour vision. 7. Write a note on the structure and functions of human eye. 8. Give the structure of ear (with diagram). 9. Describe the structure and functions of eye with the help of a diagram. 10. Draw and explain the structure of an ear. 11. “In order for us to hear, the nervous system must be set into action”. Explain. 12. Define “Rods” and “Cones” and give the differences. 13. Write a short note on ‘Transduction Process’. 14. Give the three principal parts of the ear and explain their functions. 15. Elaborate on the “Rod and Cone Vision” bringing out clearly the differences in their functional characteristics. 16. What is sensation? Discuss olfactory sensation.

17. 18. 19. 20. 21. 22. 23. 24. 25. 26. 27. 28. 29. 30. 31. 32. 33. 34. 35. 36. 37. 38.

Discuss briefly the various kinds of sensation. Draw and label the structure of an eye. Draw and label the structure of an ear. Explain auditory sensation explaining the functioning of the ear. Detail the structure and functioning of ‘Eye’ with the help of diagram. What is Auditory Stimulus? Explain the various theories of hearing. Explain critically the various theories of colour vision. What is the primary function of our sensory receptors? What is the role of sensory adaptation in sensation? What are the basic structures of the eye, and what is the physical stimulus for vision? What are the basic functions of the visual system? How do psychologists explain colour perception? Why is visual perception in hierarchical process? What are the basic building blocks of visual perception? What is the physical stimulus for hearing? How do psychologists explain pitch perception? How do we localise sound? What is the physical stimulus for touch? Where does the sensation of pain originate? What roles do cognitive processes play in the perception of pain? What is the physical stimulus for smell, and where are the sensory receptors located? Where are the sensory receptors for taste located?

Section C Answer the following questions in up to five pages or 1000 words: 1. What is sensation? Draw the structure of an ear and explain its functioning. 2. Discuss structure and functions of eye with diagram. 3. Explain different theories of hearing.

4. Explain the experience of “Vision” with the help of the structure of the eye. 5. “Each Sensory System is a kind of channel which, if stimulated, will result in a particular experience”. Explain with reference to “Seeing experience”. 6. Elaborate on the major dimensions of perceived visual dimensions— Form, Hue, Saturation, and Brightness. 7. Explain different theories of colour vision. 8. What is sensation? Draw the structure of an eye and explain its functioning. 9. Discuss all kinds of sensations briefly. 10. What is sensation? Discuss visual sensation in detail, giving its theories. 11. Describe the structure and function of ear. 12. What is gustatory sensation? Describe the mechanism of taste sensation. 13. Describe the mechanism of olfactory and tactual sensation. 14. Write brief notes on the following: (i) Cornea (ii) Iris (iii) Aqueous humour and vitreous humour (iv) Lens (v) Rods and Cones (vi) Blind spot (vii) Colour vision (viii) Ladd Franklin theory (ix) Cochlea (x) Taste buds (xi) Pain sensation

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4 Perceptual Processes INTRODUCTION Perception is one of the oldest fields in psychology. Human beings have been interested in the perception of objects in space at least since antiquity. The oldest quantitative law in psychology is the Weber-Fechner law, which quantifies the relationship between the intensity of physical stimuli and their perceptual effects. The study of perception gave rise to the Gestalt school of psychology, with its emphasis on holistic approach. English philosopher John Locke (1632–1704) claimed that the mind at birth is a tabula rasa (literally, a blank tablet). According to this view, perception is possible only after prolonged experience and learning. An opposite view to this was favoured by many German psychologists who claimed that the crucial perceptual processes are innate and do not depend directly on experience. There is, nevertheless, interesting evidence indicating that at least some perceptual skills do not require learning. Michael Wertheimer (1962) presented a new-born baby less than ten minutes old with a series of sounds. Some of the sounds were to the baby’s left and some were to his right. The baby looked in the appropriate direction every time, suggesting that primitive auditory processes are available at birth. Some degree of colour vision and discrimination is also present at birth. Adams, Maurer, and Davis (1986) discovered that neonates could distinguish grey from colours such as green, yellow, and red. For each of these colours, the neonates preferred colour and grey draught-boards to grey squares of the

same brightness. Innate factors provide some of the building blocks of perception. In between is a compromise position, supported by most psychologists, according to which innate factors and learned or environmental factors are both of vital significance in the development of perception. It does appear probable however, that innate factors and learning are both essential to normal perceptual development.

4.1 SENSATION AND PERCEPTION Sensations can be defined as the passive process of bringing information from the outside world into the body and to the brain. The process is passive in the sense that we do not have to be consciously engaging in a “sensing” process. Perception can thus be defined as the active process of selecting, organising, and interpreting the information brought to the brain by the senses. Sensation refers to the collection of data from the environment by means of the senses, while perception relates to our interpretation of this data. It takes into account experiences stored in our memory, the context in which the sensation occurs and our internal state (our emotions and motivation). Perception is a dynamic process of searching for the best available interpretation of the data received through the senses. Perception means those processes that give coherence and unity to sensory input. It covers the entire sequence of events from the presentation of a physical stimulus to the phenomenological experiencing of it. It refers to the synthesis or fusion of the elements of sensation. Perception is more than the sum of all the sensory input supplied by our eyes, ears, and other receptors. In everyday language, the terms “sensation” and “perception” are often used interchangeably. However, as you will soon know, they are very distinct, yet complementary processes. In philosophy, psychology, and cognitive science, perception is the process of attaining awareness or understanding of sensory information. The word “perception” comes from the Latin words perceptio, percipio, which means “receiving, collecting, action of taking possession, apprehension with the mind or senses.” What one perceives is a result of interplays between past experiences, including one’s culture, and the interpretation of the perceived. Perception is a single unified awareness derived from sensory processes while a stimulus is present.

Perception however is not a total response to everything outside with all our senses simultaneously. It is just an interpretation. The way we perceive our environment is what makes us different from other animals and different from each other. The response is something specific and serves some purpose on the particular occasion. Therefore, our response is selective, purposive, and relevant to our needs. We select and organise those things which are needed for our purpose and leave the rest at the background of our perceptual field. Perception belongs primarily to the knowing aspect of human behaviour. Sensation occurs in the following manner: (i) sensory organs absorb energy from a physical stimulus in the environment. (ii) sensory receptors convert this energy into neural impulses and send them to the brain. Perception follows in the sense that the brain organises the information and translates it into something meaningful. But what does “meaningful” mean? How do we know what information is important and should be focused on? It is by means of Selective attention which is the process of discriminating between what is important and what is irrelevant, and is influenced by motivation. For example, the students in class should focus on what the teacher is saying and the overheads being presented. But, students walking by the classroom may focus on people in the room, who is the teacher and so on, and not the same thing the students in the class. Perceptual expectancy which is the way we perceive the world as a function of our past experiences, culture, and biological makeup. For example, when we look at a highway, we expect to see cars, trucks, and so on, and certainly NOT airplanes. But someone from a different place with different experiences and history may not have any idea what to expect and thus be surprised when they see cars go driving by. Another example is that you may look at a painting and not really understand the message the artist is trying to convey. But, if someone tells you about it, you might begin to see things in the painting that you were unable to see before. Richard Gregory (1966), the English psychologist and perception theorist, has described perception as one of forming hypotheses about what the senses

tell us. Let us start with some definitions of perception.

4.2 SOME DEFINITIONS OF PERCEPTION According to Boring, E.G. (1942), “Sensation refers to the action by a receptor when it is stimulated and perception refers to the meaning given to the sensation.” Hebb (1966) uses the term “Sensation” when referring to the activity in neural paths up to and including the corresponding sensory areas in the brain. “Perception”, however, is defined as mediating process to which sensation gives rise directly. It is a process that mediates between sensation and behaviour. It is initiated by sensation but not completely determined by it. According to Eysenck (1972), “Perception is a psychological function which enables the organism to receive and process information.” According to Edmund Fantino and G.S. Renolds (1975), “Perception is the organizing process by which we interpret our sensory input.” According to O. Desiderato, D.B. Howieson and J.H. Jackson (1976), “Perception is the experience of objects, events or relationships obtained by extracting information from and interpreting sensations.” According to Harvey Irwin (1979), “Perception is the process by which brain constructs an internal representation of the outside world. This internal representation is what we experience as “reality” and it follows us to behave in such a way that we survive in the world.” According to Charles G. Morris (1979), “All the processes involved in creating meaningful patterns out of a jumble of sensory impressions fall under the general category of perception.” According to Silverman (1979), “Perception is an individual’s awareness aspect of behaviour, for it is the way each person processes the raw data he or she receives from the environment, into meaningful patterns.” According to Levine and Schefner (1981), “Perception refers to the way in which we interpret the information gathered (and processed) by the senses. In a word, we sense the presence of a stimulus, but we perceive what it is.” This definition embraces both aspects of perception—that it depends upon sensations (based on basic sensory information), but that these sensations require interpretation in order for perception to occur. According to Bootzin (1991), “The effortless, multimodal process of perception can be defined as the brain’s attempt to describe objects and

events in the world, based on sensory input and knowledge.” According to Woodworth, “In perception the chain of events is stimulus, response of the sense organ, sensory nerves, first cortical response which is perception.” According to Mohsin, “The simplest act of perception involves the setting of the stimulus field into figure and background relationship.”

4.3 CHARACTERISTICS OF PERCEPTION (i) Perception is cognitive: “Cognition” means “knowledge”. Perception belongs primarily to the knowing aspect of human behaviour. It gives us knowledge of objects or events or people. It is the process of obtaining knowledge of external objects, events, and objective facts by use of the senses. (ii) Perception involves sensations: Perception = Sensation + its meaning Perception means knowledge which comes through sensations. It means that sensations are essential to perception. Perception involves sensations. It is a process of interpreting or giving meaning to sensations. (iii) Perception involves memory and thought: Perception is concerned with cognition and recognition of things. It involves memory and a spontaneous and perhaps unconscious inference or thought activity over and above the sensations. (iv) Perception is innate: Gestaltists claimed that the crucial perceptual processes are innate and do not depend directly on experience. Infact, most psychologists hold that innate factors and learned or environmental factors are both of vital significance in the development of perception. (v) Perception is to analyse the world: The function of perception is to analyse the world around us into distinct objects. Perception, thus, is concerned with the differentiating or “breaking up” of the outside world or perceptual field. As Titchener remarked, “The farther perception goes…….the better do we understand the world. With perception comes knowledge, without perception we should be without science.” (vi) Perception is selective: Perception is highly selective. Many stimuli act on our sense organs but we do not respond to all of them. All of

them do not excite our sense organs. We have to select some of them. Selection, in perception, depends upon personal likes and dislikes, interests, needs, motives, readiness or set, and other subjective, objective, social, and cultural factors. (vii) Perception is a direct experience: Perception is a direct experience with persons, objects or events through a group of sensations. (viii) Perception is presentative and representative: Perception is presentative in the sense that it is influenced by external stimulus. It is representative also because it involves memory and imagination. (ix) Perception is organising: One of the most striking characteristics of perception is the fact that it is nearly always organised. Perception involves organisation, and organisation facilitates perception. According to Murphy, “Proper organisation is necessary for the understanding of a thing.” Perception is not a simple juxtaposition of sensory elements; it is fundamentally organised into coherent wholes. (x) Change in perception: Perception is also characterised by change. Change is the basis of perception. Change in events and things facilitate perception. (xi) Perception is attentive: Perception is attentive in nature. Without attention, perception is not possible. Attention is the prior condition of distinct and vivid perception. (xii) Perception is accompanied by feeling: Perception is sometimes accompanied by feeling. For example, we perceive a rose and feel pleasure; but we feel unpleasant when we are exposed to noise. (xiii) Perception is accompanied by action: Perception is sometimes accompanied by action. It is sometimes followed by an action. We climb a hill and perceive its steepness through our muscular actions. A bell is rung in the college and students have their classes. Here, perception is followed by an action. We react to certain objects in the environment in perception. (xiv) Signs and meanings: Sometime we perceive merely a sign of some fact, but we perceive the fact. We interpret the meaning of the sign and perceive an object. For example, we perceive friend on hearing her voice. This is because the sound or her voice is a sign of her being present.

(xv) Figure and ground in perception: One of the most fundamental characteristics of perceptual organisation is the way in which the visual field is segregated into one or more objects that are the central focus— the so called “figure”—and everything else, which forms the “ground”. “Figure and ground” refers to the most basic and elementary of all forms of perceptual structure. We perceive an object as a figure in a ground. We perceive a picture on a page. The picture is a figure and this page is ground. Edgar Rubin (6 Sept, 1886–3 May, 1951), a gestalt and Danish psychologist and phenomenologist from Denmark, reached several conclusions (1915, 1958) about the figure-ground relationship. According to Edgar Rubin, figure and ground possess the following properties: (a) Figure seems typically closer to the viewer or perceiver with a clear location in space, and is processed more thoroughly. In contrast, the ground seems father away. It takes a clear location. (b) Figure has form, whereas ground is relatively formless. It has a definite, clear, distinct shape, whereas the ground seems vague, formless, and shapeless. (c) Figure has “thing like” qualities, whereas ground appears as more homogeneous and unformed material. (d) Figure appears to be nearer to the observer than does the ground. The figure appears on the front, whereas the ground seems to continue behind the figure. (e) Figure is more easily identified or named than the ground. (f) The colour of the figure is more impressive. (g) Figure is more likely to be connected with meanings, feelings, and aesthetic values than is the ground. (h) Figure is bright, where as the ground is dull. (xvi) Perception is a complex process: Perception is very deep and complex process. It is a complex process involving many processes: (a) Receptor process: The first process in perception is the receptor process. The rose flower by virtue of its presence stimulates different receptor cells and thus activates different receptor processes. (b) Unification process: This is the second process in perception. For a

perception of the rose, a unification of the different sensations is necessary. (c) Symbolic process: This is the third in the main process. Most things have a sentiment or experience attached to them. A rose reminds us of the friend who created and developed in us the interest for rose flower or gardening, in general. (d) Affective process: A flower may arouse a happy memory of a friend or a feeling of sorrow at their separation. Though perception is a complex process, its basic constituents are still sensations and past experiences. While talking about the complexity of perception, Prof. Boring states, “Perception is a joint venture of the sense organs and the nervous system.”

4.4 SELECTIVE PERCEPTION/ATTENTION Perceptions come to us moment to moment. One perception vanishes as the next appears. Our attention or mental focus captures only a small portion of the visual and auditory stimuli available at a given moment, while ignoring other aspects. We cannot absorb all the available sensory information in our environment. Thus, we selectively attend to certain aspects of our environment while relegating other to the background (Johnston and Dark, 1986). “Selective perception or attention” means that at any moment, we focus our awareness on only a limited aspect of all that we experience. Selective attention is our ability to pay attention to only some aspects of the world around us while largely ignoring others—which often play a crucial role (Johnston, Mc Cann, and Remington, 1995; Posner and Peterson, 1990). Indeed, a very limited aspect. Our five senses (eyes, ears, nose, tongue, and skin) take in 11,000,000 bits of information per second, of which we consciously process about 40 (Wilson, 2002). Yet, we intuitively make great use of the other 10,999,960 bits. Another example of selective attention, the cocktail party effect, is the ability to attend selectively to only one voice among many. Imagine hearing two conversations over a headset, one in each ear, and being asked to repeat the message in our left ear while it is spoken. When paying attention to what is being said in your left ear, you won’t perceive what is said in your right

ear. If you are asked later what language your right ear heard, you may draw a blank (though you could report the speaker’s gender—male or female and loudness. At the level of conscious awareness, whatever has your attention pretty much has your undivided attention. That explains why, in a University of Utah experiment, students conversing on a cell phone were slower to detect and respond to traffic signals during a driving simulation (Strayer and Johnston, 2001). It is true of other senses, too. From the immense or huge array (range) of visual stimuli constantly before us, we select just a few to process. Ulric Neisser (1979) and Robert Becklen and Daniel Vervone (1983) demonstrated this dramatically. In other experiments, people also exhibit a remarkable lack of awareness of happenings in their visual environment. After a brief visual interruption, a big coke bottle may disappear from the scene, a railing may rise, clothing may change, and more often than not, viewers don’t notice (Resnick and others, 1996; Simons and Levin, 1998). This ‘blindness’ even occurs among people giving directions to a construction worker who, unnoticed by 2/3 of them, gets placed by another construction worker. Out of sight, out of mind! Selective attention has obvious advantages, in that it allows us to maximise information gained from the object of our focus while reducing sensory interference from other irrelevant sources (Matlin and Foley, 1997). Although perception requires attention, even unattended stimuli sometimes have subtle effects (Baars and Mc Govern, 1994; Wilson, 1979). Moreover, if someone at a loud party audibly calls your name, your attuned perceptual system may bring the voice to consciousness. Our attention often shifts to other aspects of our environment, such as a juicy bit of conversation or a mention of our own name (Moray, 1959). This is often referred to as the cocktail party phenomenon. Studies have shown that people can focus so intently on one task that they fail to notice other events occurring simultaneously—even very salient ones (Cherry, 1953; Rensink, O’Regan, and Clark, 1997).

4.5 THE ROLE OF ATTENTION IN PERCEPTUAL PROCESSING OR SELECTIVE ATTENTION Selective attention is the process of focusing on one or a few stimuli of

particular significance while ignoring others. So, we never attend equally to all the stimuli we receive at any given point in time. If we did, our nervous systems would become hopelessly overloaded. Instead, we select certain stimulus inputs to focus on, and on the other events fade into the background (Johnston and Dark, 1986). Through this process of selective attention our perceptual ability is enhanced (Moran and Desimone, 1985). To some extent, we control our perception or attention. However, a number of possible changes in these background stimuli might cause our attention to shift suddenly. Features of the stimulus such as contrast, novelty, stimulus intensity, colour, and sudden change tend to attract our attention. Psychologists have discovered that certain characteristics of stimuli tend to capture our attention almost automatically: (i) Sudden change: A sudden change generally causes a shift in attention. (ii) Contrast and novelty: Contrast and novelty or newness also tends to capture our attention. Things that are new or unusual also tend to attract our attention. (iii) Stimulus intensity: Another way of getting our attention is to vary the intensity of the stimulus. Sudden reduction of stimulus intensity can also command attention. (iv) Repetition: Repetition is another way to attract attention. This is one reason why television and radio advertisements often repeat jingles. (v) Difficult stimulus: There is also evidence that stimuli which are difficult to process may command attention. Psychologists believe that the more energy we focus on one category of stimuli, the less is left over for responding to other stimuli (Norman and Bobrow, 1975). Not all the stimuli in our environment gain access to our awareness (perception). For example, we may spend minutes talking to an acquaintance and later be unable to recall the colour of her top because we failed to take account of it. Another example is when we drive a familiar route and are astonished to observe suddenly a feature which we must have “seen” before but never noticed. Clearly a stimulus strikes or activates or stimulates one’s receptor surface is no guarantee that it will be perceived. Perception is thus selective. This is the sense in which the term “attention” is used most often, and it points to the direction that much of the relevant research has taken. A subtle distinction must be made between perception and memory. In the

first example given, our inability to report the colour of our acquaintance’s top might reflect a failure of memory rather than of perception; particularly if we were called upon to give this information some time later. It may have gained access to our perception but not to our (long-term) memory. There is, nevertheless, abundant evidence that under certain conditions, the stimulus fails to be perceived in the first place, or is perceived only dimly. Data shows that out of the stimulus complex perceived by an individual, some aspects will be selected out upon which to base her or his behaviour, whereas other aspects—although perceived—are ignored. The conclusion, then, is that in the process of employing perceived stimuli in our behavioural adjustments stimulus selection often takes place. In a sense, this is “associational” rather than perceptual selectivity. Learning must be intimately involved in the process of stimulus selection; a similar role will have to be conceded to selective perception. Which stimuli “get in” (are perceived) depends greatly on past experience. There are some who feel that learning enters selective perception in a way different from the role it assumes in instrumental behaviour. For example, that reinforcement is unimportant in the first case (Gibson and Gibson, 1955). But whatever one’s views with respect to this matter, it seems clear that a thorough understanding of discrimination learning—depends in turn upon a thorough understanding of selective perception and stimulus selection, which is to say, of perception as well as of how the products of perception are utilised. Out of the enormous flux of stimuli impinging on an organism, only certain aspects are perceived (selective perception). Selective attention or perception is not an all—or—none affair; frequently input stimuli are attenuated rather than completely blocked (see Figure 4.1). The dotted lines are meant to convey this fact (attenuation). Of the stimuli that are successful in gaining access to perception, not all are utilised as the basis for discriminative behaviour (stimulus selection—B). Again, attenuation rather than complete blocking, frequently occurs, which in this case means that perceived stimuli differ in the degree to which they become associated with responses, or in different terminology, in the degree to which they develop stimulus control. Strictly speaking, once we go beyond selective perception (A), we are dealing with the stimuli as perceived, that is perceptions.

Figure 4.1 Discrimination of learning from input A to output B: A schematisation. Note: The dashed lines indicate that attenuation rather than complete blockage has taken place.

Learning, in one capacity, or another, is involved as both A and B. Much of the learning that takes place at A (selective perception) which falls within the realm of perceptual learning and concerns how an individual comes to differentiate stimulus properties which initially appear equivalent. The variables, learning and otherwise, that control stimulus selection (B) have only recently come under serious investigation.

4.6 FACTORS AFFECTING PERCEPTION OR PSYCHOLOGICAL AND CULTURAL DETERMINANTS OF PERCEPTION One of the central assumptions of the constructivist approach to perception is that perception is not determined entirely by external stimuli. As a consequence, it is assumed that emotional and motivational states, together with expectation and culture, may influence people’s perceptual hypotheses and thus their visual perception. This notion that perception is influenced by various factors is often referred to as perceptual set. This is “a perceptual bias or predisposition or readiness to perceive particular features of a stimulus” (Allport, 1955). Basically, it is the tendency to perceive or notice some aspects of the available sense data and ignore others. The factors that influence perception and create perceptual set are discussed below.

4.6.1 Psychological or Internal Factors Perceptions are influenced by a whole range of factors relating to the individual. These include cultural background and experience, individual differences in personality or intelligence, values, past experience, motivations (both intrinsic and extrinsic), cognitive styles, emotional states, attention, perceptual set or readiness, prejudices, the context in which something is perceived and the individual’s expectations. (i) Attention: There are powerful effects of attention on perception. Perception depends on attention, in the sense that we see and hear clearly only those stimuli to which we pay attention. For an event to be perceived, it must be focused upon or noticed. Attention is a general term referring to the selective aspects of perception which function so that at any instant, an organism focuses on certain features of the environment to the (relative) exclusion of other features. Moreover, attention itself is selective, so that attending to one stimulus tends to inhibit or suppress the processing of others. Attention may be conscious in that some stimulus elements are actively selected out of the total input, although, by and large, we are not explicitly aware of the factors which cause us to perceive only some small part of the total stimulus array. (ii) Perceptual set or readiness: The cognitive and/or emotional stance that is taken towards a stimulus array strongly affects what is perceived. The tendency to perceive what we expect is called perceptual set. Readiness to perceive the environment in a particular way is termed as perceptual set. The perceptual set means the mental set when the person is mentally prepared to perceive the certain features of the object in the environment. Perceptual set or readiness facilitates perception. (iii) Motivation: What is perceived is affected by one’s motivational state. For example, hungry person sees food objects or items in ambiguous stimulus or stimuli. Two examples of motivational factors are hunger and thirst. Motivational factors increase the individual’s sensitivity to those stimuli which he considers as relevant to the satisfaction of his needs in view of his past experience with them. A thirsty individual has a perceptual set to seek a water fountain or a hotel to quench his thirst, which increases for him likelihood of perceiving restaurant signs and

decreases the likelihood of visualising other objects at that moment in time. A worker who has a strong need for affiliation, when walks into the lunchroom, the table where several coworkers are sitting tends to be perceived and the empty table or the table where only one person is sitting will attract no attention. Schafer and Murphy (1943) considered the effects of reward on perception. There are suggestions that the extent of our motivation will affect the speed and way in which we perceive the world. For example, there are suggestions that bodily needs can influence perception (so that food products will seem to be brighter in colour when you are hungry). The effects of reward on perception were also looked at by Bruner and Goodman (1947). Bruner and Goodman (1947) aimed to show how motivation may influence perception. They asked rich and poor children to estimate the sizes of coins and the poor children over-estimated the size of every coin more than the rich children. Solley and Haigh (1948) asked 4–8 years olds to draw pictures of Father Christmas at intervals during the month before Christmas and the two weeks after Christmas. They found that as Christmas approached the pictures became larger and so did Santa’s sack of toys! After Christmas, however, the toys shrank and so did Santa! This suggests that motivation (higher before Christmas than after) influenced the child’s perception of Santa and his toys making them more salient before Christmas and less salient after. Allport (1955) has distinguished 6 types of motivational-emotional influences on perception: (i) bodily needs (for example, physiological needs) (ii) reward and punishment (iii) emotional connotation (iv) individual values (v) personality (vi) the value of objects. (iv) Cognitive style: Another area where individuals show differences in their abilities to discriminate events or visual, auditory, or tactile cues from their surrounding environments is known as fielddependence/field-independence. Cognitive styles also induce set. Herman Witkin conducted much of the original research in this area in

the 1950s. Witkin (1949) identified two different cognitive styles. These relate to different ways of perceiving which are linked to personality characteristics. (a) Field-dependence: A field-dependent individual finds it difficult to concentrate on an object, problem or situation while ignoring distracting features of the surrounding context. A field-dependent person has difficulty finding a geometric shape that is embedded or “hidden” in a background with similar (but not identical) lines and shapes. The conflicting patterns distract the person from identifying the given figure. There is also a strong connection between this cognitive style and social interactions. People who are field-dependent are frequently described as being very interpersonal and having a well-developed ability to read social cues and to openly convey their own feelings. Others describe them as being very warm, friendly, and personable. Interestingly, Witkin and Donald Goodenough, in their 1981 book Cognitive Styles, explained that this may be due to a lack of separation between the self and the environment (or “field”) on some level. Field-dependent people notice a lack of structure in the environment (if it exists) and are more affected by it than other people. (b) Field-independence: A field-independent individual views the world analytically and is able to concentrate on an object, problem or situation without being distracted by its context. A person who is field-independent can readily identify the geometric shape, regardless of the background in which it is set. Individuals who are field-independent use an “internal” frame of reference and can easily impose their own sense of order in a situation that is lacking structure. They are also observed to function autonomously in social settings. They are sometimes described as impersonal and task-oriented. These people, however, do have the ability to discern their own identity of self from the field. Field-dependence and field-independence represent differences in the abilities of individuals to separate background (or field) from figure. This manner of interpretation, however, is not limited to visual cues.

Many researchers are studying auditory and other sensory perception abilities that may vary from person to person. In addition, a strong correlation has been discovered between gender and field orientation. Women are more likely to be field-dependent, whereas men are frequently field-independent. Career tasks and job descriptions are also closely aligned with field-dependence/field-independence. (v) Values: Our perceptions of others are strongly affected by our own experiences and the attitudes in us they create. If we are honest and inexperienced, what may be called innocent or naive by most, we will almost certainly presume honesty in most, if not all, of those we encounter. If we believe we are good, we presume everyone else is “really good”. By knowing honesty and integrity within themselves, honest people have a far greater chance of recognising it in others. What we see in the environment is a function of what we value, our needs, our fears, and our emotions. (vi) Needs: Biological needs and drives are the primary moves of action. When we need something, have an interest in it; we are especially likely to perceive it. For example, hungry individuals are faster than others at seeing words related to hunger when the words are flashed briefly on a screen (Wispe and Drambarean, 1953). The classic study of Bruner and Goodman (1947) on value and need as organising factor in perception indicate that personally relevant objects in the perceptual field undergo accentuation. This accentuation suggests that what is important for a person appears larger in his perception. However, Carter and Scholar have not found similar results have questioned whether this assumption is proved in all instances in which value is a prime factor in the situation. Charles Egerton Osgood (November 20, 1916-September 15, 1991) from his experiments concluded that our perception is influenced by immediate need and motives of the individual. (vii) Beliefs: What a person holds to be true about the world can affect the interpretation of ambiguous sensory signals. (viii) Emotions: Emotions can also influence our interpretation of sensory information. Negative emotions such as anger, fear, sadness or depression, jealousy and so on can prolong and intensify a person’s

pain (Fernandez and Turk, 1992; Fields, 1991). Many researchers suggest that our emotional state will affect the way that we perceive. For example, there is a term “perceptual defence” (Mc Ginnies, 1949) which refers to the effects of emotion on perception—findings from a number of experiments show that subliminally perceived words which evoke unpleasant emotions take longer to perceive at a conscious level than neutral words. It is almost as if our perceptual system is defending us against being upset or offended and it does this by not perceiving something as quickly as it should. Mc Ginnies (1949) investigated perceptual defence by presenting subjects with eleven emotionally neutral words (such as “apple”, “broom” and “glass”) and seven emotionally arousing, taboo words (such as “whore”, “penis”, “rape”). Each word was presented for increasingly long durations until it was named. There was a significantly higher recognition threshold for taboo words—that is it took longer for subjects to name taboo words. This suggested that perceptual defence was in operation and that it was causing alterations in perception. (ix) The influence of expectations or context: Our tendency to see (or hear, smell, feel, or taste) what we expect or what is consistent with our preconceived notions of what makes sense. It has already been stressed that our previous experience often affects how we perceive the world because of our expectations. The tendency to perceive what we expect is called a “perceptual set”. When we read, expectations can cause us to add an element that is missing (univerity becomes university); delete an element (hosppital becomes hospital); modify an element (unconscicus becomes unconscious); or transpose or rearrange elements (nervos becomes nervous) (Lachman, 1996). This is the idea that what we see is, at least to some extent, influenced by what we expect to see. Expectation can be useful because it allows the perceiver to focus their attention on particular aspects of the incoming sensory stimulation and helps them to know how to deal with the selected data—how to classify it, understand it and name it. However, it can distort perceptions too. Some experiments (for

example, Minturn and Bruner, 1951) have shown that there is an interaction between expectation and context. Look at the stimuli below: E.........D.........C.........13.........A 16.......15........14........13.........12 The physical stimulus ‘13’ is the same in each case but is perceived differently because of the context in which it appears—you expect it to be the letter ‘B’ in the letter context but the number ‘13’ in the number context. Expectation affects other aspects of perception— for example, we may fail to notice printing errors or writing errors because we are expecting to see particular words or letters. For example, “The cat sat on the map and licked its whiskers”—could you spot the deliberate mistake? How about the stimuli below? PARIS IN THE THE SPRING ONCE IN A A LIFETIME A BIRD IN THE THE HAND In each case what you perceived and what was physically present was probably different. Expectation certainly influences perception. (x) Personality: The personality of the perceiver as well as the stimulator has an impact on the perception process. The age, sex, race, dress, and the like of both the persons have a direct influence on the perception process. (xi) Past experience: Philosophers over the centuries have speculated on the relative importance of innate or inborn factors and of learning in perception. One extreme position was adopted by the English philosopher John Locke. He claimed that the mind at birth is a tabula

rasa (literally, a blank tablet). According to this view, perception is possible only after prolonged experience and learning. The perception of stimulus or stimuli depends upon the pre-existing experience which determines in what way and how the stimulus will be perceived. Perception is defined as the interpretation of sensation in the light of past experience. Past experience also produces various kinds of attitudes, prejudices, and beliefs about the percept. The same individual may perceive the same stimulus differently at different times due to past experience. Schafer and Murphy (1943) found that in simple visual perception even need and past experience can determine which aspect of the visual field will be perceived as “Figure” and which aspect as “Ground”. (xii) Habit: Habits die hard and therefore individuals perceive objects, situations and conditions differently according to their habits. A Hindu will bow and do Namaskar (paying obsequese) when he sees a temple while walking on road, because of his well-established habit. There are also several instances in life settings where individuals tend to react with the right response to the wrong signals. Thus a retired soldier may throw himself on the ground when he hears a sudden burst of car tyre. (xiii) Learning: The state of learning influences and plays a crucial role in the perception process. However, it should be recognised that the role of learning is more pronounced in respect of complex forms of perception where the symbolic content creeps into the process. Although interrelated with motivation and personality, learning may play the single biggest role in developing perceptual set. People perceive as per their levels of learning. It is therefore essential for any organisation to make its employees knowledgeable and educated for their effective performance and behaviour. Also, the learning of managers and workers is a twin requirement. (xiv) Organisational role and specialisation: Modern organisations value specialisation. Consequently the speciality of a person that casts him in a particular organisational role predisposes him to select certain stimuli and to disregard others. Thus, in a lengthy report, a departmental head will first notice the text relating to his department.

(xv) Economic and social background: Employee perceptions are based on economic and social backgrounds. Socially and economically developed employees have a more positive attitude towards development rather than less developed employees.

4.6.2 Cultural Factors Our needs, beliefs, emotions, and expectations are all affected, in turn, by the culture we live in. Different cultures give people practice with different environments. In a classic study done in 1960, researchers found that members of some African tribes were much less likely to be fooled by the Muller-Lyre Illusion and other geometric illusions than were westerners (Segall, Campbell and Herskovits, 1966). Replications in 1970s of this research showed that it was indeed culture that produced the differences between groups (Segall, 1994; Segall et al., 1990). Culture affects perception in many other ways: by shaping our stereotypes, directing our attention, and telling us what is important to notice and what is not. In sum, cross-cultural studies of perception suggest that perception is influenced by learning and by the experiences we have had over the years. (i) Cultural background and experience: Perception is related to an individual’s group membership and thus involves different cultural factors. Through socialisation, an individual learns to perceive things in the context and reference of his own culture. Thus, the same stimulus is perceived differently in different cultures. (ii) Prejudices: Prejudices have an effect upon perception (Pettigrew et al., 1958). Prejudice can be a powerful influence, biasing the way we think about and act towards ethnic minorities. Human beings are prone to errors and biases when perceiving themselves. Moreover, the type of bias people have depends on their personality. Many people suffer from self-enhancement bias. This is the tendency to overestimate our performance and capabilities and to see ourselves in a more positive light than others see us. People who have a narcissistic personality are particularly subject to this bias, but many others also have this bias to varying degrees (John and Robins, 1994). At the same time, other people have the opposing extreme, which may be labelled as selfeffacement bias. This is the tendency to underestimate our performance

and capabilities and to see events in a way that puts us in a more negative light. We may expect that people with low self-esteem may be particularly prone to making this error. These tendencies have real consequences for behaviour in organisations. For example, people who suffer from extreme levels of self-enhancement tendencies may not understand why they are not getting promoted or rewarded, while those who have a tendency to self-efface may project low confidence and take more blame for their failures than necessary. When human beings perceive themselves, they are also subject to the false consensus error. Simply put, we overestimate how similar we are to other people (Fields and Schuman, 1976). We assume that whatever quirks we have are shared by a larger number of people than in reality. People, who take office supplies home, tell white lies to their boss or colleagues, or take credit for other people’s work to get ahead may genuinely feel that these behaviours are more common than they really are. The problem for behaviour in organisations is that, when people believe that behaviour is common and normal, they may repeat the behaviour more freely. Under some circumstances, this may lead to a high level of unethical or even illegal behaviours. How we perceive other people in our environment is also shaped by our biases. Moreover, how we perceive others will shape our behaviour, which in turn will shape the behaviour of the person we are interacting with. One of the factors biasing our perception is stereotypes. Stereotypes are generalisations based on a group characteristic. For example, believing that women are more cooperative than men or that men are more assertive than women are stereotypes. Stereotypes may be positive, negative, or neutral. In the abstract, stereotyping is an adaptive function—we have a natural tendency to categorise the information around us to make sense of our environment. Just imagine how complicated life would be if we continually had to start from scratch to understand each new situation and each new person we encountered! What makes stereotypes potentially discriminatory and a perceptual bias is the tendency to generalise from a group to a particular individual. If the belief that men are more assertive than women leads to choosing a man over an equally qualified female candidate for a position, the decision will be biased, unfair, and potentially illegal.

Stereotypes often create a situation called self-fulfilling prophecy. This happens when an established stereotype causes one to behave in a certain way, which leads the other party to behave in a way that confirms the stereotype (Snyder, Tanke, and Berscheid, 1977). If you have a stereotype such as “Asians are friendly,” you are more likely to be friendly toward an Asian person. Because you are treating the other person more nicely, the response you get may also be nicer, which confirms your original belief that Asians are friendly. Of course, just the opposite is also true. Suppose you believe that “young employees are slackers.” You are less likely to give a young employee high levels of responsibility or interesting and challenging assignments. The result may be that the young employee reporting to you may become increasingly bored at work and start goofing off, confirming your suspicions that young people are slackers! Stereotypes persist because of a process called selective perception. Simply means that we pay selective attention to parts of the environment while ignoring other parts, which is particularly important during the planning process. Our background, expectations, and beliefs will shape which events we notice and which events we ignore. For example, an executive’s functional background will affect the changes she or he perceives in the environment (Waller, Huber, and Glick, 1995). Executives with a background in sales and marketing see the changes in the demand for their product, while executives with a background in information technology may more readily perceive the changes in the technology the company is using. Selective perception may also perpetuate stereotypes because we are less likely to notice events that go against our beliefs. A person who believes that men drive better than women may be more likely to notice women driving poorly than men driving poorly. As a result, a stereotype is maintained because information to the contrary may not even reach our brain! Let’s say we noticed information that goes against our beliefs. What then? Unfortunately, this is no guarantee that we will modify our beliefs and prejudices. First, when we see examples that go against our stereotypes, we tend to come up with subcategories. For example, people who believe that women are more cooperative when they see a female who are assertive may classify her as a “career woman.” Therefore, the example to the contrary does not violate the stereotype and is explained as an exception to the rule (Higgins and Bargh, 1987). Or, we may simply discount the information. In

one study, people in favour of and against the death penalty were shown two studies, one showing benefits for the death penalty while the other disconfirming any benefits. People rejected the study that went against their belief as methodologically inferior and ended up believing in their original position even more (Lord, Ross, and Lepper, 1979)! In other words, using data to debunk people’s beliefs or previously established opinions may not necessarily work a tendency to guard against when conducting planning and controlling activities. One other perceptual tendency that may affect work behaviour is first impressions: Initial thoughts and perceptions we form about people that tend to be stable and resilient to contrary information. The first impressions we form about people tend to have a lasting effect. In fact, first impressions, once formed, are surprisingly resilient to contrary information. Even if people are told that the first impressions were caused by inaccurate information, people hold on to them to a certain degree because once we form first impressions, they become independent from the evidence that created them (Ross, Lepper, and Hubbard, 1975). Therefore, any information we receive to the contrary does not serve the purpose of altering them. For example, imagine the first day you met your colleague. She or he treated you in a rude manner, and when you asked for her or his help, she or he brushed you off. You may form the belief that your colleague is a rude and unhelpful person. Later on, you may hear that your colleague’s mother is seriously ill, making your colleague very stressed. In reality, she or he may have been unusually stressed on the day you first met her or him. If you had met her or him at a time when her or his stress level was lower, you could have thought that she or he is a really nice person. But chances are, your impression that she or he is rude and unhelpful will not change even when you hear about her or his mother. Instead, this new piece of information will be added to the first one: She or he is rude, unhelpful, and her or his mother is sick. You can protect yourself against this tendency by being aware of it and making a conscious effort to open your mind to new information. It would also be to your advantage to pay careful attention to the first impressions you create, particularly in a case where you are as a manager doing job interviews.

4.7 LAWS OF PERCEPTION OR GESTALT GROUPING

PRINCIPLES One of the most striking characteristic of perception is that it is nearly always highly organised. The process by which we structure the input from our sensory receptors is called perceptual organisation. Aspects of perceptual organisation were first studied systematically in the early 1900s by Gestalt psychologists—German psychologists intrigued by certain innate tendencies of the human mind to impose order and structure on the physical world and to perceive sensory patterns as well-organised wholes rather than as separate, isolated parts (Gestalt means “whole”). The Gestaltists argued that most perceptual organisation reflects the basic and largely innately determined functioning of the perceptual system. “To the Gestaltists, things are affected by where they are and by what surround them...so that things are better described as “more than the sum of their parts”. Gestaltists believed that context was very important in perception. They argued that most perceptual organisation depends on innate factors and brain processes or functions of the brain. Gestalt psychology attempts to understand psychological phenomena by viewing them as organised and structured wholes rather than the sum of their constituent parts. The Gestaltists also called attention to a series of principles known as the laws of grouping—the basic ways in which we group items together perceptually. Let us now discuss the six essential laws of organisation of perceptual field. (i) Law of Proximity (or the law of nearness): “Law of Proximity” states that objects near each other tend to be perceived as a unit or the visual elements which are close to each other will tend to be grouped together [see Figures 4.2(a) and (b)]. It is the tendency to perceive items located together as a group. Law of Proximity is also called minimum-distance principle.

Figure 4.2 Law of proximity.

In Figure 4.2(a), you can find three groups of two lines and in 4.2(b) three groups of four dots. (ii) Law of Similarity: “Law of Similarity” states that objects similar to each other tend to be seen as a unit, or similar visual elements are grouped together (see Figure 4.3). This is the tendency to perceive similar items as a group.

Figure 4.3 Law of similarity.

The above figure is seen as two columns of one kind of dot and two columns of another; vertical columns rather than horizontal rows are seen. (iii) The Law of Good Continuation: This law states that we tend to perceive smooth, continuous lines rather than discontinuous fragments or those visual elements producing the fewest interruptions to smoothly curving lines are grouped together [see Figures 4.4(a) and (b)]. This is the tendency to perceive stimuli as a part of continuous pattern.

Figure 4.4 Law of good continuation.

In Figure 4.4(a), we tend to see two crossing lines rather than a Vshaped line and an inverted V-shaped line and in Figure 4.4(b) is seen a diamond between two vertical lines and not as a W on top of an M. (iv) The Law of Closure: “Law of Closure” states that a figure with a gap

will be perceived as a closed, intact figure or the missing parts of a figure are filled in to complete it [see Figures 4.5(a), (b) and (c)]. This is the tendency to perceive objects as whole entities, despite the fact that some parts may be missing or obstructed from view.

Figure 4.5 Law of closure.

The above figures are seen as a circle (a), triangle (b), and a square (c), although incomplete. This occurs because of our inclination or mental set to fill in the gaps or close the gaps and to perceive incomplete figures as complete. These non-existing lines, which are known as subjective contours, appear naturally as the result of the brain’s automatic attempts to enhance and complete the details of an image (Kanizsa, 1976). (v) Law of Symmetry: “Law of Symmetry” states that there is a tendency to organise things to make a balanced figure or symmetrical figure that includes all parts. (vi) Law of Common Fate: “Law of Common Fate” states that those aspects of a perceptual field that function or move in similar manner tend to be perceived together. This is the tendency to perceive objects as a group if they occupy the same place within a plane. The laws of organisation of perceptual field discussed thus are more specific statements and descriptions of the basic law of Pragnanz. Gestaltists proposed numerous laws of perceptual organisation, but their most basic principle was the law of Pragnanz, which is as follows: “Psychological organization will always be as ‘good’ as the prevailing conditions allow. In this definition, the term ‘good’ is undefined (Kurt Koffka, 1935)”. The figure-ground relationship and these laws of grouping help organise our visual world and encourage pattern recognition.

4.7.1 Limitations of Gestalt Laws of Organisation

(i) The major weakness of the Gestalt laws of organisation is that the laws are only descriptive statements: they fail to explain why it is that similar visual elements or those close together are grouped together. (ii) Another limitation is that most of the Gestalt laws relate primarily or exclusively to the perceived organisation of two-dimensional patterns. (iii) It is extremely difficult to apply the Gestalt laws of organisation to certain complex visual stimuli.

4.8 PERCEPTION OF FORM Perception refers to the way the whole stimuli in the environment looks, feels, tastes, or smell. According to some psychologists, perception can be defined as whatever is experienced by a person with the help of various sense organs. One important characteristic of environment of the perceived object is that it is full of forms, shapes, patterns, and colours which are quite stable and often unchangeable. According to Gestalt psychologists, “Environment of the perceived object cannot be thought of simply as the sum total of a sensory input.” There are the organisation tendencies within the person or individual which act on sensory stimuli. So, perception or the perceptual process is more subjective and objective. Perception is subjective when it is being affected by internal factors. On the other hand, perception is objective, when it is being affected by external factors. Gestalt psychologists described the principles of perceptual organisation on the basis of external factors relating to the perceiver’s environment and the internal factors related to the perceiver herself or himself. (i) Contour perception: An object is perceived or seen properly due to the contour. A contour is said to be a boundary existing between a figure and a ground. The degree of quality of this contour separating the figure from the ground is responsible for indicating us to organise the stimuli or objects into meaningful pattern. This law of contour helps in organising the perception. If there is no boundary between the figure and the ground, then the figure will not be perceived separately from the ground. Edgar Rubin (1915, 1921) called contour formative of shape, “shape-producing”. When the field is divided by a contour into figure and ground, the contour shapes the figure only, the ground appearing

shapeless. Contour separates various objects from the general background in visual perception and this is possible only because of the perceptual principle known as the principle of contour. A contour is a relatively abrupt change of gradient in either brightness or colour. Contrast enhances contour and makes the outlines of objects more distinct. Different psychologists are of the opinion that contours are always shapeless but they determine the shape of the objects. However, contour can sometimes be seen without even the difference in the brightness in the perceptual field. It means that perception is being affected by the subjective factors and such contours are called subjective contours (Loren, 1970). This shows that the contour in perception is affected by the inner elements of the perceptual field in perceiving the division of the place. Whenever the brightness changes, a contour can be perceived very easily. Thus, with the help of principle of contour, objects in the environment are easy to distinguish from the background. (ii) Contrast perception: Contrast is a physiological and retinal process which may help to explain colour constancy. Contrast offers to the sensory response and not merely to strong difference between the two stimuli. As a sensory response, the simultaneous contrast sometimes exaggerates the difference between the two stimuli. Thus in contrast perception, all the effects are produced by the changes in the brightness of the stimuli and the brightness of any region of the stimuli depends upon its background. For example, four small squares are put in four large squares with different background, and then the inner four squares being identical will be different in the brightness due to their changing background. Thus the small grey squares on a white background will look dark and on the other hand it will look light if the background is changed, that is if the background is black. The colour contrast is produced by the changes in relation to the background areas of the visual field. Simultaneous contrast occurs when the test regions are simultaneously present in contrast between the two areas. The contrast effect occurs in perception or in the spatial environment due to the change in degree of brightness or the intensity of light.

4.8.1 Figure–Ground Differentiation in Perception

As already discussed, a figure is perceived perfectly only due to the background and in figure and background relationship, figure is more prominent on the basis of its ground. As you read, the words are the figure; the white paper of the book, the ground. It is only that the background is clear that the figure can be seen properly. Perception of objects in the environment in terms of their colour, size, and shape depends on the figure and ground relationship. We usually perceive a figure against a background and sometimes we may perceive a background against a figure depending upon the characteristics of the perceiver as well as the relative strength of figure and ground. In figure and ground relationship, there is also the reversible background in which sometimes a figure becomes the background and sometimes the background becomes the figure (see Figure 4.6). Same stimulus can trigger more than one perception. This reversible figure showing white vase and the black faces has been given by Rubin. Thus, according to the principle of figure and ground relationship, perception can be organised very easily which may further lead to meaningful patterns or form.

Figure 4.6 Reversible Figure–Ground.

Figure and ground are the familiar concepts in the field of perception. Hebb (1949) in his book ‘The Organization of Behavior’ makes the point that the figure and ground relationship or the figure and ground concept is very important in the perceptual field. Figure is the simplest aspect and figure can be seen as a unit standing out from the background. While the simplest aspect in perception is figure, it has a relation with the background.

4.8.2 Gestalt Grouping Principles Gestalt approach was prominent in Europe in the first decades of twentieth century (Hochberg, 1988). Gestalt School Psychology was found in Germany in the 1910s. Some German psychologists tried to understand how, inspite of the limitations of the retinal image (retinal image is two-dimensional and very different in size and shape from the actual object), is our perception organised. Gestaltists protested that conscious experience could not be dissected without destroying the very essence of experience, namely, its quality of wholeness. Direct awareness, they said, consists of patterns or configurations and not of elements joined together. Gestaltists maintain that psychological phenomena could only be understood if they were viewed as organised, structured wholes (or Gestalten). They called themselves Gestaltists; this is based on the German word “Gestalt” meaning organised whole. According to the gestalt approach, we perceive object as wellorganised, whole structures instead of separate, isolated parts. The gestalt psychologists stressed that our ability to see object having shape and pattern is determined by interrelationships among the part (Green, 1985). One area in which the Gestalt influence is still very prominent is in research on the figure-ground relationship (Banks and Krajicek, 1991). In order to interpret what we receive through our senses, the Gestaltists theorised that we attempt to organise this information into certain groups. This allows us to interpret the information completely without unneeded repetition. The contribution of Gestalt psychologists in perception is thus noteworthy. These psychologists—Max Wertheimer (1880–1943), Kurt Koffka (1886–1941), and Wolfgang Kohler (1887–1967) described that the wholeness of the situation is more important than the parts. They found that the organisation applies certain principles in organising the perception and all these perceptual principles are related to the wholeness of the situation. The rules identified by the Gestalt psychologists are applied even to 6-month old infants. Some of the other important laws or principles of perceptual organisation are as follows: (i) Law of Wholeness: This law states that the total situation is perceived immediately as a whole. This law of wholeness was given by Gestalt psychologists. “Gestalt” in German language implies the “organised

structure”. According to this law, whole is perceived first in perception and then the other parts are visualised, so, wholeness of a situation is more important. (ii) Law of Grouping: It refers to the tendency to perceive the stimuli in some organised and meaningful pattern by grouping them. According to this law, all the stimuli existing in the environment can be organised and grouped, and only they can lead to the meaningful perception (see Figure 4.7). Thus, it is clear that by perceptual organisation and grouping, we can have meaningful perception. This grouping is done on the basis of laws already discussed in laws of perception (Section 4.7).

Figure 4.7 Laws of grouping.

(iii) Law of Connectivity: When they are uniform and linked, we perceive spots, lines, or areas as a single unit. (iv) Law of Figure and Ground Relationship: According to this law, figure is perceived perfectly only due to the background and in figure and ground relationship; figure is more prominent on the basis of its ground. “Figure and ground” refers to the most basic and elementary of all forms of perceptual structure. We perceive an object as a figure in a ground. We perceive a picture on a page. The picture is a figure and this page is the ground. Edgar Rubin (1886–1951), a gestalt and Danish psychologist and phenomenologist from Denmark, reached several conclusions (1915, 1958) about the figure–ground relationship.

According to Edgar Rubin, “Figure and ground possess the following properties: (a) The figure seems closer to the viewer, with a clear location in space. In contrast, the ground seems farther away. It takes a clear location. (b) Figure has form, whereas ground is relatively formless. The figure has a definite, clear, distinct shape, whereas the ground seems vague, formless, and shapeless. (c) Figure has “thing like” qualities, whereas ground appears as more homogeneous and unformed material. (d) Figure appears to be nearer to the observer than does the ground. The figure appears on the front, whereas the ground seems to continue behind the figure. (e) The figure is more easily identified or named than the ground. (f) The colour of the figure is more impressive. (g) The figure is more likely to be connected with meanings, feelings, and aesthetic values than is the ground. (h) The figure is bright, where as the ground is dull.” In almost all cases, the figure–ground concept is clear art. We discriminate figure from ground, imposing one important kind of organisation in our visual experiences. We also organise visual stimuli into patterns and groups. (v) Law of Contour: According to this principle, an object is seen or perceived properly due to the contour. A contour is said to be the boundary existing between a figure and its background. The degree of quality of contour separating the figure from the ground is responsible for indicating the perceiver to organise the stimuli or objects into meaningful patterns or perceptions. This law of contour helps in organising the perception. If there is no boundary between figure and ground, then figure will not be perceived separately from the ground, for example, some clouds in the sky can’t be separated from light blue sky as they looked merged as there is no separate boundary or contour. (vi) Law of Good Figure: According to this law, there is a tendency to organise things to make a balanced or symmetrical figure that includes all the parts. So, a figure including all the parts will be considered as a good figure. This can be organised easily.

(vii) Law of Contrast: Perceptual organisation is very much affected by the contrast effect. The stimuli that are in sharp contrast draw a maximum attention, for example, a very short man standing among tall men and also the contrast of black and white. (viii) Law of Adaptability: According to this law, the perceptual organisation for some stimuli depends upon the adaptability of the perceiver to perceive similar stimuli, for example, an individual who has adapted himself to work before the intense bright light will perceive the normal sunlight as quite dim. Similarly, our sense organs of touch, smell, and taste may also get accustomed or adapted to a certain degree of stimulation and getting habituated to this kind of stimulation may strongly affect the perception. Thus, all these principles are important in the organisation of perception and these principles facilitate perception which further leads to meaningful organisation of the object in the environment. The major weakness of the Gestalt laws of organisation is that the laws are only descriptive statements: they fail to explain why it is that similar visual elements or those close together are grouped together. Another limitation of the laws of organisation is that most of the laws relate primarily to the perceived organisation of twodimensional patterns. However, it is extremely difficult to apply the Gestalt laws of organisation to certain complex visual stimuli.

4.9 PERCEPTUAL SET “Set” is a very general term for a whole range of emotional, motivational, value system, social, and cultural factors which can have an influence upon cognition. As such, it helps to explain why we perceive the world around us in the way we do. Our perceptions are also influenced by many subjective factors, which include our tendency to see (or hear, smell, feel, or taste) what we expect or what is consistent with our preconceived notions of what makes sense. The tendency to perceive what we expect is called perceptual set. Set predisposes an individual towards particular perceptions and indeed facilitates her or his perception. It may be induced by emotional, motivational, social, or cultural factors. Generally, the term “set” refers to a temporary orientation or state of

readiness to respond in a particular way to a particular situation. Perceptual set is this “readiness” to perceive the environment in a particular way. The effects of perceptual set include: (i) Readiness: Set involves an enhanced readiness to respond to a signal. (ii) Attention: Set involves a priority processing channels. The expected stimulus will be processed ahead of everything else. (iii) Selection: Set involves the selection of one stimulus in preference to others. (iv) Interpretation: The expected signal is already interpreted before it occurs. The individual knows beforehand what to do when the stimulus is picked up. Allport (1955) defined perceptual set as “a perceptual bias or predisposition or readiness to perceive particular features of a stimulus.” An athlete waiting for the starting gun hears “get set” and each of the above effects comes into play. There is enhanced readiness to move, with enhanced attention, and priority selection of the expected stimulus.

4.9.1 Factors Affecting Set Factors which influence set come under two headings: (i) Aspects of the Stimulus: These include the context within which it occurs or the context in which something is perceived, the individual’s expectations, and any instructions which may have been given. The context in which stimulus is seen produces expectation and induces a particular set (Bruner and Minturn, 1955). (ii) Aspects Which Relate to the Individual: Perceptions are influenced by a whole range of factors relating to the individual. These include individual differences in personality or intelligence, past experience, motivation (both intrinsic and extrinsic), value system, cognitive styles, emotional states, prejudices, and cultural background or other factors. Past experience induces a particular set (Bruner and Postman, 1949). A number of studies have shown the effect of different kinds of motivation upon the way in which things are perceived (Gilchrist and Nesberg, 1952; Solley and Haigh, 1957). There is some evidence that an individual’s value system may induce as

set (Postman and Egan, 1948). Cognitive styles also induce set. Witkin (1949) identified two different cognitive styles—field-dependent and field independent (discussed earlier in this chapter). Another form of perceptual set is the tendency to perceive stimuli that are consistent with our expectations or beliefs, and to ignore those that are inconsistent. This phenomenon is frequently referred to as selective perception—the tendency to perceive stimuli that are consistent with our expectations or beliefs, to ignore those that are inconsistent (discussed earlier in this chapter). For example, if you believe that all neatly dressed elderly people are honest; you might not even think twice about the elderly person at the next table when your bag disappears in a shop, even if that person is the most obvious suspect. Likewise, people who distrust groups of people because of their appearance, religion, gender, or ethnic background are unlikely to recognise the good qualities of an individual who is a member of one of those groups. According to Vernon (1955), set works in two ways: 1. The perceiver has certain expectations and focuses attention on particular aspects of the sensory data: This he calls a “Selector”. 2. The perceiver knows how to classify, understand and name selected data and what inferences to draw from it. This he calls an “Interpreter”. It has been found that a number of variables, or factors such as the following influence set, and set in turn influence perception: Expectations Emotion Motivation Culture Perception of many aspects of objects in the environment is not only due to the biological characteristics of the incoming stimulation and the appropriate sensory receptor mechanism but is also due to the certain dispositions and the existing intentions within the perceiver. There are psychological processes which are more specific than the Gestalt principles and these processes play an important role in organising the incoming

stimulation towards the meaningful object. Perception or perceptual experience is being affected by expectation and anticipation. These expectations result in readiness to organise the visual input in a certain way. In other words, we can say that when the perceiver expects to perceive or is mentally prepared to perceive a particular thing, then the perception will be facilitated. According to Bruner (1957), the things for which we have expectations to perceive are more readily perceived and organised. Thus, the perceptual set enables the person to perceive meaningful perception. For example, if an ambiguous stimulus (13) is taken and by previously showing the subject four different capital letters that is Z, X, Y, A and then this ambiguous stimulus (13) is shown to the subject, it was found that the subject’s tendency was to perceive this stimulus in accordance with the capital letter that is B because of the determined expectations that is the subject was set to perceive the letter ‘B’; after perceiving the capital letters. So, when the subject was shown the broken letter considering it as a closed figure, it was perceived as ‘B’; but if the subject is mentally prepared to see the numbers, then this ambiguous stimulus was perceived as “13”. Thus, many set related tendencies and the influences occur from the significant prior interaction with the environment. Perceptual set refers to the idea that we may be ready for a certain kind of sensory input. Such expectations or set may vary from person to person and are the basic factors in both the selection of sensory input and also in organisation of the input related to the perception. The positive value of set is due to its facilitation of appropriate responses and inhibition of inappropriate. Its disadvantages appear when it does the reverse because it is not adequately oriented to the situation or to the goal (Harlow, 1951; Johnson, 1944). Several experiments have been carried on regarding the effect of set. Sipola (1935) studied the effect of set on perception using ambiguous stimuli. Bruner and Postman (1949) studied perceptual set by using playing cards and found significant effects of set on perception. Bruner and Martin (1955) also studied the effect of set on perception and found significant effects. Chapmen (1932) and Solomon and Howes (1951) found that set plays an important role in recognition, whereby Leeper (1953) proved that set effects the perception of figure-ground.

4.10 PERCEPTION OF MOVEMENT One of the key characteristics of vision is the perception of movement. Movement means any change in the position of an organism or of one or more of its parts. Movement can be inferred from the changing position of the object relative to its background. A major source of information comes from image displacement, which involves position shifts of the image of a stimulus on the retina. This happens when something moves across our field of vision, but we do not follow it with our eyes. Real movement refers to the physical displacement of an object from one position to another, depending only on the movement of images across the retina.

4.10.1 Image–Retina and Eye–Head Movement System Eye movements are the voluntary or involuntary movements of the eyes, helping in acquiring, fixating and tracking different visual stimuli. Movement is visually detected by one of two systems: (a) the image–retina system (image moves along stationary retina), or (b) the eye–head movement system (eye moves to keep image stationary on retina). Gregory (1977) proposes that these two viewing conditions serve two interdependent movement systems: (i) Image–Retina Movement System Effective stimulus is successive stimulation of adjacent receptors This system is well suited to the mosaic of the compound eye (ii) Eye–Head Movement System When a target is followed, the retinal image is roughly stationary – The eye movement has compensated for the movement of the target – Background movement? – Even a spot of light in a dark room is sufficient to induce the perception of movement The visual system monitors the movements of the eyes – Efferent signals (motor commands from the brain to the muscles of the eyes) Occur only in self-produced eye movements

4.10.2 Apparent Movement Apparent movement or motion is a cover term for a large number of perceptual phenomena in which objects that are, in fact, stationary appear to move. Illusionary movement or apparent movement refers to the apparent movement created by the stationary objects. Apparent movement, also called phenomenal motion, is the sensation of seeing movement when nothing actually moves in the environment, as when two neighbouring lights are switched on and off in rapid succession. According to Underwood, “Apparent movement is the perceived movement in which objectivity does not take place.” A good example of this kind of movement is the cinema. Wertheimer (1912) called it phi-phenomena. Phi phenomenon is a form of apparent motion produced when two stationary lights are flashed successively. If the interval between the two is optimal (in the neighbourhood of 150 milliseconds), then one perceives movement of the light from the first location to the second. More generally, Max Wertheimer used the phrase to refer to the “pure” irreducible experiencing of motion independent of other factors such as colour, brightness, size and spatial location. The phi phenomenon in the first sense was considered by Wertheimer to be a good example of the second sense and hence is sometimes called the pure phi phenomenon. Apparent movement is an optical illusion of motion produced by viewing a rapid succession of still pictures of a moving object; “the cinema relies on apparent motion”; “the succession of flashing lights give an illusion of movement”. Our perception of speed depends on three factors: the background, the size of the moving object; and velocity. (i) Background—complexity increases the perception of movement (ii) Size—smaller objects appear to be moving faster than larger objects (iii) Velocity— actual velocity is difficult to judge; have limits Autokinetic effect (Phi Phenomenon) means a stationary point of light in a completely darkened area will appear to move when we fixate on it. Apparent movement is also known as stroboscopic movement. Stroboscopic movement is experienced when the object appears to undergo a change in its location. It is any of a class of apparent motion effects produced by presenting a series of stationary stimuli separated by brief intervals. Motion pictures are the best-known example; there is no real motion on the screen, merely a sequence of still frames presented in succession.

b-movement – When two stationary lights, set a short distance apart, are alternately flashed at a certain rate the result is the perception of movement of a single spot of light back and forth. – Moreover, the resulting perception is of a spot that moved through the region where no light stimulus appeared.

4.10.3 Induced Movement Induced movement or motion is the perception of motion of a stationary stimulus object produced by real motion of another stimulus object. Induced movement is an illusionary effect, in which an object which is not actually moving appears to be moving because of the movement of surrounding objects (for example, a stationary train at a station when an adjacent train starts moving). Induced movement means a stationary form will appear to move when its frame of reference moves. If, for example, in an otherwise dark room, a moving square perimeter of light is presented with a stationary dot of light inside it, the square will be seen as stationary and the dot, moving. Induced movement or induced motion is an illusion of visual perception in which a stationary or a moving object appears to move or to move differently because of other moving objects nearby in the visual field. The object affected by the illusion is called the target, and the other moving objects are called the background or the context (Duncker, 1929).

4.10.4 Auto-kinetic Movement The autokinetic effect (also referred to as autokinesis) is a phenomenon of human visual perception in which a stationary, small point of light in an otherwise dark or featureless environment appears to move. It was first recorded by a Russian officer keeping watch, who observed illusory movement of a star near the horizon. It presumably occurs because motion perception is always relative to some reference point. In darkness or in a featureless environment there is no reference point, and so the movement of the single point is undefined. The direction of the movements does not appear to be correlated with the involuntary eye movements, but may be determined by errors between eye position and that is specified by efference copy of the movement signals sent to the extraocular muscles.

The amplitude of the movements is also undefined. Individual observers set their own frames of reference to judge amplitude (and possibly direction). Since the phenomenon is labile, it has been used to show the effects of social influence or suggestion on judgements. For example, if an observer who would otherwise say the light is moving one foot overhears another observer say the light is moving one yard then the first observer will report that the light moved one yard. Discovery of the influence of suggestion on the autokinetic effect is often attributed to Sherif (1935), but it was recorded by Adams (1912), if not others. Two factors are involved in this movement: The perception of movement may occur when one is fixating on a stationary point of light in a completely dark room. Involuntary eye movements: The autokinetic effect refers to perceiving a stationary point of light in the dark as moving. Psychologists attribute the perception of movement where there is none to “small, involuntary movements of the eyeball” (Schick and Vaughn, 1995). The autokinetic effect can be enhanced by the power of suggestion: If one person reports that a light is moving, others will be more likely to report the same thing (Zusne and Jones, 1990).

4.11 PERCEPTION OF SPACE Human beings have been interested in the perception of objects in space at least since antiquity. Space perception is a process through which humans and other organisms become aware of the relative positions of their own bodies and objects around them. Space perception is the perception of the properties and relationships of objects in space especially with respect to direction, size, distance, and orientation. It is the awareness of the position, size, form, distance, and direction of an object, or of oneself. Space perception provides cues, such as depth and distance that are important for movement and orientation to the environment.

4.11.1 Monocular and Binocular Cues for Space Perception Our impressive ability to judge depth and distance exists because we make

use of many different cues in forming such judgements. We determine distance using two different cues: monocular and binocular, depending on whether they can be seen with only one eye, or require the use of both eyes. The world around us is three-dimensional, but the data collected about the world through our senses is in two dimensions (a flat image on the retinas of our eyes). The interpretation of this data within the brain results in threedimensional perception. This perception of depth depends on the brain’s use of a number of cues. Some of these cues, as they are termed, use data from one eye only (monocular cues; “mono” means “one” and “ocular” means “eyes”). Monocular cues can be used with just one eye. Others use data from both eyes (binocular cues; “bi” means “two” and “ocular” means “eyes”). These depend on both eyes, working together.

Monocular cues or secondary cues or one-eye cues Monocular cues are those cues which can be seen using only one eye. The monocular cues depend on data received from one eye only. Monocular cues are cues or signals that can operate when only one eye is looking. Monocular cues are distance cues and are available to each eye separately. Even with the loss of the sight of one eye, a person can still perceive the world in three dimensions. It is more difficult, though. Monocular cues, those used when looking at objects with one eye closed, help an individual to form a threedimensional concept of the stimulus object. These cues are the ones used by painters to give us a three-dimensional experience from a flat painting. Painters throughout history have used monocular cues to provide an impression of depth in a flat two-dimensional painting. These are also called secondary cues. These relate to the features in the visual field itself. Monocular cues to depth or distance include the following: 1. Linear perspective: Linear perspective describes the tendency of parallel lines to appear to converge at the horizon. In other words, parallel lines appear to converge in the distance; the greater this effect, the farther away an object appears to be [see Figures 4.8(a) and (b)]. This is also known as the Ponzo Illusion, of which you can see examples in Figures 4.8(a) and 4.8(b). Notice how the converging lines create depth in the image. The distances separating the images of far objects appear to be smaller.

Imagine that you are standing between railroad tracks and looking off into the distance. The tiles would seem to gradually become smaller and the tracks would seem to gradually become smaller and the tracks would seem to run closer and closer together until they appeared to meet at the horizon [see Figure 4.8(a)]. Linear perspective is based on the fact that parallel lines converge when stretched into the distance. Parallel lines appear to come together as they recede into the distance. Parallel lines, such as railroad tracks, appear to converge with distance. For example, when you look at a long stretch of road or railroad tracks, it appears that the sides of the road or the parallel tracks converge on the horizon. The more the lines converge, the greater their perceived distance. Linear perspective can contribute to rail-crossing accidents, by leading people to overestimate a train’s distance (Leibowitz, 1985).

Figure 4.8 Linear perspective.

(ii) Height in horizontal plane: Distant objects seem to be higher and nearer objects lower in the horizontal plane. We perceive points nearer

to the horizon as more distant than points that are farther away from the horizon. This means that below the horizon, objects higher in the visual field appear farther away than those that are lower. Above the horizon, objects lower in the visual field appear farther away than those that are higher. This depth cue is called relative height, because when judging an object’s distance, we consider its height in our visual field relative to other objects. You know that the trees and houses are farther away than the lake because they are higher up in the drawing than the lake is (see Figure 4.9).

Figure 4.9 Relative height.

(iii) Relative size: The larger the image of an object on the retina, the larger it is judged to be; in addition, if an object is larger than other objects, it is often perceived as closer. The more distant they are, the smaller the objects will appear to be (see Figure 4.10). A painter who wants to create the impression of depth may include figures of different sizes. The observer will assume that a human figure or some other wellknown object is consistent in size and will see the smaller objects as more distant. If we assume that two objects are similar in size, we perceive the ones that cast the smaller retinal image as farther away. To a driver, distant pedestrians (people who walk on the road or footpath) appear smaller, which also means that small-looking pedestrians (children) may sometimes be misinterpreted as more distant than they are (Stewart, 2000).

Figure 4.10 Relative size.

If we assume that two objects are the same size, we perceive the object that casts a smaller retinal image as farther away than the object that casts a larger retinal image. This depth cue is known as relative size, because we consider the size of an object’s retinal image relative to other objects when estimating its distance. Another depth cue involves the familiar size of objects. Through experience, we become familiar with the standard size of certain objects. Knowing the size of these objects helps us judge our distance from them and from objects around them. (iv) Interposition or superimposition or overlap of objects: If one object overlaps another, it is seen as being closer than the one it covers. Overlap or interposition described the phenomenon in which objects close to us tend to block out parts of objects that are farther away from us. Interposition occurs when one object is blocked by another. Interposition occurs when one object obstructs our view of another. When an object is superimposed upon another (partly hiding it) the superimposed object will appear to be nearer. If one object partially blocks our view of another, we perceive it as closer. When one object is completely visible, while another is partly covered by it, the first object is perceived as nearer. For example, a card placed in front of another card gives the appearance of the other being behind it (see Figure 4.11).

Figure 4.11 Interposition.

(v) Relative clarity or clearness: Objects which are nearer or closer appear to be clearer and more well-defined than those in the distance. The more clearly we see an object, the nearer it seems. Because light from distant objects passes through more atmospheres, we perceive hazy objects as farther away than sharp, clear objects. A distant mountain appears farther away on a hazy (foggy or cloudy) day than it does on a clear day because haze in the atmosphere blurs fine details and we can see only the larger features (see Figure 4.12). If we see the details, we perceive an object as relatively close; if we can see only its outline, we perceive it as relatively far away.

Figure 4.12 Relative clarity or clearness.

(vi) Light and shade: Nearby objects reflect more light to our eyes. Thus, given two identical objects, the dimmer one seems farther away. Shadow has the effect of pushing darker parts of an image back (see Figure 4.13). Shading, too, produces a sense of depth consistent with the assumed light source because our brains follow a simple rule: Assume that light comes from above. Highlights bring other parts forward, thus

increasing the three-dimensional effect. This illusion can also contribute to accidents, as when a fog-shrouded vehicle or one with only its parking lights on, seems farther away than it is. Shadows are differences in the illumination of an image, and help us to see 3D objects by the shadows they cast. If something is 3D it will cast a shadow, if it is 2D it won’t.

Figure 4.13 Shadows.

(vii) Texture or gradient texture or gradients of texture: The texture of a surface appears smoother as distance increases. A gradient is a continuous change in something—a change without abrupt transitions; a gradual change from a coarse or rough texture to a fine, indistinct texture signals increasing distance. Here, objects far away appear smaller and more densely packed (see Figure 4.14). The regions closest to the observer have a coarse texture and many details; as the distance increases, the texture becomes finer and brain information can be used to produce an experience. The coarser or rougher the texture of an image, the closer it seems to be. If a pavement of bricks is to be depicted, the impression of depth is created by the texture of the bricks becoming finer as the pavement goes into the distance.

Figure 4.14 Texture gradient (Examples from Gibson, 1950).

Texture gradient refers to the level of detail we can see in an image. The closer the image is to us, the more detail we will see. If it is too close, then that detail will start becoming distorted or blurry. Likewise, the farther an image is away from us, the less detail we will see in it. (viii) Relative height or aerial perspective: We perceive objects higher in our field of vision as farther away. Below the horizon, objects lower down in our field of vision are perceived as closer; above the horizon, objects higher up are seen as closer. Lower objects seem closer—and thus are usually perceived as figure (Vecera and others, 2002). Relative height may contribute to the illusion that vertical dimensions are longer than identical horizontal dimensions. (ix) Motion parallax or relative motion: When we travel in a vehicle, objects far away appear to move in the same direction as the observer, whereas close objects move in the opposite direction. Also, objects at different distances appear to move at different velocities. Motion parallax is the tendency experienced when moving forwards rapidly, to perceive differential speeds in objects that are passing by. Motion parallax phenomenon is of use in establishing the distance of objects. It means that the objects beyond the point of fixation appear to be moving in the opposite direction to objects closer than the point of fixation to a moving observer. As we move, objects that are actually stable may appear to move. For example, if while travelling in a train, we fix our gaze on some object— say a house or tree—the objects closer than the house or tree (fixation point) appear to move backward (see Figure 4.15). The nearer an object is, the faster it seems to move. Objects beyond the fixation point appear to move with us:

the farther away the object, the lower its apparent speed. Our brains use these speed and direction clues to compute the objects’ relative distances. As you move, the apparent movement of objects pass you will be slower, the more distant they are. On a wide open road, with few objects close at hand, a car will appear to those inside it to be going more slowly than on a narrow road with hedges or fences close at hand. Another good example of motion parallax occurs when driving. If you see a lamp post in front of you it appears to approach slowly, but just as you are passing it, the lamp post seems to flash by quickly in front of you. If you were to then look behind you, the lamp post would appear to be slowly moving away from you until eventually it looked stationary.

Figure 4.15 Motion parallax.

(x) Aerial or atmospheric perspective: Objects that are far away appear fuzzier or vague than those close by because as distance increases, smog, dust, and haze reduce the clarity of the projected image (see Figure 4.16). This depth cue can sometimes cause us to judge distance inaccurately, especially if we are accustomed to the smoggy atmosphere of urban areas.

Figure 4.16 Example of aerial perspective.

(xi) Movement: When you move your head, you will observe that the objects in your visual field move relative to you and to one another. If you watch closely, you will find that objects nearer to you than the spot at which you are looking—the fixation point—move in a direction opposite to the direction in which your head is moving. On the other hand, objects more distant than the fixation point move in the same direction as your head moves. Thus, the direction of movement of objects when we turn our heads can be a cue for the relative distance of objects. Furthermore, the amount of movement is less for far objects than it is for near ones. We do not usually think about this through we experience it unaware.

Binocular cues or primary cues We also rely heavily on binocular cues—depth information based on the coordinated efforts of both eyes. Binocular cues refer to those depth cues in which both eyes are needed to perceive. These require both eyes. Seeing with both eyes provides important binocular cues for distance perception (Foley, 1985). Binocular cues, those used when looking at objects with both eyes, also function in depth perception. Primary cues relate to features of the physiology of the visual system. These include retinal disparity, convergence, and accommodation. There are two depth cues that require both eyes—retinal disparity or binocular disparity and convergence. The former is an effective cue for considerable distances, perhaps as far as 1,000 feet; the latter can be used only for objects within about 80 feet of the observer. “Accommodation” involves the lens of the eye altering its shape in order to focus the image more accurately on the retina. Ciliary muscles contract to elongate the lens and focus upon more distant objects, relax to allow it to become more rounded and focus upon nearer objects. Data are fed or sent to the brain from

kinaesthetic senses in these ciliary muscles, providing information about the nearness or distance of the object focused upon. (i) Retinal disparity or binocular disparity: By far the most important binocular cues comes from the fact that the two eyes—the retinas— receive slightly different or disparate views of the world because this cue is known as retinal disparity. Our two eyes observe objects from slightly different positions in space; the difference between these two images is interpreted by our brain to provide another cue to depth. Perhaps the most accurate cue is binocular or retinal disparity. Since our eyes see two images which are then sent to our brains for interpretation, the distance between these two images, or their retinal disparity, provides another cue regarding the distance of the object. “Retinal disparity” refers to the slightly different view of the world registered by each eye. It is the difference in the images falling on the retinas of the two eyes. By comparing images from the two eyeballs, the brain computes distance—the greater the disparity (difference) between the two images, the closer the object. Binocular disparity is based on the fact that since the eyes are a couple of inches (two and a half inches) apart, each eye has a slightly different view of an object the world; this facilitates depth perception, especially when the object is relatively close. Because of their placement in the head, the eyes see the world from different perspectives. Our retinas receive slightly different images of the world. Normally, our brains fuse these two images into a single three-dimensional image (O’Shea, 1987). At the same time, the brain analyses the differences in the two images to obtain information about distance. In the brain, the images from the two eyes are compared, in a process known as “Stereopsis”. In a sense, the brain compares the information from the two eyes by overlaying the retinal images. The greater the disagreement between the two retinal patterns, the closer is the object. The view of the object that you get with your right eye is slightly different from that you get with the left eye. Retinal disparity, therefore, provides two sets of data which, interpreted together in the brain, provide stereoscopic vision, an apparent 3D image. Within limits, the closer an object is, the greater is the retinal disparity. That is, there is greater binocular disparity when objects are close to our

eyes than when they are far away. Perception is not merely projecting the world onto our brains. Rather, sensations are disassembled into information bits that the brain then resembles into its own functional model of the external world. Our brains construct our perceptions. (ii) Convergence: Another important binocular distance cue or cue to distance is a phenomenon called convergence. Convergence refers to the fact that the closer an object, the more inward our eyes need to turn in order to focus. The farther our eyes converge, the closer an object appears to be. In order to see close objects, our eyes turn inward, toward one another; the greater this movement, the closer such objects appear to be. Convergence, a neuromuscular cue, is caused by the eyes, greater inward turn when they view a near object. When we look at an object that is no more than 25 feet away, our two eyes must converge (rotate to the inside) in order to perceive it as a single, clearly focused image. This rotation of the eyes is necessary to allow them to focus on the same object, but it creates tension in the eye muscles. The closer the object, the greater the tension. The more the inward strain, the closer the object. Objects far away require no convergence for sharp focusing. The brain notes the angle of convergence. With experience, our brains learn to equate the amount of muscle tension with the distance between our eyes and the object we are focusing on. Consequently, muscular feedback from convergening eyes becomes an important cue for judging the distance of objects within roughly 25 ft of our eyes. Convergence does not depend on the retinal images in the two eyes, but on the muscle tension that results from the external eye muscles that control eye movement. The more the inward strain, the closer the object. When you look at objects close to you, your eyes converge and the tension in the eye muscles is noticeable. You can demonstrate this by extending your arm straight out in front of you and holding up your thumb. Then, while staring at your thumb, with both of your eyes; slowly bring your thumb in towards your nose, watching your thumb all the time. As your thumb approaches your nose, you will begin to notice the tension in your eyes. Indeed, your eyes may even hurt a little as your thumb gets very close to your nose. It is these differences in the tension of the eye muscles that the brain uses to make judgements about

the distance of objects.

4.12 PERCEPTUAL CONSTANCIES—LIGHTNESS, SIZE, AND SHAPE Imagine your life in an unstable world? The world as we perceive it is a stable world. Stability of perception helps us to adapt to the environment. An important characteristic of adult perception is the existence of various kinds of constancy, for example, size and shape. That is to say, we perceive a given object as having the same size and shape regardless of its distance from us or its orientation. In other words, we see things “as they really are”, and are not fooled by variations in the information presented to the retina. The retinal image of an object is very much smaller when the object is a long way away from us than when it is very close. Perceptual constancies help us to interpret accurately the world we live in. It would be virtually impossible to operate in a world where objects change their shapes and sizes when viewed from different positions and distances. Without the operation of perceptual constancies, we would depend largely on the characteristics of images on our retina in our efforts to perceive objects. The ability (or perceptual skill) to perceive objects as stable or unchanging even though the sensory patterns they produce are constantly shifting is called perceptual constancy. Constancy is the tendency to perceive accurately the characteristics of objects (for example, size, shape, colour) across wide variations of presentation in terms of distance, orientation, lighting, and so on. That is, we perceive objects as having constant characteristics (such as size and shape), even when there are changes in the information about them that reaches our eyes (Wade and Swanston, 1991). Constancy is our tendency to perceive aspects of the environment as unchanging despite changes in the sensory input we receive from them. “Perceptual constancy” refers to the tendency to perceive objects as stable and permanent irrespective of the illumination on it, the position from which it is viewed or the distance at which it appears, despite the changing sensory images. Perceptual constancy refers to our ability to see things differently without having to reinterpret the object’s properties. In more simple words, the stability of the environment as we perceive it is termed perceptual constancy. Perception, therefore, allows us to go beyond the information

registered on our retinas. Perceptual constancy or object constancy or constancy phenomenon enables us to perceive an object as unchanging even though the stimuli we receive from it change, and so we can identify things regardless of the angle, distance, and illumination by which we view them. What happens is a process of mental reconstitution of the known image. Even though the retinal image of a receding automobile shrinks in size, the normal, experienced person perceives the size of the object to remain constant. Indeed, one of the most impressive features of perceiving is the tendency of objects to appear stable in the face of gross instability in stimulation. Though a dinner plate itself does not change, its image on the retina undergoes considerable changes in shape and size as the perceiver and plate move. Dimensions of visual experience that exhibit constancy include size, shape, brightness, and colour. For example, you recognise that small brown cat in the distance as your neighbour’s large golden retriever, so you aren’t surprised by the great increase in size (size constancy) or the appearance of the yellow colour (colour constancy) when she comes near you. And in spite of the changes in the appearance of the cat moving towards you from a distance, you still perceive the shape as that of a cat (shape constancy) no matter the angle from which it is viewed. Perceptual constancy tends to prevail over these dimensions as long as the observer has appropriate contextual cues.

4.12.1 Lightness Constancy An object’s perceived lightness stays the same, inspite of changes in the amount of light falling on it. A pair of black shoes continues to look black in the bright sun. The visual system acknowledges that black shoes are dark, relative to other lighter objects in the scene. White paper reflects 90 per cent of the light falling on it; black paper, only 10 per cent. In sunlight, the black paper may reflect 100 times more light than does the white paper indoors, but it still looks black (Mc Burney and Collings, 1984). This illustrates lightness constancy (also called brightness constancy); we perceive an object as having constant lightness even while its illumination varies. Lightness/Brightness constancy refers to our ability to recognise that colour remains the same regardless of how it looks under different levels of light. The principle of brightness constancy refers to the fact that we perceive

objects as constant in brightness and colour, even when they are viewed under different lighting conditions. That deep blue shirt you wore to the beach suddenly looks black when you walk indoors. Without colour constancy, we would be constantly re-interpreting colour and would be amazed at the miraculous conversion our clothes undertake. Perceived lightness depends on relative luminance—the amount of light an object reflects relative to its surroundings. If we view sunlit black paper through a narrow tube so nothing else is visible, it will look grey, because in bright sunshine it reflects a fair amount of light. If we view it without the tube and it is again black, because it reflects much less light than the object around it.

4.12.2 Size Constancy Size constancy refers to our ability to see objects as maintaining the same size even when our distance from them makes things appear larger or smaller. The principle of size constancy relates to the fact that the perceived size of the image it casts on the retina changes greatly. This holds true for all of our senses. Distant objects cast tiny images on our retina. Yet we perceive them as being of normal size. Size constancy is the tendency to perceive the vertical size of a familiar object despite differences in their distance (and consequent differences in the size of the pattern projected on the retina of the eye). Perception of size constancy depends on cues that allow one a valid assessment of his distance from the object. With distance accurately perceived, the apparent size of an object tends to remain remarkably stable, especially for highly familiar objects that have a standard size (see Figure 4.17).

Figure 4.17 Size constancy.

Size constancy leads us to perceive a car as large enough to carry people, even when we see its tiny image from away. This illustrates the close connection between an object’s perceived distance and perceived size. Perceiving an object’s distance gives us cues to its size. Likewise knowing its general size—that the object is, say a car—provides us with cues to its distance. The size of the representation or “image” of an object on the retina of the eye depends upon the distance of the object from the eye, the farther away it is, the smaller the representation. Size constancy relates to the fact that although the image of an object projected on the retinas of our eyes becomes smaller the more distant the object is, yet we know the real size of the object from experience and scale-up the perceived size of the object to take this into account. It means that an object’s perceived size stays the same, even though the distance changes between the viewer and the object. The objects are perceived in their original size irrespective of their retinal image. The sensory images may change but the object perceived is constant. Usually, we tend to see objects as its usual measurable size regardless of distance. Size constancy depends partly on the experience and partly on distant ones. Size constancy is fairly well developed in 6-month infants (Cruikshank, 1941). One factor that contributes to size constancy is that we are familiar with an object’s customary size. Another explanation for size constancy is that we unconsciously take distance into account when we see an object (Rock, 1983). An important American theorist James Jerome Gibson (1959) argued that perception is much more direct. We do not need to perform any calculations —conscious or unconscious—because the environment is rich with information. The way we perceive size is determined jointly by the retinal size of an object, and what can be called the egocentric distance between the observer’s eyes and the object, that is to say the distance as it appears to the individual observer (Wade and Swanston, 1991). The size of the after-image will vary proportionally with the distance from the eyes. That is, if the distance between the eye and the first after-image was 20 cm, and the distance between the eye and the wall was 100 cm, the second after-image will be five times the size of the first. This is a demonstration of Emmert’s Law. The perceived size is related to the retinal size and the

egocentric distance. Research strongly suggests that size constancy is learned rather than innate. Most infants seem to master this perceptual process by six months of age (Yonas et al. 1982). In a classic study, A.H. Holway and Edwin Boring (1941) found that subjects were able to make extremely accurate judgments of the size of a circle located at varying distances from their eyes, under conditions that were rich with distance cues. An experiment conducted by Bernice Rogowitz (1984) demonstrated that illumination is important in determining some types of perceptual constancy. Under conditions where there is no constant illumination, size constancy breaks down dramatically. Psychologists have proposed several explanations for the phenomenon of size constancy. Two factors seem to account for this tendency: size-distance invariance and relative size. First, people learn the general size of objects through experience and use this knowledge to help judge size. For example, we know that insects are smaller than people and that people are smaller than elephants. In addition, people take distance into consideration when judging the size of an object. Thus, if two objects have the same retinal image size, the object that seems farther away will be judged as larger. Even infants seem to possess size constancy. The principle of size-distance invariance suggests that when estimating the size of an object, we take into account both the size of the image it casts on our retina and the apparent distance of the object (see Figure 4.17). Another explanation for size constancy involves the relative sizes of objects. According to this explanation, we see objects as the same size at different distances because they stay the same size relative to surrounding objects. For example, as we drive toward a stop sign, the retinal image sizes of the stop sign relative to a nearby tree remain constant—both images grow larger at the same rate. The experience of constancy may break down under extreme conditions. If distance is sufficiently great, for example, the perceived size of objects will decrease; thus, viewed from an airplane in flight, there seem to be “toy” houses, cars, and people below.

4.12.3 Shape Constancy Another element of perceptual constancy is shape constancy. Sometimes an object whose actual shape cannot change seems to change shape with the

angle of our view. Because of shape constancy, we perceive the form or shape of objects as constant even while our retinal images of them change. Everybody has seen a plate shaped in the form of a circle. When we see that same plate from an angle, however, it looks more like an eclipse. Shape constancy allows us to perceive that plate as still being a circle even though the angle from which we view it appears to distort the shape. Objects project different shapes on our retinas according to the angle from which they are viewed. “Shape constancy” means that an object’s perceived shape stays the same, despite changes in its orientation toward the viewer. We continue to perceive objects as having a constant shape, even though the shape of the retinal image changes when our point of view or angle changes. “Shape constancy” refers to the fact that despite of the large variations in shape of representation of images of an object on the retina when it is near or far, we tend to perceive the object as of the same shape. The principle of shape constancy refers to the fact that the perceived shape of an object does not alter as the image it casts on the retina changes. It is the tendency to perceive the shape of a rigid object as constant despite differences in the viewing angle (and consequent differences in the shape of the pattern projected on the retina of the eye). Familiar objects are usually seen as having constant shape. A compact disc (cd) does not distort itself into an oval when we view it from an angle; we know it remains round. When we look at objects from different angles, the shape of the image projected to our retinas is different at each instance. Nevertheless, we perceive the object as unchanged. For example, when we view a door from straight on, it appears rectangular in shape. When the door is opened, we still perceive it as rectangular despite the fact that the image projected on our retinas is trapezoidal (see Figure 4.18).

Figure 4.18 Shape constancy.

The previous experience or memory is an important factor in the determination of shape constancy. Shape constancy is due to the angle of the object and the position of the perceiver. Shape constancy is even stronger when shapes appear in the context of meaningful clutter—such as a messy office desk—rather than when the shapes are shown against a clean background (Lappin and Preble, 1975). Thus, the constancy in perception occurs because of our learning, past experience, and previous knowledge of the various objects even if the object is perceived under changed conditions. Psychologists suggest that perceptual constancies are based largely on mechanism that operates below conscious awareness. When we know the true size, shape, colour or brightness of an object, we make unconscious inferences to adjust for changes in the object’s appearance under varying conditions.

4.13 ILLUSIONS—TYPES, CAUSES, AND THEORIES Though perception helps us to adapt to a complex and ever changing environment, it sometimes leads us into error. Perception can also, however, provide false interpretations of sensory information. Such cases are known as illusions, a term used by psychologists to refer to incorrect perceptions. An illusion is a false or wrong perception, in that it differs from the actual state of the perceived object. It is a misinterpretation of the correct meaning of perception. According to Crooks and Stein (1991), “An illusion is a false perception in that it differs from actual physical state of the perceived object.” An illusion is not a trick or a misperception; it is a perception. We call it an illusion simply because it does not agree with our other perceptions. Illusions demonstrate that what we perceive often depends on processes that go far beyond the raw material of the sensory input. Under illusion discrepancies between reality and perception which occur as a result of normal sensory functioning and which are as yet unexplained. Illusion is a distortion of a sensory perception revealing how the brain normally organises and interprets sensory stimulation. Each of the human senses can be deceived by illusions, but visual illusions are the most well known. While illusions distort reality, they are generally shared by most people.

Illusions may occur with more of the human senses than vision, but visual illusions, optical illusions, are the most well known and understood. The emphasis on visual illusions occur because vision often dominates the other senses. For example, individuals watching a ventriloquist will perceive the voice is coming from the dummy since they are able to see the dummy mouth the words. Some illusions are based on general assumptions the brain makes during perception. These assumptions are made using organisational principles, like Gestalt, an individual’s ability of depth perception and motion perception, and perceptual constancy. Other illusions occur because of biological sensory structures within the human body or conditions outside of the body within one’s physical environment. Unlike a hallucination, which is a distortion in the absence of a stimulus, an illusion describes a misinterpretation of a true sensation. For example, hearing voices regardless of the environment would be a hallucination, whereas hearing voices in the sound of running water (or other auditory source) would be an illusion. Illusions are perceptions that are contradictory to the physical arrangements of the stimulus situation. Illusions may be regarded as occupying the opposite end of a continuum from perceptual constancy. Whereas “constancy” produces accurate perception inspite of various transformations of reality in the sense organ, an “illusion” is produced by perceptual processes inspite of truthful representations of reality in the sense organ. Perception is not a passive reflection of sensations received, but an active process of testing hypotheses. Sometimes the data received is ambiguous or atleast the brain conceives it to be so, so that the interpretation is erroneous or an illusion. When illusion is limited to a specific person, we call it individual illusion. For example, all persons do not perceive the rope as snake in dark. The experience of universal illusions is same for most of individuals, for example, geometrical illusions. Some evidence suggests that illusions have multiple causes (Schiffman, 1990). However, one explanation is provided by the theory of misapplied constancy. This theory suggest that when looking at illusions, we interpret certain cues as suggesting that some parts are farther away than others. Our powerful tendency towards size constancy then comes into play, with the

result that we perceptually distort the length of various lines (see Figure 4.20). Learning also plays an important role in illusions. Moreover, learning seems to affect the extent to which our perception is influenced by illusions.

4.13.1 Types of Illusions Illusions are of different types as explained in the following:

Optical illusions An optical illusion is always characterised by visually perceived images that, at least in common sense terms, are deceptive or misleading. Therefore, the information gathered by the eye is processed by the brain to give, on the face of it, a percept that does not tally with a physical measurement of the stimulus source. A conventional assumption is that there are physiological illusions that occur naturally and cognitive illusions that can be demonstrated by specific visual tricks that say something more basic about how human perceptual systems work. The human brain constructs a world inside our head based on what it samples from the surrounding environment. However, sometimes it tries to organise this information it thinks best while other times it fills in the gaps. This way in which our brain works is the basis of an illusion. (i) Vertical–Horizontal illusion: Although the horizontal-vertical lines are equal in length still, the vertical line appears to be longer (see Figure 4.19). The vertical-horizontal illusion is the tendency for observers to overestimate the length of a vertical line relative to a horizontal line of the same length (Robinson, 1998). This even happens if people are aware of this. Cross-cultural differences in susceptibility to the vertical–horizontal illusion have been noted, with Western people showing more susceptibility. Also, people living in open landscapes are more susceptible to it (Shiraev and Levy, 2007).

Figure 4.19 The Vertical–Horizontal illusion.

One explanation of this illusion is that the visual field is elongated in the horizontal direction, and that the vertical-horizontal illusion is a kind of framing effect (Kunnapas, 1957). Since the monocular visual field is less asymmetric than the combined visual field, this theory predicts that the illusion should be reduced with monocular presentation. This prediction was tested in five experiments, in which the vertical– horizontal illusion was examined in a variety of situations—including observers seated upright versus reclined 90 degrees, monocular presentation with the dominant versus the nondominant eye, viewing in the dark versus in the light, and viewing with asymmetrical frames of reference. The illusion was reliably reduced with monocular presentation under conditions that affected the asymmetry of the phenomenal visual field. (ii) Muller-Lyre illusion or the arrowhead illusion: Perhaps the most famous, most studied and widely analysed visual illusion is the arrowhead illusion, first described by Franz Muller-Lyre in 1889 (Figure 4.20).

Figure 4.20 The Muller-Lyre illusion.

Muller-Lyre illusion is an illusion of extent or distance. The two lines (AB and CD) in the Muller-Lyre illusion are of the same length but the line at the bottom with its reversed arrow heads (CD) looks longer. The lengths of the two lines AB and CD appear to be different but are the same. If the arrows point outward, we perceive the line connecting them as relatively near. On the other hand, the line connecting the inwardpointing arrowheads is perceived as distant. Size constancy mechanism goes to work to “magnify” the length of the distant-appearing line, but since the lines are of the same constancy is “misplaced” and the illusion results (Gregory, 1978). According to popular interpretation, the illusion is created by the fact that the outward-turned angles draw the viewer’s eyes farther out into space, the inward-turning angles draw the eyes back toward the centre.

A British psychologist R.L. Gregory (1978) proposed that the MullerLyre illusion is the result of size constancy scaling. Size constancy scaling is a perceptual process in which knowledge of the size of objects may modify the apparent retinal size of them at different distances. An object at a distance may thus appear larger than its retinal size. The brain, therefore, uses size constancy and scales up C-D to be longer than A-B. Gregory’s theory is supported by research demonstrating that the Muller-Lyre illusion is either very weak or absent in cultures (Zulus of South east Africa) in which people have little exposure to angles (Segall et al., 1966). (iii) Moon illusion: Moon illusion is an illusion of shape or area. Whether the moon is high in the sky or on the horizon, its representation on the retina is of the same size, but it is perceived as much larger or bigger on the horizon, about 30 per cent bigger (see Figure 4.21). One explanation of this illusion says that when the moon is near the horizon, buildings and trees provide depth cues indicating that the moon is indeed far away; farther up in the sky, these cues are absent.

Figure 4.21 Moon illusion.

There is no widely accepted theory of the moon illusion (Reed, 1984; Rock and Kaufman, 1972), but it is partly based on the misperception of depth. This illusion seems to result from size constancy. When the moon is low, it appears to be farther away than when it is overhead. The moon looks up to 50 per cent larger near the horizon than when high in the sky. The interplay between perceived size and perceived distance helps explain several well-known illusions. For atleast 22 centuries, scholars have wondered and have argued about reasons for the moon illusion (Hershenson, 1989). One reason is that cues to object’s distances at the

horizon make the moon behind them seem farther away than the moon high in the night sky (Kaufman and Kaufman, 2000). Thus, the horizon moon seems larger and the same explanation is true for the distant bar in the Ponzo illusion. This illusion occurs, in part because when the moon is near the horizon, we can see that it is farther away than trees, houses, and other objects. When it is overhead at its zenith, such cues are lacking. Thus, the moon appears larger near the horizon because there are cues available that cause us to perceive that it is very far away. Once again, our tendency towards size constancy leads us astray. (iv) Ponzo illusion: The Ponzo illusion was first described by Mario Ponzo in 1913. The line A-B in this illusion appears to be longer than C-D (see Figures 4.22 and 4.23). In the railway tracks, for example, even though the two horizontal bars are of the same length, we perceive the upper one (A-B) as longer than the lower one (C-D). This illusion is said to work because the railway tracks converging in the distance provide a strong cue for depth-linear perspective. The linear perspective dictates that A-B must be farther away than C-D and so should be shorter. Thus, we receive information that the upper bar is farther away than the lower one. But sensory data received shows the lines to be the same length. A-B is thus perceived as longer as a result of size constancy scaling.

Figure 4.22 The Ponzo illusion I.

Figure 4.23 The Ponzo illusion II.

(v) The Ebbinghaus illusion or Titchener circles: The circles illusion illustrates (Figure 4.24) well the effect of context upon perception. The

Ebbinghaus illusion or Titchener circles is an optical illusion of relative size perception. In the best-known version of the illusion, two circles of identical size are placed near to each other and one is surrounded by large circles while the other is surrounded by small circles; the first central circle then appears smaller than the second central circle.

Figure 4.24 The circles illusion.

It was named for its discoverer, the German psychologist Hermann Ebbinghaus (1850-1909), and after it was popularised in England by Titchener in a 1901 textbook of experimental psychology, and hence its alternative name Titchener circles (Roberts, Harris, Yates, 2005). The context of the outer circles, larger in one case, smaller in the other, leads us to exaggerate the size of the centre in A and reduce the size of the centre circle in B, although infact they are of the same size (see Figure 4.24). Although commonly thought of as an illusion of size, recent work suggests that the critical factor in the illusion is the distance of the surrounding circles and the completeness of the annulus, making the illusion a variation of the Delboeuf’s illusion. If the surrounding circles are near the central circle it appears larger, while if they are far away it appears smaller. Obviously, the size of the surrounding circles dictates how near they can be to the central circle, resulting in many studies confounding the two variables (Roberts, Harris, Yates, 2005). The Ebbinghaus illusion has played a crucial role in the recent debate over the existence of separate pathways in the brain for perception and action (for more details see Two Streams hypothesis). It has been argued that the Ebbinghaus illusion distorts perception of size, but when a subject is required to respond with an action, such as grasping, no size distortion occurs (Goodale and Milner, 1992). However, a recent work of Franz, Scharnowski and Gegenfurtner, 2005 suggests that the original

experiments were flawed. The original stimuli limited the possibility for error in the grasping action, therefore making the grasp response more accurate, and presented the large and small versions of the stimulus in isolation—which results in no illusion because there is no second central circle to act as a reference. Franz et al. conclude that both the action and perception systems are equally fooled by the Ebbinghaus illusion. (vi) The Poggendorff illusion: This illusion was discovered in 1860 by physicist and scholar J.C. Poggendorff, editor of Annalen der Physik und Chemie, after receiving a letter from astronomer F. Zollner. In his letter, Zollner described an illusion he noticed on a fabric design in which parallel lines intersected by a pattern of short diagonal lines appear to diverge (Zollner’s illusion). Whilst pondering this illusion, Poggendorff noticed and described another illusion resulting from the apparent misalignment of a diagonal line; an illusion which today bears his name. The diagonal lines do infact intersect the two vertical lines, though the left line appears higher than the right. In this illusion, there are two parallel lines which are overlapped by two separate vertical lines, but they appear to be cut through a single continued line (see Figure 4.25).

Figure 4.25 The Poggendorff illusion.

(vii) The Ames room illusion: An Ames room is a distorted room (shown in Figure 4.26) that is used to create an optical illusion. Probably influenced by the writings of Hermann Helmholtz, it was invented by American ophthalmologist Adelbert Ames, Jr. in 1934, and constructed in the following year. An Ames room is constructed so that from the front, it appears to be an ordinary cubic-shaped room, with a back wall and two side walls parallel to each other and perpendicular to the horizontally level floor and ceiling. However, this is a trick of perspective and the true shape of the room is trapezoidal: the walls are

slanted and the ceiling and floor are at an incline, and the right corner is much closer to the front-positioned observer than the left corner (or vice versa). In the Ames room illusion, two people standing in a room appear to be of dramatically different sizes, even though they are of the same size. As a result of the optical illusion, a person standing in one corner appears to the observer to be a giant, while a person standing in the other corner appears to be a dwarf. The illusion is convincing enough that a person walking back and forth from the left corner to the right corner appears to grow or shrink.

Figure 4.26 The Ames room illusion.

(viii) The Zollner illusion: Although all nine the lines are parallel but these do not look parallel because of the curved lines on them (see Figure 4.27).

Figure 4.27 The Zollner illusion.

Lines that appear to pass behind solid objects at an angle appear to be “moved over” when they emerge. (ix) Hering illusion: This is an illusion of direction. The Hering illusion is an optical illusion discovered by the German physiologist Ewald Hering in 1861. The two vertical lines are both straight, but they look as if they

were bowing outwards (see Figure 4.28). The distortion is produced by the lined pattern on the background that simulates a perspective design, and creates a false impression of depth. The Orbison illusion is one of its variants, while the Wundt illusion produces a similar, but inverted effect.

Figure 4.28 The Hering illusion.

In this illusion, two straight lines run in parallel. However, the intersecting radial lines change the appearance of these parallel, straight lines. In this illusion, both the vertical lines are although parallel, appear to be curved. The Hering illusion looks like cat spokes around a central point, with straightlines on both sides of this central, so-called going away point. The illusion tricks us into thinking we are moving forward. Since we aren’t actually moving and the figure is static, we misperceive the straight lines as curved ones. However, when one squints, the red lines are correctly perceived as straight. (x) Orbison’s illusion: An Orbison illusion is an optical illusion where straight lines appear distorted (see Figure 4.29). There are several variants of the Orbison illusion. The illusion is similar to both the Hering and Wundt illusions. Although the Orbison illusion and other similar illusions have not been completely explained, they have stimulated much valuable research into human perceptual processes. They have also been utilised by artists to bring about entertaining and impressive effects in their works. The outer rectangle (really) and the

square appear distorted. A circle would also appear distorted.

Figure 4.29 The Orbison’s illusion.

Orbison explained these illusions with the theory that fields of force were created in the perception of the background patterns. Any line that intersected these fields would be subsequently distorted in a predictable way. This theory, in the eyes of modern science, does not have much validity (Robinson, 1998). It is still unclear exactly what causes the figures to appear distorted. Theories involving the processing of angles by the brain have been suggested. Interactions between the neurons in the visual system may cause the perception of a distorted figure (Sara Bolouki and Roger Grosse, 2007). Other theories suggest that the background gives an impression of perspective. As a result, the brain sees the shape of the figure as distorted. (xi) Parallelogram illusion: Diagonals a and b are of equal length though they appear the contrary (see Figure 4.30). This optical illusion is known as the Sander illusion, or Sander parallelogram. While one of the lines appears to be longer than the other, they are in fact both exactly the same length (see Figure 4.30).

Figure 4.30 The Parallelogram illusion.

(xii) Delboeuf’s illusion: In Figure 4.31, there are four circles. The outer circle on the left, and the inner circle on the right are of the same size, but the right one appears larger.

Figure 4.31 Delboeuf’s illusion.

Illusions are not limited to visual processes. Indeed, there are numerous examples for our other sensory modalities, including touch and audition (Sekuler and Blake, 1990; Shepard, 1964).

Auditory illusions An auditory illusion is an illusion of hearing, the sound equivalent of an optical illusion: the listener hears either sounds which are not present in the stimulus, or “impossible” sounds. In short, audio illusions highlight areas where the human ear and brain, as organic, makeshift tools, differ from perfect audio receptors (for better or for worse). One of example of an auditory illusion is a Shepard tone.

Tactile illusions Examples of tactile illusions include phantom limb, the thermal grill illusion, the cutaneous rabbit illusion and a curious illusion that occurs when the crossed index and middle fingers are run along the bridge of the nose with one finger on each side, resulting in the perception of two separate noses. Interestingly, the brain areas activated during illusory tactile perception are similar to those activated during actual tactile stimulation. Tactile illusions can also be elicited through haptic technology. These “illusory” tactile objects can be used to create “virtual objects”.

Other senses Illusions can occur with the other senses including that of taste and smell. It was discovered that even if some portion of the taste receptor on the tongue became damaged that illusory taste could be produced by tactile stimulation. Evidence of olfactory (smell) illusions occurred when positive or negative

verbal labels were given prior to olfactory stimulation. Some illusions occur as result of an illness or a disorder. While these types of illusions are not shared with everyone they are typical of each condition. For example, migraine sufferers often report Fortification illusions.

QUESTIONS Section A Answer the following in five lines or in 50 words: 1. 2. 3. 4. 5. 6. 7. 8. 9. 10. 11.

12. 13. 14. 15. 16. 17. 18.

Define perception* Cocktail party phenomenon* Binocular perception of depth Autokinetic movement* Differentiate between monocular and binocular cues Geometrical illusions Binocular cues Illusion Muller-Lyer illusion Figure and ground* Personal needs, values and perception or Role of motivation in perception Induced movement Apparent motion Selective perception Monocular cues* Contour Role of past experience in perception Phi phenomenon

Section B Answer the following questions up to two pages or in 500 words:

1. Discuss factors that contribute to the establishment of set. Which of them are external, which internal to the individual? 2. List the Gestalt principles of perceptual organisation. 3. Differentiate between ‘Figure’ and ‘Background’ in figure-ground theory of perception. 4. What is perceptual constancy? Discuss with example. 5. ‘Perception is a selective process’. Discuss. 6. Discuss laws of perceptual organisation. 7. Explain perceptual constancies. 8. What are the various factors affecting perception? 9. What are the various causes of illusions? 10. What is perception? Elaborate on space perception. 11. Write short notes on the following: (i) Monocular and binocular perception of depth (ii) Figure and ground perception (iii) Social factors affecting perception. 12. Elaborate on movement perception. 13. Bring out the principles of perceptual grouping and also list out the factors affecting perception. 14. Explain, in detail, the phenomena of constancy in light of brightness and lightness. 15. Illusions are false perceptions. Discuss. 16. Give a brief idea about the perception of depth and distance. 17. Why is selective attention important? 18. What role do the Gestalt principles play in perceptual processes? 19. What are illusions? 20. Differentiate between: (i) Figure and ground (ii) Shape and size constancy.

Section C Answer the following questions up to five pages or in 1000 words: 1. What is perception? Discuss the fundamental characteristics of

2. 3. 4. 5. 6. 7. 8. 9. 10. 11. 12. 13. 14. 15. 16. 17. 18.

perception. Discuss briefly how perception develops. Critically examine the role of organisation in perception. Define illusions and give its different theories. Write a detailed note on movement perception. How do we perceive space? Explain monocular and binocular cues in space perception. Explain in detail perception of form. Discuss the factors affecting perception. Illustrate your answer with examples. With the help of experimental evidence, highlight perception of movement. A perception is nothing more than a sensation. Evaluate this statement in the light of Gestalt theory of ‘Laws of Perception’. What is movement perception? What are the different theories of movement perception? What is perceptual constancy? Analyse the various forms of perceptual constancy. What are perceptual constancies? How are we able to judge depth and distance? What do you understand by errors in perception? Explain some geometrical illusions. Describe the various principles of perceptual organisation. Explain the following: (i) Closure (ii) Role of culture in perception (iii) Phi phenomenon (iv) Muller-Lyre illusion (v) Role of past experience in perception (vi) Moon illusion.

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5 Statistics INTRODUCTION Statistics has been used very widely in Psychology and education, too, for example, in the scaling of mental tests and other psychological data, for measuring the reliability and validity of test scores, for determining the Intelligence Quotient (IQ), in item analysis and factor analysis. The numerous applications of statistical data and statistical theories have given rise to a new field or discipline, called “Psychometry”. Statistics are a flexible tool and can be used for many different purposes. In Psychology, however, statistics are usually employed or used to accomplish one or more of the following objectives or tasks: 1. Summarising or systematising or describing large amounts of data. 2. Comparing individuals or groups of individuals in various ways. 3. Determining whether certain aspects of behaviour are related. (Whether they vary together in a systematic manner); and 4. Predicting future behaviour from current information.

5.1 NORMAL PROBABILITY CURVE (NPC) OR NORMAL CURVE OR NORMAL DISTRIBUTION CURVE OR BELL CURVE The normal curve was developed mathematically in 1733 by Abraham De Moivre (26 May, 1667–27 November, 1754) as an approximation to the

binomial distribution. His paper was not discovered until 1924.

Abraham De Moivre

Marquis De Laplace used the normal curve in 1783 to describe the distribution of errors. Although Carl Friederich Gauss was the first to suggest the normal distribution law, the merit of the contributions of Laplace cannot be underestimated. It was Laplace who first posed the problem of aggregating several observations in 1774, although his own solution led to the Laplacian distribution. It was Laplace who first calculated the value of the integral in 1782, providing the normalisation constant for the normal distribution. Finally, it was Laplace who in 1810 proved and presented to the Academy the fundamental central limit theorem, which emphasised the theoretical importance of the normal distribution. Laplace proved the central limit theorem in 1810, consolidating the importance of the normal distribution in statistics.

Marquis De Laplace

Subsequently, Carl Friederich Gauss used the normal curve to analyse astronomical data and determine the formula for its probability density function. He invented the normal distribution in 1809 as a way to rationalise

the method of least squares. The normal curve thus came to be called the Gaussian distribution. However, Gauss was not the first to study this distribution or the formula for its density function—which had been done earlier by Abraham De Moivre.

Carl Friederich Gauss

Since its introduction, the normal distribution has been known by many different names: the law of error, the law of facility of errors, Laplace’s second law, Gaussian law, and so on. By the end of the 19th century some authors started occasionally using the name normal distribution, where the word “normal” is used as an adjective, the term being derived from the fact that this distribution was seen as typical, common, and normal. Around the turn of the 20th century Pearson popularised the term normal as a designation for this distribution. The term bell-shaped curve is often used in everyday usage. The simplest case of a normal distribution is known as the standard normal distribution, described by the probability density function. It is known as a normal random variable, and its probability distribution is the normal distribution. The Gaussian distribution with m (mean) = 0 and s2 (variance) = 1 is called the standard normal distribution. The term “standard normal” which denotes the normal distribution with zero mean and unit variance came into general use around 1950s, appearing in the popular textbooks by P.G. Hoel (1947) Introduction to mathematical statistics and A.M. Mood (1950) Introduction to the theory of statistics. The Normal Probability Curve or Normal Distribution Curve is the ideal, symmetrical, bell-shaped frequency curve. It is supposed to be based on data of population. In it, the measures or frequencies are concentrated or clustered closely around the centre and taper off (become gradually less)

from this central point from top to the left and the right. There are very few measures or frequencies at the low score end of the scale, number increasing upto a maximum at the middle position and a symmetrical falling off towards the high score end of the scale. The curve exhibits almost perfect bilateral (having two sides) symmetry. It is symmetrical about the central altitude. This altitude divides it into two parts which will be similar in shape and equal in area (see Figure 5.1). This general tendency of quantitative data for a large number of measurements gives rise to the symmetrical bell-shaped form of a normal curve. It is very useful in psychological and educational measures.

Figure 5.1 Normal Probability Curve.

Intelligence measured by standard tests, educational test scores in spelling, mathematics, and reading and measures of height and weights for a large group of students are examples of psychological measurements which can be usually represented by normal distribution or curve. The normal distribution can be completely specified by two parameters: Mean Standard deviation

5.1.1 Basic Principles of Normal Probability Curve (NPC) The concept of Normal Probability Curve or NPC or Normal Curve or Normal Distribution was originally developed in a mathematical treatise by De Moivre in 1713. The “probability” (or possibility or occurrence or likelihood) of a given event is defined as the expected frequency of occurrence of this event among events of the same type. This expected frequency of occurrence is based upon knowledge of conditions determining the occurrence of the phenomena as in coin tossing, picking of a card out of a packet of playing cards, tick marking, and alternative out of a given number of alternatives or on the case of dice throwing. The probability of an event may be stated mathematically as a ratio. The probability of an unbiased coin falling heads is 1/2, and the probability of tick marking any alternative answers is 1/4, and the probability of dice showing a two-spot or dots is 1/6. These ratios called probability ratios, are defined by that fraction, the numerator of which equals the desired outcome or outcomes (probability) and the denominator of which equals the total possible outcomes. More simply put, the probability of the appearance of any face on a 6-faced cube, for example is 1/6 or the

A probability ratio always falls between the limits 0.00 (impossibility or no possibility or probability of occurrence) and 1.00 (certainty of occurrence or possibility or probability). Between these limits are all possible degrees of likelihood which may be expressed by appropriate ratios. Simple principles of probability can be better understood by the tossing of coin. For example, if we toss one coin, obviously it must fall either heads (H) or tails (T) 100% of the time. Since there are only two possible outcomes in a given throw, a head or a tail is equally probable. Expressed as a ratio, therefore, the probability of H is ; and T is ; and (H + T) = + = 1.00. While tossing two coins (a & b), there are the following four possible arrangements: (1)...........(2)...........(3)...........(4) a b...........a b...........a b...........a b H H.........H T..........T H..........T T

Probability of 2 heads (HH) Probability of 2 tails (TT) Probability of HT combination Probability of TH combination Probability =

+

The sum of our probability ratios is

+

+ or 1.00.

While tossing three coins (a, b, and c), there are the following eight possible outcomes: (1)..........(2)..........(3)..........(4)..........(5)..........(6)..........(7)..........(8) a b c......a b c.......a b c.......a b c......a b c.....a b c......a b c........a b c HHH.......HHT.......HTH.......THH.......HTT.......THT.......TTH .... TTT Probability of 3 heads (combination 1) Probability of 2 heads and 1 tail (combination 2, 3, 4)

Probability of 1 head and 2 tails (combination 5, 6, 7)

Probability of 3 tails (combination 8) The sum of these probability ratios = = Probability = 1.00 Normal distribution is probably one of the most important and widely used continuous distribution. In probability theory and statistics, Gaussian distribution is an absolutely continuous probability distribution with zero

cumulants of all orders higher than two. The normal distribution is the most used statistical distribution. The principal reasons for this are: (i) Normality arises naturally in many physical, biological, and social measurements. (ii) Normality is important in statistical inference.

5.1.2 Properties or Characteristics of the Normal Probability Curve (NPC) Following are the characteristics or properties of normal distribution or NPC: (i) Bell shaped curve: It is bell shaped and is symmetrical about its mean. (ii) Symmetric: The curve is symmetrical about a vertical axis through the mean, that is if we fold the curve along this vertical axis, the two halves of the curve would coincide. In the normal curve, the mean, the median, and the mode all coincide and there is perfect balance between the right and left halves of the figure. (iii) Unimodal: It is unimodal, that is, values mound up only in the centre of the curve. As a result of symmetry, the three measures of central tendency that is the mean, the median, and the mode of the distribution are identical. Mean, median, and mode, in an NPC fall at the same point. (iv) It is equally divided into two halves or parts, the perpendicular (vertical, upright, at an angle of 90° to a line or surface) drawn from the highest point, and the figure exhibits or displays perfect bilateral symmetry. (v) The height or altitude of the curve declines symmetrically in either direction (high-score end and low-score end) from the maximum point. (vi) It is a continuous distribution. (vii) The normal curve is asymptotic to the axis, that is, it extends indefinitely in either direction from the mean. It approaches the horizontal axis asymptotically, that is the curve continues to decrease in height on both ends away from the mean but never touches the horizontal axis. Bell curve extends to +/– infinity. (viii) The total area under the normal curve and above the horizontal axis is 1.0000 or 1.0 or 1, which is essential for a probability distribution or

curve. Area under the bell curve = 1. (xi) Total area under the curve sums to 1, that is, the area of the distribution on each side of the mean is 0.5 (0.5 to the left of the mean and 0.5 to the right). (x) It is a family of curves, that is, every unique pair of mean and standard deviation defines a different normal distribution. Thus, the normal distribution is completely described by two parameters: mean and standard deviation. (xi) In the NPC, the mean, the median, and the mode all fall exactly at the mid-point of the distribution and are numerically or mathematically (in value) equal. Since the normal curve is bilaterally symmetrical, all of the measures of central tendency that is the mean, the median, and the mode must coincide at the centre of the distribution. (xii) The probability that a random variable will have a value between any two points is equal to the area under the curve between those points. The measures of variability include certain constant fractions of the total area of the normal curve. Between the mean and 1s of the distribution lie the middle two-thirds (68.26% exactly) of the cases in the normal distribution. Between the mean and 2s are found 95.44%, and between the mean and 3s are found 99.74% or very close to 100% of the distribution. There are about 68.26 chances in 100 that a case will lie within 1s from the mean in the normal distribution; there are 95.44 chances in 100 that the case will lie within 2s from the mean; and 99.74 chances in 100 that the case will lie within 3s from the mean (see Figure 5.2). 68 chances in 100 1s 95 chances in 100 2s 99.7 chances in 100 3s

Figure 5.2 Areas of Normal Probability Curve.

(xiii) Since there is only one maximum point in the curve, the normal curve is unimodal, that is, it has only one mode. (xiv) Since the shape of the normal curve is completely determined with its parameters m (Mean) and s (Standard Deviation), the area under the curve bounded by the two ordinates also depends on these parameters. Some important areas under the curve bounded by the ordinates at s (1s) 2s, and 3s distances away from mean in either direction. That is, (a) the area between ordinates at X = m – s and X = m + s is 0.6826 or 68.26% of cases or chances. (b) the area between ordinates at X = m – 2s and X = m + 2s is 0.9544 or 95.44% of cases or chances. (c) the area between ordinates at X = m – 3s and X = m + 3s is 0.9974, that is the area under the Normal Curve beyond these ordinates is only 1 – 0.9974 (or 1.0000 – 0.9974) = 0.0026, which is very small (half of it that is 0.00134 above + 3s and 0.0013 below –3s). Thus, practically the whole area under the Normal Curve lies within limits m 3s (mean and 3s0 which is also called 3-sigma limits). 1s 0.6826 or 68.26% of cases or chances 2s 0.9544 or 95.44% of cases or chances 3s 0.9974 or 99.74% of cases or chances (xv) The standard deviation determines the width of the curve: larger values result in wider, flatter curves. (xvi) Probabilities for the normal random variable are given by areas under the curve.

(xvii) 68.26% of values of a normal random variable are within +/–1 standard deviation of its mean. 95.44% of values of a normal random variable are within +/–2 standard deviations of its mean. 99.72% of values of a normal random variable are within +/–3 standard deviations of its mean (see Figure 5.2).

5.1.3 Causes of Divergence from Normality It is often important to know as to why the frequency distribution deviates so largely from normality. The causes of divergence like skewness and kurtosis are numerous and often complex. But a careful analysis of the data may enable us to set some hypothesis concerning non-normality which may be later proved or disproved. (i) Un-representative or biased sampling may be one of the common causes of a-symmetry. (ii) Selection of the sample is also an important cause of skewness. One should hardly expect the distribution of scores obtained from a group of brilliant students of an age group to be normal nor one would look for symmetry in the distribution of scores got from a special class of dull 10 year olds even though the group is large. Neither of these groups is an unbiased selection. They are un-representative of a normal population of the representative age group. (iii) Scores obtained from small and homogeneous groups are likely to yield lepto-kurtic distribution (more peaked than normal curve) while scores from large heterogeneous groups are more likely to be platykurtic (flatter than the normal curve). (vi) The use of unsuitable or poorly made test will also not result into a normal distribution. If a test is too easy, scores will pile up at the high score end of the distribution, while if the test is too difficult, the scores will pile-up at the low end. It is also probable in case of too difficult or too easy test that the distributions will be somewhat peaked than the normal. In this skewness or kurtosis or both may also appear owing to a real lack of normality in the trait being measured. (v) The data will not remain normal when some of the hypothetical factors determining performance in a trait are dominant over others and hence are (skewness and kurtosis) present more often than chance will allow.

(vi) Difference in the size of the units in which trait has been measures will also lead to skewness. Thus, if the test items are very easy at the beginning and very difficult later on, the effect of such unusual units is the same as that encountered when the test is too easy. Scores tend to pile-up towards the high-end of the scale and are stretched out or skewed towards the low-end. There are many other minor errors in the administration and scoring of a test such as its timings or giving of instructions, errors in the use of scoring keys, large differences in practice or in motivation among the subjects. These factors will certainly cause many students to score high or low than they normally would and consequently cause skewness in the distribution.

5.1.4 Measuring Divergence from Normality Divergence from normality may be measured by the following methods:

Skewness In the normal curve model, the mean, the median, and the mode all coincide and there is perfect balance between the right and left halves of the figure. As we know, a distribution is said to be “skewed” when the mean and the median fall at different points in the distribution, and the balance (or centre of gravity) is shifted to one side or the other—to the right or the left. In a normal distribution, the mean equals the median exactly and the skewness is of course, zero. The more nearly the distribution approaches the normal form, the closer together are the mean and median, and the less the skewness (see Figure 5.3).

Figure 5.3 Skewness.

Distributions are skewed positively or to the right when scores are massed at the low (or left) end of the scale, and are spread out gradually toward the high or right end. In a positively skewed curve, the mean lies to the right of the median. A negligible degree of positive skewness shows how closely the

distribution approaches the normal form. Distributions are said to be skewed negatively or to the left when scores are massed at the high-end of the scale (the right end) and are spread out more gradually toward the low-end (or left). In a negatively skewed curve, the mean lies to the left of the median. Mean is pulled more toward the skewed end of the distribution than the median. The greater is the gap between mean and median, the greater the skewness. A useful index of skewness is given by the formula:

where s stands for Standard Deviation A simple measure of skewness in terms of percentiles is:

Kurtosis The term “kurtosis” refers to the “peakedness” or flatness of a frequency distribution as compared with the normal. Kurtosis is the degree of peakedness of a distribution. A frequency distribution as compared with the normal or Mesokurtic. A normal distribution is a Mesokurtic distribution. A frequency distribution more peaked than the normal is said to be Leptokurtic. A pure leptokurtic distribution has a higher peak than the normal distribution and has heavier tails. A pure Platykurtic distribution has a lower peak flatter than a normal distribution and has lighter tails. These are shown in Figure 5.4.

Figure 5.4 Kurtosis.

A formula for measuring kurtosis is:

where Q stands for Quartile Deviation If Ku is greater than 0.263 (Ku > 0.263), the distribution is Platykurtic; if less than 0.263 (Ku < 0.263), the distribution is Leptokurtic.

5.1.5 Applications of the Normal Probability Curve (NPC) We will consider a number of problems which may readily be solved if we can assume that our obtained distributions can be treated as normal or as approximately normal. Suppose we devise a reading test for eight-year-olds (8-year-olds) and the maximum score possible on the test is 80. The test is standardised to a normal distribution such that the Mean score, for large representative sample of 8year-olds is 40, and the Standard Deviation (SD) is 10 (M = 40, SD or s = 10). So, 50% of 8-year-olds will therefore be above 40 and 50% below 40. The area under a normal curve between any two ordinates or points depends upon the values of its parameters mean and SD (s). No matter what m and s are, the area between m – s and m + s is about 68%; the area between m – 2s and m + 2s is about 95%; and the area between m – 3s and m + 3s is about 99.7%. Almost all values fall within 3 SDs (see Figure 5.5).

Figure 5.5 Applications of Normal Probability Curve.

Area trapped between Mean and 1s is 0.3413 of the whole area of the NPC (1.0000). Hence, 34.13% of children (8-year-olds) score between 40 and 50 points on this reading test, since the SD is 10 points. 34.13% of all values fall between Mean and + 1 (or –1) SDs. Area of NPC that lies between Mean and + 1 (or –1) SDs is 0.3413. Area of NPC that lies between these ordinates that is 1s is 0.6826. Area of NPC that lies between Mean and + 2 (or –2) SDs is 0.4772. Area of NPC that fall between the ordinates 2s is 0.9544; and area of NPC that lies between Mean and +3 (or –3) SDs is 0.4987. Area between the ordinates 3s is 0.9974. The area under the normal curve beyond these ordinates (+3 and –3s) is only 1.0000 – 0.9974 = 0.0026, which is very small. Thus, practically the whole area under the normal curve lies within limits Mean and 3s, which are also called 3-sigma units (see Table 5.1). Table 5.1 Points and area of NPC Odinates or points

Area of NPC

Mean and +1 (or –1) Standard Deviation

0.3413

Between Mean and

0.6826 (0.3413 + 0.3413)

1s

Mean and +2 (or –2) Standard Deviation

0.4772

Between Mean and

0.9544 (0.4772 + 0.4772)

2s

Mean and +3 (or –3) Standard Deviation

0.4987

Between Mean and

0.9974 (0.4987 + 0.4987)

3s

Z scores are called Standard Scores or Standard Normal Variable. A Z score is the number of SDs a score is from the Mean.

or

For example, let’s say the Mean for shoe size in your class is 8, with a SD of 1.5. If your shoe size is 5 and you are asked how many SDs your shoe size is from the Mean, then ...................M = 8, X = 5, s = 1.5

= \ Z = –2 Your shoe size (size 5) is 2 SDs below the Mean (size 8), a Z score of –2. Let us deal with some more problems. Determining the area of NPC in a normal distribution within given limits. EXAMPLE 1: Given a distribution of scores with a Mean of 12 and SD (s) of 4. Assuming normality, (a) What area of NPC fall between 8 and 16? (b) What area of NPC lie above score 18? (c) What area of NPC lie below score 6? Solution: (a) where Z = Standard Normal Variable M = Mean (or m) s = Standard Deviation M = 12

s=4 Z score of score 8:

Z = –1 Z score of score 16:

Z=1 A score or X of 16 is 4 points or 1s above the Mean (M = 12) and score or X of 8 is 4 points or 1s below the Mean (M = 12). We divided this scale distance of 4 score units by the s of the distribution (SD or s = 4). It is clear that 16 is 1s (4 points) above the Mean, and that 8 is 1s (4 points) below the Mean. There is 0.6826 area of NPC between the Mean and 1s. Hence, 68.26 of scores in our distribution or approximately the middle 2/3 falls between 8 and 16. The result may also be stated in terms of “chances”. Since 68.26% of the cases, in the given distribution fall between 1 and 16, the chances are about 68 in 100 that any score in the distribution will be found between these points or ordinates. (b) The upper limit of a score of 18, namely 18.5 is 6.5 score units or 1.625s above the Mean (6.5/4 = 1.625). .....................M = 12, s = 4, X = 18.5 (Upper limit of 18 = 18.5)

= 1.625 Z = 1.625 By consulting Table A for areas under Normal Distribution, value of 1.625 is:

= 44.79s Half of the area of the curve is 0.5000 or 50% of cases. Then we take the area 0.5000 – 0.4479 = 0.0521 or 5.21% So, 0.0521 area of NPC lie above score 18. (c) The lower limit of a score of 6, namely 5.5 is 6.5 score units or 1.625s below the Mean (–6.5/4 = –1.625). .....................M = 12, s = 4, Lower limit of 6 = 5.5

Z = –1.625 By consulting Table A for areas under Normal Distribution, value of – 1.625 is:

Z = 44.79 Half of the area of the curve is 0.5000 or 50% of cases. Then we take the

area = 0.5000 – 0.4479 = 0.0521 or 5.21% So, 0.0521 area of NPC lie below score 6. EXAMPLE 2: Given a Normal Distribution with a Mean of 100 and a SD of 10. (a) What area of NPC fall or lie between the scores of 85 and 115? (b) What area of NPC lie above 125? (c) What area of NPC lie below score 87? Solution: (a)

.....................M = 100, s = 10

Z = 1.5 By consulting Table A for areas under Normal Distribution, we get 0.4332. By entering Table A, we find that 0.4332 area of NPC lies between the Mean and 1s. Table A 0.4332 By adding 0.4332 + 0.4332 = 0.8664 area of NPC lies between score 85 and 115. (b)

.....................M = 100, s = 10, Upper limit of 125 = 125.5

Z = 2.55

By entering Table A for areas under Normal Distribution, we above find that 0.4946 are of NPC in the entire distribution fall between the Mean and 2.55s. = 0.5000 - 0.4946 = 0.0054 area of the NPC must be above the upper limit of 125 in order to fill the half area of the upper half of the NPC. (c)

.....................M = 100, s = 10, Lower limit of 87 = 86.5

Z = –1.35 0.4115 are of NPC fall between Mean to score 87. = 0.5000 – 0.4115 = 0.0885 area of the NPC lie below score 87. EXAMPLE 3: Given a Normal Distribution with a Mean of 38.65 and a s of 7.85. What area of the distribution will be between 25 and 35? Solution: A score of 25 is –13.65 score units (25 – 38.65) or –1.74s from the Mean.

= –1.74s And a score of 35 is –3.65 score units (35 – 38.65) or –0.47s.

= –0.47s from the Mean. We know from Table A for areas under Normal Distribution, that 0.4591 of the area of NPC in a Normal Distribution lie between the Mean and –1.74s and that 0.1808 area of the NPC lie between the Mean and –0.47s. By simple subtraction, therefore, 0.2783 area of the NPC (0.4591

– 0.1808 = 0.2783) fall between –1.74s and –0.47s or between the scores 25 and 35. The chances are about 28(27.83) in 100 that any score in the distribution will lie between these two scores. Note that both the scores that is 25 and 35 lie on the same side of the Mean (towards lower half). EXAMPLE 4: In a sample of 1000 cases, the mean of test scores is 14.5 and SD is 2.5. Assuming normality of distribution, how many individuals scored between 12 and 16? Solution: N = 16, M = 14.5, SD = 2.5

N = 12, M = 14.5, SD = 2.5

Area between 0 (Mean) and 0.6s = 0.2257 = 22.57% 1.0 = 0.3413 = 34.13% 56.70% of 1000 = 0.2257 + 0.3413 = 0.5670 = 56.70%

5.2 CORRELATION CORRELATION

OR

COEFFICIENT

OF

Correlation determines the degree of relationship that exists between two measures or factors or variables. The two variables are said to be associated or correlated if change in one variable is accompanied by change in the other variable. If X and Y are two variables, these will be correlated if with change in X, Y also changes.

5.2.1 Some Definitions of Correlation Correlation, according to Ferguson, “is concerned with describing the degree of relationship between variables”. “Correlation” is a statistical technique with the help of which we study the extent, nature, and significance of association between given variables.

According to Guilford, “A coefficient of correlation is a single number that tells us to what extent two things are related, to what extent variations in the one go with the variations in the other.” According to A.M. Tuttle, “Correlation is an analysis of the covariance between two or more variables.” According to SimpOn and Kafka, “Correlation analysis deals with the association between two or more variables.” According to Wonnacott and Wonnacott, “Correlation analysis shows us the degree to which variables are linearly related.” Thus in correlation, we study: (i) whether the given variables are associated or not; (ii) if they are associated, what is the extent of their association; (iii) whether variables are associated positively or negatively. When the relationship is quantitative (of or concerned with quantity), then we find it out by means of measures, called co-efficient (a multiplier, a mathematical factor) of correlation. A co-efficient of correlation is a numerical measurement of the extent or limit to which correlation can be found between two or more than two variables or dimensions or factors. The numerical measure of degree of correlation between the two variables is known as the coefficient of correlation. A coefficient which measures the degree of correlation between two variables is called as a coefficient of correlation. It is generally denoted by r. This coefficient of correlation (r) helps us in measuring the extent to which two variables vary in sympathy or in opposition. Measurement of correlation means the expression of degree of correlation that exists between two or more variables. If X and Y are two variable coefficients of correlation rxy tells the degree of association between X and Y. Coefficients of correlation are indices ranging over a scale which extends from –1.00 (negative perfect correlation) through 0.00 to +1.00 (positive perfect correlation). Only rarely, if ever, will a coefficient fall at either extreme of the scale, that is, at +1.00 or –1.00. When the relationship between two sets of measures is “linear” (of a line, of length, arranged in a line) that is can be described by a straight line, the correlation between scores may be expressed by the “Product-moment” coefficient of correlation designated by the letter r. The correlation between two abilities, as represented by test scores, may also be perfect.

For example, in a class, all students (N = 10) have secured exactly the same position in two tests as shown in the following: Students

Test I

Test II

A B C D E F G H I J

1st 2nd 3rd 4th 5th 6th 7th 8th 9th 10th

1st 2nd 3rd 4th 5th 6th 7th 8th 9th 10th

The relationship is perfect, since the relative position of each subject is exactly the same in one test as in the other; and the coefficient of correlation is 1.00. When r = 1.00, the correlation between the two variables or dimensions is said to be perfect.

No correlation situation For example, we administered to 100 college students, the Army General Classification Test (AGCT) and a simple “tapping test” in which the number of separate taps made in 30 seconds is recorded. Let the mean AGCT score for the group be 120, and the mean tapping rate be 185 taps in 30 seconds. Level

AGCT (Mean score)

Taps/30 seconds

High Middle Low

130 110 100

184 186 185

There is no correspondence between the scores made by the members of one group upon the two tests, and r, the coefficient of correlation is zero. When r = 0, there is no correspondence between the scores made by the subjects upon the two tests. A zero correlation indicates no consistent relationship. Correlations whose values are close to zero (–0.09, 0.00, +0.09) are called zero correlation. Perfect relationship is expressed by a coefficient of 1.00 ( 1.00), and just no relationship by a coefficient of 0.00. A coefficient of correlation falling between 0.00 and 1.00 always implies some degree of positive association, the degree of correspondence depending upon

the size of the coefficient. A positive or direct correlation indicates that large amounts of the one variable tend to accompany large amounts of the other. If direction of change in the two variables is same, correlation is said to be positive. If the total variation is all explained by the regression line, that is if r = 1 or r = 1.00, we say that there is perfect linear correlation (and in such case also perfect linear regression). Relationship may also be negative; that is, a high degree of one trait may be associated with a low degree of another. A negative or inverse correlation indicates that small amounts of the one variable tend to accompany large amounts of the other. If direction of change in the two variables is different, correlation is said to be negative correlation. When negative or inverse relationship is perfect, r = –1.00 (negative perfect correlation). Negative coefficients may range from –1.00 to 0.00 or 0.00 to –1.00, just as positive coefficients may range from 0.00 (no relationship or correlation) up to +1.00 (positive perfect correlation) or +1.00 to 0.00. Coefficients of –0.20, –0.50, or –0.80 indicates increasing degrees of negative or inverse relationship, just as positive coefficients of +0.20, +0.50, and +0.80 indicate increasing degrees of positive relationship. In most actual problems, calculated r’s fall at intermediate points, such as +0.72, –0.26, +0.50 and so on. Such r’s (coefficients of correlation) are to be interpreted as “high” or “low” depending in general upon how close they are 1.00 (positive perfect or negative perfect). If we have only two variables and we study association or correlation between them, the technique of correlation is called simple correlation. A coefficient measuring simple correlation is called coefficient of simple correlation. If there are more than two variables and we study correlation between any two of them ignoring others, the technique of correlation is called partial correlation. A coefficient measuring partial correlation is called partial correlation coefficient. If number of variables is more than two and we study association between one variable and other variables taken together, technique of correlation is called multiple correlation. A coefficient which measures correlation is called a coefficient of multiple correlation. The two variables are said to have linear correlation if with one unit change in one variable, the other changes by a constant amount throughout the distribution. The two variables are said to have non-linear correlation if with a unit change in one variable, other variable changes by

unequal amount.

5.2.2 Characteristics or Properties of Correlation (i) Correlation determines the degree or limit or degree of relationship between two measures or dimensions or factors or variables. (ii) It is a single quantitative number. (iii) It tells us to what extent variations in the one variable or factor or measure go with the variations in the other. (iv) Tells the direction or nature of correlation, that is, whether the correlation is positive or negative. Positive or direct correlation is related to the direction of change in the two variables. Whether the correlation is direct (positive) or inverse (negative) will depend upon the direction of deviation. If the series deviate in the same direction, correlation is positive and if they deviate in the opposite direction, it is negative or inverse. (v) Range of correlation is from –1 to +1. In other words, correlation coefficient cannot take value less than –1 or more than +1. (a) 1 rxy + 1 (vi) Coefficient of correlation possesses the property of symmetry. It means rxy = ryx. (vii) If X and Y are independent, the coefficient of correlation between them is equal to zero. If the coefficient of correlation between X and Y is zero, X and Y may be independent or may not be independent. If rxy = 0, it only means the absence of linear correlation. (viii) The correlation coefficient ranges from –1 to 1. A value of 1 implies that a linear equation describes the relationship between X and Y perfectly, with all data points lying on a line for which Y increases as X increases. A value of –1 implies that all data points lie on a line for which Y decreases as X increases. A value of 0 implies that there is no linear correlation between the variables. (ix) A correlation is strong if the absolute value of the correlation coefficient is close to 1.00 (perfect correlation). Thus, when r = +0.93,

we have a strong positive or direct correlation, which means increase in one factor leads to increase in the other (see Table 5.2). Similarly, when r = –0.93, we have a strong negative or inverse correlation, which means increase in one factor leads to decrease in the other and decrease in one factor leads to increase in the other. Infact, those correlations are equally strong because –0.93 is just as close to –1.00 as +0.93 is to +1.00. It is a mistake to believe that strength depends upon direction or nature (positive or negative) so that any positive correlation would be stronger than any negative correlation. Strength of correlation depends on absolute value of r. A correlation is weak if the absolute value of the correlation coefficient is close to zero and 0.09, for example +0.23 or –0.27. In Psychology, we are more likely to find weak correlations than strong correlations. Behaviour is complex; many other variables can contaminate a relationship between onetwo target variables, reducing the strength of the correlation. Table 5.2 Interpreting the strength of various correlation coefficients Negative

Negative perfect correlation –1.00

Strong or high negative correlation

Values closer to –1.00; between –1 and –0.75; –1.00, –0.90, –0.80

Moderate negative correlation

Between –0.25 and –0.75; –0.70, –0.60, –0.50

Weak or low negative correlation

Between –0.10 and –0.25; –0.40, –0.30, –0.20

No correlation or zero correlation

0.00 to

0.09

Positive

Positive perfect correlation +1.00

Strong or high positive correlation

Values closer to +1.00; between +1 and +0.75; +1.00, +0.90, +0.80

Moderate positive correlation

Between +0.25 and +0.75; +0.70, +0.60, +0.50

Weak or low positive correlation

Between +0.10 and +0.25; +0.40, +0.30, +0.20

Several authors have offered guidelines for the interpretation of a correlation coefficient. Cohen (1988) has observed, however, that all such criteria are in some ways arbitrary and should not be observed too strictly. The interpretation of a correlation coefficient depends on the context and purposes. A correlation of 0.9 may be very low if one is verifying a physical law using high-quality instruments, but may be regarded as very high in the

social sciences where there may be a greater contribution from complicating factors. The below mentioned readings may be useful for interpreting the strength of correlation. Correlation

Negative

Positive

None Small Medium Large

–0.09 to 0.0 –0.3 to –0.1 –0.5 to –0.3 −1.0 to –0.5

0.0 to 0.09 0.1 to 0.3 0.3 to 0.5 0.5 to 1.0

In summary, the calculation method allows us to discover whether two variables are related to each other. This advantage is particularly helpful in real-life settings where an experiment would be impossible. However, a major disadvantage of correlational research is that we cannot draw the firm or strong cause and effect conclusions that an experiment permits. Correlational research does generate cause and effect hypotheses that can be tested later using the experimental method.

5.2.3 Methods of Correlation Correlation is rarely computed when the number of cases (N) is less than 25. Usually two methods are widely used to find out the coefficient of correlation: (i) Spearman’s Rank Order Method or Rank Difference Method (ii) Karl Pearson’s Product Moment Method

Rank Order method or Rank Difference method This method was developed by Charles Edward Spearman in the year 1904. Charles Edward Spearman was an English psychologist known for his work in statistics, as a pioneer of factor analysis, and for Spearman’s rank correlation coefficient. He also did seminal work on models of human intelligence, includes his theory that disparate cognitive test scores reflect a single general factor and coined the term g factor.

Charles Edward Spearman (1863–1945)

In statistics, Spearman’s rank correlation coefficient or Spearman’s rho, named after Charles Spearman and often denoted by the Greek letter r (rho) or as rs is a non-parametric measure of statistical dependence between two variables. It assesses how well the relationship between two variables can be described using a monotonic function. If there are no repeated data values, a perfect Spearman correlation of +1 or –1 occurs when each of the variables is a perfect monotone function of the other. Rank Order Method of measuring correlation is useful only in cases where quantitative or numerical expression is not possible (for example, qualities, abilities, honesty, beauty and so on), but it is possible to arrange in a serial order. This serial order is known as Rank. When it is difficult to measure the correlation among variables directly, then it is done usually by Ranking. This method was first of all used by Spearman. In this method, the coefficient of correlation is symbolically represented by r (rho) and the formula employed is:

where D difference of ranks of two variables N total number of variables Rank Difference method can be employed when (i) the variables can be arranged in order of merit. (ii) the number (N) is small and one needs a quick and convenient way of estimating the correlation. (iii) we have to take account only of the positions of the items in the series making no allowance for gaps between adjacent scores.

For example, four tests A, B, C, and D have been administered to a group of 5 children. The children have been arranged in order of merit on Test A, and their scores are then compared separately with Tests B, C, D to give the following three cases: Pupils

Test A

Test B

Test C

Test D

1 2 3 4 5

15 14 13 12 11

53 52 51 50 49

64 65 66 67 68

102 100 104 103 101

Case 1: Correlation between Test A and B. Pupils

Test A

Test B

1 2 3 4 5

15 14 13 12 11

53 52 51 50 49

. Pupils

Test A

Test B

1 2 3 4 5

15 14 13 12 11

53 52 51 50 49

All connecting lines are horizontal and parallel, and the correlation is positive and perfect, r = 1.00. The more nearly the lines connecting the paired scores are horizontal and parallel, the higher the correlation. Case 2: Correlation between Test A and C: Pupils

Test A

Test C

1 2 3 4 5

15 14 13 12 11

64 65 66 67 68

.

Pupils

Test A

Test C

1 2 3 4 5

15 14 13 12 11

68 67 66 65 64

When all connecting lines intersect in one point, the correlation is negative (increase in one leads to decrease in other and decrease in one leads to increase in other) and perfect, r = –1.00. The more nearly the connecting lines tend to intersect in one point, the larger the negative correlation. Case 3: Correlation between Test A and D: Pupils

Test A

Test D

1 2 3 4 5

15 14 13 12 11

102 100 104 103 101

.

Pupils

Test A

Test D

1 2 3 4 5

15 14 13 12 11

104 103 102 101 100

Here, no system is exhibited by the connecting lines but the resemblance is closer to Case 2 than to Case 1, so correlation is low and negative. When the connecting lines show no systematic trend, the correlation approaches zero. Let us analyse with the help of an example: EXAMPLE 1 Traits

Judge X (1)

Judge Y (2)

D(Difference) (3)

A B

2 1

1 2

1(2 – 1) –1(1 – 2)

D2(D D) (4) 1(1 1(–1

1) –1)

C D E F

4 3 6 5

N=6

N=6

5 6 4 4

–1(4 – 5) –3(3 – 6) 2(6 – 4) 2(5 – 3)

1(–1 9(–3 4(2 4(2

SD = 0 (+5 – 5)

–1) –3) 2) 2)

SD2 = 20

.

where D differences between each pair of ranks (Judge Y’s from those of Judge X) r coefficient of correlation from rank differences sum of the squares of differences in ranks N number of pairs N2 square of N(N N) D2

square of D(D

D)

Here, the correlation is positive and moderate.

EXAMPLE 2 RANK

RANK

X

Y

X

Y

1000 1250 1100 1080 1400 1550 1700

900 940 1000 930 1200 1350 1300

7 4 5 6 3 2 1

7 5 4 6 3 1 2

N=7

N=7

D(Difference)

D2(D

D)

0(7 – 7) –1(4 – 5) 1(5 – 4) 0(6 – 6) 0(3 – 3) 1(2 – 1) –1(1 – 2)

0(0 1(–1 1(1 0(0 0(0 1(1 1(–1

0) –1) 1) 0) 0) 1) –1)

SD = 0(1 – 1)

SD2 = 4

.

Here correlation is positive and very high. EXAMPLE 3 X

Y

Rank1

Rank2

D(R1 – R2)

47 50 70 72 46 50 42 58 55

68 60 54 53 60 55 48 30 45

8.5 5.5 2 1 10 5.5 11 3 4

1 2.5 7 8 2.6 6 9 12 10

7.5 3 –5 –7 –7.5 –0.5 2 –9 –6

D2(D 56.25 9.00 25.00 49.00 56.25 0.25 4.00 81.00 36.00

D)

36 49 47

43 59 56

N = 12S

N = 12S

12 7 8.5

11 4 5

1 3 3.5

1.00 9.00 12.25

SD = 0

SD2 = 339

.

Hence, correlation is positive and weak. Merits of Rank Order method (i) Is easier as compared to Karl Pearson’s method of correlation. (ii) Can be used even when actual values are not given and only ranking is given. (iii) Can be used to study the qualitative phenomena where the direct measurement is not possible and hence Karl Pearson’s method of correlation cannot be used. (iv) Is distribution free. Assumption of normality is not required. Demerits of Rank Order method (i) Is not as accurate as Karl Pearson’s method of correlation. (ii) Number of observations is large, it becomes difficult to use this method, provided ranks are given. (iii) Is rarely used in further statistical analysis. (iv) Is less sensitive than the Karl Pearson is method of correlation to strong outliers that are in the tails of both samples.

Product Moment method or Product Moment Correlation Coefficient (r) In statistics, the Pearson product-moment correlation coefficient (sometimes referred to as the PMCC, and typically denoted by r) is a measure of the correlation (linear dependence) between two variables X and Y, giving a value between +1 and –1 inclusive. It is widely used in the sciences as a measure of the strength of linear dependence between two variables. It was developed by Karl Pearson from a similar but slightly different idea introduced by Francis Galton in the 1880s. The correlation coefficient is sometimes called “Pearson’s r.” This method is most commonly used or employed because it gives fairly accurate measure of correlation existing between two variables. Karl Pearson’s coefficient of correlation is the arithmetic average of the products of the deviating one of each pair of items from their respective means, divided by the product of standard deviation. The original formula that Karl Pearson had developed was called as Product Moment Method because it was based on the product of the first moment around Mean in the two series.

or

Here is a sum calculated by Pearson’s Product Moment method of correlation Scores

Deviation

Test 1

Test 2

Subject

X

Y

x(X – MX)

y(Y – MY)

A B C D E F G H I

50 54 56 59 60 62 61 65 67

22 25 34 28 26 30 32 30 28

–12.5(50 – 62.5) –8.5(54 – 62.5) –6.5(56 – 62.5) –3.5(59 – 62.5) –2.5(60 – 62.5) –0.5(62 – 62.5) –1.5(61 – 62.5) 2.5(65 – 62.5) 4.5(67 – 62.5)

–8.4(22 – 30.4) –5.4(25 – 30.4) 3.6(34 – 30.4) –2.4(28 – 30.4) –4.4(26 – 30.4) –0.4(30 – 30.4) 1.6(32 – 30.4) –0.4(30 – 30.4) –2.4(28 – 30.4)

x2(x 156.25(–12.5 72.25(–8.5 42.25(–6.5 12.25(–3.5 6.25(–2.5 0.25(–0.5 2.25(–1.5 6.25(2.5 20.25(4.5

x) –12.5) –8.5) –6.5) –3.5) –2.5) –0.5) –1.5) 2.5) 4.5)

y2(y 70.56( –8.4 29.16( –5.4 12.96(–3.6 5.76(–2.4 19.36(–4.4 0.16(–0.4 2.56(1.6 0.16(–0.4 5.76(–2.4

y) –8.4) –5.4) –3.6) –2.4) –4.4) –0.4) 1.6) –0.4) –2.4)

xy(x

y)

1.5(–12.5 –8.4) 45.9(– 8.5 –5.4) –23.4(–6.5 3.6) 8.4(–3.5 –2.4) 11(–2.5 –4.4) 0.2(–0.5 –0.4) –2.4(–1.5 1.6) –1(2.5 –0.4) –10.8(4.5 –2.4)

J K L N = 12

71 71 74

34 36 40

SX=750

SY=365

8.5(71 – 62.5) 8.5(71 – 62.5) 11.5(74 – 62.5)

3.6(34 – 30.4) 5.6(36 – 30.4) 9.6(40 – 30.4)

72.25(8.5 72.25(8.5 132.25(11.5

8.5) 8.5) 11.5)

Sx2 = 595.00

12.96(3.6 31.36(5.6 92.16(9.6

3.6) 5.6) 9.6)

Sy2 = 282.92

30.6(8.5 47.6(8.5 110.4(11.5

3.6) 5.6) 9.6)

Sxy = 321.50

.

Correlation is positive and high.

Steps of the Karl Pearson’s Product Moment method of Correlation (i) Calculate the Mean of Test 1 (X) and the Mean of Test 2 (Y). Formula for calculating Mean is:

(ii) Find the deviation of each score on Test 1 (x) from its Mean (MX), 62.5 and enter it in column of each score in Test 2 (y) from its Mean (MY), 30.4 and enter it in column y. (iii) Square all of the x’s and all of the y’s and enter these squares in columns x2 and y2, respectively. Total or sum these columns to obtain Sx2 and Sy2.

(iv) Multiply the x’s and y’s in the same rows, and enter these products (with due regard for sign) in the xy column. Total or sum the xy column, taking account of sign, to get Sxy. (v) Substitute for Sxy(321.50) for Sx2(595.00) and for Sy2(282.92) in formula and solve for r (coefficient of correlation). EXAMPLE 1 X

Y

x(X – M)

y(Y – M)

15 18 22 17 19 20 16 21

40 42 50 45 43 46 41 44

–3.5 –0.5 3.5 –1.5 0.5 1.5 –2.5 2.5

–3.87 –1.87 6.13 1.13 –0.87 2.13 –2.87 0.13

SX = 148

SY = 351

x2(x

x)

Test 2

xy(x

y)

14.98 3.50 37.58 1.27 0.76 4.54 8.24 0.02

13.55 0.94 21.46 –1.70 – 0.44 3.20 7.18 0.33

Sx2 = 42

Sy2 = 70.9

Sxy = 44.52

Correlation is positive and high. EXAMPLE 2 Test 1

y)

12.25 0.25 12.25 2.25 0.25 2.25 6.25 6.25

.

Subjects

y2(y

Deviation

X

Y

x(X – MX)

y(Y – MY)

A B C D E F G

67 72 45 58 63 39 52

65 84 51 56 67 42 50

10.43 15.43 –11.57 1.43 6.43 –17.57 –4.57

5.72 24.72 –8.28 –3.28 7.72 –17.28 –9.28

N=7

SX = 396

SY = 415

x2(x

x)

y2(y

y)

xy(x

y)

108.78 238.08 133.86 2.04 41.34 308.70 20.88

32.71 611.07 68.55 10.75 59.59 298.59 86.11

59.65 381.42 95.79 –1.85 49.63 303.60 42.40

Sx2 = 853.68

Sy2 = 1167.37

Sxy = 927.80

.

Correlation is positive and high. Merits of Karl Pearson’s Product Moment (r) method (i) A mathematical method. (ii) Gives degree as well as direction of correlation. (iii) Used in further analysis. Demerits of Karl Pearson’s Product Moment (r) method (i) Is very difficult method. (ii) Assumes a linear relationship. (iii) Is highly affected by the presence of extreme items or scores. (iv) Cannot be used where the direct quantitative measurement of the phenomenon is not possible, for example beauty, honesty, intelligence, etc. (v) Assumes populations from which observations are taken are normal.

QUESTIONS Section A Answer the following in five lines or in 50 words: 1. 2. 3. 4. 5. 6. 7. 8. 9. 10. 11. 12. 13. 14. 15. 16.

Statistics Skewness* Negative Skewness* Positive skewness Kurtosis Platykurtic Normal Probability Curve or NPC Null hypothesis Correlation Correlation coefficient Linear correlation Define Rank Order and give its formula. Formula for Rank Difference method of correlation. Formula for Pearson’s Product Moment method of correlation. Range of Normal Probability Curve or NPC. Range of Normal Probability Curve or NPC on figure.

Section B Answer the following questions up to two pages or in 500 words: 1. What is Normal Probability Curve or NPC? Give its properties. 2. Define NPC with figure and give its characteristics. 3. Explain the nature and characteristics of a Normal Probability Curve or NPC. 4. Write about the characteristics of Normal Probability Curve or NPC. 5. Write a note on “Correlation”. 6. Write a short note on the divergence of the Normal Probability Curve or NPC. 7. Give important properties of the Normal Probability Curve or NPC.

8. 9. 10. 11.

12.

Or Write characteristics of Normal Probability Curve or NPC. Write the area and percentage of people covered between mean and 1s, 2s, and 3s. Write a short note on the characteristics of the Normal Probability Curve or NPC. Elucidate the concept of Skewness. On the assumption that I.Q. is normally distributed in the population mean of 70 and SD of 10, what (i) per cent of cases will fall above 92 I.Q. (ii) per cent of cases will fall between 63 and 86 I.Q. (iii) per cent of cases will fall below 60 I.Q. Write about the meaning and nature of correlation.

Section C Answer the following questions up to five pages or in 1000 words: 1. What is statistics? Discuss nature of Normal Probability Curve or NPC in detail. 2. Define Normal Probability Curve or NPC and explain its characteristics. 3. Write a detailed note on the Normal Probability Curve or NPC. 4. Discuss various characteristics of Normal Probability Curve or NPC and its applications. 5. Give five main properties of the Normal Probability Curve or NPC. Given a normal distribution with a mean of 120 and SD of 25. What limits will include the highest 10% of the distribution? 6. Given N = 100, M = 28.52, SD = 4.66, assuming normality of the given distribution, find (a) What per cent of cases lie between 23–25? (b) What limits include the middle 60%. 7. Give a normal distribution with a mean of 50 and standard deviation of 15: (i) What per cent of cases will lie between the scores of 47 and 60? (ii) What per cent of cases will lie between the scores of 40 and 46? (iii) What per cent of group is expected to have scores greater than 68?

8. If M = 20, SD = 5.00, assuming normality (i) Find the percentage of cases above score 18. (ii) Find the percentage of cases between score 15 to 24. (iii) Find the percentage of cases below the score 16. 9. If M = 24, SD = 4.00, assuming normality, find: (i) Area above 20. (ii) Area below 18. (iii) Area between the score 22–32. 10. What is coefficient of correlation? Discuss its nature and characteristics. 11. Write about the meaning and nature of correlation. 12. What is a coefficient of correlation? Discuss the basic assumptions of Pearson’s product moment correlation. 13. Find the correlation between the two sets of scores given below, using the Product Moment method: X: 15, 18, 22, 17, 19, 20, 16, 21. Y: 40, 42, 50, 45, 43, 46, 41, 41. 14. Find the correlation between the two sets of scores given using the Product Moment method: X: 16, 19, 23, 18, 15, 20, 21 Y: 40, 42, 46, 35, 30, 34, 35 15. Calculate correlation using Rank Order method. X: 44, 47, 44, 49, 53, 56, 49, 44, 50, 52 Y: 74, 72, 74, 71, 70, 68, 70, 73, 75, 71 16. Find out the correlation between the scores made by ten students on two tests: Subjects

Test 1 (X)

Test 2 (Y)

A B C D E F G H I

67 65 50 58 62 66 53 59 62

85 83 72 77 84 87 70 79 82

J

58

81*

17. Calculate correlation of the following data using Pearson Product Moment method: X: 24, 35, 26, 19, 38, 43, 22, 27, 42, 34. Y: 72, 85, 77, 79, 81, 80, 74, 78, 91, 73. 18. Calculate correlation of the following data using Rank Difference method: X: 12, 15, 24, 28, 8, 15, 20, 20, 11, 26 Y: 21, 25, 35, 24, 16, 18, 25, 16, 16, 38 19. Find out the correlation between X and Y from the following data. Why is the method applied appropriate? X: 25, 26, 27, 28, 30, 29, 32, 31 Y: 27, 28, 29, 34, 35, 32, 34, 34 20. Find out coefficient of correlation by Rank Order of the following data: X: 1000, 1250, 1100, 1080, 1400, 1550, 1700 Y: 900, 940, 1000, 930, 1200, 1350, 1300 21. Find the coefficient of correlation between X and Y from the following data: ............................................................................X...............Y No. of items:......................................................15..............15 Mean:.................................................................25..............18 Square of deviation from mean:.....................136............138 Sum of the product of deviations of X and Y from their respective means:.......................122

REFERENCES Cohen, J., Statistical Power Analysis for the Behavioral Sciences (2nd ed.), 1988. De Moivre, A., The Doctrine of Chances, 1738. Ferguson, G.A., Statistical Analysis in Psychology and Education. Galton, F., Inquiries into Human Faculty and Its Development, AMS Press, New York, 1863/1907/1973.

Galton, F., Hereditary Genius: An Inquiry into its Laws and Consequences, Macmillan, London, 1869/1892. Gauss, Carolo Friderico., (in Latin), Theoria motvs corporvm coelestivm in sectionibvs conicis Solem ambientivm, [Theory of the motion of the heavenly bodies moving about the Sun in conic sections], English translation, 1809. Guilford, J.P., Fundamental Statistics in Psychology and Education, McGraw-Hill, New York, 1956. Guilford, J.P., Fundamental Statistics in Psychology and Education, McGraw-Hill, New York, 1965. Gupta S.P., Statistical Methods, Sultan Chand & Co., New Delhi. Hoel, P.G., Introduction to Statistic, Asia Publishing House, New Delhi, 1957. Kerlinger, F.A., Foundations of Behavioural Research, Century Craft, New York, 1966. Laplace, Pierre-Simon., Analytical Theory of Probabilities, 1812. Mood, A.M., Graybill, F.A. and Boes, D.C., Introduction to the Theory of Statistics (3rd ed.), McGraw-Hill, New York, 1973. Pearson, C., “My custom of terming the curve the Gauss–Laplacian or normal curve saves us from proportioning the merit of discovery between the two great astronomer mathematicians”, 1904. Pearson, K., “Das Fehlergesetz und seine Verallgemeinerungen durch Fechner und Pearson, A rejoinder”, Biometrika, 4, pp. 169–212, 1904. Pearson, K., “Notes on the history of correlation”, Biometrika, 13(1), pp. 25– 45, 1920. Shergill, H.K., Psychology, Part I, PHI Learning, New Delhi, 2010. Simp On and Kafka., Basic Statistics, Oxford & I.B.H. Publishers. Spearman, C., “General intelligence—objectively determined and measured”, American Journal of Psychology, 15, pp. 201–293, 1904. Tuttle, A.M., Elementary Business and Economic Statistics, Solutions Mannual. Wonnacott, T.H. and Wonnacott, R.J., Introductory Statistics, Wiley, New York, 1990.

PART B Chapter 6: Psychophysics Chapter 7: Learning Chapter 8: Memory Chapter 9: Thinking and Problem-Solving

6 Psychophysics INTRODUCTION Psychophysics can be defined as the study of how physical stimuli are translated into psychological experience. In academics, the specialty area within the field of Psychology that studies sensory limits, sensory adaptation, and related topics is called Psychophysics. The subject matter of this field is the relationship between the physical properties of stimuli and the psychological sensations they produce. Psychophysics is a branch of psychology and an area of research and is concerned with the effect of physical stimuli (such as sound waves). Psychophysics was introduced and established by Gustav Theodor Fechner in the mid-19th century (1860), and since then its central inquiry has remained the quantitative relation between stimulus and sensation. Psychophysics is an important field because there is not a direct or simple relationship between stimuli and sensations. Since our knowledge of the outside world is limited to what our sensations tell us, we need to understand under what conditions our sensations do not directly reflect the physical nature of the stimulus. Sensory adaptation is a process that alters the relationship between stimuli and sensations, but numerous other circumstances provide examples of this lack of a none-to-one relationship. The concept of the difference in the threshold provides another good example. The word “psychophysics” is made up of two words—psycho + physics.

“Psycho” includes the study of stimulus whereby “physics” includes the study of physical constitution. In simpler words, psychophysics is the study of relations of dependency between mind and body. But this could not explain the nature of psychophysics. A key tenet in this context has been Weber’s law. Weber’s law is a law of psychophysics stating that the amount of change in a stimulus needed to detect a difference is in direct proportion to the intensity of the original stimulus. Psychophysical methods are used today in vision research and audiology, psychophysical testing, and commercial product comparisons (for example, tobacco, perfume, and liquor).

6.1 SOME DEFINITIONS OF PSYCHOPHYSICS G.T. Fechner (1801–1887) defined psychophysics as “an exact science of the functional relations of dependency between body and mind.” According to Guilford (1954), “Psychophysics has been regarded as the science that investigates the quantitative relationship between physical events and corresponding psychological events.” According to English and English (1958), “Psychophysics is the study of the relation between the physical attributes of the stimulus and the quantitative attributes of sensation.” According to Stevens (1962), ‘Psychophysics is an exact science of functional relations of dependency between body and mind.” According to Eysenck (1972), “Psychophysics concerns the manner in which living organisms respond to the energetic configurations of the environment.” According to Andrews (1984), “Psychophysics is that branch of psychology, which is concerned with subjective measurements.” On the basis of above definitions, it can be said that psychophysics is that branch of Psychology which studies the quantitative relationship between stimulus and response or between physical attributes of stimulus and sensation in the context of the factors that affect this relationship. The living organism responds in the presence of stimulus. The stimulus here refers to the physical energy changes in the inner and outer environment of the living organism. In the presence of a stimulus, interaction takes place between the organism’s pre-experiences and the stimulus and as a result the organism responds.

6.2 THE THRESHOLD The word “threshold” and its Latin equivalent, limen, means essentially what one would guess: a boundary separating the stimuli that elicit one response from the stimuli that elicit or evoke a different response. Threshold is a dividing line between what has detectable energy and what does not. For example, many classrooms have automatic light sensors. When people are not in a room for a while, the lights go out. However, once someone walks into the room, the lights go back on. For this to happen, the sensor has a threshold for motion that must be crossed before it turns the lights back on. So, dust floating in the room should not make the lights go on, but a person walking in should. Let’s understand it with the help of another example. Let a very light weight be placed gently on an organism’s palm. If the weight is below a certain value, subject’s report is “No, I don’t feel it”, because when the intensity of a stimulus is small enough, you cannot detect it at all. But if the weight is increased trial by trial, it eventually reaches a value which gets the positive response, “Yes, now I feel it”. There is a point where the intensity of a stimulus is just sufficient for you to be able to detect it. The value of the weight has crossed the lower threshold, often called the Stimulus Threshold, and abbreviated into RL (from the German Reiz Limen)—psychophysics having begun as a German enterprise. Stimulus threshold is also called Absolute Threshold of sensation and refers to “the value of a quantitative variable at which a stimulus is just detectable” (Eysenck, 1972). The absolute threshold is the least intense stimulus in a given modality that is detectable. This will apply to all our senses, but it is not constant, however. Psychologists have coined the term absolute threshold to denote our sensory threshold. They define absolute threshold as the smallest magnitude of a stimulus that can be reliably discriminated from no stimulus at all 50 per cent of the time. According to Underwood, “Absolute Threshold is that minimal physical stimulus value (or maximal for upper thresholds) which will produce a response 50 per cent of the time.” The absolute threshold is the lowest intensity which is sensed 50 per cent of the time. The absolute threshold is the 50 per cent point. For example, a ticking watch is kept at a certain distance from your ear and you are not able to hear it because its intensity is below the point on the physical continuum but when it is brought a bit near,

you are able to hear its ticking sound which makes you feel its presence. This is the absolute or Reiz or stimulus Limen or threshold. There is always a single level of intensity below which you never detect a stimulus and above which you always do in any particular set of circumstances. This is the background activity against which you sense something. The brain has some difficulty when there is an external stimulus present or when the nerve impulses just represent neural noise. A threshold is always a statistical value; customarily the lower threshold is defined as that value of the stimulus which evokes a positive (“Yes”) response on 50 per cent of the trials. Threshold is the statistically determined point at which a stimulus is adequate to elicit or evoke a specified organismic response. Thresholds vary with individuals (individual differences) and also vary from moment to moment for a single individual. As such the best measure of a threshold is a statistical abstraction—the mean or median of many threshold measurements. But what happens if we proceed to increase the weight in one experiment beyond the stimulus threshold? Organism will report that it feels heavier and heavier, and we can determine a Differential Threshold or Difference Threshold, abbreviated DT or DL for Differenz Limen. Psychologists refer to the amount of change in a stimulus required for a person to detect it as the difference threshold. A second threshold in which psychologists are interested is that which is termed just noticeable difference (j.n.d). Difference Threshold is the minimum amount of stimulus intensity change needed to produce a noticeable change. The smaller the change we can detect, the greater our sensitivity. In other words, the difference threshold is the amount of change in a physical stimulus necessary to produce a just noticeable difference (j.n.d) in sensation. The greater the intensity (example, weight) of a stimulus, the greater the change needed to produce a noticeable change. For example, when you pick up a 5 lb weight, and then a 10 lb weight, you can feel a big difference between the two. However, when you pick up 100 lbs, and then 105 lbs, it is much more difficult to feel the difference. Differential threshold or Differenz Limen is also known as Just Noticeable Difference (JND or j.n.d) and refers to the amount of physical change necessary to bring about it and is just noticed. It is a point on the physical continuum at some distance from the standard stimulus. This is the minimum

difference in intensity of a pair of stimuli for them to be perceived as dissimilar. This minimum difference in intensity can be perceived 50 per cent of the time. This term was invented by Gustav Fechner (1801–1887). According to Underwood, “Difference threshold is that physical stimulus difference that is noticeable 50 per cent of the time.” According to D’Amato, “Differenz limen is the minimum amount of stimulus change required to produce a sensation difference.” According to Townsend, “The distance from the standard stimulus to the difference threshold is called the difference limen and is established by varying or changing a stimulus from the intensity of an identical constant stimulus and increasing the difference until the subject reports that she or he perceives a difference.” For example, when we are listening to a music and suddenly the volume is raised or lowered, we find the difference between the previously heard one and that of the present one. This point which discriminates the two volumes in the stimulus (music) dimension is the difference threshold. Generally it has been noted that the discrimination in the change in stimulus is based on neural process as well on “All or None Law”. A fact about difference thresholds that has captured the attention of psychophysicists since the nineteenth century is that the size of the difference threshold increases as the strength of the stimulus increases. When a stimulus is strong, changes in it must be bigger to be noticed than when the stimulus is weak. Most three-way bulbs provide light energy in three approximately equal steps (such as a 50-, 100-, and 150-watt bulb), but the greatest difference in brightness in the room is noticeable after the first click of the switch—the sofa that you just tripped over in the darkness is now plainly visible. Turning up the light to the next level adds a less noticeable increase in perceived brightness; and the third level adds even less in apparent brightness. At each level of increasing illumination, the difference threshold is greater, so the perceived increase in brightness is less. If you were to turn on another 50-watt bulb at this point—with the three-way bulb at its highest illumination—you might not see any increase in apparent brightness because your difference threshold is not so high. The ability to detect small changes in the intensity of weak stimuli, but only large changes in the intensity of strong stimuli was first formally noted by German psychophysicist Ernst Weber (1795–1878). This phenomenon is called “Weber’s Law”. Weber discovered a relationship between the absolute

stimulus intensity and the j.n.d. Just noticeable difference is that change in intensity of a stimulus which can be detected by an individual 50 per cent of the time. The smallest difference in intensity which can be detected is proportional to the original stimulus intensity. Weber’s law governs the relationship between j.n.d and the background intensity of a stimulus against which a change occurs. The difference in intensity divided by the background intensity is equal to a constant (K) which is different for each sense modality. For example, you are sitting at a table with just one candle. Someone comes in with a second candle and you will probably notice the difference immediately. But if you were in a room lighted by three 100-watt electric light bulbs and someone brought in a candle you would not notice the difference. The ratio of the just noticeable difference to the background intensity will be constant. The formula Weber arrived at is as follows:

Where DI is the increase in stimulus intensity needed to make a just noticeable difference, I is the background intensity, and K is a constant, known as Weber’s constant, which will vary with different sense modalities. Table 6.1 shows some of the values of K. Table 6.1 Some of the values of K Sense modality

Weber’s constant

Vision (brightness of white light) Hearing (loudness of tone) Taste (for salt) Pressure on skin Pain (something hot on the skin) Kinaesthetic (lifted weights)

1/60 1/10 1/3 1/7 1/30 1/50

Let us take another example. Suppose you are holding a 100-gram weight. You need to add an additional 2-gram weight before you would notice the difference. Weber’s constant for lifted weights is 1/50, your background weight is 100 grams: 2/100 = 1/50. Interestingly, the amount of the change needed to be detected half the time (the difference threshold) is almost always indirect proportion to the intensity of the original stimulus. Thus, if a waiter holding a tray on which four glasses had been placed is just able to detect the added weight of one glass, he would

just be able to feel the added weight from two more glasses if the tray were already holding eight glasses. The amount of detectable added weight would always be in the same proportion, in this case 1/4. Regarding the relevance of this bit of information, Weber’s law tells us that what we sense is not always the same as the energy that enters the sense organ. The same magnitude of physical change in intensity can be obvious one time, yet go undetected under different circumstances. This fact has important practical implications. For example, you are chosen to help design the instrument for a new airplane. The pilot wants an easier way to monitor the altitude or height of the plane, so you put in a light that increases the intensity as the plane nears the earth—the lower the altitude, the more intense the light. That way, you assume, the pilot can easily monitor changes in altitude by seeing changes in brightness, right? According to Weber’s law, this would be a dangerous way to monitor altitude. At high altitudes, the intensity of the light would be low, so small changes could be easily detected; but at low altitudes, the intensity would be so great those large changes in altitude—even fatal or dangerous ones— might not be noticed. That is why the people who design instruments for airplanes, cars, and the like need to know about psychophysics. Both Absolute Threshold and Difference Threshold will vary, not only for different people, but also for the same person under different circumstances. These circumstances may include differences in environmental conditions and also internal conditions such as motivation. Our sense organs operate efficiently within certain ranges of stimulus intensity (eyes; 400–700—nm; ears: 20–20,000 Hz). An individual cannot feel the presence of a stimulus below the physical continuum of the stimulus (threshold). Similarly, there is an upper limit above which some stimuli are not perceived by the individual or the organism. This upper threshold is called the Terminal Threshold. For example, if we go on raising or increasing the intensity of sound, there will be a stage which is the Terminal Threshold or Upper Threshold or Upper Limen. For example, if we go on raising the intensity of sound, there will be a single stage when we won’t be feeling sensation but irritation, of course, which is the terminal threshold.

6.3 PSYCHOPHYSICAL METHODS Psychophysical methods are a set of procedures psychologists have

developed to investigate sensory thresholds. “The methods used to study the stimulus—response relationships in which stimuli are varied along a physical dimension are commonly called psychophysical methods” (Underwood, 1965). These psychophysical methods are procedures by which the experimenter may quantify relations between a stimulus and the sensation or experiences that follow. The following are the psychophysical methods given by G.T. Fechner:

6.3.1 Method of Limits The first of these psychophysical methods is known as the method of limits. This method is also known as the Method of Serial Exploration, Method of Minimal Changes, Method of Just Noticeable Difference or Method of Least Noticeable Difference. The use to which the method is put decides the name by which one identifies it. However, the basic idea of establishing limits is contained in all variations of the method of limits. Usually this method is used to determine the threshold of a subject’s sensitivity. The procedure involved in this method consists of the experimenter’s gradually lowering the intensity or value of a stimulus until it is no longer perceived by the subject or by increasingdecreasing the value of two stimuli until it becomes just noticeable different (j.n.d). Or by increasing the value of a stimulus until it is no longer perceived (Terminal Threshold). Any threshold or limen is not a static thing but rather tends to vary within a subject throughout even a short examination period and varies from subject to subject as well. As such, the thresholds have become statistical entities in terms of units of whatever type of stimulus used.

Measurement of absolute threshold The determination of the absolute threshold in this method is most accurately performed by using an ascending and a descending series of presentation. The experimenter gradually increases in an ascending series the stimulus value from a point well below the possible threshold of the subject reports sensation of the stimulus. The experimenter then explores the series in a descending manner by lowering the stimulus from a point well above the sensation point to a point where the subject reports the subject reports no sensation of the stimulus. Both types of trials (ascending and descending) are

repeated several times to provide a more reliable estimate of the threshold. The mid-point between these two determined points is taken as the absolute threshold. The application of this method in the determination of two-point threshold is usually done to demonstrate the difference in cutaneous (skin sensation) sensitivity in one part of the body as compared to another part and find out just how far apart the two points of aesthesiometer must be for the subject to report that she or he feels two points instead of one. The experimenter as such applies to the subject’s upper arm the two points of aesthesiometer when they are very close together. The subject is blindfolded and the procedure is explained to her or him so that she or he understands that she or he is to report whether one or two points are stimulating her or him. Several trials are taken in the ascending series by increasing the distance between the two points until the subject reports two points. The descending series of trials is conducted in the same manner starting with the points very far apart and descending the distance throughout the trials until the subject reports one point. The calculation of the two-point threshold of the subject from these data involves finding the average of all the thresholds discovered as the result of the ascending and descending series. The following table is a representation of one such experiment: Trials Distance in mm

A

D

A

D

A

D

A

D

A

D

23 22 21 20 19 18 17 16 15 14

2 2 2 2 2 2 2 1 1 1

2 2 2 2 2 2 2 2 1 1

2 2 2 2 2 2 2 1 1 1

2 2 2 2 2 2 2 1 1 1

2 2 2 2 2 2 2 1 1 1

2 2 2 2 2 2 2 1 1 1

2 2 2 2 2 2 2 2 1 1

2 2 2 2 2 2 2 2 2 1

2 2 2 2 2 2 2 1 1 1

2 2 2 2 2 2 2 1 1 1

Transition points

16.5

15.5

16.5

16.5

16.5

16.5

15.5

14.5

16.5

16.5

Mean of the Transition points = Sum of all Transition points = 16.5 + 15.5 + 16.5 + 16.5 + 16.5 + 16.5 + 15.5 + 14.5 + 16.5 + 16.5 = 161

Number of Transition points = 10 Mean of the Transition points = 161/10 = 16.10 mm Thus, the mean of individual thresholds would define our accepted absolute threshold value—that stimulus value which will elicit a response 50 per cent of the time. A basic assumption of this method is that people change their response each time the sensory threshold is crossed. For this reason, the threshold for each trial is presumed to lie somewhere between the intensities of the last two stimuli presented. Experimenters obtain an overall estimate of the threshold by computing the average threshold across all individual ascending and descending trials. The use of both ascending and descending series also helps researchers take account of two common tendencies. The first, referred to as errors of habituation, is participants’ tendency to continue to say no in an ascending series and yes in a descending series—independent of whether the participant actually hears the sound. The second, termed as errors of anticipation, is people’s tendency to change their response to a stimulus before such a change is warranted.

Measurement of differential threshold The differential threshold allows the experimenter to answer the problem of just how much change must take place in a stimulus before a subject is able to report accurately a change. The differential threshold varies in much the same fashion as the absolute threshold. The ascending and descending series of presentation are applied here as well for accurate results. Let us take into consideration the weight lifting experiment. To attain the differential threshold value, we need a standard stimulus, the intensity (weight, strength) of which will not vary. We set this standard at a known physical intensity value and then proceed to find out how much the variable stimulus must differ from the standard before the subject reports a j.n.d. We start the variable weight that is lighter than the standard (ascending) and then gradually increase the weight of it or start with a weight that is heavier than the standard (descending) and decrease it slowly and reach at a point when the subject reports them (variable and standard stimuli). We do not stop at this point but instead we continue decreasing the intensity of the variable until subject reports that the variable is now lighter than the standard. We

take the subject through successive experiences or various trials of “heavier”, “equal”, and “lighter”. This procedure is repeated with the ascending series, with the variable weight being set initially so that it is clearly lighter than the standard and then gradually increases the weight. The following table is a representation of one such experiment: Trials Weight in g

A

D

A

D

A

D

A

D

A

D

165 160 155 150 125 120 (St.) 115 110 105 100 75 T+ T–

+ + + + = = = = – – – 137.5 107.5

+ + + + + = = – – – – 122.5 112.5

+ + + + = = – – – – – 137.5 117.5

+ + + + + + = – – – – 117.5 112.5

+ + + + = = – – – – – 137.5 117.5

+ + + + = = – – – – – 137.5 117.5

+ + + + + + = – – – – 117.5 112.5

+ + + + = = – – – – – 137.5 117.5

+ + + + + + – – – – – 122.5 117.5

+ + + + + + – – – – – 122.5 117.5

where St. is the standard stimulus T+ is the transition point, that is, change between + and = signs T– is the transition point, that is, change between – and = signs. Sum of T+ = 137.5 + 122.5 + 137.5 + 117.5 + 137.5 + 137.5 + 117.5 + 137.5 + 122.5 + 122.5 = 1290 Number of trials = 10 .......................Mean T+ = Sum of T– = 107.5 + 112.5 + 117.5 + 112.5 + 117.5 + 117.5 + 112.5 + 117.5 + 117.5 + 117.5 = 1150 Number of trials = 10 .......................Mean T– = Upper Differential Limen (DL) = Mean (T+) – Standard

= 129 – 120 = 9 Lower Differential Limen (DL) = Standard – Mean (T–) = 120 – 115 = 5 Upper DL = 9 Lower DL = 5

Point of Subjective Equality (PSE) = = PSE = 122 Interval of Uncertainty (IU) = Mean (T+) – Mean (T–) = 129 – 115 = 14 IU = 14 Constant Error (CE) = PSE – Standard = 122 –120 =2 CE = 2

Limitations of method of limits (i) Error of habituation: Error of habituation is caused by the subject’s habit of reporting even in the absence of the stimulus and continuing to do so when the stimulus becomes apparent. For example, in a descending series, we keep the weight well above the threshold and then gradually are reduced. Due to the error of habituation, the subject falls into a “habit” or “set” toward giving the response “heavier” and thus continue reporting this even below the threshold. The error of habituation would thus tend to make the descending series threshold lower than the ascending series threshold.

(ii) Error of anticipation: Error of anticipation, which the subject commits by reporting the next value because he expects a change and not because a change is apparent or visible. Such an error would tend to make the ascending thresholds lower and descending thresholds higher. However, these effects can be determined only by comparing ascending and descending series—not by analysing a single trial or a group of ascending or descending trials. Both the errors can be minimised by careful instruction to the subject and by varying the level at which each successive series is started so that the subject does not get “set” for any particular number of stimuli before a change nor is he likely to become habituated.

6.3.2 Method of Constant Stimuli This method is also known as Frequency Method, Method of Right and Wrong Cases, Method of Constant Stimulus Difference, and Constant Method and is one of the oldest psychological method. Traditionally, it has been used for much the same purpose as the Method of Limits, that is, to measure thresholds. According to Woodworth, “The constant method is the most accurate and most widely applicable of all psychophysical methods. It eliminates experimental errors as found in the Method of Limits and Method of Average Error.” In the method of constant stimuli, the range of sound intensities to be tested is selected in advance, and each stimulus is presented many times in an irregular order. Stimuli are chosen so that some stimuli are below the threshold and others are at or above the threshold. In the Method of Limits, the subject is presented a stimulus of gradually changing magnitude (strength, intensity) and is asked to report when the experience ceases (descending series) or when the experience starts (ascending series) but “in the Method of Constant Stimuli, each trial consists of the presentation of an invariable stimulus and the subject is asked to report its presence or absence” (Underwood). Here, the stimuli are not presented in an ascending or descending order of magnitude but rather in a random order.

Measurement of absolute threshold In the usual application of this method, the subject is confronted or faced with the task of reporting to the experimenter whether one stimulus (one

point of asthesiometer) or two points of asthesiometer are felt by him. The experimenter by the preliminary work determines the approximate value of the subject’s absolute threshold. Then a series of stimuli is chosen extending from well below to well above the threshold in random order and the subject’s responses are noted accordingly. Trials Distance in mm

1

2

3

4

5

6

7

8

9

10

19 18 17 16 15 14 13

2 2 2 2 2 1 1

2 2 1 1 2 1 1

1 2 2 2 1 1 1

2 2 2 1 1 1 1

2 2 2 2 2 1 1

2 2 2 1 2 1 2

2 1 2 1 1 2 1

2 2 1 2 2 1 1

2 1 1 2 1 2 2

2 2 2 1 1 2 1

Frequency of Judgements Distance in mm

One-point sensation

Two-point sensation

% of two-point sensation

19 18 17 16 Db 50% 15 Da 14 13

1 2 3 4 5 7 8

9 8 7 6 5 3 2

90 80 70 60b 50a 30 20

The following formula is applied for calculating the Reiz Limen (RL) or Absolute threshold or Stimulus threshold.

where Db is the stimulus value about 50% response = 16 b is the % of value for Db = 60 Da is the stimulus value giving below 50% response = 15 a is the % value for Da = 50 As such

Measurement of differential threshold (DT) The determination of DL by this method requires a standard stimulus against which other stimuli of varying magnitude are judged. Let us take for example the weight lifting experiment that is, judging weight differences. Here we first note the responses accordingly in the trials as +, –, and = which denotes heavier, lighter, and equal and then prepare the frequency table on its basis as given below: Heavier

Lighter

Equal

Weight in g 78 76 74 72 Db 70 St. 68 Da 66 64 62

f

%

f

%

f

%

20 17 15 7 4 2 1 0 0

100 85 75 35 b 20 10 a 5 0 0

0 0 0 5 8 8 15 20 20

0 0 0 25 40 40 75 100 100

0 3 5 8 8 10 4 0 0

0 15 25 40 40 50 20 0 0

Upper Threshold (UT) = where Db is the stimulus value giving nearest % above standard and b is its % value Da is stimulus value giving nearest % below standard and a is its % value

.

Point of Subjective Equality (PSE) =

Interval of Uncertainty (IU) = UT – LT = 74.4 – 65.6 IU = 8.8 Differential Threshold (DL) =

Constant Error (CE) = PSE – Standard CE = 70 – 70 CE = 0 Thus in this method, the randomisation of the stimuli eliminates the error of expectation and habituation which is availed in the Method of Limits. Method of constant stimuli is time-consuming and requires that experimenters pretest the range of stimuli in advance.

6.3.3 Method of Average Error It is also known as Method of Equation and Method of Reproduction or Adjustment. It is one of the oldest and most fundamental of the psychophysical methods and aims at determining equal (equivalent) stimuli by active adjustment on the part of the observer or subject (Guilford). In some types of experimentation, it becomes necessary to deal with the problem of equality of two stimuli. According to Underwood, “the method of average error consists in presenting S (subject) with some constant or standard stimulus and asks him to match it by manipulating a variable stimulus”. This method is used when the experimenter desires the subject to reproduce a stimulus accurately. The stimulus presented is constant and the subject manipulates a variable stimulus until he feels the two are subjectively equal. Each attempt of the subject in terms of amount of error (variable error) between the subjective estimate of the stimulus and the known stimulus value is recorded. The average of these errors is established and this value is taken as a measure of the systematic error involved in the subject’s judgement that the two stimuli were subjectively equal. If the subject tended to vary considerably in the errors he made, then he is considered to have less precision of response. In this way, it is believed that the sensitivity of the subject is determined by his consistency

and variable error. The constant error is stated in terms of the variability. The nearer the mean to the standard stimulus value, the less is his constant error, and smaller the variability of his responses, the greater is his sensitivity. Actually, the method of average error is designed to study the precision of observation or the precision of any matching procedure. In other words, it is used to study the errors which enter in observations.

Method of average error and Muller-Lyre illusion We do not always see things as they exist in physically measured reality. This is demonstrated in Figure 6.1.

Figure 6.1 Muller-Lyre illusion.

Muller-Lyre illusion is an illusion of extent or distance. The two lines (A and B) in the Muller-Lyre illusion are of the same length but the line at the bottom with its reversed arrow heads (B) looks longer (see Figure 6.1). The lengths of the two lines A and B appear to be different but are the same. Here the differences in the direction of the “trials” tend to make line B appears longer than A even though the measurements show that they are exactly of the same length. In using this illusion as a laboratory instrument or device, line B is constructed so that it can be made longer or shorter. The subject is asked to make the length of line B equivalent to that of A. Consequently, we take several matches and then after measuring the length of line B for each setting, we use a measure of central tendency (Mean) of these lines, usually the mean which apparently equal to line A. Sometimes the experimenter sets B much longer than A and sometimes much shorter than A in this process and the subject adjusts the settings so that B is equal to A. Due to the illusionary nature, the B line in Figure 6.1 will always be set consistently shorter than A. Several such trials are taken using both, that is, Right as well as Left hand and both directions—Outgoing/Outward as well Incoming/Inward before we come to draw the conclusion. The trials are written according to the following table: Trials

Direction

1

2

3

4

5

6

7

8

9

10

Right Outgoing/Outward Left Outgoing/Outward Right Incoming/Inward Left Incoming/Inward

Point

of

Subjective

Equality

(PSE)

=

Space Error = Movement

Error

=

Constant Error = PSE – Standard The Constant Error (CE) is stated in terms of variability. The nearer the Mean to the standard stimulus value, the fast is his constant error and the smaller the variability of his sensitivity. Error due to fatigue = Errors in Muller-Lyre Illusion Experiment (i) Space error: Space error occurs because the judgement is influenced systematically by the spatial position of the stimuli, whether they are to the left or to the right of the subject. The space error in Muller-Lyre illusion is calculated by taking the average reproductions of Right and Left trials and finding out their difference. (ii) Movement error: The inward and outward movements made by the subject in adjusting the length of the variable line when produce difference in the sensation of movement lead to movement error in Muller-Lyre illusion experiment. The movement error is calculated by taking the average reproduction of “In” and “Out” trials and finding out the difference. (iii) Constant error: The constant error refers to the amount of error produced while adjusting the feather-headed line (variable stimulus)

with the arrow-headed line (standard stimulus). The difference between the standard stimulus and the variable stimulus is called the constant error. They occur either due to the conditions of the experiment or due to the perceptual biases of the subject. Constant errors represent the systematic tendency to overestimate or under estimate the standard stimulus. Pre-planned random design, changing the order of presentation, practice, and knowledge of results can reduce the errors in Muller-Lyre illusion. But the errors cannot be reduced to nil since Muller-Lyre illusion is universally found.

QUESTIONS Section A Answer the following in five lines or in 50 words: 1. 2. 3. 4. 5. 6. 7. 8. 9. 10. 11. 12. 13. 14. 15. 16.

Define Psychophysics Psychometrics Threshold Absolute Limen Stimulus Threshold Differential Threshold Upper Threshold Weber’s Law Fechner’s Law Just noticeable difference or j.n.d or JND PSE (Point of Subjective Equality) What is Error of Habituation? What is Stimulus Threshold? What do you understand by Stimulus Equality? What is Constant Error? What is the main difference between physical and psychological continua? 17. Error of Expectation 18. Variable and Constant Errors

19. Errors in Method of Limits 20. Constant Errors 21. Problems of Psychophysics

Section B Answer the following questions up to two pages or in 500 words: 1. What is meant by the absolute threshold of sensation? 2. What are just noticeable differences (j.n.d)? What is the relationship between a j.n.d and the background intensity of a stimulus? 3. Define Weber’s law. State in your own words what it means in practical terms. 4. Discuss method of limits. or Describe method of limits. 5. Discuss Fechner’s law. 6. Discuss problems of psychophysics. 7. Explain Weber’s law. 8. What do you understand by just noticeable difference and Weber’s law? 9. Explain method of constant stimuli. 10. What does the term absolute threshold refer to, and what are psychophysical methods? 11. Why is signal detection theory important? 12. What is a differential threshold? 13. Can subliminal messages affect our behaviour?

Section C Answer the following questions up to five pages or in 1000 words: 1. Discuss various concepts of psychophysics. 2. Discuss method of constant stimuli. 3. What is the difference between method of limits and method of constant stimuli? Discuss the method of constant stimuli in detail.

4. Discuss the average error method of psychophysics.* 5. Explain measurement of stimulus threshold with the method of constant stimuli. 6. How will you determine differential limen by the method of constant stimuli? 7. Explain the determination of differential threshold by the method of limits. 8. What is classical psychophysics? Explain how the ‘method of constant stimuli’ is superior to the other methods of psychophysics. 9. Distinguish between absolute and differential threshold. Explain and illustrate Weber’s law in this connection. 10. Define PSE, IU and DL. 11. In weight lifting experiment, the following data is obtained: Wt. in g

Heavier (+) frequency

Lighter (–) frequency

Equal (=) frequency

58 56 54 52 50 48 46 44 42

47 40 33 29 19 14 9 5 3

1 6 9 11 15 15 9 4 0

2 4 8 10 16 21 32 41 47

Name the method and calculate PSE, IU and DL. 12. What is psychophysics? Explain the method of average error in detail.

REFERENCES Andrews, L.B., “Exhibit A: Language”, Psychology Today, pp. 28–33, 1984. Baron, R.A., Psychology, Pearson Education Asia, New Delhi, 2003. D’Amato, M.R., Experimental Psychology, Tata McGraw-Hill, New Delhi, 2004. English, H.B. and English, A.V.A.C., A Comprehensive Dictionary of Psychological and Psychoanalytical Terms, Longmans, Green, New York, 1958. Eysenck, H.J., Arnold, W., and R. Meili, (Eds.), Encycopaedia of Psychology, Search Press, London, 1972.

Fechner, G., Elemente der Psychophysik, Springer, Berlin, 1860. Guilford, J.P., Psychometric Methods, McGraw-Hill Education, 1954. Guilford, J.P., Fundamental Statistics in Psychology and Education, McGraw-Hill, New York, 1965. Guilford, J.P., Fields of Psychology, Van Nostrand, New York, 1966. Guilford, J.P., The Nature of Human Intelligence, McGraw-Hill, New York, 1967. Stevens, S.S., “The surprising simplicity of sensory metrics”, American Psychologist, 17, pp. 29–39, 1962. Townsend, J.T., “Theoretical analyses of an alphabetic confusion matrix”, Perception & Psychophysics, 9, pp. 40–50, 1971a. Townsend, J.T., “Alphabetic confusion: A test of models for individuals”, Perception & Psychophysics, 9, pp. 449–454, 1971b. Underwood, B.J., “False recognition produced by implicit verbal responses”, Journal of Experimental Psychology, 70, pp. 122–129, 1965. Underwood, B.J., Experimental Psychology, Appleton, New York, 1966. Weber, E.H., (1795–1878) “Leipzig physiologist”, JAMA 199 (4), 272–3, 1967 Jan 23, doi.10.1001/jama.199.4.272, PMID 5334161, 1967. Woodworth, R.S., Psychology, Methuen, London, 1945.

7 Learning INTRODUCTION Any response that an organism is not born with is said to have been acquired or learned. From infancy, we are constantly learning new skills, gaining information, and developing beliefs and attitudes. Learning goes on not only in a formal situation but throughout life. Learning, right or wrong, brings about relatively permanent and ephemeral changes in the behaviour of a person. Learning is a key process in human behaviour. It is revealed in the spectrum of changes that take place as a result of one’s experience. Learning may be defined as “Any relatively permanent change in behaviour or behavioral potential produced by experience” (Gordon, 1989). Behavioural changes occurring due to the use of drugs or fatigue or emotions or alterations in motives, growth, or maturation are not considered learning. Systematic changes resulting due to practice and experience and relatively permanent are illustrative of learning.

7.1 SOME DEFINITIONS OF LEARNING According to Woodworth (1945), “Any activity can be called learning so far as it develops the individual (in any respect, good or bad) and makes him alter behaviour and experiences different from what they would otherwise have been.” According to Postman and Egan (1949), “Learning may be defined as the

measurable changes in behaviour as a result of practice and condition that accompany practice.” According to Hilgard and Atkinson (1956), “Learning is a relatively permanent change in behaviour that occurs as the result of practice.” According to G.A. Kimble and Germazy (1963), “Learning is a relatively permanent change in a behavioral or response potentiality or tendency that occurs as a result of reinforced practice.” The phrase “relatively permanent” serves to exclude temporary or momentary behavioural change that may depend on such factors such as fatigue, satiation, and the effects of drugs or alteration in, motives. “Reinforcement” is the crux of behaviourism. Without reinforcement, extinction will occur. “Practice” which means that for learning to emerge, sooner or later, the behaviour must be emitted and repeated (reinforced) occurrences will improve learning. The notion of practice also allows for the exclusion of other behavioural changes of a relativity permanent kind that are generally not considered to be instances of learning, such as native tendencies of particular species (for example, imprinting) and maturational changes (for example, flying in birds). According to Underwood (1966), “Learning is the acquisition of new responses or the enhanced execution of old ones.” According to Crow and Crow (1973), “Learning is the acquisition of habits, knowledge, and attitudes. It involves new ways of doing things, and it operates in an individual’s attempts to overcome obstacles or to adjust to new situations. It represents progressive changes in behaviour . It enables him to satisfy interests to attain goals.” According to Bandura (1977), “Learning is a change in acquired information (and hence in performance potential) that can occur just by virtue of being an observer in the world.” According to Morgan and King (1978), “Learning is defined as any relatively permanent change in behaviour which occurs as a result of practice and experience.” According to Bootzin (1991), “Learning is a long lasting change in an organism’s disposition to behave in certain ways as a result of experience.” According to Crooks and Stein (1991), “Learning is a relatively enduring change in potential behaviour that results from experience.”

According to Baron (1995), “Any relatively permanent change in behaviour potential resulting from experience is called learning.” According to Mangal (2002), “Learning stands for all those changes and modifications in the behaviour of the individual which he undergoes during his life time.” The term “learning” refers to the process by which experience or practice results in a relatively permanent change in behaviour. Learning is such a pervasive and continual process that we can easily overlook how much learning we actually do everyday.

7.2 CHARACTERISTICS FEATURES OF THE LEARNING PROCESS The process of learning has certain distinctive characteristics such as the following: (i) Learning connotes change: Learning is a change in behaviour, for better or worse. Throughout her or his life, an individual acquires new patterns of inner motivations or attitudes, and of overt (external) behaviour. These result from the changes taking place within her or him. At the same time, she or he may be strengthening attitudes and behaviour patterns that are in the process of formation, or weakening old patterns that already have been established. (ii) Learning is a complex process: At one and same time, an individual is: (a) learning new skills or improving those that already are operating. (b) building a store of information or knowledge, and (c) developing interests, attitudes, and ways of thinking. (iii) Learning always involves some kind of experience: One experiences an event occurring in a certain sequence on a number of occasions. If one event happens, then it may be followed by certain other events. For example, one learns that if the bell rings in the hostel after sunset, it means that dinner is ready to be served. They have learned that bell signalled the serving of the food. It is through repeated experience of satisfaction that leads to the formation of habit. Sometimes, one single experience can lead to learning, for example, child strikes a matchstick on the matchbox’s side and gets her or his fingers burnt. Such an

experience makes the child learn to be careful in handling the matchbox in future. (iv) Learning is a change that takes place through practice or experience. However, changes due to growth or maturation, drugs, fatigue, satiation, emotions, etc. are not learning. (v) The behavioural changes that occur due to learning are relatively permanent. Exactly, how long cannot be specified but it must last a fairly long time. Whatever is learnt is stored in memory and therefore becomes enduring, long lasting, and permanent. (vi) We cannot see learning occurring directly. We estimate it by measuring performance. (vii) Learning is an inferred process and is different from performance. Performance is an individual’s observed behaviour or response of action. Let us understand the term “inference”. For example, you are asked by your teacher to remember a multiplication table. You read that table a number of times. Then you say that you have learnt the table. You are asked to recite that table and you are able to do it. The recitation of that table by you is your performance. On the basis of your performance, the teacher infers that you have learned that table. Learning that can be inferred from performance is called potent learning. Learning becomes potent with practice and training. Whereas, learning that cannot be easily inferred from performance is called latent learning. Learning has taken place but has not yet manifested itself in changes in performance. It occurs in the absence of changes in behaviour. This form of learning usually occurs when reward or positive reinforcement is not provided. (viii) Learning is engaged in consciously or unconsciously; it may be “informal” in that it represents learning as an aspect of an individual’s daily situational experiences, or “formal” to the extent that the learning situation is organised according to definite objective, planned procedures, and expected outcomes. (ix) The direction of the learning can be vertical and or horizontal. Vertical learning applies to the addition of knowledge to that which already is possessed in a particular area of knowledge, the improvement of a skill in which some dexterity has been achieved, or the

strengthening of development attitudes and modes of thinking. It is vertical if more facts are covered at higher levels so as to move toward perfection. Horizontal learning means that the learner is widening her or his learning horizons, competence in new forms of skills, gaining new interests, discovering new approaches to problem-solving, and developing different attitudes toward newly experienced situations and conditions. Learning is horizontal if more facts are covered at the same level. As learning proceeds both vertically and horizontally, that which is learned is integrated and organised as functioning units of expanding experiences. (x) Learning is cumulative, with no breaks, until a hundred per cent mastery has been achieved. (xi) Learning is an active process in which the learner is fully aware of the learning situation, is motivated to learn, has intention to learn, and participates in the learning process. A passive person cannot learn. (xii) Learning is goal-directed. The nature of learning is purposeful. For meaningful and effective learning, the purpose of learning must be clear, vivid, and explicit. (xiii) Much of our learning consists of the formation of habit patterns as we are stimulated by conditions that surround us to imitate the behaviour of others or to try out various forms of response. (xiv) Enforced learning can have equally undesirable effects upon young people.

7.3 FACTORS AFFECTING LEARNING (i) Maturation: A child who has not reached a sufficient stage of mental and physical development when she or he tries to perform school tasks characteristic of that stage and that, which entails a higher level of development. However, with proper readiness building procedure, normal development difficulties can be overcome. (ii) Experience: Previous experience determines a child’s readiness for learning. Prior exposure to basic skills is necessary before complex tasks are tackled. (iii) Relevance of materials and methods of instruction: Research has

shown that children are more ready to learn materials that meets their needs and fits their already established interests. They are more ready to learn skills of spelling, reading and writing when they have fun doing them. (iv) Emotional attitude and personal adjustment: Emotional stress blocks readiness for learning especially those resulting from unmet needs, overprotection, rejection in the home, previous experience of school failure, and other home difficulties.

7.4 CONDITIONING Although the term “conditioning” is often used in a much wider context, it is more properly restricted to “simple” forms of learning, in particular to classical and instrumental conditioning, two very active areas of research interest. Psychologists often use the word “conditioning” as a synonym for learning in animals as well as in human beings. Generally, the term ‘conditioning’ refers to acquiring a pattern of behaviour but psychologists have referred it as a “part of an expression that describes a specific process of learning.” (C.G. Morris) According to Srivastava, “Conditioning is a process by which a previously ineffective stimulus (or object or situation) becomes effective in eliciting a lateral response.” Drever defines conditioning as “A process by which a response comes to be elicited by a stimulus, object, or situation other than that to which it is the natural or normal response.” Underwood defines conditioning as a “Procedure for studying learning in which a discrete response is attached to more or less discrete stimulus.” In general, it can be said that when an individual learns to respond in natural manner to an unnatural stimulus, then it can be said that he has conditioned it. The form of learning in which the capacity to elicit a response is transferred from one stimulus to the other is called conditioning. Conditioning can be both classical or Pavlovian or respondent as well as instrumental or operant.

7.4.1 Factors Affecting Conditioning (i) Stimulus characteristics: Traditional classical conditioning theory holds that the nature of the neutral stimulus is unimportant.

(ii) Stimulus generalization: A stimulus similar to the original Conditioned Stimulus (CS) also elicits the Conditioned Response (CR). (iii) Stimulus discrimination: A stimulus distinct from the CS does not elicit the CR. (iv) Timing: Conditioning is strongest when the CS is presented immediately before the UCS (usually less than a few seconds). If presented after or at the same time there is little or no conditioning. It was traditionally believed that if the UCS is presented after too long a delay, conditioning does not occur. (v) Predictability: Conditioning is strongest when the CS is always followed by the UCS (that is, reliably predicts the UCS). (vi) Signal strength: Conditioning is faster and stronger when the UCS is stronger (that is, louder, brighter, more painful, etc.) (vii) Attention: A subject is more likely to become conditioned to a stimulus that they are paying attention to. (viii) Second order conditioning: Once conditioned, a CS can serve as the UCS to another neutral stimulus. Two models of learning demonstrated the research activities of learning psychologists during the early part of this century. One model was developed by Ivan Petrovich Pavlov (1849 – 1936) and is commonly called classical conditioning; the other model was suggested by Edward Lee Thorndike (1874 – 1949) and refined by Burrhus Frederic Skinner (1904 – 1990) and is referred to as instrumental or operant conditioning. The initial experiments of both groups attempted to identify the conditions for learning using nonhuman subjects. Pavlov used his famous salivating dogs, while Thorndike studied the effects of reward on the behaviour of cats. Skinner employed rats in his early experiments, then pigeons, and finally among other species, humans.

7.4.2 Classical Conditioning or Pavlovian or Simple or Respondent Conditioning Classical conditioning was the first type of learning to be discovered and studied within the behaviourist tradition (hence the name classical). The term ‘classical’ means “in the established manner” and “classical conditioning” refers to conditioning in the manner established by the Russian physiologist,

Ivan Petrovich Pavlov (1849-1936), a Russian scientist trained in biology and medicine, the first investigator to study this process extensively in the laboratory. Scientific references to classical conditioning are commonly associated with Ivan P. Pavlov, the Russian physiologist who was awarded a Nobel Prize in 1904 for his research on digestive functioning. He was a major theorist in the development of classical conditioning. Other notable contributions of Ivan P. Pavlov include discovery of Conditioned Reflexes; CS, US, CR, UR; Conditioned Inhibition; and Excitatory and Inhibitory Inhibition. The classical conditioning was first discovered by Ivan P. Pavlov (1895), while he was studying the digestive processes in animals. It is also known as simple conditioning; simple because the organism enters situation only in a high mechanical or automatic way. Association is an outstanding aspect as well as centrally important in classical conditioning. Here the organism learns to respond in a distinct manner even in the absence of the particular stimulus. It is crucial for an association to be formed between the unconditioned and the conditioned stimulus. For that to happen, it is important for the two stimuli to occur close together in time. Conditioning is usually greatest when the conditioned stimulus (tone) precedes the unconditioned stimulus (food) by a short interval of time (about half a second is ideal) and stays on while the unconditioned stimulus is presented. If the unconditioned stimulus (food) is presented shortly before the conditioned stimulus (tone), however, there is little or no conditioning. This situation is called backward conditioning. Conditioned stimulus (tone) allows the dog to predict that the unconditioned stimulus (food) is about to be presented. The tone provides a clear indication that food is about to arrive, and so it produces an effect or response, that is salivation. Pavlov was not the first scientist to study learning in animals but he was the first to do so in an orderly and systematic way, using a standard series of techniques and a standard terminology to describe his experiments, and their results. He chose food as the stimulus and secretion of saliva as the response. In the course of his work on the digestive system of the dogs, Pavlov had found that salivary secretion was elicited not only by placing food in the dog’s mouth but also by the sight and smell of food and even by the sight and sound of the technician who usually provided the food. He observed that dogs deprived of food began to salivate when one of his assistants walked into the room. He began to investigate this phenomenon and established the laws of

classical conditioning. For Pavlov at first, these “psychic secretions” (because it is caused by psychological process, not by food actually being placed in the mouth) merely interfered with the planned study of digestive system. From about 1898 until 1930, Pavlov occupied himself with a study of this subject. Pavlov also found he could train a dog to salivate to other stimuli, for example a tone. Some neutral stimulus such as a bell (or tone or light) is presented just before some effective stimulus (food). Dogs (and other animals) salivate when food is put in their mouths. A response such as salivation, originally evoked or elicited only by the effective stimulus (food) eventually appears when initially neutral stimulus is presented. Pavlov’s dogs began to salivate at the sound of the bell, which naturally does not make the dog salivate. The response is said to have become conditioned. But since they had learned that the bell signaled the appearance of food, their mouths watered on cue even in the absence of food. The dogs had been conditioned to the bell which normally wouldn’t have caused salivation. Classical conditioning seems easiest to establish for involuntary reactions mediated by the autonomic nervous system. In Pavlov’s terminology, the food is an unconditioned stimulus (US or UCS). Unconditioned or natural stimulus will naturally (without learning) elicit or bring about a reflexive or involuntary response. Classical conditioning starts with a reflex: an innate, involuntary behaviour, for example, salivation, eye blinking, etc. It invariably (unconditionally) elicits salivation, which is termed as unconditioned response (UR or UCR). The ticking of a metronome or tone before conditioning is a neutral or orienting stimulus and during conditioning, it is repeatedly paired with the natural or the unconditioned stimulus. The elicitation of the conditioned response (CR, salivation) by the conditioned stimulus (ticking of the metronome or tone) is termed as conditioned reflex or response, the occurrence of which is reinforced by the presentation of the unconditioned stimulus (food). Now, the neutral or orienting stimulus (ticking of the metronome or tone) is transformed into a conditioned stimulus (CS), that is, when the CS is presented by itself it elicits or evokes or produces or causes the CR (salivation, which is the same involuntary response as the UR; the name changes because it is elicited or evoked by a different stimulus).

Paradigm of classical conditioning or specific model of classical

conditioning or the three stages of classical conditioning US or UCS Unconditioned stimulus UR or UCR Unconditioned response CS Conditioned stimulus CR Conditioned response Stage 1: Before conditioning In order to have classical or respondent conditioning, there must be present a stimulus that will automatically or reflexively elicit a specific response. This stimulus is called the unconditioned stimulus or US or UCS because there is no learning involved in connecting the stimulus and response. Here the US or UCS is food. There must also be a stimulus that will not elicit this specific response, but will elicit an orienting response (see Figure 7.1). This stimulus is called a neutral stimulus or an orienting stimulus, for example a tone.

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Figure 7.1 Classical conditioning: Before conditioning.

Stage 2: During conditioning During conditioning, the neutral stimulus will first be presented, for example tone, followed by the unconditioned stimulus (food). Over time, the learner will develop an association between these two stimuli, that is he will learn to make a connection between the two stimuli, the tone and the food. An association is developed (through pairing) between the neutral stimulus, that is tone and the unconditional stimulus, that is food so that the animal or dog responds to both events and stimuli in the same way (see Figure 7.2).

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Figure 7.2 Classical conditioning: During conditioning.

Stage 3: After conditioning After conditioning, the previously neutral or orienting stimulus, for example, a tone will elicit the response previously only elicited by the unconditioned stimulus (food) that is salivation. The stimulus in now called a conditioned stimulus (CS) because it will now elicit a different response as a result of conditioning or learning. The response is now called a conditioned response (CR) because it is elicited by a stimulus as a result of learning. The two responses, unconditioned (salivation) and conditioned (salivation) look the same, but they are evoked or caused by different stimuli and are therefore given different labels. After conditioning, both the US or UCS and the CS will elicit the same involuntary response. The animal or dog learns to respond reflexively to a new stimulus (see Figure 7.3).

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Figure 7.3 Classical conditioning: After conditioning.

Basic processes or features about classical conditioning Generalization or Stimulus Generalization: “Generalization” refers to the fact that the strength of the conditioned response, for example, salivation depends on the similarity between the test stimulus and the previous training stimulus. The conditioned response of salivation was greatest when the tone presented on its own was the same as the tone that had previously been presented just prior to food. However, a smaller amount of salivation was obtained when a different tone was used. Stimulus generalization is, performing a learned response in the presence of similar stimuli. For example, if the dog has been classically conditioned at the sound of a dinner bell, it will salivate to a ringing telephone or to high-pitched notes on a piano, etc. John Brodaeus Warson (1878–1958) and his student Rosalie Rayner showed how rapidly generalization occurs (Watson and Rayner, 1920). They classically conditioned an eleven month old boy named Albert to fear a harmless laboratory rat by repeatedly pairing presentation of the rat with the loud noise. Soon, little Albert began to show fear at the sight of the rat alone, without the noise following. Moreover, his fear appeared to generalize to other furry objects like a rabbit or a dog, a sealskin coat, even a bearded Santa Clause mask. More similar a subsequent stimulus is to the one that prevailed during learning; the more likely it is that generalization will occur. Certain situations or objects may resemble each other that the learner reacts to one as the other. Pavlov had termed the dog’s salivating at the sound of the bell as Irradiation, which is known as Irradiation Generalization today. Several psychologists through experimentation found that

generalization gradient show that the tendency to generalize increases with the similarity of new stimuli to the training stimuli (Glaser, 1962; Statts and Statts, 1963). Discrimination or Stimulus Discrimination: Discrimination is an important aspect of conditioning. Discrimination is learning to make a particular response only to a particular stimulus. For example, you train the dog to salivate only when it hears a particular bell and to ignore all other bells. Here the individual makes different responses to two or more stimuli and exercises more control over behaviour. Experimental Extinction: The repeated presentation of the conditioned stimulus (tone) in the absence of the unconditioned stimulus (food) removes the conditioned response (salivation). When Pavlov presented the tone on its own several times without being followed by food, there was less and less salivation and will result in the gradual disappearance or extinction of the conditioned response. When the conditioned stimulus (CS) appears alone so often that the subject no longer associates it with the unconditioned stimulus (UCS or US) and stops making the conditioned response (CR) then this process are referred to as extinction. Extinction is an important process. It is the removal of reinforcement following the occurrence of some response that has been reinforced in the past. Experimental extinction or disappearance of conditioned response or salivation occurs when the tone no longer predicts the arrival of the food. Extinction effects are most readily obtained when trials are massed. Several psychologists as Schlosberg (1934), Reynolds (1945), and Guthrie (1952) have found that typical extinction procedures effect in reducing the effects of conditioned responses. Spontaneous Recovery: Extinction does not mean that the dog has totally lost the conditioned reflex or response. When dog is brought back to the experimental situation, the dog salivates to the conditioned stimulus, that is, tone. This is called spontaneous recovery. Pavlov had trained his dogs to salivate at the sound of the bell (CS) and then caused the learning to extinguish. But after a few days, he took them again, and found that at the sound of the bell, their (dogs’) mouths watered without training. This phenomenon is called spontaneous recovery but spontaneous recovery indicates that learning is not permanently lost.

Theories of classical conditioning Different psychologists are of different views regarding classical conditioning. The Stimulus-Response (S-R) theorists have explained it in that context whereby the Stimulus-Stimulus (S-S) theorists have explained it according to their own views. Stimulus-Response learning (S-R learning) stands for any kind of learning assumed to be fundamentally governed by the forming of some link or bond between a particular stimulus and a specific response. Learning based on the association between two stimuli is called StimulusStimulus (S-S) learning. Some of the theories are discussed below: The S-S theorists believe that in classical conditioning, an association of the afferent state of affairs is produced by the conditioned stimulus with the afferent activity produced by the unconditioned stimulus (UCS). According to this theory, one stimulus that is the conditioned stimulus (CS) gains the property of initiating, eliciting, or evoking the sensory consequences or the central nervous system activities that are characteristics of the second stimulus that is the unconditioned stimulus (US). Supporters of this viewpoint include Spence (1951), Woodworth and Schlosberg (1954), Bitterman (1965) and Konorski (1967). Edwin Ray Guthrie (1935, 1952, and 1959) on the other hand lays emphasis on the S-R relationships and points out that it is the characteristic of an organism that whenever a response occurs, it is immediately and completely associated with all stimuli present at that instant. Thus, according to this viewpoint, conditioning should be analysed on the basis of the description of the response and the specification of all afferent activity occurring at the same time. The response at first may be UR but after trials its form and temporal characteristic change. The response-produced stimuli generated by organism’s reactions are an important part of the total afferent state in such conditioning.

Factors influencing classical conditioning There are four major factors that facilitate the acquisition of a classically conditioned response: (i) The number of pairings: Repeated pairings US + CS, US + CS... >

learning—doesn’t happen on single pairing—generally more pairings, the stronger the conditioned response. (ii) The intensity of the unconditioned stimulus: If a conditioned stimulus is paired with a very strong unconditioned stimulus, the conditioned response will be stronger and acquired more rapidly compared to pairing with a weaker unconditioned stimulus. (iii) How reliably the conditioned stimulus predicts the unconditioned stimulus: The neutral stimulus must reliably predict the occurrence of the unconditioned stimulus. (iv) Spacing of pairing: This is the temporal relationship between the conditioned stimulus and the unconditioned stimulus. If pairing CS + US follows too rapidly slower learning—if pairing CS + US too far apart slower learning—CS and US shouldn’t occur alone— intermittent pairing reduces rate and strength.

7.4.3 Instrumental or Operant Conditioning “A human fashions his consequences as surely as he fashions his goods or his dwelling. Nothing that he says or does is without consequences” (Norman Cousins). The term “instrumental conditioning” was first suggested by Hilgard and Marquis (1940) as the behaviour of organism is instrumental in determining the stimulation of the immediately succeeding moments. The reward is response contingent. Earlier B.F. Skinner (1935) had suggested the term “operant” for the same fact. According to Bernard “Instrumental conditioning involves the active participation of the organism to a much greater extent than does classical conditioning.” Reward or punishment is an integral part of instrumental conditioning. Need, satisfaction, and relief from tension or avoidance of punishment are all part of the total process. Learning to make or to withhold a particular response of its consequences has come to be called operant conditioning. An important difference between operant and classical conditioning usually involves reflexive or involuntary responses, whereas operant conditioning usually involves voluntary ones. It is the stimulus that follows a voluntary response that changes the probability of whether the response is likely or unlikely to occur again. There are two types of consequences: positive (sometimes called pleasant) and negative (sometimes called aversive or unpleasant). These can be added to or taken

away from the environment in order to change the probability of a given response occurring again. Thorndike labelled this type of learning— instrumental. Skinner renamed instrumental as operant because it is more descriptive (that is in this learning, one is “operant” on, and is influenced by the environment). “Operant conditioning”, in other words, is learning to obtain reward or to avoid punishment. In classical conditioning, reward (food) is not response contingent. But in instrumental conditioning, the reward is response contingent. Laboratory experiments of such conditioning among small mammals or birds are common. Rats or pigeons may be taught to press levers for food; they also learn to avoid or terminate electric shock. The major theorists for the development of operant or instrumental conditioning are Edward Lee Thorndike, John Brodaeus Watson, and B.F. Skinner. To the American psychologist Edward Lee Thorndike must go the credit for initiating the study of instrumental conditioning. Thorndike began his studies as a young research student at about the times that Pavlov was starting his work on classical conditioning. Our environment, Skinner the leading behaviourist in modern psychology argued, is filled with positive and negative consequences that mould or shape our behaviour as the piece of fish moulded the behaviour of Thorndike’s cat. According to instrumental conditioning, consequences of any behaviour determine its probability of occurrence. The best-known example of instrumental conditioning is provided by the work of B.F. Skinner (1904–1990). Notable contributions of B.F. Skinner include Operant Conditioning, Operant Chambers, Schedules of Reinforcement, and Functional analysis. He placed a hungry rat in a small box (often called a Skinner box) containing a lever. When a rat pressed the lever, a food pellet appeared. The rat slowly learned that food could be obtained by pressing, and so it pressed the lever more and more often. Our friends and families control us with their approval or disapproval. Our jobs control us by offering or withholding money. Our schools control us by passing or failing us thus affecting our offering access to jobs. To Skinner, infact, the distinctive patterns of behaviour that each person has are merely the product of all the many consequences that person has experienced. Thorndike’s typical experiment involved placing a cat inside a “puzzle box”, an apparatus from which the animal could escape or get food only by pressing a panel, opening the door or pulling a loop of string. Thorndike

measured the speed with which the cat gained its release from the box on successive trials. He observed that on early trials, the animal would behave aimlessly or even frantically, stumbling on the correct response purely by chance; with the repeated trials, however, the cat eventually would execute this response efficiently with a few seconds of being placed in the box. One of the simplest ways of establishing that change in behaviour results from the temporal relationship (in relation to time) between the conditioned stimulus and the unconditioned stimulus in classical conditioning or between the response and the reinforcer in an instrumental conditioning case. A gap of even a few seconds between the rate of pressing the lever and the delivery of food will seriously interfere with the animal’s ability to learn the connection. However, though the operant behaviour is voluntary, they can still be influenced by external factors, in particular, by their own consequences. Consequences determine the fate of behaviour. In instrumental conditioning, the reward is response contingent. These consequences can either increase or decrease the frequency of operant response. A consequence that causes the behaviour to be repeated (to increase its frequency) is called reinforcement or reward. Much of instrumental conditioning is based on the law of reinforcement: the probability of a response occurring increases if that response is followed by a reward or positive reinforcer such as food or praise. The effects of a reward are greater if it follows shortly after the response has been produced than if it is delayed. A consequence that suppresses a behaviour (decreases its frequency) is called punishment. Punishment weakens behaviour by adding a negative stimulus. After a response, a negative or aversive stimulus is added which weaken the frequency or occurrence of the response. Of course, what is regarded or punishing differ from person to person. It is much more objective to define reinforcement and punishment in terms of their effects on subsequent behaviour that is whether they increase or decrease the frequency of the response. According to D’Amato, “Instrumental conditioning is learning based on response contingent reinforcement that does not involve choice among experimentally defined alternatives.” Here, the subject’s responses become the instrument of reinforcement. Reinforcement is the basis of instrumental conditioning which might be positive as well negative in nature. Following an action or response with something pleasant is called positive reinforcement as giving the dog food when it performs a trick. On the other

hand, negative reinforcement following a response by removing that is unpleasant as the dog learns to press the bar to turn off an electric shock. These types of reinforcers are often called aversive or noxious stimulus and conditioning in which such stimulus is used is called aversive conditioning but positive reinforcement is given to learn is called appetitive conditioning. On the basis of reinforcement, Conorski (1948) has classified instrumental conditioning in the following manner: (i) Reward instrumental conditioning: It is also known as nondiscriminative conditioning. In Skinner’s original conditioning experiment, the rat was first allowed to get accustomed to or used to the box so that it may not get frightened. Then as the animal was put in the box, it began to explore until finally pressing the bar and getting the food. After continued exploration, the rat learned to press the bar and attain food. The rat’s operation (press the bar) here was to do so to get food (reward). (ii) Avoidance instrumental conditioning: Here, the negative reinforcement is used to promote learning to prevent the unpleasant condition from occurring. Avoidance conditioning with animals usually includes some sort of warning device like light, buzzer, electric shock, and the like. (iii) Omission or inactive instrumental conditioning: In this type of conditioning, the organism learns to omit the response that does not provide positive reinforcement or reward. In such learning, the organism comes to know that if he will elicit such particular response he will fail to get reward, and as such, he learns to omit those responses. This type of conditioning is also called as inactive conditioning. (iv) Punishment instrumental conditioning: This type of conditioning is very common. From the time, we are very young; we learn that if we violate certain codes of conduct or behaviour, we may get punished or punishment. As such, we become conditioned to the act of not repeating due to punishment. Through punishment, certain behaviour is extinguished.

Theories of operant conditioning Two theories are very popular in the field of instrumental or operant

conditioning: (i) Inhibition theory: According to this theory, if the CS is regularly presented for many seconds before the US, an inhibition of delay is built and the CR occurs late only after the onset of the CS. If the US is altogether omitted then inhibition develops with greatest rapidity and results in extinction. When CS and US are paired or are closely massed or if they are continued for weeks, then gradual diminition of CR occurs. Pavlov believed that activity of the nervous system can be categorised as excitory or inhibitory with former being associated with reflexes and the latter with the non-occurrence. It is so because the cortical cells under the influence of the conditioned stimulus always tend to pass through sometimes very slowly into a state of inhibition. (ii) Interference theory: Guthrie has explained the instrumental conditioning on the basis of three types of situations that include the bulk of the instrumental procedure, usually characterised as “extinction”. In each situation, the key to successful replacement of the unwanted response involves a recombination of stimuli and responses so that the new response becomes conditioned to the new stimulus and vice versa.

Determinants or factors of instrumental conditioning Since conditioning is referred to as a process in which the capacity to elicit or evoke a response is transferred from one stimulus to another, there happens to be several factors that influence the rate of instrumental conditioning. These factors are as follows: (i) Reinforcement: Reinforcement is a prominent factor of conditioning since conditioning depends on the nature and amount of reinforcement. Hunty (1958) found that the more is the amount of reinforcement, the better is conditioning. Behaviour is maintained by reinforcement; to eliminate the behaviour, find and eliminate the reinforcer. (ii) Number of reinforcements: The association between stimulus and response depends on the number of reinforcements. The number of reinforcements positively and significantly helps in establishing a strong association between stimulus and response. The number of reinforcements refers to the amount of reinforcements given in the trials.

Bacon (1962, 1965) found that the amount of reinforcement helps in increasing or improving the learning. (iii) Contiguity: One of the basic learning conditions is contiguity, the simultaneous occurrence of stimuli and the response. Classical conditioning involves contiguity of the conditioned and unconditioned stimulus. Instrumental conditioning involves contiguity of the response and the reinforcing stimulus or reward. It is one of the necessary learning conditions for developing associations between stimulus and the response (Guthrie, 1952). Association is the basis of all kinds of learning. (iv) Motivation level: Motivation level has been suggested as a prominent factor for learning. The motivation level of the organism or the subject helps in establishment of strong association between the stimulus and the response. Thorndike from his experimental studies found motivation essential for conditioning and that one way to speed up the process and maximise the likelihood that the correct response will be discovered is to increase motivation. Deverport (1956) also found the same results from his experimental study.

7.4.4 Types of Reinforcement It is the consequences of behaviour that determines its fate. The “law of effect”, originally proposed by Thorndike (1911) becomes the keystone of instrumental behaviour. Social approval and parental attention are as effective reinforcers for some types of behaviour as food and water are for others. Behaviour is maintained by reinforcement. Therefore to eliminate the behaviour, find and eliminate the reinforcement. Reinforcement is of two types: (i) Positive reinforcement: In a positive reinforcement, when a hungry cat presses a lever and receives a pellet of food, lever pressing is being positive reinforcement and is likely to occur again. The frequency of a response increases because that response causes the arrival of a subjectively satisfying stimulus. The term ‘reinforcement’ always indicates a process that strengthens behaviour; the word positive has two cues associated with it. First, a positive or pleasant stimulus is used in the process. Second, the reinforcer is added. In positive reinforcement, a

positive reinforcer is added after a response and increases the frequency of the response or the rate of occurrence of the response or desired behaviour. There are two major types of positive reinforcers or rewards: (i) Primary reinforcers: “Primary reinforcers” are stimuli that are needed to live, for example foods, water, air, sleep, and so on. (ii) Secondary reinforcers: “Secondary reinforcers” are rewarding because we have learned to associate them with primary reinforcers. Secondary reinforcers include money, praise, appreciation, and attention. (ii) Negative reinforcement: In contrast, when behaviour is followed by the removal of an unpleasant stimulus, negative reinforcement occurs. The term “reinforcement” always indicates a process that strengthens behaviour; the word negative has two cues associated with it. First, a negative or aversive stimulus is used in the process. Second, the reinforcer is subtracted. In negative reinforcement, after the response, the negative reinforcer is removed which increases the frequency of the response or the rate of occurrence of response or behaviour. Negative reinforcement tends to increase the frequency of the response that precedes it. There are two types of negative reinforcement: escape and avoidance. The organism tries to escape from or avoid the unpleasant stimulus by performing the behaviour that enabled it to do so before. In general, the learner must first learn to escape before she or he learns to avoid. A cause-and-effect relationship exists between a particular behaviour and the outcome that follows it. In a negative reinforcement, the frequency of the response increases because the response was caused by the removal of some subjectively unpleasant stimulus. For example, when a rat presses a lever that turns off an electrical shock, lever pressing is negatively reinforced. Here the rat is engaging in escape learning, pressing the lever allows it to escape from the shock. Alternatively, pressing the lever might enable the rat to stop the shock from being turned on and so avoid it. This is called avoidance learning. Both escape and avoidance responses can be established through negative reinforcement. Negative reinforcement and punishment both involve aversive stimuli, such as electric shock. Humans and other species learn to behave in ways that

reduce their exposure to aversive stimuli just as they learn to increase their exposure to positive reinforcers or rewards. When behaviour is followed by the arrival of an unpleasant stimulus, punishment occurs. Punishment tends to decrease the frequency or occurrence of the response that precedes it. The organism tries to prevent the unpleasant stimulus from occurring another time by not performing the behaviour again. Instrumental conditioning in which a response is followed by an aversive or unpleasant stimulus is called punishment training. The aversive stimulus should occur shortly after the undesirable response, otherwise the effects of the aversive stimulus are reduced. Skinner claimed that punishment does not produce new learning, instead, suppresses certain behaviours temporarily. Estes (1944), through his research, suggested that effects of punishment are short-lived.

7.4.5 Reinforcement Schedules or Schedules of Reinforcement Schedule of reinforcement is the way in which rewards are given for appropriate behaviour. A continuous reinforcement schedule is one in which the reinforcer or reward is given after every response. Continuous reinforcement is providing a reward each time the desired behaviour occurs. It works best for establishing a conditioned operant response. However, it is very rare in everyday life for our actions to be continuously reinforced. Continuous reinforcement leads to the lowest rate of responding. Once a response has been established, however, the best way to maintain is the partial reinforcement schedule. In partial reinforcement schedule, only some of the responses are rewarded. Partial reinforcement schedule is a pattern of reinforcement in which reinforcement occurs intermittently (see Table 7.1). There are four main schedules of partial reinforcement and are discussed below: (i) Fixed ratio schedule: The behaviour is rewarded after it occurs a specific number of times. Every nth, like every fifth or tenth response is rewarded. A reinforcer is given after a specified number of correct responses. This schedule is best for learning a new behaviour. (ii) Variable ratio schedule: A reward might be given after ten responses, sometimes after seven, still other times fifteen or twenty and so on. A reinforcer is given after a set number of correct responses. After

reinforcement, the number of correct responses, necessary for reinforcement, changes. This schedule is best for maintaining behaviour. (iii) Fixed interval schedule: A reward is delivered the first time the behaviour occurs after a certain interval of time has elapsed. The first correct response after a set amount of time, for example 60 seconds, has passed is reinforced, that is a consequence is delivered. The time period required is always the same. (iv) Variable interval schedule: A reward may be given after a variable time interval has passed. The first correct response after a set amount of time, for example 60 seconds has passed is rewarded or reinforced. After the reinforcement, a new time period (shorter or longer) is set with the average equaling a specific number over a sum total of trials. Table 7.1 Various schedules of reinforcement and their outcomes Schedule

Outcome

Continuous

moderate rate of response; low response to extinction

Fixed-ratio

very high rate of response; low resistance to extinction

Variable-ratio

high rate of response; high resistance to extinction

Fixed-interval

slow rate of response; low resistance to extinction

Variable-interval

steady rate of response; high resistance to extinction

Variable schedules, especially variable ratio leads to very fast rates of responding. The probability of a response has been found to decrease if it is not followed by a positive reinforcer. This phenomenon is called experimental extinction. No longer, reinforcing a previously reinforced response using either positive or negative reinforcement, results in the weakening of the frequency of the response. Those schedules of reinforcement associated with the best conditioning also show the most resistance to extinction. It has been found that the rats who have been trained on the variable ratio schedule kept responding in extinction (in the absence of reward or reinforcer) longer than rats on any other schedule, whereas rats trained with continuous reinforcement stop responding the soonest.

7.4.6 Classical and Operant Conditioning: A Comparison Two forms of conditioning—classical or Pavlovian or respondent and operant or instrumental have some similarities and differences.

Similarities Some of the major similarities are as follows: (i) In classical conditioning, the organism learns that the conditioned stimulus (CS) is the signal or sign for the occurrence of unconditioned stimulus (US or UCS) because of their temporal and spatial contiguity. Likewise, in operant or instrumental conditioning, the subject (rat or pigeon) is placed in the Skinner box, which presents a new stimulus situation, and the organism learns to press the lever. The response may be considered as an action leading to food being dropped in the pellet. The stimulus in the box and the sight of the lever may be considered as conditioned stimulus (CS). Lever pressing is a conditioned response (CR) that is followed by food on the pellet. Thus, operant conditioning has some elements of classical conditioning. In both kinds of conditioning—classical and instrumental, food is used as the reward. (ii) Both forms of conditioning are examples of simple learning. In both types of conditioning same kinds of processes such as extinction, generalization, discrimination, and spontaneous recovery are observed. Let us study them as a table as in Table 7.2. Table 7.2 Differences between classical and instrumental conditioning Classical conditioning

Instrumental conditioning

The responses are under the control of some stimulus because they are reflexes, automatically elicited by the appropriate stimulus. Such stimuli are selected as unconditioned stimuli and responses elicited by those are known as unconditioned responses. Thus, classical conditioning in which unconditional stimulus elicits response, is often called response conditioning. Involuntary responses are conditioned.

The responses are under the control of organism and are voluntary or operant responses. Voluntary responses are conditioned.

The unconditioned and conditioned stimuli are well defined.

The conditioned stimulus is not defined. Moreover, what is called reinforcer in the operant conditioning is called unconditioned stimulus in instrumental conditioning.

The experimenter controls the occurrence of the unconditioned stimulus.

The occurrence of reinforcer is under the control of the organism. The subject has to be active in

Thus, for US or UCS in classical conditioning, the organism remains passive. A passive animal is presented with various conditions and unconditioned stimuli.

order to be reinforced. Learning involves the human or animal interacting actively with the environment.

In both forms of conditioning, the technical terms used to characterise the experimental proceedings are different. What is called reinforcer in instrumental or operant conditioning is called unconditioned stimulus in classical conditioning. A US or UCS has got two functions. In the beginning, it elicits the response and reinforces the response to be associated and elicited later on by the conditioned stimulus.

What is called unconditioned stimulus in classical conditioning is called reinforcer in instrumental conditioning.

The reward is not response contingent.

The reward is response contingent.

7.5 TRANSFER OF TRAINING Transfer of training means the influence of the learning of one skill has on the learning or performance of another. It is the application of a skill learned in one situation to a different but similar situation. In psychology, transfer of training is the effect of having learned one activity on an individual’s execution of other activities. Transfer of training may be defined as the degree to which trainees apply to their jobs the knowledge, skills, behaviours, and attitudes they gained in training. Transfer of training or as it is sometimes referred to as “transfer of learning” means the ability of a trainee to apply the behaviour, knowledge, and skills acquired in one learning situation to another. “Transfer of training”, as it relates to workplace training, refers to the use put by training participants of the skills and knowledge they learned to their actual work practices. Transfer of training is the influence the learning of one skill has on the learning or performance of another. Will knowledge of English help a person learn French? Are skillful table-tennis players generally good lawn-tennis players? Can a child who does not know how to add learn to multiply? Such questions represent the problems of transfer of training. Since Baldwin and Ford’s (1988) review of the literature over a decade ago, considerable progress has been made in understanding factors affecting transfer. Much of the research has focused on training design factors that influence transfer (cf. Kraiger, Salas and Cannon-Bowers, 1995; Paas, 1992; Warr and Bunce, 1995). Another stream of research has focused on factors in the organisational environment that influence individuals’ ability and opportunity to transfer (Rouillier and Goldstein, 1993; Tracey, Tannenbaun and Kavanaugh, 1995). Other researchers have focused on individual

differences that affect the nature and level of transfer (Gist, Bavetta, Stevens, 1990; Gist, Stevens, Bavetta, 1991). Finally, recent work has focused on developing instruments to measure transfer and its antecedent factors in the workplace (Eiwood Holton, Bates, Ruona, 1998; Holton, Bates, Seyler, and Carvalho, 1997).

7.5.1 Types of Transfer of Training Basically three kinds of transfer of training can occur: positive, negative, and zero. (i) Positive transfer occurs when a previously acquired skill enhances one’s performance of a new one. Positive transfer occurs when solving an earlier problem makes it easier to solve a later problem, just as when a skill developed in one sport helps the performance of a skill in another sport. (ii) Negative transfer is an obstacles to effective thinking. Negative transfer occurs when the previously acquired skill impairs one’s attempt to master the new one, just as when a skill developed in one sport hinders the performance of a skill in another sport. Negative transfer occurs when the process of solving an earlier problem makes later problems harder to solve. It is contrasted with positive transfer. Learning a foreign language, for example, can either hinder the subsequent learning of another language. A better understanding of the processes of thought and problem solving can be gained by identifying factors that tend to prevent effective thinking. Some of the more common obstacles, or blocks, are mental set, functional fixedness, stereotypes, and negative transfer. A mental set, or “entrenchment,” is a frame of mind involving a model that represents a problem, a problem context, or a procedure for problem solving. When problem solvers have an entrenched mental set, they fixate on a strategy that normally works well but does not provide an effective solution to the particular problem at hand. (iii) Zero transfer occurs where one type of learning or learning of one skill has no impact on the learning of a new skill or learning.

7.6 SKILL LEARNING

“Skill learning” means the gradual learning of new skills such as cognitive, motor, and perceptual skills. One of the most valuable things a teacher can do is to help students prepare for lifelong learning. Improved learning skills— concentrating, reading and listening, remembering, using time, and more— are immediately useful and will continue paying dividends for a long time. Personal motives for learning can be immediate or long-term, extrinsic or intrinsic. You may be eager to learn because its fun now, or it will be useful later, or both. Study is “the process of applying the mind in order to acquire knowledge” (Webster’s Dictionary). So study skills are learning skills that are also thinking skills when study includes “careful attention to, and critical examination and investigation of, a subject.” Because learning and thinking are closely related, modern theories of learning (constructivism) emphasize the importance of thinking when we learn.

7.6.1 Types of Skills There are a number of skills such as the following: Cognitive—or intellectual skills that require thought processes Perceptual—interpretation of presented information Motor—movement and muscle control Perceptual motor—involve the thought, interpretation and movement skills The teaching of a new skill can be achieved by various methods: Verbal instructions Demonstrations Video Diagrams Photo sequences

7.6.2 Fitts and Posner’s Theory Fitts and Posner (1967) suggested that the learning process is sequential and that we move through specific phases as we learn. There are three stages to learning a new skill:

(i) Cognitive phase: This phase includes the identification and development of the component parts of the skill. It involves formation of a mental picture of the skill. (ii) Associative phase: This phase includes linking the component parts into a smooth action. It involves practicing the skill and using feedback to perfect the skill. (iii) Autonomous phase: This phase includes the developing the learned skill so that it becomes automatic. It involves little or no conscious thought or attention whilst performing the skill. Not all performers reach this stage. The leaning of physical skills requires the relevant movements to be assembled, component by component, using feedback to shape and polish them into a smooth action. Rehearsal of the skill must be done regularly and correctly.

7.6.3 Schmidt’s Schema Theory Schmidt’s theory (1975) was based on the view that actions are not stored rather we refer to abstract relationships or rules about movement. Schmidt’s schema is based on the theory that every time a movement is conducted four pieces of information are gathered: the initial conditions—starting point certain aspects of the motor action—how fast, how high the results of the action— success or failure the sensory consequences of the action—how it felt Relationships between these items of information are used to construct a recall schema and a recognition schema. The recall schema is based on initial conditions and the results and is used to generate a motor program to address a new goal. The recognition schema is based on sensory actions and the outcome.

7.6.4 Adam’s Closed Loop Theory Adam’s theory (1971) has two elements:

Perceptual trace—a reference model acquired through practice Memory trace—responsible for initiating the movement The key feature of this theory is the role of feedback. Analyse the reference model actions, the result of those actions and the desired goals Refine the reference model to produce the required actions to achieve the desired goals

7.7 TRANSFER OF LEARNING Transfer of learning can take place in the following ways: Skill to skill – this is where a skill developed in one sport has an influence on a skill in another sport. If the influence is on a new skill being developed then this is said to be proactive and if the influence is on a previously learned skill then this is said to be retroactive Theory to practice – the transfer of theoretical skills into practice • Training to competition – the transfer of skills developed in training into the competition situation

7.7.1 Effects of Transfer of Learning The effects of transfer can be: Negative – where a skill developed in one sport hinders the performance of a skill in another sport. Zero – where a skill in one sport has no impact on the learning of a new sport. Positive – where a skill developed in one sport helps the performance of a

skill in another sport. Direct – where a skill can be taken directly from sport to another. Bilateral – transfer of a skill from side of the body to the other—use left and right. Unequal – a skill developed in one sport helps another sport more than the reverse.

7.7.2 How do We Assess Skill Performance? Initially, compare visual feedback from the athlete’s movement with the technical model to be achieved. Athletes should be encouraged to evaluate their own performance. In assessing the performance of an athlete, consider the following points: Are the basics correct? Is the direction of the movement correct? Is the rhythm correct? It is important to ask athletes to remember how it felt when correct examples of movement are demonstrated (kinaesthetic feedback). Appropriate checklists/notes can be used to assist the coach in the assessment of an athlete’s technique. The following are some examples: Sprint technique Running technique for the middle distance runner

7.7.3 How are Faults Caused? Having assessed the performance and identified that there is a fault then you need to determine why it is happening. Faults can be caused by: Incorrect understanding of the movement by the athlete Poor physical abilities Poor co-ordination of movement

Incorrect application of power Lack of concentration Inappropriate clothing or footwear External factors for example weather conditions

7.7.4 Strategies and Tactics Strategies are the plans we prepare in advance of a competition, which we hope will place an individual or team in a winning position. Tactics are how we put these strategies into action. Athletes in the associative phase of learning will not be able to cope with strategies, but the athlete in the autonomous phase should be able to apply strategies and tactics. To develop strategies and tactics we need to know: the strengths and weaknesses of the opposition our own strengths and weaknesses environmental factors

Remember Practice makes permanent, but not necessarily perfect.

7.8 LEARNING SKILLS: 3 KEY THEORIES Learning skills require learning how to learn. The three behavioural learning theories are actually so important that psychologists (Franzoi, 2008) consider them to be both learning and motivational theories; since they help us understand why behaviour is learned and why it continues. Infact, it’s hard to learn something new because people are truly creatures of habit.

7.8.1 Classical Conditioning The classic and the first of the behavioural motivation for learning skill was the classical condition. Made famous by the Ivan Pavlov, who won the Noble prize in Medicine in 1904, this theory of skill learning explains how the mind learns to associate a stimulus and a response.

The original experiment was focused on conditioning in dogs, thus you sometimes hear people talk about “Pavlov’s dogs.” But what works on dogs, works on people too. The theory explains why companies spend big time and money on branding. It also offers one explanation for the power of advertising to influence our purchase behaviour. Unfortunately, classical conditioning impacts are often subtle, often beyond conscious awareness, so one is not aware of the stimulusresponse relationship. So it’s not so well known, compared to the used and widely applied theory of learning skills known as operant conditioning.

7.8.2 Operant Conditioning If you should know one theory, this is it. “You can’t learn to swim by reading about it.” —HENRY MINTZBERG There are theories, and then there is the theory—Operant conditioning (often called behavioral modification) widely used, especially in America. Its power lies in the understanding how to use positive and negative consequences. Behaviour modification is especially attractive since it’s an easy to apply and one of the easiest to learn of the learning theories. Behaviour modification works on both people and animals. You don’t have to act like a therapist who sorts out the underlying beliefs, attitudes, motives, values, etc. for driving behaviour. Instead, all you have to do is consider the behaviours, antecedents and consequences as shown in

Table 7.3. Table 7.3 The ABCs of behaviour modification Antecedents

Antecedents serve as external stimuli that remind us to take action. For convenience they are lumped into four categories: prompts, goals, feedback and modelling.

Behaviour

To the behaviourist, behaviour falls into two categories; it’s either desired or undesired. In this case, perception is everything. A parent’s desired behaviour of completing school homework is a child’s undesired behaviour. Some people think there is third category called, “I don’t care.” For example, we might see someone walking down the street who throws a cigarette on the ground. But since it’s an “I don’t care,” behaviour, we do not act to modify that person’s behaviour.

Consequences

A consequence is the motivational energy that either increases or decreases the probability of a behaviour occurring again.

The theory says focus on a particular skill or behaviour, not these ambiguous performance terms such as character, values, traits, etc. No one can fix “laziness,” “bad attitude,” or even “bad manners” if these are not grounded to a specific behaviour. For example, do bad manners mean cleaning teeth with a tooth pick, coughing on the soup, or chewing food with an open mouth? If we know how to change internal and external consequences, we can influence the ability to learn skills. It’s commonly used as part of a learning program to provide the motivation that driving the learning of skill. Many people have contributed to this theory, the best known being Harvard Psychologist B.F. Skinner.

7.8.3 Vicarious Learning or Modelling You have heard it before, “Monkeys see, monkeys do.” Learning skills is no mystery to a psychologist. But for some reason, this knowledge has not filtered into the general public. Within the world of psychology, there are two general schools of thought regarding learning skills. On the cognitive side of things, there are many theories. But on the behavioural side, there are only three theories. The third type of theory for learning skills is known as vicarious

learning or modelling. It is sometimes called social proof (Cialdini, 1998); although some have argued that other mechanisms are at work (Bandura, 1977). The college educated typically underestimates the importance of modelling. Being raised with books, they associate learning skills with the printed works. Of course, we do learn from books. Unfortunately, book learners tend to underestimate the skill learning potential of observational learning. And so, many miss the opportunity to influence conveyed by using this technique as related by the story below. There is a story told about a Japanese company that had taken over a facility in Poland. As the factory manager walked across the facility, he notices that people lacked pride, and would through all sorts of trash such as cigarettes on the floor. As he walked about the facility, he would pick up the trash on the floor. Pretty soon those around him did the same thing, as did others down the chain of command. Pretty soon the trash around the facility disappeared. Human beings learn of a tremendous amount from watching and observing others. The most obvious example is young children, were a boy imitates the father and a little girl imitates her mother. So the old saying, “Monkeys see, monkeys do,” rings true for humans. The same process goes on in organisations. New employees don’t know exactly how to act and so observe others to figure out what they need to do. This role modelling occurs at all levels of the organisation. In fact, the one person most watched in all organisations is one’s boss. Individuals possessing keen powers of observation posses an incredible advantage. They are able to see others behaviour and learning skills by incorporating new behaviours into their behavioural repertoire. For example, one can model leaders by learning their persuasive and motivational skills. “A fool never learns from their own mistakes; an average person sometimes learns from mistakes made; the exceptional learn from the mistakes of others.” — MURRAY JOHANNSEN

Conclusion A number of theories explain the how’s? of learning skills. Knowledge is better than ignorance; but knowledge is never enough. One must also know how to build and learn skills. If one knows how to use each of these three techniques, you will be able to learn new skills must faster.

QUESTIONS Section A Answer the following in five lines or in 50 words: 1. 2. 3. 4. 5. 6. 7. 8. 9. 10. 11. 12. 13. 14. 15. 16. 17. 18. 19. 20. 21. 22. 23.

Define Learning* Negative Transfer of Training Define conditioning Conditioned Stimulus (CS) Unconditioned Stimulus (UCS) Unconditioned Response (UCR) Extinction* Stimulus Generalization* Concept of Reinforcement Stimulus Discrimination Types of Reinforcement Proactive Inhibition Retroactive Inhibition Prompting Method What is Simultaneous Conditioning? Give two factors affecting ‘Generalization’. Extinction of Conditioned Response* Knowledge of Results Generalization of Conditioned Response Higher Order Conditioning Classical Conditioning Instrumental Conditioning Law of Effect*

24. Generalization 25. Reinforcement and its types

Section B Answer the following questions up to two pages or in 500 words: 1. 2. 3. 4.

5. 6. 7. 8. 9. 10. 11. 12. 13. 14. 15. 16. 17. 18.

19. 20. 21.

What is learning? Discuss the characteristics of learning. What is classical conditioning? Give its important features. What is the difference between classical and instrumental conditioning? Discuss classical conditioning with experimental evidence. Discuss different schedules of reinforcement with examples. Discuss operant conditioning with suitable experimental evidence. What is classical conditioning? Upon what factors does acquisition of a classically conditioned response depend? What is extinction? What is the difference between stimulus generalization and stimulus discrimination? What is operant conditioning? What are examples of primary reinforcers? How do negative reinforcement and punishment differ? What are schedules of reinforcement? How does reward delay affect operant conditioning? When is the use of continuous reinforcement desirable? Define reinforcement. Discuss its types. Discuss Pavlov’s classical conditioning theory of learning. or What is the classical conditioning theory of Pavlov? Discuss extinction of conditioned response. Explain Skinner’s instrumental conditioning theory of learning. What is instrumental conditioning? Differentiate between avoidance and escape conditioning citing experiments.

22. Citing experiments, explain the process of transfer of training. 23. Explain the importance of maturation in learning.

Section C Answer the following questions up to five pages or in 1000 words: 1. 2. 3. 4. 5. 6. 7. 8. 9. 10.

Discuss different conditions essential for classical conditioning.* Explain Skinner’s instrumental conditioning theory of learning. What is reinforcement? Discuss its types.* Discuss various schedules of reinforcement with examples. What is meant by conditioned response learning? Bring out its important features. Elucidate various features of instrumental conditioning along with experimental evidence. Cite experimental evidence to explain classical conditioning and discuss the factors affecting it. Explain Instrumental conditioning of learning with experimental works. “Learning is a process which brings about changes in the individual’s way of responding as a result of environment.” Explain. What is learning by condition? Discuss the salient features of classical conditioning.

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8 Memory INTRODUCTION Memory is a subject that has been of interest for over thousands of years. Memory is our cognitive system (or systems) for storing and retrieving information. In Psychology, memory is an organism’s ability to store, retain, and recall information. Traditional studies of memory began in the fields of Philosophy, including techniques of artificially enhancing the memory. The late nineteenth and early twentieth century placed memory within the paradigms of cognitive psychology. In recent decades, it has become one of the principle pillars of a branch of science called Cognitive Neuroscience, an interdisciplinary link between Cognitive Psychology and Neuroscience. Memory is our cognitive storage system (or systems) in the brain or mind for storing and retrieving information. It is truly a crucial aspect of our cognition. If we did not possess memory, we would be unable to remember the past, retain new information, and solve problems or plan for future. We use memory for a large number of purposes. We are able to benefit from our learning and experience only because of our memory. Memory involves storing information over time. Memory is very closely related to learning. Learning is very essential for the survival, development, and progress of human race. Whereas, learning is the process of acquiring new information or skills, memory is the retention of what you have learned as well as retrieval for future reference or use (Squire, 1987). Learning and memory, therefore, work together. You cannot really learn if you are unable

to remember, and unless you acquire new data (that is, learn it), you have nothing for memory to store. “Memory” refers to the mental function of retaining information about stimuli, events, images, ideas, and the like after the original stimuli are no longer present. “Memory” may be defined as the retaining, recalling or reproduction of past events, impressions, and experiences without the presence of actual stimulus. The power that we have to ‘store’ our experiences, and to bring them into the field of our consciousness sometime after the experiences have occurred, is termed “memory” (Ryburn, 1956).

8.1 SOME DEFINITIONS OF MEMORY According to C.G. Morris, “Memory is a process by which learned material is retained.” According to Woodworth and Schlosberg, “Memory is the ability for doing it over again for what one has learnt to do.” According to Hilgard and Atkinson, “To remember means to show in present response some sign of earlier learned responses.” According to H.J. Eysenck, “Memory is the ability of an organism to store information, from earlier learned responses, experience, and retention and reproduce that information in answer to specific stimuli.” According to Lefton (1985), “Memory is the ability to recall or remember past events or previously learned information or skills.” According to Bootzin (1991), “Memory is the cognitive process of preserving current information for later use.” According to Crooks and Stein (1991), “The term memory has a dual meaning. It refers to the process or processes whereby we store and preserve newly acquired information for later recall.” Here, the term memory describes either putting information into storage or pulling it back into conscious awareness. According to Baron (1995), “Memory is the capacity to retain and later retrieve information.” The following are the general characteristics of human memory: (i) Human memory is an active, rather than passive. Our memory does not record an event as accurately as a video recorder; instead, memory actively blends that event with other relevant information. For example,

a memory of an event ten years old may be influenced by stories you have heard from other family members. (ii) Human memory is a complex process involving factors like learning, retention, recall, and recognition. (iii) Human memory is highly organised. The more organised the information or material in memory, the better we are able to remember it. (iv) Memory accuracy depends upon how we encode material. For example, we will remember the definition for encoding if we think about its meaning; we will simply forget that definition if we simply glance at it. (v) Memory accuracy depends upon how we measure retrieval. It has been noticed that people’s scores on multiple-choice test are higher than on a fill-in-the-blank test. Recognising the central role of memory, psychologists have studied it systematically for more than one hundred years. The ultimate goal of memory research is to produce theoretical accounts of memory which are of practical use. Infact, memory was the focus of some of the earliest research in Psychology—studies conducted by Hermann Ebbinghaus (24 Jan, 1850–26 Feb, 1909), a German psychologist, in the late nineteenth century. The credit for the first systematic experimental study of memory goes to Hermann Ebbinghaus (1885), who devised 23,000 nonsense syllables. In 1885, he published his first book on memory. Using himself as a subject, Ebbinghaus memorised and recalled hundreds of nonsense syllables—meaningless combination of letters, such as teg or bom (consonant-vowel-consonant). Some of his findings about the nature of memory and forgetting have stood the test of time and are valid even today. He found that, at first we forget materials we have memorised quite rapidly but that later, forgetting proceeds more slowly. He was the first to plot a forgetting curve which shows the rate at which humans are able to retain lists of nonsense syllables after various intervals of time. And he found that distributed practice, in which we spread out our efforts to memorise materials over time, is often superior to massed practice, in which we attempt to do all our memorising at once.

Hermann Ebbinghaus (1850–1909)

Criticism of Ebbinghaus’ experiments: (i) Ebbinghaus was both the subject and the experimenter of his experiments. His findings are said to be fallacious, unscientific, and biased. (ii) Materials and methods used by Ebbinghaus could only be utilised by literate and educated persons and not by illiterates, animals, and children. (iii) Recall method used by Ebbinghaus has least strength in measuring memory in comparison to other methods like recognition, relearning, and reconstruction. If one does not recall a material, it does not mean that she or he has forgotten it. It might have been repressed.

8.2 THE PROCESS OF MEMORISING OR THE THREE STAGES OF MEMORY The information can be stored for less than a second or as long as your life time. For example, you use memory when you must store the beginning of a word (perhaps ‘mem’-) until you hear the end of the word (-ory). We also use memory when we recall the name of our favourite childhood teacher. Memory requires or involves three stages: Encoding, Storage, and Retrieval. These three stages are closely linked together. In order for the information to be retrieved, it must have been stored previously. Atkinson and Shiffrin (1968) proposed a highly influential model of memory, sometimes known as Modal Model of Memory. These researchers noted that human memory must accomplish the three basic tasks of encoding, storage, and retrieval. Encoding, the first stage, includes the processes occurring at the time of learning. During encoding, we transfer sensory stimuli or the information coming to our senses into a form that can be placed in memory.

Encoding or registration involves receiving, processing and combining of received information. Encoding means converting information into a form that can be entered into memory. It is in this stage that sensory events are coded and changed to a format that makes additional processing possible. When you place information into memory, you often elaborate or transform it in some way. This elaboration process is part of what is called “encoding”. The methods we use to carry out this process such as naming objects or mentally picturing words or vivid imagery are called encoding strategies. Effortful encoding is an active process and involves willful or voluntary or deliberate attempt to put something into memory. We deliberately try to encode the details of an event; we actively work to place them into short-term memory. A second kind of encoding, that is also very common, is automatic encoding; a kind of encoding that seems to happen with no deliberate effort. It is as if our memory just soaks up this kind of data with no conscious effort. Researchers have found that information about our location in time and space and how often we experience different kinds of stimuli are among the things we typically encode automatically (Hasher and Zacks, 1984). Through practice, one can learn to encode other kinds of data automatically. Storage means creation of a permanent record of the encoded information. In other words, it means retaining information over varying periods of time. The second stage is the storage stage. During this second stage, some of the information presented for learning is stored away in a long-term store, and we hold the information in memory for later use—perhaps less than a second, perhaps fifty years. Usually the incoming material remains there until it is either needed or lost altogether. “Storage” means somehow retaining information over varying periods of time. Storage is a synonym of memory. Once information has been attended to and encoded, it must be kept active in short-term memory in order to be retained. Information entering short-term memory is lost rather quickly unless it is renewed through rehearsal. Rehearsal usually involves some kind of speech either overt or covert as when you repeat a telephone number aloud or implicit, when you repeat a number mentally. Rehearsal, in other words, often maintains things phonetically: it is sounds of the words that are repeated and stored (Baddeley, 1982). Studies suggest that no more than half a minute new information stays in

short-term memory (Brown, 1958; Peterson and Peterson, 1959). The exact duration depends on the amount of rehearsal they are able to squeeze in. Other factors also affect the duration of short-term memory. Its duration depends on the degree to which new information or new material happens to be associated with the information held in long-term storage. In addition, the duration of short-term memory is affected by whether or not a person is motivated to remember.

George Armitage Miller (Born on 3 Feb, 1920)

Working memory is generally considered to have limited capacity. The earliest quantification of the capacity limit associated with short-term memory was the “magical number seven” introduced by Miller in 1956 (Hulme, Roodenrys, Brown, and Mercer, 1995), in paper titled “The magical number seven, plus or minus two”. He noticed that the memory span of young adults was around seven elements, called chunks, regardless whether the elements were digits, letters, words or other units. He thus summarised the results of many experiments, all of which indicated that majority of people can hold only between 5 to 9 items in short-term memory at any one time. We expand our limited capacity by chunking information. We see group of letters as word (small chunks), group of words as phrases (larger chunks), and series of phrases as sentences (even larger chunks). Short-term memory can hold about seven chunks, but each chunk may contain a great deal of information. Chunk is a familiar unit of information based on previous learning. “Chunking” is a term suggested by George A. Miller for the organisation process whereby distinct ‘bits’ of information are collected together perceptually and cognitively into larger, coordinated wholes, or ‘chunks’. It means grouping pieces of data into units. Later research revealed that span does depend on the category of chunks used (for example, span is around seven for digits, around six for letters, and around 5 for words), and even on features of the chunks within a category.

For instance, span is lower for long than for short words. In general, memory span for verbal contents (digits, letters, words, and so on) strongly depends on the time it takes to speak the contents aloud, and on the lexical status of the contents (that is whether the contents are words known to the person or not) (Cowan, 2001). Several other factors also affect a person’s measured span, and therefore it is difficult to pin down the capacity of short-term or working memory to a number of chunks. Nonetheless, Cowan (2001) has proposed that working memory has a capacity of about four chunks in young adults (and less in children and old adults). The way information enters the long-term memory is not completely understood. The process depends partly on the amount of time we rehearse things; the longer the rehearsal, the more likely is long-term storage. But even more important is the type of rehearsal. If we simply repeat something to ourselves without giving it thought (as when we rehearse a telephone number), that information seldom becomes part of our long-term knowledge. In contrast, if we take a new piece of information and mentally do something with it, form an image of it, apply it to a problem, relate it other things—it is more likely to be deposited in the long-term storage. These different approaches can be described as shallow processing or mere maintenance rehearsal versus deep processing or elaborative rehearsal (Craik and Lockhart, 1972). “Maintenance rehearsal” involves a repetition of processes which have already been carried out (for example, simply repeating a word over and over again), whereas “elaborative rehearsal” involves deeper processing of the stimulus material that is to be learned. The hypothalamus is a structure in the brain thought to be involved in the maintenance rehearsal or shallow processing of information. Emphasising the meaning of a stimulus is especially conducive to deep processing. During retrieval, the third stage, we successfully retrieve information or locate the item or information and use it. Retrieval, recall or recollection means calling back the stored information in response to some cue for use in a process or activity. Retrieval means locating and accessing specific information when it is needed at later times. In this stage, previously stored material is reclaimed due to a present demand, we locate and access information when it is needed at later times. It is the process or processes involved in remembering or gaining access to information stored in long-term memory. A good memory must reflect “an ideal revival” as Stout (1938) said

“So far as ideal revival is merely reproduction….. This productive aspect of ideal revival requires the object of past experiences to be re-instated as far possible in the order and manner of their original occurrence.” Psychologists have studied two basic kinds of retrieval from long-term storage —recognition and recall (Brown, 1968). “Recognition” involves deciding whether you have ever encountered a particular stimulus before or the awareness that an object or event is one that has been previously seen, experienced, or learned. Recognition is little more than a matching process. When asked if we recognise something, we consider its features and decide if they match those of a stimulus that is already stored in memory. In doing so, we tend to evaluate not the object as a whole, but rather its various parts (Adams, 1987). If all the parts match, the object is quickly recognised. If, however, some of the parts match while others do not, we are left with the feeling of only vague familiarity. “Recall”, in contrast, is the process of retrieving information from memory. It is an experimental procedure for investigating memorial processes whereby the subject must reproduce material previously learned. It entails retrieving specific pieces of information, usually guided by retrieval cues. Recall involves more mental operations than recognition does. When we try to recall something, we must first search through long-term memory to find the appropriate information. Then we must determine, as in recognition, whether the information we have come up with matches with the correct response. If we think it does, we give the answer, if we think it does not, we search again. Recall can be free recall or cued recall. In “free recall”, you would be asked to say or recite or write down as many of the words of the list as you could remember in any order. In “cued recall”, you might be given the first few letters of each word and asked to think of the appropriate list word (for example, mou... as a cue for the word mouth). Retrieval cues are especially important to the success of search components of recall.

8.3 TYPES OF MEMORY The below discussed three types of memory—sensory memory, short-term memory, and long-term memory differ in terms of how long information or material is stored in them, in their storage capacity, and in terms of the way in which information is forgotten.

8.3.1 Sensory or Immediate Memory or Sensory Register or Sensory Stores When information becomes available to an organism, the initial step in processing begins with the sensory register. This component of the memory system is activated when environmental stimuli evoke the firing of receptor cells in specialised sensory organs, such as those contained in the eye or ear. Sensory memory provides temporary storage of information brought to us by our senses. Sensory memory corresponds approximately to the initial 200–500 milliseconds after an item is perceived. The ability to look at an item, and remember what it looked like with just a second of observation, or memorisation, is an example of sensory memory. With very short presentations, participants often report that they seem to “see” more than they can actually report. The first experiments exploring this form of sensory memory were conducted by George Sperling (1960) using the “partial report paradigm”. Subjects were presented with a grid of 12 letters, arranged into three rows of 4. After a brief presentation, subjects were then played either a high, medium or low tone, cuing them which of the rows to report. Based on these partial report experiments, Sperling was able to show that the capacity of sensory memory was approximately 12 items, but that it degraded very quickly (within a few hundred milliseconds). Because this form of memory degrades so quickly, participants would see the display, but be unable to report all of the items (12 in the “whole report” procedure) before they decayed. This type of memory cannot be prolonged via rehearsal. Information coming to our senses first enters sensory memory, which is a storage system that records information from the senses with reasonable accuracy for a brief or small period of time. It can hold a large number of items, but each item fades away extremely quickly—in less than two seconds. Information held in the sensory register remains there only briefly, usually less than a second for visual stimuli and less than four seconds for auditory stimuli. Sensory memory or sensory register has two major purposes: (i) We need to keep an accurate record of physical stimulus for a brief time while we select the most important stimuli for the further processing. (ii) The stimuli that are bombarding your senses are constantly and rapidly

changing. Sensory memory is affiliated with the transduction of energy (change from one energy form to another). The environment makes available a variety of sources of information like light, sound, smell, heat, cold, and so on, but the brain only understands electrical energy. The sense organs receive information from the senses and transform it to a form that can be received and understood by the brain. In the process of transduction, a memory is created. This memory is very short (less than half second for vision and about 3 seconds for hearing). For the information to be transferred to the next level, that is short-term memory store, it is important that the information in the sensory memory store is attended to. Individuals are more likely to pay attention to a stimulus or information if it has an interesting feature. Second, individuals are more likely to pay attention if the stimulus activates a known pattern.

8.3.2 Short-term and Long-term Memory William James (1842–1910), an American psychologist and philosopher at Harvard University, brother of the novelist Henry James, argued that we should distinguish two kinds of memory which he referred to as primary memory (is basically the psychological present, and consists of what is currently happening or what has just happened) and secondary memory (relates to the psychological past, recollection of events which may have happened days, weeks, or even years ago). Richard C. Atkinson (Born in March, 1929) has had a long and distinguished career as an educator, administrator, and scientist. Richard C. Atkinson and Richard M. Shiffrin (an American psychologist) in 1968 distinguished between short-term (primary memory) and long-term (secondary memory) in their stage model of information processing or the multi-store model of memory or the stage theory or the multi-store approach. This model is widely accepted and the focus of this model is on how information is stored in memory.

Short-term memory (STM) Short-term memory allows recall for a period of several seconds to a minute without rehearsal. Short-term memory holds relatively small amounts of information for brief periods of time, usually thirty seconds or less. Its capacity is also very limited. This was what proved by George Miller. Modern estimates of the capacity of short-term memory are lower, typically on the order of 4–5 items, and we know that memory capacity can be increased through a process called chunking. For example, in recalling a 10-digit telephone number, a person could chunk the digits into three groups: first, the area code (such as 215), then a three-digit chunk (123) and lastly a four-digit chunk (4567). This method of remembering telephone numbers is far more effective than attempting to remember a string of 10 digits; this is because we are able to chunk the information into meaningful groups of letters. Herbert Simon showed that the ideal size for chunking letters and numbers, meaningful or not, was three. This may be reflected in some countries in the tendency to remember telephone numbers as several chunks of three numbers with the final four-number groups, generally broken down into two groups of two. Psychologists now usually refer to this kind of memory as working memory. Short-term memory is also called “working memory” and relates to what we are thinking about at any given moment in time (Alan Baddeley and Graham Hitch, 1974). In Freudian terms, this is conscious memory. Shortterm memory may be thought of as a stage of conscious activity. STM contains only the small amount of material we are currently using. The name, working memory, for short-term memory is appropriate because it handles the material we are currently or presently working with, rather than the items that were unattended in sensory memory or the items stored away in the long-

term memory (Baddeley, 1986, 1990, 1992). The frontal lobes of the cerebral cortex are the structures associated with working memory. Atkinson and Shiffrin (1968) argued that information from the environment is initially received by sensory registers or modality-specific stores. Each of the senses can be regarded as a separate “modality”. They suggested that we could have sensory memory or sensory register for all the senses—vision, hearing, smell, taste, and skin senses. However, researches have primarily concentrated on vision and hearing. Visual stimuli or information go to a special visual store (the iconic store), auditory stimuli or information go to a special auditory store (the echoic store), and so on for each of the senses. In short-term store, the information is selected and attended to and processed. The information that is not selected and attended to simply fades away or decays rapidly. Information from short-term memory or store goes to long-term memory or store through a process of rehearsal. Short-term memory is believed to rely mostly on an acoustic code for storing information, and to a lesser extent a visual code. Conrad (1964) found that test subjects had more difficulty recalling collections of words that were acoustically similar (for example, dog, hog, fog, bog, log). However, some individuals have been reported to be able to remember large amounts of information, quickly, and be able to recall that information in seconds.

Long-term memory (LTM) Long-term memory is also called “permanent memory”. In Freudian terms, it called pre-conscious and unconscious memory. “Pre-conscious” means that the information is relatively easily recalled with little effort. According to Atkinson and Shiffrin model, some information passes from short-term memory to long-term. Long-term memory has two important features: the lasting nature of the stored information and the great size of the repository. Long-term memory has unlimited capacity. It allows us to retain vast or huge amounts of information for very long periods of time. It stores memories that are decades old, as well as memories that arrived a few minutes ago. Longterm memory contains a huge amount of very diverse information. These memories are also much more permanent than those that are in the sensory memory and short-term memory. And it is the long-term memory that allows us to remember factual information such as the capital of our country. Organisation plays an important role in memory. Organisation can make it

easier to retrieve information (De Groot, 1966; Pearlstone, 1966). The effects of organisation on memory occur because learners use their knowledge to make sense of the to-be-learned material. Material from the long-term memory is recalled category by category. The way in which presented information is structured and organised by the knowledge stored in long-term memory is called categorical clustering. The storage in sensory memory and short-term memory generally have a strictly limited capacity and duration, which means that information is available only for a certain period of time, but is not retained indefinitely. By contrast, long-term memory can store much larger quantities of information for potentially unlimited duration (sometimes a whole life span). Given a random seven-digit number, we may remember it for only a few seconds before forgetting, suggesting it was stored in our short-term memory. On the other hand, we can remember telephone numbers for many years through repetition; this information is said to be stored in long-term memory. According to Atkinson and Shiffrin (1968), the long-term memory storage of information usually depends on the amount of rehearsal; the greater the amount of rehearsal of the to-be-learned material or information, the better that long-term memory becomes. Multi-store model of Atkinson and Shiffrin (1968) claims that all rehearsal leads to long-term memory; maintenance rehearsal usually leads to improved long-term memory. Maintenance rehearsal is the activity you carry out when you look up a telephone number in the directory and repeat it to yourself until you have finished dialing. Whereas, Gus Craik and Robert Lockhart (1972), proponents of levels-ofprocessing theory, claims that elaborative rehearsal benefits or improves long-term memory, but maintenance rehearsal or rote rehearsal does not. They suggested that the more deeply information is processed; the more likely it is to be retained. Merely repeating information silently to ourselves (maintenance rehearsal) does not necessarily move information from shortterm memory to long-term memory. The two processes most likely to move information into long-term memory are elaboration and distributed practice. Elaboration was important to memory. “Elaboration” refers to the amount of information that is processed at a particular level. Elaborative rehearsal is an encoding process that involves the formation of associations between new information and items already stored in the long-term store. Information in short-term memory enters long-term memory storage through elaborative

rehearsal. Elaborative rehearsal means when we think about its meaning and relate it to other information already in long-term memory. Evidence for the importance of elaboration was reported by Craik and Tulving (1975). Investigations by Reder and Ross (1983) have shown that memory benefits from more elaborate encodings. Imaging, method of loci, peg word method, rhyming, initial letter, and so on are several examples of elaboration that are commonly used in the teaching-learning process. Atkinson and Shiffrin proposed that passing of information from one memory system to another involves the operation of active control processes that act as filters, determining which information will be retained. Information in sensory memory enters short-term memory when it becomes the focus of our attention, whereas sensory impressions which do not engage attention fade and quickly disappear. It is necessary to attend to material, information, or an event within the short-term store in order to remember it later (Moray, 1959). So, where memory is concerned, selective attention— our ability to pay attention to only some aspects of the world around us while largely ignoring others—often plays a crucial role (Johnston, Mc Cann, and Remington, 1995; Posner and Peterson, 1990). In contrast, information in the short-term memory enters long-term memory storage through elaborative rehearsal (deep processing)—when we think about its meaning and relate it to other information already in long-term memory. Unless we engage in such cognitive effort, information or material in shortterm memory, too, quickly fades away and is lost. In contrast, merely repeating information silently to ourselves (maintenance rehearsal) does not necessarily move information from short-term memory to long-term memory. Recall is better if retrieval context is like the encoding context or situation (Begg and White, 1985; Eich, 1985; and Tulving, 1983). This is called encoding specificity principle, a notion proposed by Endel Tulving, according to which remembering depends on the amount of overlap between the information contained in the memory trace and that available in the retrieval environment. The encoding specificity principle predicts that recall will be the greatest when testing conditions match the learning conditions. In contrast, forgetting is more likely when the two contexts do not match. It has been found that memory traces that are high in distinctiveness, that is unique in some way like a natural disaster are better remembered than those that are not distinct (Eysenck and Eysenck, 1983).

While short-term memory encodes information acoustically, long-term memory encodes it semantically. Baddeley (1966) discovered that after 20 minutes, test subjects had the most difficulty recalling a collection of words that had similar meanings (for example, big, large, great, huge). Short-term memory is supported by transient patterns of neuronal communication, dependent on regions of the frontal lobe (especially dorsolateral prefrontal cortex) and the parietal lobe. Long-term memories, on the other hand, are maintained by more stable and permanent changes in neural connections widely spread throughout the brain. The hippocampus is essential (for learning new information) to the consolidation of information from short-term to long-term memory, although it does not seem to store information itself. Without the hippocampus, new memories are unable to be stored into long-term memory, and there will be a very short attention span. Furthermore, it may be involved in changing neural connections for a period of three months or more after the initial learning. One of the primary functions of sleep is thought to be improving consolidation of information, as several studies have demonstrated that memory depends on getting sufficient sleep between training and test. Additionally, data obtained from neuroimaging studies have shown activation patterns in the sleeping brain which mirror those recorded during the learning of tasks from the previous day, suggesting that new memories may be solidified through such rehearsal.

8.3.3 Models of Memory Models of memory provide abstract representations of how memory is believed to work. Below are several models proposed over the years by various psychologists. Note that there is some controversy as to whether there are several memory structures, for example, Tarnow (2005) finds that it is likely that there is only one memory structure between 6 and 600 seconds.

Atkinson-Shiffrin model The multi-store model (also known as Atkinson-Shiffrin memory model) was first recognised in 1968 by Atkinson and Shiffrin. Atkinson and Shiffrin proposed that information moving from one memory system to another involves the operation of active control processes that act as filters, determining which information will be retained. Information in sensory memory enters short-term memory when it becomes the focus of our

attention, whereas sensory impressions that do not engage attention fade and quickly disappear. Information in short-term memory enters long-term storage through elaborative rehearsal. Elaborative rehearsal is when we think about its meaning and relate it to other information already in long-term memory. Unless we engage in such cognitive effort, information in shortterm memory, too, quickly fades away and is lost. The multi-store model has been criticised for being too simplistic. For instance, long-term memory is believed to be actually made up of multiple subcomponents, such as episodic and procedural memory. It also proposes that rehearsal is the only mechanism by which information eventually reaches long-term storage, but evidence shows us that we are capable of remembering things without rehearsal.

Working memory model In 1974, Baddeley and Hitch proposed a working memory model which replaced the concept of general short-term memory with specific, active components. In this model, working memory consists of three basic stores: the central executive, the phonological loop and the visuo-spatial sketchpad. In 2000, this model was expanded with the multimodal episodic buffer. The central executive essentially acts as attention. It channels information to the three component processes: the phonological loop, the visuo-spatial sketchpad, and the episodic buffer. The phonological loop stores auditory information by silently rehearsing sounds or words in a continuous loop: the articulatory process (for example, the repetition of a telephone number over and over again). Then, a short list of data is easier to remember. The visuospatial sketchpad stores visual and spatial information. It is engaged when performing spatial tasks (such as judging distances) or visual ones (such as counting the windows on a house or imagining images). The episodic buffer is dedicated to linking information across domains to form integrated units of visual, spatial, and verbal information and chronological ordering (for example, the memory of a story or a movie scene). The episodic buffer is also assumed to have links to long-term memory and semantical meaning. The working memory model explains many practical observations, such as why it is easier to do two different tasks (one verbal and one visual) than two similar tasks (for example, two visual), and the aforementioned word-length

effect. However, the concept of a central executive as noted here has been criticised as inadequate and vague.

Levels of processing Craik and Lockhart (1972) proposed that it is the method and depth of processing that affects how an experience is stored in memory, rather than rehearsal. (i) Organisation: Mandler (1967) gave participants a pack of word cards and asked them to sort them into any number of piles using any system of categorisation they liked. When they were later asked to recall as many of the words as they could, those who used more categories remembered more words. This study suggested that the act of organising information makes it more memorable. (ii) Distinctiveness: Eysenck and Eysenck (1980) asked participants to say words in a distinctive way, for example, spell the words out loud. Such participants recalled the words better than those who simply read them off a list. (iii) Effort: Tyler et al. (1979) had participants solve a series of anagrams, some easy (FAHTER) and some difficult (HREFAT). The participants recalled the difficult anagrams better, presumably because they put more effort into them. (iv) Elaboration: Palmere et al. (1983) gave participants descriptive paragraphs of a fictitious African nation. There were some short paragraphs and some with extra sentences elaborating the main idea. Recall was higher for the ideas in the elaborated paragraphs.

8.3.4 Classification by Information Type Anderson (1976) divides long-term memory into declarative (explicit) and procedural (implicit) memories. Declarative memory requires conscious recall, in that some conscious process must call back the information. It is sometimes called explicit memory, since it consists of information that is explicitly stored and retrieved. Declarative memory can be further sub-divided into semantic memory, which concerns facts taken independent of context; and episodic memory, which concerns information specific to a particular context, such as a time

and place. Semantic memory allows the encoding of abstract knowledge about the world, such as “Paris is the capital of France”. Episodic memory, on the other hand, is used for more personal memories, such as the sensations, emotions, and personal associations of a particular place or time. Autobiographical memory—memory for particular events within one’s own life—is generally viewed as either equivalent to, or a subset of, episodic memory. Visual memory is part of memory preserving some characteristics of our senses pertaining to visual experience. One is able to place in memory information that resembles objects, places, animals or people in sort of a mental image. Visual memory can result in priming and it is assumed some kind of perceptual representational system underlies this phenomenon. In contrast, procedural memory (or implicit memory) is not based on the conscious recall of information, but on implicit learning. Procedural memory is primarily employed in learning motor skills and should be considered a subset of implicit memory. It is revealed when one does better in a given task due only to repetition—no new explicit memories have been formed, but one is unconsciously accessing aspects of those previous experiences. Procedural memory involved in motor learning depends on the cerebellum and basal ganglia. Topographic memory is the ability to orient oneself in space, to recognise and follow an itinerary, or to recognise familiar places. Getting lost when travelling alone is an example of the failure of topographic memory. This is often reported among elderly patients who are evaluated for dementia. The disorder could be caused by multiple impairments, including difficulties with perception, orientation, and memory.

8.3.5 Classification by Temporal Direction A further major way to distinguish different memory functions is whether the content to be remembered is in the past, retrospective memory, or whether the content is to be remembered in the future, prospective memory. Thus, retrospective memory as a category includes semantic, episodic and autobiographical memory. In contrast, prospective memory is memory for future intentions, or remembering to remember (Winograd, 1988). Prospective memory can be further broken down into event- and time-based prospective remembering. Time-based prospective memories are triggered by a time-cue, such as going to the doctor (action) at

4 pm (cue). Event-based prospective memories are intentions triggered by cues, such as remembering to post a letter (action) after seeing a mailbox (cue). Cues do not need to be related to the action (as the mailbox example is), and lists, sticky-notes, knotted handkerchiefs, or string around the finger are all examples of cues that are produced by people as a strategy to enhance prospective memory.

8.3.6 Physiology Brain areas involved in the neuroanatomy of memory such as the hippocampus, the amygdala, the striatum, or the mammillary bodies are thought to be involved in specific types of memory. For example, the hippocampus is believed to be involved in spatial learning and declarative learning, while the amygdala is thought to be involved in emotional memory. Damage to certain areas in patients and animal models and subsequent memory deficits is a primary source of information. However, rather than implicating a specific area, it could be that damage to adjacent areas, or to a pathway travelling through the area is actually responsible for the observed deficit. Further, it is not sufficient to describe memory, and its counterpart, learning, as solely dependent on specific brain regions. Learning and memory are attributed to changes in neuronal synapses, thought to be mediated by long-term potentiation and long-term depression. Hebb distinguished between short-term and long-term memory. He postulated that any memory that stayed in short-term storage for a long enough time would be consolidated into a long-term memory. Later research showed this to be false. Research has shown that direct injections of cortisol or epinephrine help the storage of recent experiences. This is also true for stimulation of the amygdala. This proves that excitement enhances memory by the stimulation of hormones that affect the amygdala. Excessive or prolonged stress (with prolonged cortisol) may hurt memory storage. Patients with amygdalar damage are no more likely to remember emotionally charged words than nonemotionally charged ones. The hippocampus is important for explicit memory. The hippocampus is also important for memory consolidation. The hippocampus receives input from different parts of the cortex and sends its output out to different parts of the brain also. The input comes from secondary and tertiary sensory areas that have already processed the information a lot. Hippocampal damage may also cause memory loss and

problems with memory storage.

8.4 CONCEPT OF MNEMONICS OR TECHNIQUES OF IMPROVING MEMORY In Greek mythology, ‘Mnemosyne’ (from which the word “mnemonic” is derived) was the mother of the nine muses of arts and sciences. Memory was considered the oldest and most revered of all mental skills, from which all others are derived. It was believed that if we had no memory, we would have no science, no art, and no logic. Mnemonic devices are methods for storing memories so that they will be easier to recall. In each mnemonic device, an additional indexing cue or hint is memorised along with the material to be learned. More is less with mnemonics; memorising something more will improve retrieval and result in less forgetting. Mnemonic devices are strategies or techniques that use familiar associations in storing new information to be easily retrieved or recalled. Mnemonic devices are strategies for improving retrieval that take advantage of existing memories in order to make new material more meaningful. All mnemonic systems are based on the structuring of information so that it is easily memorised and retrieved. Retrieval is enhanced when we elaborate on the material we are learning—when we organise or make it meaningful during the encoding process. A memory trick, or “mnemonic system”, was based on the idea that memory for items, individuals, exemplars, units, numbers, words, dates, cards, or other scattered bits of information could be improved if the information was systematically organised in some purposeful way (Solso, 2005). A mnemonic (the m is silent: ne-mahn’-ick) is a technique or devise, such as a rhyme or an image, that uses familiar associations to enhance the storage and the recall of information in memory. Three important parts are incorporated into this definition: (i) the use of familiar associations, (ii) the storage, or coding, of information, and (iii) the remembering of information that is stored. The most successful techniques assist in all three. Mnemonics are cues that enhance memory by linking new organisational sets of information to memory elements that already exist. Mnemonics represent just one of the many memory features of the complex human memory network.

Of all the practical applications of memory research, the provision of techniques for improving memory would be of greatest use. Success in any field is to a large measure or extent dependent on an individual’s ability to recall or retrieve specific information. Such mnemonic techniques (that is techniques designed to aid or improve memory) have been developed, and have a lengthy history going back to the ancient Greeks. Learning better ways to study can make the learning process more enjoyable, can increase the amount of information that you learn and retain, and can improve your grades. A few mnemonic devices or specific encoding strategies that we can use to aid our retrieval by helping us organise and add meaningfulness to new material are discussed below. Try some of these prescriptions or helpful hints provided by psychologists for better and more effective learning and memory; they could make a “big” difference.

8.4.1 Method of Loci Early Greek and Roman orators used a technique called “the method of loci”. Greeks invented the method of loci (that is the method of locations) which enables people to remember a large number of items in the correct order. ‘Loci” is the Latin word for “places”. Method of loci is the oldest imageryrelated and best documented mnemonic devise. “Method of loci” is the mnemonic devise of forming interactive visual images of materials to be learned and items previously associated with numbers. The method of loci is attributed to the Greek poet Simonides (Yates, 1966). The idea is to get in your mind a well-known location. This enables people to remember a large number of items in the correct order. The first step in this method is to memorise a series of locations, such as places along a familiar walk. After that, mental imagery is used to associate each of the items in turn with a specific location. Visually place the material you are trying to recall in different locations throughout your house in some sensible order. When the individual then wants to recall the items, she or he carries out a “mental walk”, simply recalling what is stored at each location. When the time comes for you to retrieve the material, mentally walk through your chosen locations, retrieving the information you have stored at each different place. The loci are arranged in a familiar sequence, one easy to imagine moving through. The next step is to create some bizarre imagery in which the items on the shopping list are associated with the loci. For

example, you could remember the items that needed to be bought at the shops by imagining each item at different places along the walk—a loaf of bread at the park entrance and so on. Gordon Bower (1970, 1972) of Stanford University has analysed the method of loci and illustrated the way this technique might be used to remember a shopping list. For example, the shopping list (left column) and loci (right column) are as follows: hot dogs.....................driveway cat food.....................garage interior tomatoes....................front door bananas.....................coat closet shelf whiskey.....................kitchen sink Bower illustrates the process involved in the method of loci in the following way: The first image is a “giant hot dog rolling down the driveway”; the second, “a cat eating noisily in the garage”; the third, “ripe tomatoes splattering over the front door”; the fourth, “bunches of bananas swinging from the closet shelf”; the fifth, a “bottle of whiskey gurgling down the kitchen sink”; and, finally, recall of the list activated by mentally touring the familiar places, which cues the items on the list. Stanford University psychologist Gordon Bower (1973) found that persons who use the method of loci were able to reach almost three times as many words from lists as those who did not. The method of loci consists of identification of familiar places sequentially arranged, creation of images of the to-be-recalled items that are associated with the places, and recall by means of “revisiting” the places, which serves as a cue for the to-be-recalled items. The method of loci is basically a peg system, in which the items that have to be remembered are associated with convenient pegs (for example, locations on a walk). “Peg word method” is the mnemonic device of forming interactive visual images of materials to be learned and items previously associated with numbers. One of the better-known mnemonic devices that also involve imagery is called the peg word method (Miller, Galanter, and Pribram, 1960). This strategy is most useful when we must remember items in order. Using this device is a two-step process. The first step is to associate common nouns (peg words) that rhyme with the numbers from 1 to 10 (and

beyond if you are up to it). The second step is to form an interactive image of the word you are memorising and the appropriate peg word. A more recent peg system proposed by Miller, Galanter, and Pribram (1960) is the one based on the rhyme: One is bun, two is shoe, three is a tree, four is a door, five is a hive, six is sticks, seven is heaven, eight is a gate, nine is a mine, ten is a hen. Mental imagery is used to associate the first item that must be remembered with a bun, the second item with a shoe, and so on. The advantage of this version of the peg system is that you can rapidly produce any specific item in the series (for example, the fifth or the eighth). The basic idea behind peg word system or peg list system is that one learns a set of words that serve as “pegs” on which items to be memorised are “hung”, much as a hat rack on which hats, scarves, and coats may be hung. After the peg list has been learned, the learner must “hook” a set of items to the pegs. It may sound like a lot of extra work to go through, but once you have mastered tour peg word scheme, the rest is remarkably easy. The peg systems are effective in enhancing memory because first they provide a useful organisational structure. Secondly, the pegs act as powerful retrieval cues, and thus tend to prevent cue-dependent forgetting from occurring. Thirdly, the use of imagery has been found to increase learning in other situations. There are other mnemonic techniques which attempt to impose organisation and meaning on the learning material. For example, the difficult task of remembering someone’s name can be greatly facilitated in the following way. First of all, you change the person’s name slightly into something which you can imagine. Then you choose a distinctive feature of that person’s face, and associate the image with that feature. In one study

(Morris, Jones, and Hampson, 1978), the use of this technique improved people’s ability to put names to faces by approximately 80 per cent. Mnemonics also includes visual imagery and organisation of encoded material.

8.4.2 Key Word Method It is easier to memorise information that you understand than information that you do not. Some of the things that you need to memorise will be meaningful to you if you take the time to think about it before you try to memorise it, but sometimes you will have to give additional meaning to the things you are memorising. Atkinson (1972) suggested that to improve memory for foreign language vocabulary, it is useful to imagine some connection visually trying the two words together. He calls this the key word method of study. The key word method can also be used to help remember pairs of English words (After Wollen, Weber, and Lowry, 1972). Subjects in the key word group learned more words in two training sessions than comparable control subjects did in there. The researchers also found that, in general, it is better to provide the key word rather than have the subject generate it. By actively enhancing the meaningfulness of what was learned using the key word method, the students were able to greatly improve its storage in memory (Raugh and Atkinson, 1975). Research data suggest that it actually works very well (Pressley et al., 1982). The key word method was used by Atkinson (1975), Atkinson and Raugh (1975), and Raugh and Atkinson (1975) in second-language instruction. A key word is an “English word that sounds like some part of the foreign word” (Atkinson, 1975).

8.4.3 Use of Imagery or Forming Mental Images or Pictures in Our Minds Canadian psychologist Allan Paivio (1971) should receive credit for resuscitating the concept of imagery during the mid-1960s. Forming mental images or pictures in our minds is another technique that improves memory. There is considerable agreement among psychologists that when someone learns objects, events, and facts or principles, they do not only learn their

meaning as to what they denote and connote, but also learns to have their visuo-spatial representations in mind. This is called imagery. Imagery is defined as a transformation process that converts different sources of information into visual form. Such imageries are used to enhance one’s memory. You can easily guess that it would be easier to learn concrete concepts in comparison to abstract ones. For example, it is easier to learn what is a tree or an apple, because you learn its meaning and associate it with an image of a tree or an apple. It has been shown that the less vague or bizarre the material to be memorised, the easier it becomes to store it in memory and recall it. Using imagery at encoding to improve retrieval has proven to be very helpful in many different circumstances (Begg and Paivio, 1969; Marschark et al., 1987; Paivio, 1971, 1986).

8.4.4 Organisational Device An important component of mnemonic techniques is their effectiveness in organising material. Short-term memory (STM) has limited capacity to store information. In STM, one can hold only 7 2 items. However, by chunking these items, you are able to optimise or maximise the storage capacity. You have also learned that retention is organised. You learned that in free recall category, clustering and hierarchical organisation take place. Organisation of memorised material in a hierarchy is another mnemonic, which improves memory. It is a form of outline, which provides structure to different concepts and categories. You can hierarchically organise the household goods in categories of different levels. This will improve memory for things that are used in a home. All mnemonic systems are based on the structuring of information so that it is easily memorised and recalled or retrieved. These organisational schemes may be based on places, time, orthography, sounds, imagery, and so on. Another powerful mnemonic device is to organise information into semantic categories, which are then used as cues for recall.

8.4.5 First Letter Technique or Acronym Method A widely used mnemonic is called “first letter technique” or acronyms or words formed on the basis of the first letters in a phrase or group of words. In this method, the first letters of each word in a list are combined to form an acronym. Suppose you have to remember a set of concept names, you can

take the first letter of each concept and combine them in triagrams (three letters in each) or words. It is used when the order of concepts is important. For example, PPCC is an acronym for memorising or remembering four stages of alcoholism: Prealcoholic, Predromal, Crucial, and Chronic. In medical sciences, this technique is widely used such as ICU, ENT, PRICE and so on. These two abbreviated are terms Intensive Care Unit and Ears Nose Throat, and Position, Rest, Ice, Composition, Elevation, respectively. The third one is used in treatment of traumas and sport injuries. Acronym BHAJSA to remember sequence of Mughal kings—Babar, Humayun, Akbar, Jahangir, Shah Jahan, and Aurangzeb. If you were to learn this list of important cognitive psychologists—Shepard, Craik, Rumelhart, Anderson, Bower, Broadbent, Loftus, Estes, Posner, Luria, Atkinson, Yarbus, Erickson, Rayner, Vygotsky, Intons-Peterson, Piaget, Sternberg, an acronym SCRABBLE PLAYER VIPS will help. Acronym POLKA stands for P for peg word; O for organisational schemes; L for loci; K for key word; A for additional systems (Acronym and Acrostic). An acrostic is a phrase or sentence in which the first letters are associated with the to-be-recalled word. Acronyms are even more useful if they form a real word.

8.4.6 Narrative Technique Then there is a narrative technique. In this technique, you create a story in which the characters move through various experiences and create a story or narrative chaining. “Narrative chaining” is the mnemonic device of relating words together in a story, thus organising them in a meaningful way. Research by Bower and Clark (1969) shows us that we can improve the retrieval of unorganised material if we can weave it into a meaningful story. This technique is called “narrative chaining”. Those who used a narrative chaining technique recalled 93 per cent of the words (on average), whereas those who did not use narrative chaining to organise the random list of words recalled only 13 per cent of them. Organising unrelated words into stories helps us remember them.

8.4.7 Method of PQRST Have you ever asked yourself, why do you come to college or university, attend classes, and study at home? You do so because you have to acquire

knowledge and skills. Even though you are hardworking student and devote lots of time in reading books, you may not be able to remember as much as you expect to remember. Perhaps, you do not know the most effective technique for improving memory for better remembering. Thomas and Robinson developed a technique, which they called the ‘method of PQRST’. This is used to help students in studying their textbooks and remembering more. The acronym PQRST refers to five stages of studying a textbook. They are: Preview, Question, Read, Self-recitation, and Test Suppose you have to read a chapter of a book. Read the contents and hurriedly go through the various sections and sub-sections in it. This exercise will help you organise the various topics discussed and you will get a clear outline of the contents. Now raise questions about the different sections and try to anticipate the kind of information each section is likely to provide. Now start reading the book. This will provide you the answers of the questions arising from each section. After having read the section, try to rewrite what you read in it. This will encourage retrieval practice by involving sub-vocal or vocal recall. After completion of all sections, test your comprehension and knowledge about the chapter. The PQRST exercise is certain to prove highly beneficial to your reading practice, memory organisation, and elaboration. You are advised to use PQRST in reading books. How long you study is as important as is the method of study adopted by you. You must not be a passive recipient of information from your text, but you should be active learner using deep level of processing and elaboration of each point discussed in the text.

8.4.8 The SQ3R Method The task of learning and remembering relatively long and complicated material can be eased by the use of a method of study known as “SQ3R”, which stands for Survey, Question, Read, Recite, and Review. These initials

stand for the five steps in effective textbook study outlined by Robinson. The active SQ3R study technique was originated by educational psychologist Francis Robinson (1970) of Ohio State University. The SQ3R method can improve your ability to learn information from textbooks. S: Survey: When reading a textbook, it is important to survey or look ahead at the contents of the text before you begin to read. Infact, before you read, you should try to find out as much as you can about the text material you are going to read. The more general information we possess about a topic, the easier it is to learn and remember new specific information about the topic (Ausubel, 1960; Deese and Deese, 1979). Textbooks have headings and these greatly aid studying and reviewing. Q: Question: After surveying and reviewing the material you will be reading, Robinson suggests that you ask questions before and during reading the text. Questions should reflect your own personal struggle to understand and digest the contents of the textbook. R: Read: After the S and Q steps, read the material. R: Recite: When studying, reciting the material or repeating it to you is definitely the most useful part of the study process and makes learning more efficient. A.I. Gates (1917) found those individuals who spent 80 per cent of their time reciting lists and only 20 per cent reading them recalled twice as much as those who spent all of their time reading. R: Review: The goal of the review process is to over learn the material, which means to continue studying material after you have mastered it. The learning process is not over when you can first recite the new information to yourself without error. Your ability to recall this information can be significantly strengthened later by reciting it several more times before you are tested (Krueger, 1929). The SQ3R method of study works in practice and seems in accord with sound psychological principles (Morris, 1979). It involves the learner actively, rather than passively, in the learning process. It also helps the integration of the learner’s previous knowledge with the information contained in the text. SQ3R has helped students raise their grades at several colleges (Adams et al., 1982; Anderson, 1985; Beneke and Harris, 1972).

8.4.9 Schemas

The encoding specificity hypothesis tells us that how we retrieve information is affected by how we have encoded it. Recall is better if retrieval context is like the encoding context or situation (Begg and White, 1985; Eich, 1985; and Tulving, 1983). This is called “encoding specificity principle”, a notion proposed by Endel Tulving, according to which remembering depends on the amount of overlap between the information contained in the memory trace and that available in the retrieval environment. The encoding specificity principle predicts that recall will be greatest when testing conditions match the learning conditions. In contrast, forgetting is more likely when the two contexts do not match. One of the processes that influence how we encode and retrieve information is our use of schemas (sometimes referred to as “scripts”). A “schema” is a system of organised general knowledge stored in long-term memory that guides the encoding of information. Schemas provide a framework that we can use to understand new information and also to retrieve that information later (Alba and Hasher, 1983; Lord, 1980).

Which mnemonic technique is the “best”? Unless relevant information is attended to, even the best mnemonic technique is useless. It seems that the first step in the successful coding of information is focusing our attention on the information we want to hold in our memory. Attention, also an important part of memory is the key initial stage in the memory process. Where it is not exercised, even the best mnemonic technique will fail. Douglas Herrmann (1987) found that some techniques work well for some types of material, while other techniques work well for other types. Specifically, for paired-associate learning, imagery mediation worked best; for free-recall learning, the story mnemonic seemed to be superior; while for serial learning, the method of loci worked well. Garcia and Diener (1993) found that when tested over a week the methods of loci, peg word, and acrostic proved to be about equal in effectiveness.

Limitations of various mnemonic techniques Inspite of the successes of the various mnemonic techniques, they are rather limited in a number of ways. While they allow us to remember long lists of unrelated items, they may not help us much with the complex learning required to pass examinations or to remember the contents of the book. It is

certainly true that most mnemonic techniques do not lead to increased understanding of the learning material. However, these methods have limited applications and do not provide answers to solve memory problems of all students. Infact, there is no simple method of improving one’s memory. For overall improvement in memory, multiple techniques or devices must be applied. One, who is interested in improving one’s memory power, must be highly motivated to do so. Primarily, one must have good physical and mental health; have as much sleep as is sufficient to keep one in good health and readiness to do mental work. For this purpose, you are required to maintain an optimal or balanced level of activity. Preparing a timetable allocating time for your daily routine, exercises, entertainment, and study and all other activities is necessary. Along with it, one should also maintain a diary for assessing one’s memory and collecting new information.

8.5 RECONSTRUCTIVE MEMORY When we are required to retrieve information from long-term memory, many of the details will not be available for recall. Consequently, we embellish our report with fictitious events; that is, we fill in with material “that must have been”. This process of combining actual details from the long-term store with items that seem to fit the occasion is the basis for what is known as reconstructive memory.

Sir Frederic Bartlett (1886–1969)

One of the classic studies of memory reconstruction was done by Sir Frederic Bartlett (1886-1969) over a half-century ago (Bartlett, 1932). Bartlett’s theory of reconstructive memory is crucial to an understanding of the reliability of eyewitness testimony as he suggested that recall is subject to personal interpretation dependent on our learnt or cultural norms and values —the way we make sense of our world. In his famous study “The War of the Ghosts”,

Bartlett (1932) showed that memory is not just a factual recording of what has occurred, but that we make “effort after meaning”. By this, Bartlett meant that we try to fill what we remember with what we really know and understand about the world. As a result, we quite often change our memories so they become more sensible to us. Many people believe that memory works something like a videotape. Storing information is like recording and remembering is like playing back what was recorded, with information being retrieved in much the same form as it was encoded. However, memory does not work in this way. It is a feature of human memory that we do not store information exactly as it is presented to us. Rather, people extract from information the gist, or underlying meaning. In other words, people store information in the way that makes the most sense to them. We make sense of information by trying to fit it into schemas, which are a way of organising information. Schemas are mental “units” of knowledge that correspond to frequently encountered people, objects or situations. They allow us to make sense of what we encounter in order that we can predict what is going to happen and what we should do in any given situation. These schemas may, in part, be determined by social values, and therefore prejudiced. Schemas are therefore capable of distorting unfamiliar or unconsciously “unacceptable” information in order to “fit in” with our existing knowledge or schemas. This can, therefore, result in unreliable eyewitness testimony. Bartlett tested this theory using a variety of stories to illustrate that memory is an active process and subject to individual interpretation or construction. His participants heard a story and had to tell the story to another person and so on, like a game of “Chinese Whispers”. The story was a North American folk tale called “The War of the Ghosts”. When asked to recount the detail of the story, each person seemed to recall it in their own individual way. With repeated telling, the passages became shorter, puzzling ideas were rationalised or omitted altogether and details changed to become more familiar or conventional. For example, the information about the ghosts was omitted as it was difficult to explain, whilst participants frequently recalled the idea of “not going because he hadn’t told his parents where he was going” because that situation was more familiar to them. For this research Bartlett

concluded that memory is not exact and is distorted by existing schema, or what we already know about the world. It seems, therefore, that each of us “reconstructs” our memories to conform to our personal beliefs about the world. This clearly indicates that our memories are anything but reliable, “photographic” records of events—they are individual recollections which have been shaped and constructed according to our stereotypes, beliefs, expectations, etc. The implications of this can be seen even more clearly in a study by Allport and Postman (1947), of the following picture.

When asked to recall details of this picture, participants tended to report that it was the black man who was holding the razor. Clearly this is not correct and shows that memory is an active process and can be changed to “fit in” with what we expect to happen based on your knowledge and understanding of society (for example, our schemas). More recent work on memory reconstruction has focused on where in the information-processing scheme the memory distortion takes place. Some evidence indicates that events are broken down and reconstituted when they are first stored (Kintsch, 1974). But other findings argue against an encoding interpretation of reconstructive changes and implicate retrieval mechanisms in the process. Hasher and Giffrin (1978) have shown that the recall of ambiguous stories is profoundly influenced by content clues given after a period of study and prior to testing. Specifically, if just prior to recall test, you provide hints that the story was about a sailor, there is a high probability that the reader will remember the story as having involved a sailor, even when no such person was mentioned in the original script. Alternatively, if

you provide a clue that indicates that the story was about a factory worker, then a factory worker will be woven into the memory fabric. Such data argue rather forcefully for changes during retrieval, in as much as the same information gets stored during the initial study sessions.

8.6 EXPLICIT MEMORY AND IMPLICIT MEMORY: DEFINITIONS Long-term memory can be divided into episodic memory (long-term memory for autobiographical or personal events, usually including some information about the time and place of a particular episode or event) and semantic memory (long-term memory or organised knowledge about the world and about language stored in long-term memory) or into procedural knowledge (knowledge relating to knowing how, and including motor skills; memory for such knowledge is typically revealed or expressed by skillful performance and not by conscious recollection) and declarative knowledge (knowledge in long-term memory which is concerned with knowing that; this form of knowledge encompasses episodic memory and semantic memory, and can be contrasted with procedural knowledge. In cognitive terminology, procedural memory (memory for how to do a task) is separate from declarative memory (memory for facts about a task or event), and either may exist without the other (Schacter, 1987). If you have ever found yourself saying “I used to know how to do that” (for example about playing a game, tying a knot, riding unicycle, playing a musical instrument), you have implicitly expressed that your declarative knowledge about some experiences has survived, despite the fading of the relevant procedural knowledge. Conversely, if you have ever found yourself saying about some skill-based activity, “I can’t tell you how I do it, but I can show you”, you are claiming that some skill is represented in your memory in a format that is not compatible with overt verbal description. It is also possible to distinguish between different kinds of long-term memory on the basis of the way in which memory is tested. Experiments have been able to demonstrate remembering without awareness. We typically think of memory as explicit memory—we can recall or recognise something. Explicit memory is conscious memory, memory for material of which one is aware. Explicit memory for previously presented materials is tapped by tasks like recall and recognition when the individual is

consciously aware of the knowledge held and can recall it or recognise it among several alternatives. But there is also implicit memory—we might change how we think or behave as a result of some experience that we do not consciously recall (Schacter, 1992). Not all knowledge held in the mind is available to consciousness. Implicit memory is unconscious memory, memory for material of which one is unaware. Normal people can “forget” (that is, can fail to show evidence of any explicit memory) a prior experience like solving a puzzle or learning a new motor skill, but at the same time they show in their skill while actually performing the task that they have practiced before. In other words, the person being studied consciously remembers some event that the experimenter knows has occurred because it happened within the setting of the experiment and that the subject was clearly conscious of at the time it occurred. But at a later time, although the subject cannot consciously remember having had that experience, she or he still performs the task better than a novice presented with the task for the first time. This dissociation between explicit and implicit memory demonstrates that experiences that are not consciously remembered can still influence our behaviour. The phenomenon of implicit memory is usually now interpreted within a strictly cognitive (non-Freudian) perspective. The cognitivists tend to see it as evidence that the representational code in which skills tend to be encoded in the brain is not necessarily compatible with verbal reporting. The representation of the skill itself can be present in memory (in a procedural format not available to consciousness), even in the absence of conscious memory for the event during which the skill was acquired.

8.6.1 The Differentiation Graf and Schachter (1985) argued that there is an important theoretical distinction between explicit and implicit memory, which they defined in the following way:

Explicit memory “Explicit memory” is revealed when performance on a task requires conscious recollection of previous experiences. Traditional measures of longterm memory such as free recall, cued recall, and recognition all involve the use of direct instructions to retrieve information about specific experiences,

and are therefore measures of explicit memory. “Explicit memory” is memory which involves the conscious recollection of previous occurrences. Explicit memory refers to the conscious recall of information, the type of memory you might use when answering a question on an examination. For example, if you were asked to recall the Indian prime minister who preceded S. Manmohan Singh, you would answer, “Atal Bihari Vajpai”. You are consciously making an association between the cue, or question, and the answer. We use explicit memory for answering direct questions. Explicit memory involves the conscious recall of previous experiences.

Implicit memory Implicit memory, on the other hand, is more germane or of interest to our discussion since it refers to memory that is measured through a performance change related to some previous experience. Implicit memory is a type of memory in which previous experiences aid in the performance of a task without conscious awareness of these previous experiences. “Implicit memory” is revealed when performance on a task is facilitated in the absence of conscious recollection. Implicit memory for previously presented material can be tapped by a variety of tasks, most commonly priming. Priming means the triggering of specific memories by a specific cue. Implicit memory is memory which does not require the conscious recollection of past experiences. Word completion, for example, is a test of implicit memory. The existence of implicit memory is compellingly displayed in cases of amnesia, in which, despite the patient’s inability explicitly to recall previously presented material, performance on tasks like priming is virtually normal. Studies of amnesic patients showed good implicit memory but poor explicit memory (Cohen, 1984; Graf, Squire, and Mandler, 1984). The limitation of distinction between explicit and implicit memory is that the distinction is descriptive rather than explanatory. Recent studies have indicated that many of the memories remain outside the conscious awareness of a person. Implicit memory is a kind of memory that a person is not aware of. It is a memory that is retrieved or recalled automatically. One interesting example of implicit memory comes from the experience of typing. If someone knows typing that means she or he also knows the particular letters on the keyboard. But many of the typists cannot correctly label blank keys in a drawing of a typewriter. Implicit memories lie

outside of the boundaries of awareness. In other words, we are not conscious of the fact that a memory or record of a given experience exists. Nevertheless, implicit memories do influence our behaviour. This kind of memory (implicit memory) was found in patients suffering from brain injuries. They were presented a list of common words. A few minutes later, the patients were asked to recall (free recall) words from the list. They showed no memory for the words. However, if they primed to say a word that began with these letters, they were able to recall (cued recall) words. Implicit memories are also observed in people with normal memories. Perhaps the main reason why psychologists have become interested in the distinction between explicit and implicit memory is because it appears to shed light on the memory problems of amnesic patients. Amnesic patients gradually perform rather poorly when given tests of explicit memory, but often perform as well as normal individuals when given tests of implicit memory. An interesting experiment demonstrating this was reported by Graf, Squire, and Mandler (1984). They used three different tests of explicit memory (free recall, cued recall, and recognition) for lists of words: free recall and cued recall, where the first three letters of each list of words were given for recognition. They also used a test of implicit memory: word completion. On the word-completion test, subjects were given three-letter word fragments (for example, bar—) and simply had to write down the first word they thought of which started with those letters (for example, barter, bargain, barbour, bar-at-law). Implicit memory was assessed by the extent to which the word completions corresponded to words on the list previously presented. Amnesic patients did much worse than control subjects on all the tests of explicit memory, but the two groups did not differ in their performance on the test of implicit memory. This can be demonstrated as in Figure 8.1.

Figure 8.1 Free recall, cued recall, recognition memory, and word completion in amnesic patients and controls.

There are several other studies in which amnesic patients showed good implicit memory but poor explicit memory. For example, Cohen (1984) made use of a game known as the Tower of Hanoi. The game involves five rings of different sizes and three pegs. The rings are originally placed on the first peg with the largest one at the bottom and the smallest one at the top. The task is to produce the same arrangement of rings on the third peg. In order to achieve this, only one ring at a time can be moved, and a larger ring can never be placed on a smaller one. Inspite of the complex nature of this task, Cohen (1984) discovered that amnesic patients found the best solution as rapidly as control subjects. However, there was a significant difference between the performances of the two groups, when they were given a recognition test of explicit memory. On this test, they were presented with various arrangements of the rings. Some of these arrangements were taken from various stages of the task on route to the best solution. Others were not. The subjects had to decide which belonged to which. The control subjects performed reasonably well on this test, whereas the performance of the amnesic patients was near to chance level. The fact that the amnesic patients performed well on the Tower of Hanoi task but showed poor conscious awareness of the steps involved in producing that performance suggests that their implicit memory was good but their explicit memory was not.

Memory research used to be based mainly on the assessment of explicit memory. It was therefore assumed that amnesic patients had very little ability to form new long-term memories. So, memory can be demonstrated by successful performance (implicit memory) regardless of whether or not there is conscious awareness of having acquired the relevant information in the past. While the distinction between explicit and implicit memory appears to be an important one in the light of amnesia research, it does suffer from some limitations. In particular, the distinction is descriptive rather than explanatory. Thus, for example, knowing that amnesic patients have good implicit memory but poor explicit memory is not more than the first step on the way to an explanation of amnesia, because the processes involved in implicit and explicit memory are not known. Measurement of Implicit Memory In measurement of implicit memory, the participant has to perform some task which is rooted in memory, but the participant is not conscious of the fact that her or his memory is being tested. There are two implicit measures, which are widely used. One is called word completion and the other one is called repetition priming. (i) Word completion task: In this task, fragments of words are given and the participant is required to complete the fragmented words. A fragmented word is an incompletely spelled word (for example, r—v— r). Such a word is completed by adding the necessary letters that are missing. In such fragments, any set of letters may be necessary for completion of the word, any set of letters may be missing, and enough letters are left for correct completion. For example, let us take the fragment –r—g—n—l. It can be completed in two ways, that is, “original”, or “regional”. If you are able to complete the fragments in this way then it means that these two words are stored in your memory and you know them. (ii) Repetition priming task: This task uses the technique of priming. For example, if one has experienced some words in a story read recently, she or he may not be able to recall all the words used. However, if asked to complete fragments of words to be completed, the person is most likely to do so in such a way that the completed word is from the words experienced in the story. The experience of reading the words in the story has primed the participant or prepared her or him for certain kinds

of words. The fragments get connected with the previous experience. For example, suppose you have experienced many words associated with the festival of lights. Now you are asked to complete the word that is c—a—k— e —s. you will immediately make it ‘crackers’ because you are primed in this direction.

8.7 EYEWITNESS MEMORY OR TESTIMONY Eyewitness testimony is a legal term for the use of an eyewitness to a crime to provide testimony in court about the identity of the perpetrator. The term is common in Forensic Psychology. It refers to an account given by people of an event they have witnessed. For example, they may be required to give a description at a trial of a robbery or a road accident or a murder someone has seen. This includes identification of perpetrators, details of the crime scene and so on. Eyewitness testimony is an important area of research in cognitive psychology and human memory. In all kinds of criminal cases, eyewitness memory or testimony against the accused is considered to be the most reliable type of evidence. An “eyewitness” is one who incidentally watched the event of crime being committed as she or he was present at that time. Since the eyewitness recounts the event under oath, it is assumed that she or he gives truthful description of the event because the events experienced are stored in memory. Undoubtedly, under ordinary circumstances recall from memory is generally accurate. However, it is also true that memory, being constructive as well as reconstructive, is not always flawless. Research in eyewitness testimony is mostly considered a subfield within legal psychology; however, it is a field with very broad implications. Human reports are normally based on visual perception, which is generally held to be very reliable (if not irrefutable). Research in cognitive psychology, in social psychology, as well as in the philosophy of science and in other fields seems, however, to indicate that the reliability of visual reports is often much overrated. In a classic study, Loftus presented a short film to a group of participants. The film showed a collision of two cars. Subsequently, the viewers were asked about what they had seen, and were asked to provide estimates of the speed of the cars at the time the collision took place. In reality, the

experimenter phrased the questions differently. Some of the viewers were asked about the cars “colliding”, some were asked about the cars “hitting” each other, and others were asked about cars “contacting”, or “bumping”, each other. The estimates of the speeds of the cars varied according to the question put to the viewers. Thus, when “smashed” was used, the estimated speed of the cars was 41 mph (miles per hour) but was about 31 mph when they “contacted” each other. This laboratory study shows the kinds of distortions that are possible in reporting some witnessed event. In a series of subsequent experiments, Loftus found that misinformation introduced after an eyewitness observation is capable of altering a witness’s memory. The probability of such mistakes increases if misinformation takes place after a week. Changes in memory are very common and people often fail to realise that it is distortion. People unwillingly adapt the wrong information. We know the significance of eyewitness testimony in legal or criminal cases in which guilty may be convicted or acquitted depending on the strength of the evidence, that is eyewitness testimony. The studies indicate that an eyewitness’ testimony about some event can be influenced by how the questions put to the witness are worded. Such testimonies often tell not only what people actually saw but also what information they obtained later on. The reporting may be affected by person’s attitudes and expectations. When a crime is committed, the criminal often leaves crucial or significant clues behind. Sometimes these clues prove his or her guilt (for example, fingerprints), but more frequently, they are less useful. For example, one or more eyewitnesses may have seen the crime taking place, and their accounts of what happened may vary from a major part of the prosecution’s case. Unfortunately, however, juries are sometimes too inclined to trust eyewitness testimony or evidence. This has led to thousands of innocent people being sent to prison solely on the basis of eyewitness accounts. Psychologists have investigated the factors that can make eyewitness testimony inaccurate. There are two major kinds of factors: (i) The eyewitness may have failed to attend closely to the crime and/or the criminal. (ii) The memory of the eyewitness may have become distorted after the crime has been committed. It may seem likely that the main reason why eyewitnesses remember

inaccurately is because of inattention. However, eyewitness memories are fragile and can easily be influenced by later events.

8.7.1 Fragility of Memory Loftus and Palmer (1974) showed participants a film of multiple car accident. After looking at the film, the participants were asked to describe what had happened in their own words. Then they answered a number of specific questions. Some of the participants were asked, “About how fast were the cars going when they smashed into each other?’, whereas for other participants the verb “hit” replaced “smashed into”. The estimated speed was influenced by the verb used in the question, averaging 10.5 mph when the verb “smashed into” was used versus 8.0 mph when verb “hit” was used. Thus, the wording of the question influenced the way in which the multiple car accident was remembered. One week later, all the participants were asked the following question: “Did you see any broken glass?’. Inspite of the fact that there was actually no broken glass in the incident, 32 per cent of those who had been asked before about speed using the verb “smashed into” said they saw broken glass. In contrast, only 14 per cent of those asked using the verb “hit” said they saw broken glass. Thus, our memory for events is rather fragile and can easily be distorted.

8.7.2 Leading Questions Lawyers in most countries are not allowed to ask leading questions which suggest the desired answer (for example, “when did you stop beating your wife?’). However, detectives and other people who question eyewitnesses shortly after an incident sometimes ask leading questions in their attempts to find out what happened. The effects that leading questions can have on eyewitnesses’ memory were shown by Loftus and Zanni (1975). They showed people a short film of a car accident, and then asked them various questions about it. Some of the eyewitnesses were asked the leading question, “Did you see the broken headlight?, which suggests that there was a broken headlight. Other eyewitnesses were asked the neutral question, “did you see a broken headlight?’. Even though there was actually no broken headlight, 17 per cent of those asked the leading question said they had seen it, against only 7 per cent of those asked the neutral question.

8.7.3 Hypnosis Police forces in several countries make use of hypnosis with eyewitnesses in order to improve their memory. Problems with the use of hypnosis were found by Putnam (1979). He showed his participants a videotape in which a car and a bicycle were involved in an accident. Those who were questioned about the accident under hypnosis made more errors in their answers than did those who responded in the normal state. Hypnosis makes people less cautious in reporting their memories than they are normally. This lack of caution can lead to the recovery of “lost” memories. However, it also produces many inaccurate memories. For example, hypnotised people will often “recall” events from the future with great confidence!

8.7.4 Confirmation Bias Eyewitness memory can also be distorted through what is known as confirmation bias. It is the tendency to seek information that confirms existing beliefs. This bias occurs when what is remembered of an event fits the individual’s expectations rather than what really happened. For example, students from two universities in the United States (Princeton and Dartmouth) were shown a film of a football game involving both universities. The students showed a strong tendency to report that their opponents had committed many more fouls than their own team.

8.7.5 Violence Loftus and Burns (1982) found evidence that the memory of an eyewitness is worse when a crime is violent than when it is not. They showed their participants two filmed versions of a crime. In the violent version, a young boy was shot in the face near the end of the film as the robbers were making their gateway. Inclusion of the violent incident reduced memory for details presented up to two minutes earlier. The memory-reducing effects of violence would probably be even greater in the case of a real-life crime, because the presence of violent criminals might endanger the life of the eyewitness.

8.7.6 Psychological Factors Juries tend to pay close attention to eyewitness testimony and generally find

it a reliable source of information. However, research into this area has found that eyewitness testimony can be affected by many psychological factors such as the following: Anxiety/Stress Reconstructive Memory Weapon Focus

Anxiety/Stress Anxiety or stress is almost always associated with real life crime of violence. Deffenbacher (1983) reviewed 21 studies and found that the stressperformance relationship following an inverted-U function proposed by the Yerkes Dodson Curve (1908). This means that for tasks of moderate complexity (such as EWT), performances increases with stress up to an optimal point where it starts to decline. Clifford and Scott (1978) found that people who saw a film of a violent attack remembered fewer of the 40 items of information about the event than a control group who saw a less stressful version. As witnessing a real crime is probably more stressful than taking part in an experiment, memory accuracy may well be even more affected in real life. However, a study by Yuille and Cutshall (1986) contradicts the importance of stress in influencing eyewitness memory. They showed that witness of a real life incident (a gun shooting outside a gun shop in Canada) had remarkable accurate memories of a stressful event involving weapons. A thief stole guns and money, but was shot six times and died. The police interviewed witnesses, and thirteen of them were reinterviewed five months later. Recall was found to be accurate, even after a long time, and the two misleading questions inserted by the research team had no effect. One weakness of this study was that the witnesses who experienced the highest levels of stress where actually closer to the event and this may have helped with the accuracy of their memory recall. The Yuille and Cutshall study illustrates two important points: (i) There are cases of real-life recall where memory for an anxious/stressful event is accurate, even some months later. (ii) Misleading questions need not have the same effect as has been found

in laboratory studies (for example, Loftus and Palmer).

Reconstructive memory This, as already explained, is just combining actual happenings with events that just seem to fit the occasion. Sir Fredric Bartlett was one of those who did studies on memory reconstruction. Bartlett’s theory of reconstructive memory is crucial to an understanding of the reliability of eyewitness testimony, as he suggested that recall is subject to personal interpretation dependent on our learnt or cultural norms and values—the way we make sense of our world. In his famous study War of the Ghosts, Bartlett (1932) showed that memory is not just a factual recording of what has occurred, but that we make “effort after meaning.” By this, Bartlett meant that we try to fit what we remember with what we really know and understand about the world. As a result, we quite often change our memories so they become more sensible to us. He concluded by his study that our memories are “photographic” records of events, that is individual recollections which have been shaped and constructed according to our beliefs and expectations. And therefore our memories are not reliable.

Weapon focus This refers to an eyewitness’ concentration on a weapon to the exclusion of other details of a crime. In a crime where a weapon is involved, it is not unusual for a witness to be able to describe the weapon in much more detail than the person holding it. Loftus et al. (1987) showed participants a series of slides of a customer in a restaurant. In one version, the customer was holding a gun, in the other the same customer held a chequebook. Participants who saw the gun version tended to focus on the gun. As a result they were less likely to identify the customer in an identity parade those who had seen the chequebook version. However, a study by Yuille and Cutshall (1986) contradicts the importance of stress on weapon and focus in influencing eyewitness memory. They showed that witness of a real life incident (a gun shooting outside a gun shop in Canada) had remarkable accurate memories of a stressful event involving weapons. A thief stole guns and money, but was shot six times and

died. The police interviewed witnesses, and thirteen of them were reinterviewed five months later. Recall was found to be accurate, even after a long time, and the two misleading questions inserted by the research team had no effect. The Yuille and Cutshall study illustrates three important points: (i) There are cases of real-life recall where memory for an emotional/stressful event is accurate, even some months later. (ii) Misleading questions need not have the same effect as has been found in laboratory studies (for example, Loftus and Palmer). (iii) Contrary to some research, “weapon focus” does not always affect recall. R.J. Shafer offers this checklist for evaluating eyewitness testimony (Garraghan, 1946): (i) Is the real meaning of the statement different from its literal meaning? Are words used in senses not employed today? Is the statement meant to be ironic (that is, mean other than it says)? (ii) How well could the author observe the thing he reports? Were his senses equal to the observation? Was his physical location suitable to sight, hearing, touch? Did he have the proper social ability to observe: did he understand the language, have other expertise required (for example, law, and military); was he not being intimidated by his wife or the secret police? (iii) How did the author report?, and what was his ability to do so? (a) Regarding his ability to report, was he biased? Did he have proper time for reporting, proper place for reporting, adequate recording instruments? (b) When did he report in relation to his observation? Soon? Much later? (c) What was the author’s intention in reporting? For whom did he report? Would that audience be likely to require or suggest distortion to the author? (d) Are there additional clues to intended veracity? Was he indifferent on the subject reported, thus probably not intending distortion? Did he make statements damaging to himself, thus probably not seeking to distort? Did he give incidental or casual information, almost certainly

not intended to mislead? (iv) Do his statements seem inherently improbable: for example, contrary to human nature, or in conflict with what we know? (v) Remember that some types of information are easier to observe and report on than others. (vi) Are there inner contradictions in the document? Louis Gottschalk adds an additional consideration: “Even when the fact in question may not be well-known, certain kinds of statements are both incidental and probable to such a degree that error or falsehood seems unlikely. If an ancient inscription on a road tells us that a certain proconsul built that road while Augustus was prince royal, it may be doubted without further corroboration that that proconsul really built the road, but would be harder to doubt that the road was built during the principate of Augustus. If an advertisement informs readers that “A and B Coffee may be bought at any reliable grocer’s at the unusual price of fifty cents a pound”, all the inferences of the advertisement may well be doubted without corroboration except that there is a brand of coffee on the market called ‘A and B Coffee’” (Gottschalk, 1950). Garraghan says that most information comes from “indirect witnesses”, people who were not present on the scene but heard of the events from someone else (Garraghan, 1946). Gottschalk says that a historian may sometimes use hearsay evidence. He writes, “In cases where he uses secondary witnesses, however, he does not rely upon them fully. On the contrary, he asks: (i) On whose primary testimony does the secondary witness base his statements? (ii) Did the secondary witness accurately report the primary testimony as a whole? (iii) If not, in what details did he accurately report the primary testimony? Satisfactory answers to the second and third questions may provide the historian with the whole or the gist of the primary testimony upon which the secondary witness may be his only means of knowledge. In such cases the secondary source is the historian’s “original” source, in the sense of being the “origin” of his knowledge. Insofar as this “original” source is an accurate report of primary testimony, he tests its credibility

as he would that of the primary testimony itself.” (Gottschalk, 1950). Conclusion: There are various reasons why the evidence given by eyewitness can be inaccurate. Of particular importance is the fact that an eyewitness’ memory for a crime or accident is fragile. It can easily be distorted by questions that convey misleading ideas about what happened.

8.8 METHODS OF RETENTION 8.8.1 Paired-associate Learning In this method, first, a list of paired words is made. The first word of the pair will be the stimulus and the second word as response, for example, ben-time, kug-lion, and the like. The first word member of each pair may be from the same language or two different languages. This method is used in learning of some foreign language equivalent to mother tongue words. In the above list, the first member of the pairs (stimulus word) are non-sense syllables (a consonant-vowel-consonant combination, for example, ben or kug) and the second words of the list are English nouns (response words), for example, time and lion. The learner is first shown both the stimulus and response pairs together, and is instructed to remember and recall the response term after the presentation of each stimulus term. After that, the learning trial begins. One by one, the stimulus words are presented and the participant tries to give the correct response term. In case of failure, the learner is shown the response word. Trials continue until the participant or the learner gives all the response words without a single error.

8.8.2 Serial Learning In this method, first, a list of verbal items like familiar words, unfamiliar words, non-sense syllables, and so on is prepared. The participant or the learner is presented the entire list and required to produce the items in the same serial order as in the list. In the first trial, the first item of the list is shown, and the participant has to produce the second. If the participant or the learner fails to do so in the prescribed time, the experimenter presents the second item. Now, the second item becomes the stimulus and the participant has to produce the third item that is the response word. This procedure is called serial anticipation method. Learning trials continue until the participant correctly anticipates all the items in the list.

8.8.3 Free Recall During this task a subject would be asked to study a list of words and then sometime later they will be asked to recall or write down as many words that they can remember. In this method, the participants or the learners are presented a list of words, which they read and speak out. Each word is shown at fixed periods of exposure. Immediately after the presentation of the list, the participants or the learners are required to recall the words in any order they can. Studies indicate that the items placed in the beginning (primacy effect) or in the end (recency effect) of the lists are easier to be recalled than those placed in the middle which are more difficult to learn. In cognitive psychology, the common finding that in a free recall situation, the materials that are presented first in a series or items which are towards the beginning of the list (primary items) are better recalled than those that are presented in the middle of the list. This is also called the “law of primacy” or the “principle of primacy”. Whereas, the common finding is that in a free recall experiment, the items that are presented towards the end of a list, that is most recent in time at the point of recall are more likely to be correctly recalled than those in the middle of the list. This is also called the law or the principle of recency. The generalization that in a free recall experiment the likelihood of an individual item from a list being recalled is a function of the location of that item in the serial presentation of the list during learning. This is called serialposition effect.

8.8.4 Recognition Subjects are asked to remember a list of words or pictures, after which point they are asked to identify the previously presented words or pictures from among a list of alternatives that were not presented in the original list.

8.9 FORGETTING Forgetting is a very familiar and common phenomenon. Broadly, forgetting is the loss of the ability to recall, recognise or reproduce that which was previously learned. Psychologists generally use the term “forgetting” to refer to apparent loss of information already encoded and stored in long-term memory. “Forgetting” (retention loss) refers to apparent loss of information already encoded and stored in an individual’s long-term memory. Forgetting

is the failure to recall what was once learnt, retained, and experienced. Forgetting is a spontaneous or gradual process in which old memories are unable to be recalled from memory storage. It is subject to delicately balanced optimisation that ensures that relevant memories are recalled. Forgetting can be reduced by repetition and (or more elaborative cognitive processing information). Reviewing information in ways that involve active retrieval seems to slow the rate of forgetting.

8.9.1 Some Definitions of Forgetting According to Aristotle, “Forgetting is fading of original experience with passage of time. It arises due to disuse.” According to Goddard, “Retention may be viewed in either positive or negative aspect and forgetting is negative aspect of retention.” According to Drever (1952), “Forgetting means failure at any time to recall an experience, when attempting to do so or to perform an action previously learned.” According to English and English (1958), “Forgetting: The loss or losing, temporary or permanent of something earlier learned, losing ability to recall, recognize or do something.” According to Munn (1967), “Forgetting is failing to retain or to be able to recall which has been acquired.” According to Stagner and Solley (1970), “Forgetting is the negative aspect of the memory. It is the failure to recall that which was once learned. How, to say that it is simply the failure to recall recognizes or retain……”

8.9.2 Types of Forgetting (i) Natural or normal or passive forgetting and morbid or abnormal or active forgetting: In “natural” or “normal” or “passive” forgetting, forgetting occurs in a normal way without making any effort or attempt with the passage or lapse of time or because of the disuse of the material learnt earlier. Whereas, in “morbid” or “abnormal” or “active” forgetting, a person deliberately forgets and consciously represses the unpleasant and painful material or information or experiences to be forgotten into the unconscious. (ii) General and specific forgetting: In “general” forgetting, there is a total loss of previously learnt material, whereas, in “specific” forgetting there

is partial loss or loss of specific parts of previously learnt material. (iii) Physical or organic and psychological forgetting: In “physical” or “organic” forgetting, certain physical illnesses, age, accidents, defects in the nervous system or brain can alter the functioning of the brain and nervous system, and causes forgetting. Whereas in ‘psychological” forgetting, psychological factors like stress, anxiety, conflicts, emotional and psychological disorders cause forgetting. Much of what we think we have forgotten does not really qualify “forgotten” because it was never encoded and stored in the first place. Memory has three major components; encoding, storage, and retrieval. Forgetting may occur due to failure at any of the stages. It may occur because of the failure of encoding, or storage, or retrieval.

8.9.3 Reasons for Forgetting (i) Trace decay: Trace decay focuses on the problem of availability caused when memories decay. Trace theory states that when something new is learned, a neuro-chemical, physical “memory trace” is formed in the brain, and over time, this trace tends to disintegrate, unless it is occasionally used. Hebb said that incoming information creates a pattern of neurons to create a neurological memory trace in the brain which would fade away with time. Repeated firing causes a structural change in the synapses. Rehearsal of repeated firing maintains the memory in STM until a structural change is made. (ii) Interference: Interference theory refers to the idea that forgetting occurs because the recall of certain items interferes with the recall of other items. Interference is an important cause of forgetting (Bushman and Bonacci, 2002). Interference is the negative inhibiting effect of one learning experience on another. It is the blurring of one memory by other memories that are similar to it and which compete with its recall and retrieval. In nature, the interfering items are said to originate from an over-stimulating environment. A vast amount of experimental evidence and everyday experience too indicates that learning new things interfere with our memory of what we learnt earlier and prior learning interferes with our memory of things learnt later. Interference theory exists in two branches, Retroactive and Proactive inhibition, each referring in contrast to the other. Memory interference resulting from

activities that came after or subsequent to the events you are trying to remember is called retroactive interference or inhibition. “Retroactive inhibition” is when the later memory interferes with the past memory, causing it to change in a particular extent. It is called “retroactive” because the interference is with the memory of events that came before the interfering activity. Later learning disrupts memory for earlier learning. John Jenkins and Karl Dallenbach (1924) discovered the sleep benefits in a classic experiment. Jenkins and Dallenbach found that retention after sleep was far superior to retention after waking activities even when the time interval between learning and retention were identical. In the sleeping conditions, some activity is present as the subject does not always go to sleep immediately after the learning is complete. Even during sleep, many reactions like muscular movements, circulatory, digestive, and other bodily functions continue to occur. During sleep, though complete psychological vacuum may not be possible, almost all the activities of the ‘O’ are at a minimum. Thus, fewer reactions occur which might interfere or inhibit with the recall of what originally learned. So, forgetting is minimum during sleep. Day after day, two people, each learned some non-sense syllables, and then tried to recall them after up to eight hours of being awake or sleep at night. Forgetting occurred more rapidly after being awake and involved with other activities. The investigators surmised that forgetting is not so much a matter of the decay of old impressions and associations as it is a matter of interference, or obliteration of the old by the new. Later experiments have confirmed that the hour before a night’s sleep (but not the minute before sleep) is a good time to commit information to memory (Fowler and others, 1973). “Proactive interference” or inhibition, on the other hand, is due to events that come before the to-be-remembered information or material. Previous learning interferes with later learning and memory or retention. “Proactive interference” is when older memory interferes with the later memory, causing it to damage. The interference disrupts the various kinds of association between stimuli and responses formed during learning. Interference also somehow has its greatest effect on the memory of retrieval cues. Both retroactive and proactive interference are greatest when two

different responses have been associated with the same stimulus, intermediate when two similar stimuli are involved and least when two quite different stimuli are involved. Infact, probably only a small fraction of forgetting can be attributed to retroactive and proactive interference. (iii) Retrieval failure: Forgetting is a process of fading of learned or memorised experiences with the passage of time. According to this view, forgetting is controlled by the time factor. Impressions fade away as the time passes. It is called the theory of disuse or decay. Psychologists believe that learning results in neurological changes in the brain resulting in the formation of traces in the brain. These memory traces or impressions made on the brain get weaker and finally fade away or decay with the passage of time or by not using that information for a long period of time that is through disuse. There is progressive loss in retention with lapse of time. According to Albert Schweitzer (1875– 1965), a physician, “Happiness is nothing more than health and a poor memory.” Apart from these three main causes or reasons of forgetting, there are the following other causes: (iv) Storage failure: Forgetting from long-term memory take place due to many factors. It may be due to decay of memory traces, because the stored material is not in use for a long period of time. Owing to disuse, the memory traces fade and ultimately become inaccessible. More often than not, memory trace is there in long-term memory, but interference in proper search for retrieval of information by situational factors leads us to think that the trace is lost forever. They appear to be lost, but memory traces, are never completely lost. Memory deteriorates with time, if they are not in use. The course of forgetting is initially rapid, and then levels off with time (Wixted and Ebbensen, 1991). (v) Encoding failure: Age can affect encoding efficiency. The same brain areas jump into action when young adults are encoding new information, are less responsive among older adults. This slower encoding helps explain age-related memory decline (Grady and others, 1995). (vi) Organic cause: Forgetting that occurs through physiological damage or dilapidation to the brain is referred to as “organic” causes of

forgetting. Certain physical illnesses or diseases, age, accidents, and the like can cause some form of damage to brain tissue and can alter the functioning of the brain and nervous system which results in forgetting or amnesia. These theories encompass the loss of information already retained in LTM or the inability to encode new information (examples include Alzheimer’s, Amnesia, Dementia), consolidation theory and the gradual slowing down of the Central Nervous System due to ageing. (vii) Confusion: Atkinson and Shiffrin claimed that forgetting often occurs because of confusion among similar long-term memories. They argued that nearly all forgetting from LTM is due to an inability to find the appropriate memory trace rather than to the disappearance of the trace from the memory system.

Endel Tulving (Born on 26 May, 1927)

(viii) Trace-dependent forgetting and cue-dependent forgetting: According to Endel Tulving (1927), a cognitive psychologist and a Canadian neuroscientist, trace-dependent forgetting and cue-dependent forgetting are the only two major causes of forgetting. “Trace-dependent forgetting” occurs because the memory trace has deteriorated or decayed or required information or material has been lost from the memory system. Physiological traces in the brain are not available at the time of recall or retrieval. “Cue-dependent forgetting” occurs when the memory trace still exists, but there is no suitable retrieval cue to trigger off the memory. The information is not accessible. It is a kind of forgetting in which the required information or material is in the LTM store, but cannot be retrieved without a suitable retrieval cue. The cues present at the time of learning are not present at the time of recall or interfering and competing cues are present and they block the memory. Cue-dependent or retrieval failure is the failure to recall a memory due to missing

stimuli or cues that were present at the time the memory was encoded. It is one of the five cognitive psychology theories of forgetting. It states that memory is sometimes temporarily forgotten purely because it cannot be retrieved, but the proper cue can bring it to mind. The information still exists, but without these cues, retrieval is unlikely. Furthermore, a good retrieval cue must be consistent with the original encoding of the information. If the sound of the word is emphasised during the encoding process, the cue should also put emphasis on the phonetic quality of the word. Information is available, however, just not readily available without these cues. (ix) Motivated forgetting or repression: Motivated forgetting or repression is discussed in detail later in this chapter. Forgetting, like attention, is selective. Forgetting, in some sense, is good because if forgetting does not take place, our life will be burdened with useless and unpleasant information. Memory researcher Daniel Schacter (1999) enumerates seven ways our memories fail us, and calls them seven sins of memory. They are as follows: Absent-mindedness: Inattention to details produces encoding failure. Transience: Transience includes storage decay over time. Information which is not used over time fades away. Blocking: It includes inaccessibility of stored information or material. Three sins of distortion: Misattribution: Misattribution includes confusing the source of information. Suggestibility: Suggestibility is the lingering effect of misinformation. Bias: Bias includes belief-coloured recollections. One sin of intrusion: Persistence: Persistence includes unwanted memories.

8.9.4 Factors Affecting Forgetting (i) Rate of original learning: When an individual learns with speed, forgetting will be slow and when learning is slow, the individual tends to forget quickly. (ii) Over-learning: Over-learning is the term used to describe the practice that continues after a perfect recall has been scored. Over-learning is essential for improving retention or retrieval. For example, nursery rhymes and multiplication tables. (iii) Interference: Interference can hamper memorisation and retrieval. There is retroactive interference when learning new information causes forgetting of old information, and proactive interference where learning one piece of information makes it harder to learn similar new information. Greeenberg and Underwood (1950) have conducted several experiments using within-groups or subject’s designs on proactive inhibition and have shown that the greater the number of prior lists learned, the higher is the amount of proactive inhibition. Muller and Pilzecker, a notable German psychologist have held that the time which lapses between the original learning and subsequent recall better known as the retention interval as such is not important for forgetting, but the activities with which the individual is engaged during the retention interval are more important in explaining forgetting. Thus, the interpolated activity that is the activity during the retention interval and not the disuse is the cause of forgetting. Muller and Pilzecker therefore define retroactive inhibition as a decrement in retention due to an interpolated activity introduced between the original learning and subsequent recall. In other words, the interpolated activity introduced during the retention interval determines forgetting to a large extent. This view of Muller and Pilzecker was verified by Jenkins and Dallenbach (1924). Jenkins and Dallenbach (1924) drew the following revolutionary conclusion: “Forgetting is not so much a matter of decay of old impressions and associations, as it is a matter of inhibitions, interference and obliteration of the old by the new.” Vanormer, Spright and number of similar other investigators have supported this view of Jenkins and Dallenbach. There are several factors which influence the phenomenon of retroactive

inhibition: Nature of interpolated activity Intensity of interpolated activity Temporal location of interpolated activity Length of interpolated activity Degree of original learning Use of same sense modality Emotional quality of the interpolated activity Mimami and Dallenbach (1946) have also found that when the retention interval is free from activity, like complete and sound sleep, there is almost no loss of retention. Thus, when a learning activity is followed by another activity, forgetting is greater and it is less when the same activity is followed by rest. (iv) Periodic reviews: Reviews soon after the original learning may prevent the very rapid forgetting that normally takes place immediately after practice. (v) Meaningfulness: The most effective method to improve retention is to make the subject matter meaningful. Meaningful material is forgotten less rapidly than the non-sense or meaningless material. (vi) Intention to learn: Most people feel that we are more likely to remember something if we deliberately try to learn it. The learners’ intention while learning affects both the retention of material and the rate of original learning. But Hyde and Jenkins (1973) reported that memory is determined by the nature of the processing that occurs at the time of learning rather than by the presence or absence of intention to learn the material. (vii) Spaced versus massed learning: The spacing of repetition of practice period influences retention. One may learn the subject matter superficially for immediate use by cramming. But, for permanent retention, a time interval between repetitions is more effective. (viii) Emotion: Emotion can have a powerful impact on memory. Numerous studies have shown that the most vivid autobiographical memories tend to be of emotional events, which are likely to be recalled more often and with more clarity and detail than neutral events.

8.10 MOTIVATED FORGETTING OR REPRESSION Theory on the relationship between motivation and forgetting or repressive (suppressive) forgetting states that unhappy memories are easily forgotten, that is forgetting is a motivated and intentional process. This theory was put forward by Sigmund Freud. According to him, forgetting is due to conscious repression or suppression by the person. “Repression” is a mental function which cushions the mind against the unpleasant effect of painful, traumatic, and unacceptable experiences, events, memories or conflicts. Freud claimed that repressed memories are traumatic and painful and are strongly associated with anxiety, guilt, or other negative emotions. The anxiety associated with memory is so great that the memory is kept out or pushed out of consciousness although it still exists in the unconscious mind.

8.11 TIPS FOR MEMORY IMPROVEMENTS Do you feel that you have a poor memory? You may just have some lessthan-effective habits when it comes to taking in and processing information. Barring disease, disorder, or injury, you can improve your ability to learn and retain information. Just like muscular strength, your ability to remember increases when you exercise your memory and nurture it with a good diet and other healthy habits. There are a number of steps you can take to improve your memory and retrieval capacity. First, however, it’s helpful to understand how we remember.

8.11.1 Brain Exercises Memory, like muscular strength, is a “use it or lose it” proposition. The more you work out your brain, the better you’ll be able to process and remember information. Novelty and sensory stimulation are the foundation of brain exercise. If you break your routine in a challenging way, you’re using brain pathways you weren’t using before. This can involve something as simple as brushing your teeth with your nondominant hand, which activates little-used connections on the nondominant side of your brain. Or try a “neurobic” exercise–an aerobic exercise for your brain–that forces you to use your faculties in unusual ways, like showering and getting dressed with your eyes closed. Take a course in a subject you don’t know much about, learn a new

game of strategy, or cook up some recipes in an unfamiliar cuisine. That’s the most effective way to keep your synapses firing.

8.11.2 General Guidelines to Improve Memory In addition to exercising your brain, there are some basic things you can do to improve your ability to retain and retrieve memories: (i) Pay attention: You can’t remember something if you never learned it, and you can’t learn something—that is, encode it into your brain—if you don’t pay enough attention to it. It takes about eight seconds of intent focus to process a piece of information through your hippocampus and into the appropriate memory center. So, no multitasking when you need to concentrate! If you distract easily, try to receive information in a quiet place where you won’t be interrupted. (ii) Tailor information acquisition to your learning style: Most people are visual learners; they learn best by reading or otherwise seeing what it is they have to know. But some are auditory learners who learn better by listening. They might benefit by recording information they need and listening to it until they remember it. (iii) Involve as many senses as possible: Even if you’re a visual learner, read out loud what you want to remember. If you can recite it rhythmically, even better. Try to relate information to colours, textures, smells and tastes. The physical act of rewriting information can help imprint it onto your brain. (iv) Relate information to what you already know: Connect new data to information you already remember, whether it’s new material that builds on previous knowledge, or something as simple as an address of someone who lives on a street where you already know someone. (v) Organise information: Write things down in address books and datebooks and on calendars; take notes on more complex material and reorganise the notes into categories later. Use both words and pictures in learning information. (vi) Understand and be able to interpret complex material: For more complex material, focus on understanding basic ideas rather than memorising isolated details. Be able to explain it to someone else in your own words.

(vii) Rehearse information frequently and “over-learn”: Review what you’ve learned the same day you learn it, and at intervals thereafter. What researchers call “spaced rehearsal” is more effective than “cramming.” If you’re able to “over-learn” information so that recalling it becomes second nature, so much the better. (viii) Be motivated and keep a positive attitude: Tell yourself that you want to learn what you need to remember, and that you can learn and remember it. Telling yourself you have a bad memory actually hampers the ability of your brain to remember, while positive mental feedback sets up an expectation of success.

8.11.3 Healthy Habits to Improve Memory Treating your body well can enhance your ability to process and recall information.

Healthy habits that improve memory Regular exercise

• Increases oxygen to your brain. • Reduces the risk for disorders that lead to memory loss, such as diabetes and cardiovascular disease.

• May enhance the effects of helpful brain chemicals and protect brain cells. Managing stress

• Cortisol, the stress hormone, can damage the hippocampus if the stress is unrelieved. • Stress makes it difficult to concentrate.

Good sleep habits

• Sleep is necessary for memory consolidation. • Sleep disorders like insomnia and sleep apnea leave you tired and unable to concentrate during the day.

Not smoking

• Smoking heightens the risk of vascular disorders that can cause stroke and constrict arteries that deliver oxygen to the brain.

8.11.4 Nutrition and Memory Improvement You probably know already that a diet based on fruits, vegetables, whole grains, and “healthy” fats will provide lots of health benefits, but such a diet can also improve memory. Research indicates that certain nutrients nurture and stimulate brain function. B vitamins, especially B6, B12, and folic acid, protects neurons by breaking down homocysteine, an amino acid that is toxic to nerve cells. They’re also involved in making red blood cells, which carry

oxygen. (Best sources: spinach and other dark leafy greens, broccoli, asparagus, strawberries, melons, black beans and other legumes, citrus fruits, soybeans.) Antioxidants like vitamins C and E, and beta carotene, fight free radicals, which are atoms formed when oxygen interacts with certain molecules. Free radicals are highly reactive and can damage cells, but antioxidants can interact with them safely and neutralise them. Antioxidants also improve the flow of oxygen through the body and brain. (Best sources: blueberries and other berries, sweet potatoes, red tomatoes, spinach, broccoli, green tea, nuts and seeds, citrus fruits, codliver oil.) Omega-3 fatty acids are concentrated in the brain and are associated with cognitive function. They count as “healthy” fats, as opposed to saturated fats and trans fats, protecting against inflammation and high cholesterol. (Best sources are cold-water fish such as salmon, herring, tuna, halibut, and mackerel; walnuts and walnut oil; flaxseed and flaxseed oil). Since older adults are more prone to B12 and folic acid deficiencies, a supplement may be a good idea for seniors. An omega-3 supplement (at any age) if you don’t like eating fish. But nutrients work best when they’re consumed in foods, so try your best to eat a broad spectrum of colourful plant foods and choose fats that will help clear, not clog, your arteries.

QUESTIONS Section A Answer the following in five lines or in 50 words: 1. 2. 3. 4. 5. 6. 7. 8. 9. 10.

Memory Encoding Chunk Chunking Cued recall Declarative knowledge Recall method Free recall Proactive interference or inhibition Retroactive interference

11. 12. 13. 14. 15. 16. 17. 18. 19. 20. 21. 22. 23. 24. 25. 26. 27. 28. 29. 30. 31. 32. 33. 34. 35. 36. 37. 38. 39. 40. 41. 42.

Retroactive inhibition Procedural knowledge Repression Motivated forgetting Decay Implicit memory Explicit memory Memory span Retention Define short-term memory Sensory memory Sensory register Explain types of inhibition. Give three ways of reducing forgetting Write three characteristics of memory Write three methods of measuring short-term memory Name the Psychologist who introduced ‘Nonsense Syllables’ to study memory Curve of forgetting Draw ‘Forgetting Curve’ given by Ebbinghaus Ebbinghaus Nonsense syllables What is recognition? Eyewitness testimony Mnemonic Recognition method Short-term memory Saving methods Semantic memory Decaying Storage Retrieval Multi-store model

43. 44. 45. 46. 47. 48. 49. 50. 51. 52. 53.

Confirmation bias Elaboration Long-term memory Proactive interference Repression Recognition STM LTM Strength of memory Maintenance rehearsal Deep processing

Section B Answer the following questions up to two pages or in 500 words: 1. What do you mean by term ‘Memory’? Discuss its past process. 2. What is mnemonics? How does this help in improving memory? Give examples. 3. Evaluate the role of delay and interference in forgetting citing daily examples. 4. Explain different factors of forgetting. 5. Discuss different methods of retention. or What is retention? Explain the methods of testing retention. 6. Discuss methods of measuring long-term memory. 7. Explain ‘Retention Curve’ given by Ebbinghaus. 8. Explain differences between short-term and long-term memory. or Differentiate between long-term and short-term memory. 9. “Forgetting is an active and purposeful mental process”. Elucidate. 10. What is remembering? Describe the processes involved in remembering. 11. What is short-term memory? How does it differ from long-term memory?

12. What is proactive inhibition? How does it differ from retroactive inhibition? 13. According to the Atkinson and Shiffrin model, what basic tasks are carried out by memory? 14. What are sensory memory, short-term memory, and long-term memory? 15. What tasks does working memory perform? 16. What are episodic memory and semantic memory? 17. What are retrieval cues, and what role do they play in memory? 18. What is procedural memory? 19. What is repression? What role does it play in memory?

Section C Answer the following questions up to five pages or in 1000 words: 1. What do you understand by memory? Discuss the process of memory. 2. Describe the interference theory of forgetting. What factors other than interference cause forgetting? 3. Define memory and discuss its past process. 4. Discuss the causes of forgetting. 5. What is forgetting? Discuss the causes of forgetting. 6. What is retention? How it can be measured? 7. Explain differences between short-term and long-term memory. 8. Explain the interference theory of forgetting. 9. Discuss different factors of forgetting. 10. Define memory and explain in detail long-term memory. 11. What is forgetting? Explain the various causes of forgetting. 12. What are the marks of a good memory? Suggest methods to improve memory. 13. Define forgetting. How retroactive inhibition and proactive inhibition effect forgetting? 14. What is forgetting? Discuss various factors that contribute to forgetting.

15. “Forgetting is not so much a matter of decay of old impressions and associations as it is a matter of inhibition, interference and obliteration of the old by the new.” Explain this statement citing empirical findings. 16. Discuss the importance of psychoanalytic causes of forgetting in practical life. 17. Critically examine Bartlett’s theory of constructive changes in memory. 18. Discuss in detail the mnemonic devices used to improve memory. 19. Discuss the various stages of memory system. 20. What is meant by encoding? How does encoding failure lead to forgetting? Explain with examples. 21. What are retroactive interference and proactive interference? What role do they play in forgetting? 22. What factors potentially reduce the accuracy of eyewitness testimony? 23. Write brief notes on the following: (i) Theory of disuse (ii) Massed versus Distributed practice (iii) Recall versus Recognition (iv) Reconstruction method (v) Role of interpolated activity in forgetting (vi) Encoding and Storage (vii) Retrieval failure (viii) Chunking (ix) Sensory memory

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9 Thinking and Problem-Solving INTRODUCTION “Thinking” or “cognition” refers to all the mental or cognitive activities associated with processing, understanding, remembering, and communicating. Cognition is a general term used to denote thinking and many other aspects of our higher mental processes. Psychological understanding of the physiological basis of thought does not seem to have progressed very far. As Bourne, Ekstrand, and Dominowski (1971) wrote, “Thinking is one of those mysterious concepts that everyone understands and no one can explain.” According to G.C. Oden, “Thinking, broadly defined, is nearly all of psychology; narrowly defined, it seems to be none of it.” Cognition is the scientific term for “the process of thought”. Usage of the term varies in different disciplines; for example, in psychology and cognitive science, it usually refers to an information processing view of an individual’s psychological functions. Other interpretations of the meaning of cognition link it to the development of concepts, individual minds, groups, and organisations. The term cognition is derived from the Latin word cognoscere, which means “to know”, “to conceptualise”, or “to recognise”. It refers to the faculty for the processing of information, applying knowledge, and changing preferences. In psychology and in artificial intelligence, cognition is used to refer to the mental functions, mental processes (thoughts) and states of intelligent entities (humans, human organisations, highly autonomous

machines). Cognition is the mental activity associated with thought, decisionmaking, language, and other higher mental processes.

9.1 SOME DEFINITIONS OF THINKING Several different definitions of thinking have been offered over the years. According to Charles Osgood (1953), thinking occurs whenever behaviour is produced for which “the relevant cues are not available in the external environment at the time the correct response is required, but must be supplied by the organism itself.” While this definition seems to capture part of what is involved in thinking, it is too general. For example, simply recalling information from long-term memory would often fit Osgood’s definition, but would seem to lack the complexity of processing usually associated with thinking. A more adequate definition of thinking was offered by Humphrey (1951). He suggested that thinking is “What happens in experience when an organism —human or animal, meets, recognises, and solves a problem.” Humphrey’s definition is reasonably satisfactory, but begs the question of what we mean by a “problem”. This issue was addressed by John Anderson (1980), who argued that the activity of problem solving typically involves the following three ingredients: (i) The individual is goal-directed, in the sense of attempting to reach a desired end state. (ii) Reaching the goal or solution requires a sequence of mental processes rather than simply a single mental process, for example, putting your foot on the brake when you see a red light is goal-directed behaviour, but the single process does not usually involve thinking. (iii) The mental processes involved in the task should be cognitive rather than automatic; this ingredient needs to be included to eliminate routine sequences of behaviour, such as dealing a pack of playing cards. According to Ross (1951), “Thinking is mental activity in its cognitive aspect or mental activity with regard to psychological objects.” According to Garrett (1960), “Thinking is an implicit or hidden behaviour involving symbols such as ideas and concepts and images, etc.” According to Valentine (1965), “In strict psychological discussion it is well to keep the thinking for an activity which consists essentially of a

connected flow of ideas which are directed towards some end or purpose.” According to Mohsin (1967), “Thinking is an implicit problem solving behaviour.” According to Garrett (1968), “Thinking is behaviour which is often implicit and hidden and in which symbols (images, ideas, and concepts) are ordinarily employed.” According to Haber (1969), “Thinking is a covert and invisible process.” According to Gilmer (1970), “Thinking is a problem solving process in which we use ideas or symbols in place of overt activity.” According to Fantino and Reynolds (1975), “Thinking is a problemsolving activity that can be readily studied and measured.” According to Rathus (1996), “Thinking is a mental activity that is involved in understanding, processing, and communicating information. Thinking entails attending to information, mentally representing it, reasoning about it, and making judgments and decisions about it.” According to Solso (1997), “Thinking is a process by which a new mental representation is formed through the transformation of information by complex interaction of the mental attributes of judging, abstracting, reasoning, imagining, and problem solving.” According to Morgan and King (2002), “Thinking consists of the cognitive rearrangement and manipulation of both information from the environment and symbols stored in LTM.” According to some definitions, thinking is stimulated by some ongoing external event. In these terms, the thinking is problem directed or geared toward reaching some decision that may then be expressed in some overt behaviour as you can find in Figure 9.1. But external stimuli may not always be necessary. Thinking can involve material extracted from our memories; thus, it is not tied to events that are immediately present in our external environment. Further, thinking may not be goal directed at all, except in so far as it provides some kind of mental entertainment, as in the case of daydreaming.

Figure 9.1 Thinking.

Thinking is any covert cognitive or mental manipulation of ideas, images, symbols, words, propositions, memories, concepts, percepts, beliefs or intentions. Thinking is an activity that involves the manipulation of mental representations of various features of the external world. Even though thinking may always involve a problem of some kind, the topic of thinking is traditionally divided into a number of more specific topics, including problem-solving (typically involves processing information in various ways in order to move toward desired goals), reasoning (mental activity through which we transform available information in order to reach conclusions), and decision-making (the process of choosing between two or more alternatives on the basis of information about them), and judgement (the process of forming an opinion or reaching a conclusion based on the available material: the opinion or conclusion so reached). It should be noted, however, that many of the same cognitive processes span these different areas of study. Thinking is a higher cognitive process a complex process a mental or cognitive activity a symbolic activity not perceptual or overt manipulation mental exploration implicit (internal) behaviour an implicit or inner activity a covert or implicit process that is not directly observable

private behaviour an implicit problem-solving behaviour purposeful behaviour goal-directed behaviour a process of internal representation of external events. Thinking may thus be defined as a pattern of behaviour in which we make use of internal representations (symbols, signs, and so on) of things and events for the solution of some specific, purposeful problem. Psychologists consider thinking as the manipulation of mental representations of information. The representation may be a word, a visual image, a sound, or data in any other modality. What thinking does is to transform the representation of information into a new and different form for the purpose of answering a question, solving a problem or aiding in reaching a goal.

9.2 CHARACTERISTICS OF THINKING Following are some of the characteristics of thinking: (i) Thinking is a covert or internal and complex cognitive process. (ii) Thinking is an implicit or internal or hidden behaviour or mental exploration. (iii) Thinking is a process that involves some manipulation of knowledge in the cognitive system. (iv) Thinking is a process of internal representation of external events, belonging to the past, present or future, and may even concern a thing or an event which is not being actually observed or experienced by the thinker. (v) Thinking is a process that goes on internally in the mind of the thinker and can be inferred from the behaviour of that person. Let us understand the term “inference”. For example, you are asked by your teacher to remember a multiplication table. You read that table a number of times. Then you say that you have learnt the table. You are asked to recite that table and you are able to do it. The recitation of that table by you is your performance. On the basis of your performance, the teacher infers that you have learned that table. (vi) Thinking is goal-directed and results in behaviour directed towards the

solution of the problem. Motivation plays an important role in thinking. (vii) In thinking, the thinker uses symbols such as ideas, concepts, and images in the problem-solving process. (viii) Thinking involves information from past experiences. (ix) Thinking involves many cognitive and higher mental processes like sensation, perception, memory, reasoning, imagination, conceptformation, and problem-solving. (x) Thinking makes use of language.

9.3 TYPES OF THINKING (i) Critical thinking: This is convergent thinking. It assesses the worth and validity of something existent. It involves precise, persistent, objective analysis. When teachers try to get several learners to think convergently, they try to help them develop common understanding. (ii) Creative thinking: This is divergent thinking. It generates something new or different. It involves having a different idea that works as well or better than previous ideas. (iii) Convergent thinking: Convergent thinking is a term coined by Joy Paul Guilford, a psychologist well-known for his research on creativity, as the opposite of divergent thinking. It generally means the ability to give the correct answer to standard questions that do not require significant creativity, for instance in most tasks in school and on standardised multiple-choice tests of intelligence. This type of thinking is cognitive processing of information around a common point, an attempt to bring thoughts from different directions into a union or common conclusion. Convergent thinking reflects the capacity to focus on a single problem and ignore distractions. People who can focus on tasks, and ignore distractions are convergent thinkers. Convergent thinking is a style of thought that attempts to consider all available information and arrive at the single best possible answer. Most of the thinking called for in schools is convergent, as schools require students to gather and remember information and make logical decisions and answers accordingly. Convergent thinking is not, generally speaking, particularly creative and is best employed when a single correct answer does exist and can be discovered based on an analysis of available

stored information. Convergent thinking is the reduction or focusing of many different ideas into one possible problem solution. Convergent thinking, which narrows all options to one solution, corresponds closely to the types of tasks usually called for in school and on standardised multiple-choice tests. In contrast, creativity tests designed to assess divergent thinking often ask how many different answers or solutions a person can think of. (iv) Divergent thinking: In contrast to the convergent style of thought is divergent thinking, which is more creative and which often involves multiple possible solutions to problems. This type of thinking starts from a common point and moves outward into a variety of perspectives. When fostering divergent thinking, teachers use the content as a vehicle to prompt diverse or unique thinking among students rather than a common view. (v) Inductive thinking: This is the process of reasoning from parts to the whole, from examples to generalizations. (vi) Deductive thinking: This type of reasoning moves from the whole to its parts, from generalizations to underlying concepts to examples. (vii) Closed questions: These are questions asked by teachers that have predictable responses. Closed questions almost always require factual recall rather than higher levels of thinking. (viii) Open questions: These are questions that do not have predictable answers. Open questions almost always require higher order thinking.

9.4 TOOLS OR ELEMENTS OF THOUGHT OR THINKING Thoughts are forms created in the mind, rather than the forms perceived through the five senses. Thought and thinking are the processes by which these imaginary sense perceptions arise and are manipulated. Thinking allows human beings to model the world and to represent it according to their objectives, plans, ends and desires. Thinking is assumed to comprise a number of mental processes in which events, objects, and ideas are manipulated in some symbolic way. (i) Images: Wilhelm Wundt (1832–1920) proposed that thought was always accompanied by pictorial images. This view was not shared by psychologist and Wundt’s student Oswald Kulpe (1862–1955). Kulpe

proposed that thinking could occur without the mental pictures. Thinking often involves the manipulation of visual images. Visual images are mental pictures of objects or events in the external world. Research seems to indicate that mental manipulations performed on images of objects are very similar to those that would be performed on the actual objects (Kosslyn, 1994). People report using images for understanding verbal instructions, by converting the words into mental pictures of actions, and for enhancing their own moods, by visualising positive events or scenes (Kosslyn et al., 1991). New evidence also seems to indicate that mental imagery may have important practical benefits, including helping people change their behaviour to achieve important goals, such as losing weight or enhancing certain aspects of their performance (Taylor et al., 1998). (ii) Concepts: Concepts are very useful for studying the process of thinking. Without concept attainment or formation, thinking is not possible. Concepts are mental categories for objects, events, experiences, or ideas that are similar to one another in one or more respects. They allow us to represent a great deal of information about diverse objects, events, or ideas in a highly efficient manner. A concept is a symbol that represents a class of objects or events that share some common properties. The common properties are called the attributes of the concept and they are related to one another by a rule or set of rules. An attribute is some feature of an object or event that varies along certain dimensions. Qualities that exist in all members of a class are referred to as defining attributes. Typical attributes are those that are associated with most members of a class, but not all. Psychologists often distinguish between logical and natural concepts. Logical concepts are ones that can be clearly defined by a set of rules or properties. In contrast, natural concepts have no fixed or readily specified set of defining features. As natural concepts are formed, their attributes associated with them may be stored in memory. Concepts are closely related to schemas, cognitive frameworks that represent our knowledge of and assumptions about the world. (iii) Symbols and signs: According to English and English, Sign: A conventional gesture standing for a word or words or for an idea, for

example, nodding for “yes”, the language of the deaf……the positive or negative quantity of a mathematical expression, or, the printed or written marks (+ or –) for positive or, more generally any mark having a fixed conventional meaning, for example, S the sign for algebraic summation. James Drever defined symbol “as an object or activity representing and standing as a substitute for something else…” P.L. Harriman defined symbol as “Symbol: any stimulus (for example, object, spoken word, ideational element) which elicits a response originally attached to another stimulus.” (iv) Language: Language and thought are closely related. It is through language that we share our cognition with others. (vii) Brain functioning: Brain is said to be the chief instrument or seat for the carrying out of the process of thinking.

9.5 CHARACTERISTICS OF CREATIVE THINKERS Creative thinking involves creating something new or original. It involves the skills of flexibility, originality, fluency, elaboration, brainstorming, modification, imagery, associative thinking, attribute listing, metaphorical thinking, and forced relationships. The aim of creative thinking is to stimulate curiosity and promote divergence. Creative thinking involves imagining familiar things in a new light, digging below the surface to find previously undetected patterns, and finding connections among unrelated phenomena. —ROGER VON OECH “Creativity” is not just a collection of intellectual abilities. It is also a personality type, a way of thinking and living. Although creative people tend to be unconventional, they share common traits. For example, creative thinkers are confident, independent, and risktaking. They are perceptive and have good intuition. They display flexible, original thinking. They dare to differ, make waves, challenge traditions, and bend a few rules. Creative persons do have higher intelligence quotient (IQ) than general population, but they do not differ on this criterion from persons in their own field judged as non-creative (Barron and

Harrington, 1981). Creative people are typically at least above average in intelligence, but not necessarily extraordinarily so; other factors are as important as their IQ—especially the ability to visualise, imagine, and make mental transformations. A creative person looks at one thing, and sees modifications, new combinations, or new applications. Analogical thinking is central to creativity. The creative person “makes connections” between one situation and another, between the problem at hand and similar situations. The creative person thinks critically. Critical thinking involves logical thinking and reasoning including skills such as comparison, classification, sequencing, cause/effect, patterning, webbing, analogies, deductive and inductive reasoning, forecasting, planning, hypothesising, and critiquing. Another important talent for creative problem-solving is the ability to think logically while evaluating facts and implementing decisions. Sometimes it is even necessary to “find order in chaos.” Creative thinkers value ideas. Highly creative people are dedicated to ideas. They don’t rely on their talent alone; they rely on their discipline. They know how to manipulate it to its fullest. Creative thinkers explore options. As Albert Einstein put it, “Imagination is more important than knowledge.” Good thinkers come up with the best answers. They create backup plans that provide them with alternatives. Creative thinkers celebrate the offbeat. Creativity, by its very nature, often explores off of the beaten path and goes against the grain. Creative thinkers connect the unconnected. Because creativity utilises the ideas of others, there’s great value in being able to connect one idea to another—especially to seemingly unrelated ideas. Tim Hansen says, “Creativity is especially expressed in the ability to make connections, to make associations, to turn things around and express them in a new way.” Creative thinkers don’t fear failure: Charles Frankel asserts that “anxiety is the essential condition of intellectual and artistic creation.” Creativity requires a willingness to look stupid. It means getting out on a limb—knowing that the limb often breaks!

Highly creative individuals may display a great deal of curiosity about many things; are constantly asking questions about anything and everything; may have broad interests in many unrelated areas. May devise collections based on unusual things and interests. Highly creative individuals may generate a large number of ideas or solutions to problems and questions; often offer unusual (“way out”), unique, clever responses. Highly creative individuals are often uninhibited in expressions of opinion; are sometimes radical and spirited in disagreement; are unusually tenacious or persistent—fixating on an idea or project. Highly creative individuals are willing to take risks, are often people who are described as a “high risk taker, or adventurous, or speculative.” Highly creative individuals may display a good deal of intellectual playfulness; may frequently be caught fantasising, daydreaming or imagining. Often wonder out loud and might be heard saying, “I wonder what would happen if…” or “What if we change …” Highly creative individuals can manipulate ideas by easily changing, elaborating, adapting, improving, or modifying the original idea or the ideas of others. Highly creative individuals are often concerned about improving the conceptual frameworks of institutions, objects, and systems. Highly creative individuals may display keen senses of humor and see humor in situations that may not appear to be humorous to others. Sometimes their humor may appear bizarre, inappropriate, and irrelevant to others. Highly creative individuals are unusually aware of his or her impulses and are often more open to the irrational within him or herself. They may freely display opposite gender characteristics (freer expression of feminine interests in boys, greater than usual amount of independence for girls). Highly creative individuals may exhibit heightened emotional sensitivity. They may be very sensitive to beauty, and visibly moved by aesthetic experiences. Highly creative individuals are frequently perceived as nonconforming; accept disordered of chaotic environments or

situations; are frequently not interested in details, are described as individualistic; or do not fear being classified as “different”. Highly creative individuals may criticise constructively, and are unwilling to accept authoritarian pronouncements without overly critical self-examination. Like all of us, creative people make mistakes, and they subject themselves to embarrassment and humiliation. They must be willing to fail. Thomas Watson, founder of IBM (International Business Machines), even recommended that one route to success was to “double your failure rate.” One particularly common trait of creative people is enthusiasm. The phrases “driving absorption,” “high commitment,” “passionate interest,” and “unwilling to give up” describe most creative people. The high energy also appears in adventurous and thrill-seeking activities. Don’t some of your most creative colleagues ride motorcycles, fly airplanes? Curiosity and wide interests are related traits, whether the creative person is a research scientist, entrepreneur, artist, or professional entertainer. A good sense of humour is common. Creative people tend to have a childlike sense of wonder and intrigue, and an experimental nature. They may take things apart to see how they work, explore old attics or odd museums, or explore unusual hobbies and collections. In other words, “the creative adult is essentially a perpetual child—the tragedy is that most of us grow up.” Another interesting combination some creative people display is a tolerance for complexity and ambiguity and an attraction to the mysterious. Creative thinking requires working with incomplete ideas: relevant facts are missing; rules are cloudy, “correct” procedures nonexistent. Because most ideas evolve through a series of modifications, approximations, and improvements, creators must cope with uncertainty. Many creative people seem to couple their interest in complexity and ambiguity with their lively imaginations and openmindedness, and some are strong believers in flying saucers, extrasensory perception, or other dubious phenomena. So far the creative personality looks pretty good. However,

exasperated parents, teachers, colleagues, and supervisors are all familiar with some negative traits of creative people. They can be stubborn, uncooperative, indifferent to conventions and courtesies, and they are likely to argue that the rest of the parade is out of step. Creative people can be careless and disorganised, especially with matters they consider trivial. Absentmindedness and forgetfulness are common. Some are temperamental and moody; a few cynical, sarcastic, or rebellious. Most creative people realise there are a time to conform and a time to be creative. In any case, managers must learn to control negative traits to maximise creative output while maintaining the company’s standards. The key is patience and understanding, founded on the knowledge that such traits are common among people who are naturally independent, unconventional, and bored by trivialities. Because rigid enforcement of rules will alienate creative people and squelch their creativeness, flexibility and rule-bending are necessary on occasion. Humor is a management technique that can effectively convey your message without arousing negative emotions: “How’s the new plan coming? Any chance you’ll get it to me by Friday? It’ll give me the excuse to be busy this weekend. With my in-laws visiting and all….” The creative person approaches all aspects of life creatively: she or he is well-adjusted, mentally healthy, democratic-minded and “forward growing.”

9.6 PROBLEM A problem is anything that obstructs your path to achieve a goal. Problem is a situation in which there is a discrepancy between one’s current state and one’s desired or goal state, with no clear way of getting from one to the other. According to Morgan and King, “Problem is any conflict or difference between one situation and another situation we wish to produce our goal.” A problem exists when there is a discrepancy between one’s present state and one’s perceived goal, and there is no readily apparent way to get from one to the other. In other words, we can say that a problem exists when there

is a discrepancy between one’s present status and some goal one wishes to obtain, with no obvious way to bridge the gap. The essence of a problem is that one must figure out what can be done to resolve a predicament or dilemma and to achieve some goal. Some problems are trivial or insignificant and short-term, whereas others are important and long-term. In situations where the path to goal attainment is not clear or obvious, one needs to engage in problem-solving behaviours. Solving a problem is devising a strategy and executing it to achieve the goal by overcoming the difficulty. A problem may have more than one possible solution. Many times what is needed is an optimised solution which represents the shortest path to overcome the difficulty, with economy of resources. Problem-solving varies along three dimensions: problem type, problem representation, and individual differences. Problems vary by structuredness, complexity, and abstractness. Problem representations vary by context and modality. A host of individual differences mediate individual’s abilities to solve those problems. Although dichotomous descriptions of general types of problems are useful for clarifying attributes of problems, they are insufficient for suggesting specific cognitive processes and instructional strategies. Additional accuracy and clarity is needed to resolve specific problem types.

9.6.1 Problem Types Structuredness Jonassen (1997) distinguished well-structured from ill-structured problems and recommended different design models for each, because they call on distinctly different kinds of skills. The most commonly encountered problems, especially in schools and universities, are well-structured problems. Typically found at the end of textbook chapters, these wellstructured “application problems” require the application of a finite number of concepts, rules, and principles being studied to a constrained problem situation. These problems have also been referred to as transformation problems (Greeno, 1978) which consist of a well-defined initial state, a known goal state, and constrained set of logical operators. Well-structured problems have certain characteristics:

present all elements of the problem; are presented to learners as well-defined problems with a probable solution (the parameters of problem specified in problem statement); engage the application of a limited number of rules and principles that are organised in a predictive and prescriptive arrangement with well-defined, constrained parameters; involve concepts and rules that appear regular and well-structured in a domain of knowledge that also appears well-structured and predictable; possess correct, convergent answers; possess knowable, comprehensible solutions where the relationship between decision choices and all problem states is known or probabilistic (Wood, 1983); and have a preferred, prescribed solution process. Ill-structured problems are the kinds of problems that are encountered in everyday practice, so they are typically emergent dilemmas. Because they are not constrained by the content domains being studied in classrooms, their solutions are not predictable or convergent. Also they may require the integration of several content domains. Solutions to problems such as pollution may require components from math, science, political science, and psychology. There may be many alternative solutions to problems. However, because they are situated in everyday practice, they are much more interesting and meaningful to learners, who are required to define the problem and determine which information and skills are needed to help solve it. Ill-structured problems: appear ill-defined because one or more of the problem elements are unknown or not known with any degree of confidence (Wood, 1983); have vaguely defined or unclear goals and unstated constraints (Voss, 1988); possess multiple solutions, solution paths, or no solutions at all (Kitchner, 1983), that is, no consensual agreement on the appropriate solution; possess multiple criteria for evaluating solutions; possess less manipulable parameters;

have no prototypic cases because case elements are differentially important in different contexts and because they interact (Spiro et al, 1987, 1988); present uncertainty about which concepts, rules, and principles are necessary for the solution or how they are organised; possess relationships between concepts, rules, and principles that are inconsistent between cases; offer no general rules or principles for describing or predicting most of the cases; have no explicit means for determining appropriate action; require learners to express personal opinions or beliefs about the problem, so ill-structured problems are uniquely human interpersonal activities (Meacham and Emont, 1989); and require learners to make judgements about the problem and defend them. Researchers have long assumed that learning to solve well-structured problems transfers positively to learning to solve ill-structured problems. Although information processing theories believed that “the processes used to solve ill-structured problems are the same as those used to solve well structured problems” (Simon, 1978), more recent research in situated and everyday problem-solving makes clear distinctions between thinking required to solve convergent problems and everyday problems. Dunkle, Schraw, and Bendixen (1995) concluded that performance in solving well-defined problems is independent of performance on ill-defined tasks, with ill-defined problems engaging a different set of epistemic beliefs. Clearly more research is needed to substantiate this finding, yet it is obvious that well-structured and ill-structured problem-solving engage different intellectual skills.

Complexity Just as ill-structured problems are more difficult to solve than well-structured problems, complex problems are more difficult than simple ones. There are many potential definitions of problem complexity. For purpose of this study, complexity is assessed by the: (i) number of issues, functions, or variables involved in the problem. (ii) number of interactions among those issues, functions, or variables.

(iii) predictability of the behaviour of those issues, functions, or variables. Although complexity and structuredness invariably overlap, complexity is more concerned with how many components are in the problem, how those components interact, and how consistently they behave. Complexity has more direct implications for working memory than for comprehension. The more complex a problem is, the more difficult it will be for the problem solver to actively process the components of the problem. While ill-structured problems tend to be more complex, well-structured problems can be extremely complex making ill-structured problems fairly and comparatively simple. Complexity is clearly related to structuredness, though it is a sufficiently independent factor to warrant consideration.

9.6.2 Characteristics of Difficult Problems As elucidated by Dietrich Dorner and later expanded upon by Joachim Funke, difficult problems have some typical characteristics which can be summarised as follows: (i) Intransparency (lack of clarity of the situation) commencement opacity continuation opacity (ii) Polytely (multiple goals) inexpressiveness opposition transience (iii) Complexity (large numbers of items, interrelations and decisions) enumerability connectivity (hierarchy relation, communication relation, allocation relation) heterogeneity (iv) Dynamics (time considerations) temporal constraints temporal sensitivity phase effects dynamic unpredictability The resolution of difficult problems requires a direct attack on each of

these characteristics that are encountered. We use problem-solving when we want to reach a certain goal, and this goal is not readily available. Problem-solving is a major human activity in our interpersonal relationships as well as our occupations in this hightechnology society (Lesgold, 1988). According to Anderson (1980), problem-solving generally possesses the following three features: (i) The individual is goal-directed, in the sense of trying to reach a desired end state. (ii) Reaching the goal or solution requires various mental processes rather than just one. (iii) The mental processes involved do not occur automatically and without thought. Problem-solving is different from simply executing a well-learned response or series of behaviours. It is also distinct from learning new information.

9.7 PROBLEM-SOLVING Problem-solving is a mental process and is part of the larger problem that includes problem finding and problem shaping. Problem-solving includes the processes involved in solving the problem (see Figure 9.2). Considered the most complex of all intellectual functions, problem-solving has been defined as higher-order cognitive process that requires the modulation control of more routine or fundamental skills. Problem-solving occurs when an organism or an artificial intelligence system needs to move from a given state to a desired goal state.

Figure 9.2 Problem-solving.

Cognitions include one’s ideas, beliefs, thoughts, and images. When we know, understand, or remember something, we use cognitions to do so. Cognitive processes involve the formation, manipulation, learning, memory, problem-solving, language user, and intelligence. Because problem-solving, language use, and intelligence rely so heavily on the fundamental processes of perception, learning, and memory, we can refer to them as “higher” cognitive processes. Problem-solving can be defined as a goal directed process initiated in the presence of some obstacles and the absence of an evident solution. Problemsolving means the efforts to develop or choose among various responses in order to attain desired goals. Problem-solving is a mental process and is part of the larger problem process that includes problem finding and problem shaping. Considered the most complex of all intellectual functions, problem-solving has been defined as higher-order cognitive process that requires the modulation and control of more routine or fundamental skills. Problem-solving occurs when an organism or an artificial intelligence system needs to move from a given state to a desired goal state. Problem-solving is the framework or pattern within which creative thinking and reasoning take place. It is the ability to think and reason on given levels of complexity. People who have learned effective problemsolving techniques are able to solve problems at higher levels of complexity than more intelligent people who have no such training. In general, the state of tension is created in mind when an individual faces a problem. He exercises his greatest effort and uses all his abilities, intelligence, thinking, imagination, observation, etc. Some individuals are able to solve problems sooner than others. That indicates that there are levels of problem-solving ability—ranging from average ability to highest ability depending upon the difficulty level of the problem. A simple problem can be solved by the person having average problem-solving ability, while high level of ability is required to solve complex problems. Perhaps man’s greatest use of sentence language has been the system that he has developed for its application to problem-solving. It is not language alone but also the way in which he uses language. Two men of equal ability with language may not be equal in their ability to solve problems. Problem-solving is a process of overcoming difficulties that appear to

interfere with the attainment of a goal. Simple problems can well be solved by instinctive and habitual behaviours. More difficult problems require a series of solution attempts, until the successful solution is reached. Problems still more difficult require a degree of understanding, a perception of the relationships between the significant factors of a problem. It has been found that persons having higher intelligence and reasoning ability can solve the complex problems quickly. Therefore, it is necessary that we try to develop intelligence, reasoning ability as well as the problemsolving ability through proper education and training. Problem-solving ability is highly correlated with intelligence, reasoning ability, and mathematical ability. The nature of human problem-solving methods has been studied by psychologists over the past hundred years. There are several methods of studying problem-solving, including; introspection, behaviourism, simulation, computer modelling and experiment.

9.7.1 Some Definitions of Problem-solving According to Woodworth and Marquis (1948), “Problem-solving behaviour occurs in novel or difficult situations in which a solution is not obtainable by the habitual methods of applying concepts and principles derived from past experience in very similar situations.” According to Hilgard (1953), “Whenever goal oriented activity is blocked, whenever a need remain unfulfilled, a question unanswered, perplexity unrelated, the subject faces a problem.” According to Skinner (1968), “Problem-solving is a process of overcoming difficulties that appear to interfere with the attainment of a goal. It is a procedure of making adjustment inspite of interferences.” According to D.M. Johnson (1972), “When a person is motivated to reach the goal, but fails in the first attempt to reaching the goal, the problem arises for the person in that situation.” According to Eysenck (1972), “Problem-solving is that process which starts from cognitive situation and ends in achieving desired goal.” According to Simon Hemson (1978), “A novel problem is defined as one which an individual cannot solve by a previously learned response pattern. The ability to cope with novel problems has often been linked with the capacity for reasoning.”

According to Weiner (1978), “Problem-solving is a form of learning in which individual has to overcome some obstacles or barrier in order to reach a desired goal toward this and individual typically use different strategies.” According to Baron (1997), “Problem-solving refers to an effort to develop or choose among various responses in order to attain desired goals.” According to Solso (1998), “Problem-solving is thinking that is directed towards the solving of a specific problem that involves both the formation of responses and the selection among possible responses.” According to Mangal (2004), Problem-solving behaviour may be said “to be a deliberate and purposeful act on the part of an individual to realize the set goals or objectives by inventing some novel methods or systematically following some planned step for removal of the interferences and obstacles in the path of the realization of these goals when usual methods like trial and error, habit-formation and conditioning fail.” Gagne (1980) believed that “the central point of education is to teach people to think, to use their rational powers, to become better problem solvers”. Most educators, like Gagne, regard problem-solving as the most important learning outcome from life. The ability to solve problems, we all believe, is intellectually demanding and engages learners in higher-order thinking skills. Over the past three decades, a number of information processing models of problem-solving, such as the classic General Problem Solver (Newell and Simon, 1972), have been promulgated to explain problem-solving. The General Problem Solver specifies two sets of thinking processes associated with the problem-solving processes, understanding processes and search processes. Another popular problem-solving model, the IDEAL problem solver (Bransford and Stein, 1984) describes problem-solving as a uniform process of Identifying potential problems, Defining and representing the problem, Exploring possible strategies, Acting on those strategies, and Looking back and evaluating the effects of those activities. Gick (1986) synthesised these and other problemsolving models (Greeno, 1978) into a simplified model of the problemsolving process, including the processes of constructing a problem representation, searching for solutions, and implementing and monitoring solutions. Although descriptively useful, these problem-solving models conceive of all problems as equivalent, articulating a generalisable problemsolving procedure. These information-processing conceptions of problem-

solving assume that the same processes applied in different contexts yield similar results. The culmination of this activity was an attempt to articulate a uniform theory of problem-solving (Smith, 1991). Problem-solving is not a uniform activity. Problems are not equivalent, either in content, form, or process. Schema-theoretic conceptions of problemsolving opened the door for different problem types by arguing that problemsolving skill is dependent on a schema for solving particular types of problems. If the learner possesses a complete schema for any problem type, then constructing the problem representation is simply a matter mapping an existing problem schema onto a problem. Existing problem schemas result from previous experience in solving particular types of problems, enabling the learner to proceed directly to the implementation stage of problemsolving (Gick, 1986) and trying out the activated solution. Experts are better problem solvers because they recognise different problem states which invoke certain solutions (Sweller, 1988). If the type of problem is recognised, then little searching through the problem space is required. Novices, who do not possess problem schemas, are not able to recognise problem types, so they must rely on general problem-solving strategies, such as the information processing approaches, which provide weak strategies for problem solutions. As depicted in Figure 9.3, the ability to solve problems is a function of the nature of the problem, the way that the problem is represented to the solver, and a host of individual differences that mediate the process.

Figure 9.3 Process of problem-solving.

The first proper attempt to study problem-solving was by Edward Lee Thorndike (1874–1949) in 1898. Thorndike regarded problem-solving (at least in animals) as a very slow and difficult business involving trial and error, with the animal (cat) acting in a random way until one response proves successful. German psychologists known as Gestaltists (German psychologists in the early part of the twentieth century who argued that problem-solving involves restructuring and insight), Max Wertheimer (1880-1943) and Wolfgang Kohler (1887–1967) adopted a very different viewpoint in the early years of the twentieth century. They argued that solving a problem requires restructuring or reorganising the various features of the problem situation in an appropriate way and insight. “Restructuring” is the notion of the Gestaltists that problems need reorganising in order to solve them. This restructuring usually involves a flash of insight or sudden understanding or the “aha” experience. “Insight” means a sudden understanding in which the entire problem is looked at in a different way. The Gestaltists argued that problem-solving could be very fast and efficient when insight occurred. Infact, thinking and problem-solving usually involve more purpose and direction than Thorndike admitted, and insight happens more rarely than the Gestaltists imagined. Beginning with the early experimental work of the Gestaltists in Germany (for example, Duncker, 1935), and continuing through the 1960s and early 1970s, research on problem-solving typically conducted relatively simple, laboratory tasks (for example, Duncker’s “X-ray” problem; Ewert and Lambert’s 1932 “disk” problem, later known as Tower of Hanoi) that appeared novel to participants (for example, Mayer, 1992). Various reasons account for the choice of simple novel tasks: they had clearly defined optimal solutions, they were solvable within a relatively short time frame, and researchers could trace participants’ problem-solving steps, and so on. The researchers made the underlying assumption, of course, that simple tasks such as the Tower of Hanoi captured the main properties of “real world” problems, and that the cognitive processes underlying participants’ attempts to solve simple problems were representative of the processes engaged in when solving “real world” problems. Thus researchers used simple problems

for reasons of convenience, and thought generalisations to more complex problems would become possible. Perhaps the best-known and most impressive example of this line of research remains the work by Allen Newell and Herbert Simon. Simple laboratory-based tasks can be useful in explicating the steps of logic and reasoning that underlie problem-solving; however, they omit the complexity and emotional valence of “real-world” problems. In clinical psychology, researchers have focused on the role of emotions in problemsolving (D’Zurilla and Goldfried, 1971; D’Zurilla and Nezu, 1982), demonstrating that poor emotional control can disrupt focus on the target task and impede problem resolution (Rath, Langenbahn, Simon, Sherr, and Diller, 2004). In this conceptualisation, human problem-solving consists of two related processes: problem orientation, the motivational/attitudinal/affective approach to problematic situations and problem-solving skills, the actual cognitive-behavioural steps, which, if successfully implemented, lead to effective problem resolution. Working with individuals with frontal lobe injuries, neuropsychologists have discovered that deficits in emotional control and reasoning can be remediated, improving the capacity of injured persons to resolve everyday problems successfully (Rath, Simon, Langenbahn, Sherr, and Diller, 2003). A problem situation has three major components: (i) An initial state or the original state, which is the situation as it is perceived to exist at the moment or as it exists at the moment, as perceived by the individual. (ii) The goal state, which is the situation solver, would like it to be or which is what the problem solver would like the situation to be. (iii) The rules or routes or restrictions or strategies that govern the possible strategies for moving from the original state to the goal state or for getting from the initial state to the goal state. Psychologists have studied problem-solving activities to learn about the thinking processes that are going on when the solutions are being sought. Among the earliest contributors to this field were the Gestalt psychologists (recall their contributions to the field of perception), especially Max Wertheimer, Wolfgang Kohler, and Karl Duncker. The Gestaltists distinguish between two kinds of thinking in problem-solving: productive and

reproductive thinking. If the parts of a problem are viewed in a new way to reach a solution, then the thinking is described as productive. But when solving the problem involves the use of previously used solutions, then the thinking is reproductive. According to cognitive psychologists, problems exist on a continuum, ranging from well-defined to ill-defined. “Well-defined problems” are those in which the initial or original state and the goal state are clearly defined and specified, as are the rules for allowable problem-solving operations. “Illdefined problems” are often more difficult. We don’t have a clear idea of what we are starting with, nor are we able to identify a ready solution. With these problems, we usually have a poor conception of our original state and only a vague notion of where we are going and how we can get there; we also have no obvious way of judging whether a solution we might select is correct (Matlin, 1989).

9.7.2 Strategies Technique for Effective Problem-solving “Strategy” is a systematic plan for generating possible solutions that can be tested to see if they are correct. The main advantage of cognitive strategies appears to be that they permit the problem solver to exercise some degree of control over the task at hand. They allow individuals to choose the skills and knowledge that they will bring to bear on any particular problem (Gagne, 1984). Some of the well-established strategies are as follows. Techniques in problem-solving can probably be as many, as the number of unique problems that exist. The domain of human knowledge is ever expanding and so are problem-solving tools and techniques that exist. What is needed is clarity in thinking and clear sense of purpose. Here is a list of some of the best techniques of problem-solving. These methods are generic strategies for problem-solving that could be applied to solving any problem in business, personal life or any kind of technical problem. The success of a solution also lies in its clinical execution. Even if you have a solution, you need to have the courage to execute it and stand by its soundness for it to work. (i) Trial and Error: Some problems have such a narrow range of possible solutions that we decide to solve them through trial and error. Trial and error involves trying different responses until, perhaps, one works. Trial

and error is testing possible solutions until the right one is found. The method of trial and error is one of the techniques of problem-solving which is most commonly used. The idea is to keep trying out solutions and improving on them, by learning through mistakes. It is a kind of brute force methods, which does work, but can be time consuming. (ii) Algorithm: One main type of problem-solving is algorithmic (working out all possible alternative steps towards the problem solution). An “algorithm” is a problem-solving strategy that guarantees that you will arrive at a solution. It will involve systematically exploring and evaluating all possible solutions until the correct one is found. It is sometimes referred to as a generate-test strategy because one generates hypotheses about potential solutions and then tests each one in turn. An algorithm is a method that always produces a solution to a problem sooner or later. Although time consuming, these exhaustive searches guarantee the solution of a problem. Researchers call any method that guarantees a solution to a problem in algorithm. An algorithm that is useful for other problems is a systematic random search, in which you try out all possible answers. An algorithm involves a systematic exploration of every possible solution until correct one is found. This strategy originated in the field of mathematics, where its application can produce guaranteed solutions. Algorithm is a step-by-step procedure that guarantees a solution. Because step-by-step algorithms can be laborious, they are well-suited to computers. Computers can rapidly sort through hundreds, thousands, and even millions of possible solutions without growing tired or suffering from boredom. Algorithms generate a correct solution, if you are aware of all the possibilities—but in real life, that is a big “if”. Often algorithms simply require too much effort. We often solve problems with simple, commonly used and most often studied strategies, called heuristics. But these strategies are inefficient and unsophisticated because it considers all possibilities, even the unlikely ones (Newell and Simon, 1972). “Algorithm” is a methodological, logical rule or procedure that guarantees solving a particular problem. It contrasts with the usually

speedier—but also more error-prove use of heuristics. (iii) Heuristics: Another main type of problem-solving is heuristics, which means looking at only those parts of the problem which are most likely to produce results. Heuristic methods are applied to problem-solving and decision-making; they are informal rule of thumb which facilitate problem-solving, but sometimes at the expense of accuracy. Heuristics are more economical strategies than algorithms. When one uses a heuristic, there is no guarantee of success. On the other hand, heuristics are usually less time consuming than algorithm strategies and lead toward goals in a logical, sensible manner. Heuristic is a short-cut strategy. “Heuristics” refer to a variety of ruleof-thumb strategies that may lead to quick solutions but are not guaranteed to produce results. Heuristics are possible when the person has some knowledge and experience to draw on for the solution. Heuristic is a simple thinking strategy that often allows us to make judgements and solve problems efficiently; usually speedier but also more error-prone than algorithms. These search techniques do not guarantee solution, as in the case of algorithm, but they substantially reduce the search time. (iv) Insight: Sometimes we are unaware of using any problem-solving strategy; the answer just comes to us. Such sudden flashes of inspiration we call “Insight”. Insight is a sudden and often novel realisation of the solution to a problem; it contrasts with strategy-based solutions. Insight provides a sense of satisfaction. After solving a difficult problem or discovering how to resolve a conflict, we feel happy. (v) Testing hypotheses: A somewhat more systematic approach to problem-solving is provided by the strategy of testing hypotheses. Hypothesis testing is assuming a possible explanation to the problem and trying to prove (or, in some contexts, disprove) the assumption. (vi) Means-ends analysis: Means-ends analysis and the analogy approach are the two commonest forms of heuristic problem-solving. Means-ends analysis is a method used in problem-solving identified by Newell and Simon in which an attempt is made to reduce the difference between the current position on a problem and the desired goal position. In a meansends analysis, the problem solver divides the problem into a number of

sub-problems, or smaller problems that may have more manageable solutions. Each of these sub-problems is solved by figuring out the difference between your present situation and your goal, and then reducing that difference, for example, by removing barriers (Mayer, 1991). In other words, you figure out which “ends” you want and then determine what “means” you will use to reach those ends. In this strategy, the difference between the present state and the desired state (the goal) is analysed. Means-ends analysis means choosing an action at each step to move colser to the goal. Sometimes the correct solution to a problem depends upon temporarily increasing—rather than reducing—the difference between the original situation and the goal. It is painful to move anybody backward across the river to where they originally began (Gilhooly, 1982; Thomas, 1974). (vii) The analogy approach: When we use the analogy approach, we use a solution to an earlier problem to help solve a new one. Like the meansends approach, the analogy heuristic usually—but not always— produces a correct solution. According to a survey, most college level courses in critical thinking emphasise the use of analogies (Halpern, 1987). Analogy is the application of techniques that worked in similar situations in the past (Genter and Holyoak, 1997; Holyoak and Thagard, 1997). People frequently solve problems through the use of analogy— although they may remain unaware that they have done so (Burns, 1996; Schunn and Dunbar, 1996). (viii) Abstraction: Solving the problem in a model of the system before applying it to the real system. Method of abstraction is modelling the problem by taking the core details into consideration, while chiseling away the unnecessary stuff. Then you solve the problem in an abstract way, before handling it in reality. (ix) Brainstorming: (Especially among groups of people) Suggesting a large number of solutions or ideas and combining and developing them until an optimum is found. This technique of problem-solving is about synthesising an optimum solution through discussion of a range of solutions that every member of problem-solving team comes up with. Large teams often work this way, by selecting the best part out of

multiple solutions to make the best one. (x) Divide and conquer: This works by cutting a large, complex problem into smaller, solvable problems by attacking them separately. It is putting the jigsaw puzzle of a solution together, by solving the problem partially. (xi) Lateral thinking: Approaching solutions indirectly and creatively. This is a range of artistic techniques of problem solving which employs unconventional, creative or “out of the box” thinking. This is the method that geniuses often employ as they harness their unique powers of visualising a solution from a radical perspective. (xii) Method of focal objects: Synthesising seemingly non-matching characteristics of different objects into something new. (xiii) Morphological analysis: Assessing the output and interactions of an entire system. (xiv) Reduction: Transforming the problem into another problem for which solutions exist. Reductive analysis is all about transforming an unknown problem, for which solution doesn’t exist, into a known problem for which solution does exist. If you do not have a solution to a problem, then you don’t change the solution, but transform the problem and restate it in such a way, that you can have a solution! (xv) Research: Employing existing ideas or adapting existing solutions to similar problems. Research based methods or techniques of problemsolving depend on the pre-existing library of known solutions that exist. From these known solutions, a new customised solution can be constructed which is suited for your specific problem. You research available solutions and improve on them. (xvi) Root cause analysis: Eliminating the cause of the problem. This is what you call a problem-solving technique which solves the problem by attacking the root cause from which the problem emanates. It is solving the problem deeply and entirely, by studying it thoroughly and identifying its root causes. Once the root cause is negated, the problem no longer remains a problem!

9.7.3 Barriers to Effective Problem-solving Mindlessness

Mindlessness is a barrier to successful problem-solving. According to Ellen Langer, “mindlessness” means that we use information too rigidly, without becoming aware of the potentially novel characteristics of the current situation (Langer, 1989; Langer and Piper, 1987). In other words, we behave mindlessly when we rely too rigidly on previous categories. We fail to attend to the specific details of the current stimulus; we under-use our bottom-up processes. One example of mindlessness is mental set. Mental set applies to people when they solve problems with a mental set: problem solvers keep using the same solution they used in previous problems, even though there may be easier ways of approaching the problem. A “mental set” is a tendency to perceive or respond to something in a given (set) way. It is a cognitive predisposition. We may develop expectations that interfere with effective problem-solving. “Mental set” is a tendency to approach a problem in a set or predetermined way regardless of the requirements of the specific problem. It is the tendency to react to new problems in the same way one dealt with old problems. When we operate under the influence of a mental set, we apply strategies that have previously helped us to solve similar problems, instead of taking the time to analyse the current problem carefully. Such a habitual strategy is an effective one as long as the problems are of a similar nature. But some problems may only look similar. The result is that the individual uses a solution to the problem that does not work, or uses a complex strategy when a much simpler solution would have worked. This latter point is illustrated in the classic water jar experiment of Luchins (1942). The subjects found the complicated solution needed to solve the first problem and applied it to the second and so forth. The seventh problem could have been solved by a much easier method, but the mental set kept the individual from seeing that. The water jar test, first described in Abraham Luchins’ 1942 classic experiment, is a commonly cited example of an Einstellung situation. The experiment’s participants were given the following problem: you have 3 water jars, each with the capacity to hold a different, fixed amount of water; figure out how to measure a certain amount of water using these jars. It was found that subjects used methods that they had used previously to find the solution even though there were quicker and more efficient methods

available. The experiment throws light on how mental sets can hinder the solving of novel problems. In Luchins’ experiment, subjects were divided into two groups. The experimental group was given five practice problems, followed by 4 critical test problems. The control group did not have the five practice problems. All of the practice problems and some of the critical problems had only one solution, which was “B minus A minus 2×C.” For example, one is given Jar A holding 21 units of water, B holding 127, and C with 3. If an amount of 100 units must be measured out, the solution is to fill up Jar B and pour out enough water to fill A once and C twice. One of the critical problems was called the extinction problem. The extinction problem was a problem that could not be solved using the previous solution B-A-2C. In order to answer the extinction problem correctly, one had to solve the problem directly and generate a novel solution. An incorrect solution to the extinction problem indicated the presence of the Einstellung effect. The problems after the extinction problem again had two possible solutions. These post-extinction problems helped determine the recovery of the subjects from the Einstellung effect. The critical problems could be solved using this solution (B-A-2C) or a shorter solution (A – C or A + C). For example, subjects were instructed to get 18 units of water from jars with capacities 15, 39, and 3. Despite the presence of a simpler solution (A + C), subjects in the experimental group tended to give the lengthier solution in lieu of the shorter one. Instead of simply filling up Jars A and C, most subjects from the experimental group preferred the previous method of B-A-2C, whereas virtually the entire control group used the simpler solution. Interestingly, when Luchins and Luchins gave experimental group subjects the warning, “Don’t be blind,” over half of them used the simplest solution to the remaining problems. Thus, this warning helped reduce the prevalence of the Einstellung effect among the experimental group. The results of the water jars experiment illustrate the concept of Einstellung. The majority of the experimental subjects adopted a mechanised state of mind and relied on mental sets formed through previous experience. However, the experimental subjects would have been more efficient if they had employed the direct method of solving the problem rather than applying the same solution from previous examples.

Mental set often facilitate problem-solving, but it can also get in the way. Mental set is a tendency to approach a problem in a particular way; especially a way that has been successful in the past but may or may not be helpful in solving a new problem. As perceptual set predisposes what we perceive, a mental set predisposes how we think. Many people approach problems in similar ways all the time even though they can’t be sure they have the best approach or an approach that will work better. Doing this is an example of mental set—a tendency to approach situations the same way because that way worked in the past. For example, a child may enter a store by pushing a door open. Every time they come to a door after that, the child pushes the door expecting it to open even though many doors open only by pulling. This child has a mental set for opening doors. A mental set, or entrenchment, is a frame of mind involving a model that represents a problem, a problem context, or a procedure for problem-solving. When problem solvers have an entrenched mental set, they fixate on a strategy that normally works well but does not provide an effective solution to the particular problem at hand. According to Myers, mental set is a tendency to approach a problem in a particular way, especially a way that has been successful in the past but may not be helpful in solving a new problem. Another kind of mindlessness is functional fixedness or functional set, which means that the function we assign to an object tends to remain fixed or stable. Functional fixedness is a limitation in problem-solving in which subjects focus on only very possible functions or uses of objects and ignore other, more unusual uses. “Functional fixedness” is the tendency to be so set or fixed in our perception of the proper function of a given object that we are unable to think of using it in a novel way to solve a problem. Perceiving and relating familiar things in new ways is part of creativity. Successful problem-solving often requires overcoming functional fixedness. Functional fixedness may be thought of as a type of mental set. The process was first investigated by Karl Duncker (1945). He defined it as the inability to find an appropriate new use for an object because of experience using the object in some other function. It refers to the difficulties people have in a problem-solving task when the problem calls for a novel or new use

of a familiar object. The problem solver fails to see a solution to a problem because she or he has “fixed” some “function” to an object that makes it difficult to see how it could help with the problem at hand. Duncker’s label was derived from the fact that the functional utility of objects seems fixed by our experience with them. Functional fixedness and mental sets both demonstrate that mistakes in cognitive processing are usually rational. In general, objects in our world have fixed functions. The strategy of using one tool for one task and another tool for another task is generally wise because each was specifically designed for its own task. Functional fixedness occurs, however, when we apply that strategy too rigidly. However, in the case of mental sets, we mindlessly apply the past experience strategy too rigidly and fail to notice more effective solutions.

Fixation “Fixation” is the inability to see a problem from a new perspective; an impediment or barrier or hindrance to problem-solving. Past success can indeed help solve problems. But it may also interfere with our finding new solutions. This tendency to repeat solutions that have worked in the past is a type of fixation called “mental set”. Mental set (the tendency to use techniques used before even when they are less effective), functional fixedness (the tendency to assume that objects can only be used for the purpose for which they were designed), and einstellung (innate perceptual rules which steer us towards certain occasionally inappropriate ways of solving problems) can all hinder our problem-solving abilities.

Confirmation bias A major obstacle to problem-solving is our eagerness to search for information that confirms our ideas, a phenomenon known as confirmation bias. This is a tendency to search for information that confirms one’s preconceptions. According to Baron (1988) and Nickerson (1998), “Confirmation is our tendency to test conclusions or hypotheses by examining only, or primarily, evidence that confirms our initial views”. Peter Wason (1960) demonstrated this reluctance to seek information that might disprove one’s beliefs. We seek evidence that

will verify our ideas more eagerly than we seek evidence that might refute them (Klayman and Ha, 1987; Skov and Sherman, 1986).

9.7.4 Overcoming Barriers with Creative Problem-solving “Creativity” means the ability to produce unusual, high quality solutions when solving problems (Eysenck, 1991). Creative solutions to problems are innovative and useful. In the context of problem-solving, “creative” means much more than unusual, rare, or different. Someone may generate a very original plan to solve a given problem, but unless that plan is likely to work, we should not view it as creative (Newell et al., 1962; Vinacke, 1974). Creative solutions should be put to the same test as more ordinary solutions: Do they solve the problem at hand? Creative solutions generally involve new and different organisations of problem elements. At the stage of problem representation, creativity is most noticeable. Seeing a problem in a new light or combining elements in a new and different way may lead to creative solutions. There is virtually no correlation between creative problem-solving and what is usually referred to as “intelligence” (Barron and Harrington, 1981; Horn, 1976; Kershner and Ledger, 1985). Creative problem-solving often involves divergent thinking—that is, starting with one idea and generating from it a number of alternative possibilities and new ideas (Dirkes, 1978; Guilford, 1959). Divergent thinking is the creation of many ideas or potential problem solutions from one idea. One simple test for divergent thinking skills requires one to generate as many uses as possible for simple objects. When we engage in convergent thinking, we take many different ideas and try to focus and reduce them to just one possible solution. Convergent thinking is the reduction or focusing of many different ideas into one possible problem solution. Obviously, convergent thinking has its place, but for creative problemsolving, divergent thinking is generally more useful, because possibilities are explored. All these new and different possibilities for a problem’s solution need to be judged ultimately in terms of whether they really work.

9.7.5 Phases in Problem-solving John Dewey (1859–1952) in his book How we Think, presented five phases or steps that are involved in the solution of a problem:

John Dewey (1859–1952)

(i) Awareness and comprehension of the problem (Realisation of the problem). (ii) Localisation, evaluation, and organisation of information (Search for clarity). (iii) Discovery of relationships and formulation of hypothesis (The proposal of hypothesis). (iv) Evaluation of hypothesis (Rational application). (v) Application (Experimental verification). Graham Wallas (1926) suggested that thinking and problem-solving involve a total of four stages: (i) Preparation, in which relevant information is collected and initial solution attempts are made. (ii) Incubation, in which the individual stops thinking consciously about the problem. (iii) Illumination, in which the way to solve the problem appears suddenly in an insightful way. (iv) Verification, in which the solution is checked for accuracy. Bourne, Dominowski and Loftus (1979) enumerated three steps or stages: Preparation, Production, and Evaluation by proclaiming “We prepare, we produce, and we evaluate in the task of problem-solving.” John Bransford and Barry Stein (1984) advocated five steps that are basically associated with the task of problem-solving: I Identifying the problem. D Defining and representing the problem. E Exploring possible strategies. A Acting on the strategies.

L Looking back and evaluating the effects of one’s activities. According to Crooks and Stein (1991), the following are the stages of problem-solving: (i) Representing the problem: Logically, the first step in problem-solving is to determine what the problem is and to conceptualise it in familiar terms that will help us better understand and solve it. When you understand a problem, you construct a mental representation of its important parts (Greeno, 1977). You pay attention to the important information and ignore the irrelevant clutter or encumber that could distract you from the goal. Many complicated problems become much simpler if you first devise some kind of external representation—for example, some methods of representing the problem on paper (Mayer, 1988; Sternberg, 1986). Sometimes the most effective way to represent a problem is to use symbols or matrix. The “matrix” is a clear chart that represents all possible combinations, and it is an excellent way to keep back of items, particularly when the problem is complex. The method of representation that works best quite naturally depends upon the nature of the problem. Other methods include a simple list, a graph or a diagram, visual image and the like. The manner in which you represent the problem in your mind will significantly influence the ease with which you can generate solutions. Some problems can be represented visually. A much more logical approach is to represent the problem mathematically. Our understanding of a problem is influenced not only by how we represent it in our minds, but also by how the problem is presented to us. (ii) Generating possible solutions: Once we have a clear idea about what the problem is, the next step is to generate possible solutions. Sometimes, these solutions are easy. Other more complicated problems may require you to generate more complex strategies. (iii) Evaluating the solution: The final stage in problem-solving is to evaluate your solution. In some cases, this is a simple matter. With some other types of problems, the solution may be much more difficult to evaluate problems that are unclear. Poorly defined problems are almost always difficult to evaluate.

9.7.6 Steps in Problem-solving “The message from the moon... is that no problem need be considered insolvable.” —NORMAN COUSINS There are seven main steps proposed generally by psychologists to follow when trying to solve a problem. These steps are as follows: (i) Define and identify the problem (ii) Analyse the problem (iii) Identifying possible solutions (iv) Selecting the best solutions (v) Evaluating solutions (vi) Develop an action plan (viii) Implement the solution (ix) Problem awareness (x) Problem understanding (xi) Collection of the relevant information (xii) Formulation of hypotheses or hunch for the possible solutions (xiii) Selection of the correct solution (xiv) Verification of the concluded solution or hypothesis

9.7.7 Stages in Problem-solving Psychologists have viewed problem-solving as a process of stages since Wallas, in 1926, first described his stage model. Techniques for studying problem-solving have progressed enormously since that time. Problemsolving is still viewed as involving a number of discrete stages, although there is disagreement over the number of stages required. Following are some of the widely accepted stages: (i) Preparation: The initial preparation stage of problem-solving involves a great deal of information gathering, including an assessment that requires a clear definition of the problem. What is the problem? What are its starting and end points? What seem to be the obstacles? What kinds of information are needed to work toward a solution? If a problem seems familiar, reproductive thinking might lead to the conclusion that a previously successful solution may be successful again. Research has

shown that one of the strengths of expert problem solvers is that they can draw on their considerable experience to generate reproductive solutions (Larkin, Mc Dermott, Simon, and Simon, 1980). For such experienced problem solvers, the preparation stage may be a very brief one. One key factor in the preparation stage is the assessment of how the problem is structured. Most problems can be represented in several ways, and one of these ways may lead to a faster solution. (ii) Production: In the second stage of problem-solving, potential solutions begin to be generated. The most primitive procedure used to find a solution is labelled random search. This search is carried out without any knowledge of what strategies might be most promising. In essence, it is a form of trial and error totally without guidance. The would-be solver tries one approach and then another and perhaps arrives by chance, at a solution. This strategy can be linked to trying to open a combination lock without knowing the combination. Although time consuming, these exhaustive searches guarantee a solution of the problem. Researchers call any method that guarantees solution to a problem an “algorithm”. Algorithms do not always involve exhaustive searches. Using algorithm allows the solution to be easily determined, and the problem solver does not even have to understand the algorithm. However, for most problems, the only existing algorithm is exhaustive search. (iii) Heuristic techniques: A more fruitful approach is to select certain paths that offer the promise of a solution. These searches are called “heuristics” and are possible when the person has some knowledge and experience to draw on for the solution. Heuristic searches, the more commonly used strategies in problem-solving, are the strategies psychologists have most often studied. One often used heuristic technique is the means-end-analysis. In this strategy, the difference between the present state and the desired state (the goal) is analysed. The approach attempts to reduce that difference by dividing the problem into a number of sub-problems that may have more manageable solutions. By using sub-goals, the eventual goal of becoming a doctor, and the planning that is involved in dealing with the sub-goals makes the larger goal more attainable. The use of sub-

problems is an especially effective strategy when the problem itself is ill defined. Another heuristic strategy involves working backward from the goal to the present condition. Working backward is an effective strategy for certain types of problems, for example, solving mazes (to work backward from the goal “area” instead of starting at the point labelled “start”). Research has shown that effective problem-solving often makes use of a combination of heuristic strategy. Misuse of heuristics: Heuristics are approaches to problem-solving that are helpful but can be a hindrance as well. Daniel Kahneman and Amos Tversky (1973, 1984) have studied two heuristics, availability and representativeness, that often lead to wrong decisions in solving problems. Misuse occurs when we lack all the information we need in making a decision. In these ambiguous states we are more likely to make our judgements in terms of our own limited experiences (availability) or on the basis of characteristics that may be present, assuming that they are representative of something, and thereby ignoring other information that might lead to different decision (representativeness). By understanding the factors that hinder problem-solving (poor preparation, inability to restructure the problem, anxiety level that is too high, mental set, functional fixedness, misused heuristic), psychologists hope to find ways of making people better problem solvers. One approach to better problem-solving is to teach people to think more creatively. (iv) Evaluation: In this stage, the solution is evaluated in terms of its ability to satisfy the demands of the problem. If it meets all the criteria, then the problem is solved. If not, then the person goes back to the production stage to generate additional solutions. In some cases, several solutions may be generated, all of which solve the problem. Yet some solutions may be better than others; that is, they are more cost efficient, involves less time, are more humane, and so forth. These alterative solutions are compared at the evaluation stage. (v) Incubation: Some versions of the stages of problem-solving include incubation as a stage, but others do not. The consensus view seems to be

that the incubation stage is only sometimes present. Incubation occurs when the problem has been put aside; that is, when the individual stops thinking about the problem and engages in some other activity. During this incubation period, the solution may suddenly appear, or a new approach may become apparent that leads the individual back to the production stage, where the solution is then achieved. Many people have experienced this phenomenon, and the literature is filled with anecdotal evidence of its existence. Researchers are unsure about what is happening during the incubation period. One possibility is that it allows the person to recover from the mental fatigue that has built up from working on the problem. Some problem-solving attempts bog down when the individual keeps trying the same approach; the incubation may get the person out of that rut long enough to discover a new approach. The fact that these solutions or new approaches can occur when the person is not working on the problem raises an interesting point: Does problem-solving continue unconsciously? This notion of unconscious processing has been a popular one for more than 50 years. In essence, it is impossible to test this hypothesis. And in many incubation instances, solutions to the problems do not appear (Silveira, 1971).

9.7.8 Steps of Creative Problem-solving Process The Osborne Parnes’s method is one of the most popularly followed methods in creative problem-solving. As per the Osborne Parnes’ Creative ProblemSolving process, the creative problem-solving method would contain six logical steps. (i) Creative problem-solving activities. (ii) Collecting data about the problem, observing the problem as objectively as possible. (iii) Examining the various parts of the problem to isolate the major part, stating the problem in an open-ended way. (iv) Generating as many ideas as possible, regarding the problem brainstorming. (v) Choosing the solution that would be most appropriate, developing and selecting criteria to evaluate the alternative solutions. (vi) Creating a plan of action.

9.7.9 Factors Affecting Problem-solving Smith (1991) distinguished between external and internal factors in problemsolving. External factors are those that describe the problem. Internal factors are those that describe the problem solver. (i) Nature of the problem: It is clear that problems vary in their nature, in their presentation, in their components, and certainly in the cognitive and affective requirements for solving them. Jonassen (1997) distinguished well-structured from ill-structured problems and articulated different kinds of cognitive processing engaged by each. Smith (1991) distinguished external factors, including domain and complexity, from internal characteristics of the problem solver. And Mayer and Wittrock (1996) described problems as ill-defined/welldefined and routine/nonroutine. There is increasing agreement that problems vary in substance, structure, and process. (ii) Understanding and analysis of the problem: The second important factor that affects problem-solving process deals with the identification and measurement of the problem. In this step, all the various aspects are considered such as when exactly does the problem occur, where exactly it occurs, what damage potential does it have, why exactly does the person needs to solve the problem and how will the person benefit by solving the problem. (iii) Motivation: Intrinsic motivation (enjoyment of the creative process) is essential to creativity, whereas extrinsic motivation (fame, fortune) actually may impede creativity. One important factor related to ill-structured problem-solving success is intrinsic motivation, that is, students’ willingness to persist in solving the problem. Goal orientation, a motivational variable, explains reasons why students engage in the activity because they want to either learn or perform. The most commonly encountered problems in everyday practice are ill structured, with vaguely defined goals and unstated constraints that present uncertainty about which concepts, rules, and principles should be used to find those solutions (Ge and Land, 2003). Intrinsic motivation is particularly important to young adolescents to help them persist in deriving a solution to illstructured problems (Mac Kinnon, 1999).

(iv) Attention: Attention may be crucial for different aspects of successful insight problem-solving. Attention may play a role in helping people to decide what elements of a problem to focus on or in helping them to direct the search for relevant information internally and externally. Some studies have suggested that directing people’s attention to a particular element of a problem can improve performance (for example, Glucksberg and Weisberg, 1966) and people who pay more attention to peripherally presented information make better use of that information in a subsequent task (Ansburg and Hill, 2003). (v) Familiarity: Perhaps the strongest predictor of problem-solving ability is the solver’s familiarity with the problem type. Experienced problem solvers have better developed problem schemas which can be employed more automatically (Sweller, 1988). Mayer and Wittrock (1996) refer to routine and nonroutine aspects of the problem. We believe that routineness is rather an aspect of the problem solver and is not endemic in the nature of the problem itself. Although familiarity with a type of problem will facilitate solving similar problems, that skill seldom transfers to other kinds of problems or even the same kind of problem represented in another way (Gick and Holyoak, 1980, 1983). (vi) Past experience: In general terms, our ability to think effectively and to solve problems rapidly increases as we accumulate experience. Past experience is usually effective because the experience and knowledge we have gained from the past are of great value in most situations. The useful effects of past experience are known as positive transfer effect. Positive transfer effect, as applied to problem-solving, is the finding that performance on a current problem benefits from previous problemsolving. It is an improved ability to solve a problem because of previous relevant past experience. One of the clearest examples of positive transfer effect comes from the study of expertise or special skill. Expertise has been studied with respect to the game of chess. The search for the secret of chess-playing expertise was begun by De Groot (1966). Studies such as the one by De Groot suggest that grandmasters have somewhere between 10, 000 and 100, 000 chess patterns stored in longterm memory. Holding and Reynolds (1982) suggest that expert players have superior strategic skills as well as more knowledge of chess

positions. One way in which we use the past experience to help solve the current or present problem is by drawing an analogy or comparison between the current problem and some other situation. Inspite of the fact that past experience is usually helpful; there are several other situations in which previous learning actually seriously disrupts thinking and problem-solving. However, the best way of tackling a new problem is usually to make use of our previous experience with similar problems. The fact that adults can solve most problems far more rapidly than children provides striking evidence of the usefulness of past experience, as does the fact that stored knowledge is an important factor in expertise. In other words, although past experience sometimes interferes with problem-solving, it generally has a helpful effect. Negative transfer effect, as applied to problem-solving, is an interfering or disruptive effect of previous problem-solving on a current problem. Negative transfer effect means the negative effects of past experience on current problem-solving. An example of how past experience can limit our thinking is the well-known nine-dot problem. The task is to join up all the dots with four connected straight lines without lifting your pen from the paper. The problem can only be solved by going outside the square formed by the dots, but very few people do this. It seems that past experience leads us to assume that all of the lines should be within the square. A classic study on the negative transfer effect was carried out by Karl Duncker (1945). The task was to mount a candle on a vertical screen. Various objects were spread around, including a box full of nails and a box of matches. The solution involved using the box as a platform for the candle, but only a few of the participants found the correct answer. Their past experience led them to regard the box as a container rather than a platform. Their performance was better when the box was empty rather than full of tacks—the latter set-up emphasised the container-like quality of the box. Duncker’s study involved a phenomenon called functional fixedness. This is the tendency to think (on the basis of past experience) that objects can only be used for a narrow range of functions on the basis of

how they have been used in the past. However, a limitation with Duncker’s study is that we really do not know in detail about the participants’ relevant past experience. In particular, we do not know the ways in which they had used boxes in the past. (vii) Mental set: Previous experience of solving similar types of problems can be useful. However, it is possible for previous experience to make it more difficult to solve a problem if the previous experience produces a “mental set”. This occurs when a person becomes so used to utilising a particular type of operator that tend to use it even when there is a different or even similar approach. Luchins (1942) demonstrated this experimentally. According to Luchins (1942), the participants in his experiments developed a “mental set”, or way of approaching the problems, which led them to think in a rather blinkered or inflexible way. In his own words, “Einstellung (mental set or habituation)……...creates a mechanised state of mind, a blind attitude towards problems; one does not look at the problem on its own merits but is led by a mechanical application of a used method.” As already discussed, mental set is a barrier to effective problem-solving. (viii) Functional fixedness: This is our tendency to assume that particular objects have a specific use and that they cannot be used for something else. Functional fixedness is like a mental set for the uses of objects as we found in the experiment by Duncker (1945). In that, because of functional fixedness (that boxes’ only function is to contain things) many participants failed to solve the problem because they attempted to fix the candle to the wall by using melted wax or tin tacks. The solution is to empty the box, use one or two tin tacks to fix the box to the wall, and then fix the candle to the box. One of the tests for creativity is to see how far people overcome functional fixedness in thinking up alternative uses for everyday objects. The Gestalt psychologists believed that humans have innate ways of processing information which cause us to see things in particular ways and therefore try to solve problems in ways which may not always be successful if we apply them rigidly. The Gestaltists called this rigidity of perception and thinking einstelling (einstelling can be translated as “attitude” or “view”).

(ix) Creativity: Creative individuals can come up with many different ways to solve problems. To think creatively allows us deal with people, and generate solutions effectively. (x) Prejudices: Prejudice is a prejudgement, an attitude formed on the basis of insufficient information, a preconception. It can be about any particular thing, event, person, idea, group, etc. Prejudice is a failure to react towards a person as an individual with individual qualities and a tendency instead to treat her or him as possessing the presumed stereotypes of her or his socially or racially defined group. (xi) Problem representation: Problems also vary in how they are presented to the problem solver. Problems in the real world, of course, are embedded in their natural contexts, which require the problem solver to distinguish important from irrelevant components and construct a problem space for generating solutions. Learning problems are almost always contrived or simulated, so instructional designers must decide which problem components to include and how to represent them. Designers provide or withhold contextual cues, prompts, or other clues about information that needs to be mapped onto the problem space. How overt those cues are will determine the difficulty and complexity of the problem. Additionally, designers make decisions about the modality for representing different problem components. Perhaps the most important issue is the fidelity of the problem representation. Is the problem represented in its natural complexity and modality, or is it filtered when simulated? Should social pressures and time constraints be represented faithfully? That is, does the problem have to be solved in real time, or can it be solved in leisure time? What levels of cooperation or competition are represented in the problem? These are but a few of the decisions that designers must make when representing problems for learning. (xii) Domain and structural knowledge: Another strong predictor of problem-solving skills is the solver’s level of domain knowledge. How much someone knows about a domain is important to understanding the problem and generating solutions. However, that domain knowledge must be well integrated in order to support problem-solving. The integratedness of domain knowledge is best described as structural

knowledge (Jonassen, Beissner, and Yacci, 1993). It is the knowledge of how concepts within a domain are interrelated. It is also known as cognitive structure, the organisation of relationships among concepts in memory (Shavelson, 1972). (xiii) Domain-specific thinking skills: Domain knowledge and skills are very important in problem-solving. Structural knowledge may be a stronger predictor of problem-solving than familiarity. Robertson (1990) found that the extent to which think-aloud protocols contained relevant structural knowledge was a stronger predictor of how well learners would solve transfer problems in physics than either attitude or performance on a set of similar problems. Structural knowledge that connects formulas and important concepts in the knowledge base are important to understanding the principles of Physics. Gordon and Gill (1989) found that the similarity of the learners’ graphs (reflective of underlying cognitive structure) with the experts was highly predictive of total problem-solving scores (accounting for over 80% of the variance) as well as specific problem-solving activities. Well integrated domain knowledge is essential to problem-solving. Likewise, previous experience in solving problems also supports problem-solving. (xiv) Cognitive controls: Individuals also vary in their cognitive controls, which represent patterns of thinking that control the ways that individuals process and reason about information (Jonassen and Grabowski, 1993). Field independents are better problem solvers (Davis and Haueisen, 1976; Maloney, 1981; Heller, 1982; Ronning, Mc Curdy, and Ballinger, 1984). However, it is reasonable to predict that learners with higher cognitive flexibility and cognitive complexity will be better problem solvers because they consider more alternatives (Stewin and Anderson, 1974) and they are more analytical. The relationship between cognitive styles and controls needs to be better established. (xv) Affective and conative: Mayer (1992) claims that the essential characteristics of problem-solving are directed cognitive processing. Clearly, problem-solving requires cognitive and metacognitive processes. Cognitive is a necessary but insufficient requirement for problem-solving, which also requires significant affective and conative elements as well perseverance (Jonassen and Tessmer, 1996). Knowing

how to solve problems and believing that you know how to solve problems are often dissonant. Problem-solving also requires a number of affective, especially self-confidence and beliefs and biases about the knowledge domain. For example, Perkins, Hancock (1986) found that some students, when faced with a computer programming problem, would disengage immediately, believing that it was too difficult while other would keep trying to find a solution. If problem solvers do not believe in their ability to solve problems, they will most likely not succeed. Their self-confidence of ability will predict the level of mindful effort and perseverance that will be applied to solving the problem, which provide evidence of motivation. Also, if problem solvers are predisposed to certain problem solutions because of personal beliefs, then they will be less effective because they over-rely on that solution. Conative criteria relate to motivation to perform, which relates mostly to mindful effort and perseverance. Greeno (1991) claims that most students believe that if math problems have not been solved in a few minutes, the problem is probably unsolvable and there is no point in continuing to try, despite the fact that mathematician often work for hours on a problem. (xvi) General problem-solving skills: There is a general belief that some people are better problem solvers because they use more effective problem-solving strategies. That depends on the kind of strategies they use. Solvers who attempt to use weak strategies, such as general heuristics like means-ends analysis that can be applied across domains, generally fair no better than those who do not. However, solvers who use domain-specific, strong strategies are better problem solvers. Experts effectively use strong strategies, and some research has shown that less experienced solvers can also learn to use them (Singley and Anderson, 1989). (xvii) Individual vs. group problem-solving: The final individual difference in problem-solving methods relates to whether the problem is being solved by an individual or a group of people. One of the strongest predictors of problem-solving success is the application of an appropriate problem schema. That is, has the problem solver constructed

an adequate mental model of the problem and the system in which the problem occurs? A good conceptual model of the problem system along with the strategic knowledge to generate appropriate solutions and the procedural knowledge to carry them out will result in more successful problem solutions. When complex problems are solved by groups of people, sharing a similar mental model of the problem and system will facilitate solutions. When mental models are dissonant, more problems occur. So, team mental models must be constructed so that the members of the group work with similar conceptions of the problem, its states, and solutions.

9.7.10 Tips on Becoming a Better Problem Solver Our superb problem-solving skills are what have made us the dominant species on the planet. The following points can help to become a better problem solver: (i) Make sure you understand the problem and have defined it correctly. Every problem has, at its core, a need that must be satisfied. Make sure you understand what that need is. The worst result is spending lots of your time solving what you believe to be the problem only to find that you missed the mark. Equally bad is failing to solve the problem because you do not understand it. Perhaps it would be solvable but you are focused on the wrong need. (ii) Identify all the assumptions you are making to solve this problem. This exercise alone will help you better understand the problem. Furthermore, it may help you realise that some of the assumptions are either faulty or that they can be further dissected in ways that will help you solve the problem. (iii) Take it one step at a time. Break your problem up into parts and try to solve one at a time rather than seeing the problem as one big obstacle that must be overcome. (iv) Put together a team. It is well established that functioning teams are better problem solvers than an individual. If possible, assemble a team to address your problem. At least pull in a colleague or friend to get their input and pick their brains about the problem. Not only will other human beings give you ideas and perspectives you had not thought of,

but the process of articulating your thoughts to another human being will sharpen your thinking. (v) Your mind is a powerful analytical tool that will tear apart at your problem with laser fine precision. While that is an incredibly effective and important process, the analytical part of your mind will also tend to narrow your focus and squelch your creativity. Start with “brainstorming” your needs and possible solutions to them while keeping your critical and analytical skills in check. Only after you let your creative side loose should you start bringing your powers of critical analysis to each creative idea. (vi) Take some time off. Take a break. Get a good night’s sleep. Go for a run. Work on another project for a while. While you shift gears your subconscious will continue sifting through the problem. The solution may come to you when you least expect it. Even if it doesn’t, you will return to the problem refreshed and clearer headed. (vii) Learn problem-solving techniques. The more you know, the better problem solver you can be. (viii) Use the techniques repeatedly, until they become a habit. This “programming” assures the power of your subconscious mind will be there to help you. (ix) Allow many ideas to flow forth. You can always discard ideas later, or make them into something useful, but you have to have ideas first—and the more, the better. Suspend judgement or any critical impulses until you have a list of possible solutions to look over.

9.8 CONCEPT ATTAINMENT Concept attainment is based on the work of Jerome Seymour Bruner (born October 1, 1915), an American psychologist who has contributed to cognitive psychology and cognitive learning theory in educational psychology, as well as to history and to the general philosophy of education. He argued that concept attainment is “the search for and listing of attributes that can be used to distinguish exemplars from nonexemplars of various categories” (Bruner, Goodnow, and Austin, 1967).

Jerome Bruner (Born Oct. 1, 1915)

According to Joyce and Weil (2000) “Concept attainment requires a student to figure out about the attributes of a category that is already formed in another person’s mind by comparing and contrasting examples that contain the characteristics of the concept with exemplars that do not contain those attributes.” A concept is a category that is used to refer to a number of objects and events. A concept is a name expressed in the words often, only in one word. Examples of concepts of categories are apple, cow, fan, and so on. A concept may be used interchangeably with the word ‘category’. A concept is defined as “A set of features or attributes or characteristics connected by some rule.” Concepts are those objects, events, or behaviour, which have common feature or features. A feature is any characteristic or aspect of an object, event, or living organism that is observed in them and can be considered equivalent to some features observed or discriminated in other objects. Discrimination of features depends upon the degree of the observer’s perceptual sensitivity. Properties as colour, size, number, shape, smoothness, texture, roughness, and softness are called features. Rules that are used to connect the features to form a concept may be simple or complex. A rule is an instruction to do something. Psychologists have studied two types of concepts: natural and artificial concepts. Artificial concepts are those that are well defined and rules connecting the features are rigid and precise. In a well-defined concept, the features that represent the concept are both singly necessary and jointly sufficient. Every object must have the entire features in order to become an instance of the concept. On the other hand, natural concepts or categories are usually illdefined. Numerous features are found in the instances of the natural concepts or category. Such concepts include biological objects, real world products,

human artifacts such as tools, clothes, houses, and so on. The concept of a square is well-defined concept. It must have four attributes that is closed figure, four sides, and each side of equal length, and equal angle. Thus, square consists of these four features connected by rule. The features that are not included in the rule are considered irrelevant features.

9.9 REASONING Reasoning is the cognitive process of looking for reasons, beliefs, conclusions, actions or feelings. In general, thinking, with the implication that the process is logical and coherent—more specifically, problem-solving, whereby well-informed hypotheses are tested systematically and solutions are logically deduced. Different forms of such reflection on reasoning occur in different fields. In philosophy, the study of reasoning typically focuses on what makes reasoning efficient or inefficient, appropriate or inappropriate, good or bad. Philosophers do this by either examining the form or structure of the reasoning within arguments, or by considering the broader methods used to reach particular goals of reasoning. Psychologists and cognitive scientists, in contrast, tend to study how people reason, which cognitive and neural processes are engaged, how cultural factors affect the inferences people draw. The properties of logic which may be used to reason are studied in mathematical logic. The field of automated reasoning studies how reasoning may be modelled computationally. Lawyers also study reasoning.

9.9.1 Some Definitions of Reasoning According to Woodworth (1945), “In reasoning, items (facts or principles) furnished by recall, present observation or both; are combined and examined to see what conclusion can be drawn from the combination.” According to Gates (1947), “Reasoning is the term applied to highly purposeful controlled selective thinking.” According to Munn (1967), “Reasoning is combining past experiences in order to solve a problem which cannot be solved by mere reproduction of earlier solutions.” According to Garrett (1968), “Reasoning is step-wise thinking with a purpose or goal in mind.”

According to Skinner (1968), “Reasoning is the word used to describe the mental recognition of cause-and-effect relationships. It may be the prediction of an event from an observed cause or the inference of a cause from an observed event.” According to Mangal (2004), Reasoning may be termed “As highly specialized thinking which helps an individual to explore mentally the causeand-effect relationship of an event or solution of a problem by adopting some well-organized systematic steps based on previous experiences combined with present observation.” Reasoning is the cognitive process of looking for reasons, beliefs, conclusions, actions or feelings. Philosophers and logicians have often drawn distinction between deductive and inductive reasoning. Scientific research into reasoning is carried out within the fields of psychology and cognitive science. Psychologists attempt to determine whether or not people are capable of rational thought in various different circumstances. Experimental cognitive psychologists carry out research on reasoning behaviour. Experimenters investigate how people make inferences about factual situations, hypothetical possibilities, probabilities, and counterfactual situations.

9.9.2 Deductive Reasoning Deduction means reasoning that begins with a specific set of assumptions and attempts to draw conclusions or derive theorems from them. In general, it is a logical operation which proceeds from the general to the particular. Deductive reasoning goes from general to specific. “Deductive reasoning” is concerned with conclusions which follow necessarily if certain statements or premises are assumed to be true. It is very important to note that the validity of a given conclusion is based solely on logical principles, and is not affected in any way by whether or not that conclusion is actually true. Deductive reasoning means starting from the general rule and moving to specifics. Deductive reasoning is a form of reasoning in which definite conclusions follow, provided that certain statements are assumed to be true. Reasoning in an argument is valid if the argument’s conclusion must be true when the premises (the reasons given to support that conclusion) are true. One classic example of deductive reasoning is that found in syllogisms like the following: Premise 1: All humans are mortal.

Premise 2: Socrates is a human. Conclusion: Socrates is mortal. The reasoning in this argument is valid, because there is no way in which the premises, 1 and 2, could be true and the conclusion, 3, be false. Validity is a property of the reasoning in the argument, not a property of the premises in the argument or the argument as a whole. In fact, the truth or falsity of the premises and the conclusion is irrelevant to the validity of the reasoning in the argument. The following argument, with a false premise and a false conclusion, is also valid (it has the form of reasoning known as modus ponens). Modus ponens is one of the key rules of syllogistic inference, according to which the conclusion “B is true” follows from the premises “A is true” and “if A, then B”. Premise 1: If green is a colour, then grass poisons cows. Premise 2: Green is a colour. Conclusion: Grass poisons cows. Again, if the premises in this argument were true, the reasoning is such that the conclusion would also have to be true. In a deductive argument with valid reasoning, the conclusion contains no more information than is contained in the premises. Therefore, deductive reasoning does not increase one’s knowledge base, and so is said to be nonampliative. Deductive reasoning, or deduction, starts with a general case and deduces specific instances. Deduction starts with an assumed hypothesis or theory, which is why it has been called “hypothetico-deduction”. This assumption may be wellaccepted or it may be rather more shaky—nevertheless, for the argument it is not questioned. Deduction is used by scientists who take a general scientific law and apply it to a certain case, as they assume that the law is true. Deduction can also be used to test an induction by applying it elsewhere, although in this case the initial theory is assumed to be true only temporarily. EXAMPLE Say this Gravity makes things fall. The apple that hit my head was

Not this

due to gravity.

The apple hit my head. Gravity works!

They are all like that—just look at him!

Look at him. They are all like that.

Toyota make wonderful cars. Let me show you this one.

These cars are all wonderful. They are made by Toyota, it seems.

There is a law against smoking. Stop it now.

Stop smoking, please.

Discussion Deductive reasoning assumes that the basic law from which you are arguing is applicable in all cases. This can let you take a rule and apply it perhaps where it was not really meant to be applied. Scientists will prove a general law for a particular case and then do many deductive experiments (and often get PhDs in the process) to demonstrate that the law holds true in many different circumstances. In set theory, a deduction is a subset of the rule that is taken as the start point. If the rule is true and deduction is a true subset (not a conjunction) then the deduction is almost certainly true. Using deductive reasoning usually is a credible and “safe” form of reasoning, but is based on the assumed truth of the rule or law on which it is founded.

Validity and soundness Deductive conclusions can be valid or invalid. Valid arguments obey the initial rule. For validity, the truth or falsehood of the initial rule is not considered. Thus valid conclusions need not be true, and invalid conclusions may not be false. When a conclusion is both valid and true, it is considered to be sound. When it is valid, but untrue, then it is considered to be unsound. Within the field of formal logic, a variety of different forms of deductive reasoning have been developed. These involve abstract reasoning using symbols, logical operators and a set of rules that specify what processes may be followed to arrive at a conclusion. These forms of reasoning include Aristotelian logic, also known as syllogistic logic, propositional logic, predicate logic, and modal logic. Most research on deductive reasoning has made use of syllogisms, in which a conclusion is drawn from two premises or statements. The deductive reasoning is prone to error when it comes to affirmation of the consequent

and denial of the antecedent. The most important theoretical issue is whether or not people think rationally and logically when they are engaged in deductive reasoning. The existence of numerous errors on most syllogistic reasoning tasks might suggest that people tend to think logically. However, poor performance could occur for reasons other than illogical thinking. As Mary Henle (1962) pointed out, many errors occur because people misunderstand or misrepresent the problem, even if they then apply logical thinking to it. Henle (1962) also argued that some errors occur because of the subject’s “failure to accept the logical task”. This happens if, for example, the subject focuses on the truth or falsity of the conclusion without relating the conclusion to the preceding premises. Braine, Reiser, and Rumain (1984) have extended and developed Henle’s (1962) theoretical approach. According to their natural deduction theory, most of the errors found in deductive reasoning occur because of the failures of comprehension. According to Braine et al. (1984), it is because we normally expect other people to provide us with the information that we need to know. Braine et al. (1984) obtained some evidence to support their theoretical views. According to them, people have a mental rule corresponding to modus ponens. As a result, syllogisms based on modus ponens are easy to handle, and pose no comprehension problems. Byrne (1989) has shown that this is not always true.

9.9.3 Inductive Reasoning Inductive reasoning goes from specific to general. In simple words, it is a form of reasoning which begins with a specific argument and arrives at a general logical conclusion. In many cases, induction is termed as “strong” and “weak” on the basis of the credibility of the argument put forth. “Inductive reasoning” involves making a generalised conclusion from premises that refer to particular instances. Inductive reasoning means starting from specifics and deriving a general rule. In this type of reasoning, the process of induction is followed. “Induction” means a process of reasoning in which general principles are inferred from specific cases. It is a logical operation which proceeds from the individual to the general: what is assumed true of elements from a class is assumed true of the whole class. Induction is a form of inference producing propositions about unobserved objects or

types, either specifically or generally, based on previous observation. It is used to ascribe properties or relations to objects or types based on previous observations or experiences, or to formulate general statements or laws based on limited observations of recurring phenomenal patterns. Inductive reasoning, or induction, is reasoning from a specific case or cases and deriving a general rule. It draws inferences from observations in order to make generalizations. In general terms, the conclusions of inductively valid arguments are probably but not necessarily true. Interestingly, the chances of the conclusion being false are significant even when all the premises, on which the conclusion is based, are true. Much of the research on inductive reasoning has been concerned with concept learning. According to Bourne (1966), a concept exists “whenever two or more distinguishable objects or events have been grouped or classified together, and set apart from other objects on the basis of some common feature or property characteristic of each.” Probably the best known research on concept learning was carried out by Bruner, Goodnow, and Austin (1956). In many of their studies, they employed a “selection paradigm”. Bruner et al. (1956) discovered that focusing was generally more successful than scanning, in the sense that fewer cards needed to be selected before the concept was identified. They also carried out experiments on concept learning using what they termed the ‘reception paradigm’ in which the experimenter rather than the subject decided on the sequence of positive and negative instances to be presented. Within this paradigm, most subjects used either a wholist or a partist strategy. In the wholist strategy, all of the features of the first positive instance are taken as the hypothesis. Any of these features that are not present in subsequent positive instances are eliminated from the hypothesis. In contrast, the partist strategy involves taking part of the first positive instance as a hypothesis. The wholist strategy was generally more effective than the partist strategy. Inductive reasoning contrasts strongly with deductive reasoning in that, even in the best, or strongest, cases of inductive reasoning, the truth of the premises does not guarantee the truth of the conclusion. Instead, the conclusion of an inductive argument follows with some degree of probability. Relatedly, the conclusion of an inductive argument contains more information than is already contained in the premises. Thus, this method of

reasoning is ampliative. A classic example of inductive reasoning comes from the empiricist David Hume: Premise: The sun has risen in the east every morning up until now. Conclusion: The sun will also rise in the east tomorrow. Inference can be done in four stages: (i) Observation: collect facts, without bias. (ii) Analysis: classify the facts, identifying patterns of regularity. (iii) Inference: From the patterns, infer generalisations about the relations between the facts. (iv) Confirmation: Testing the inference through further observation. Example of strong inductive reasoning “All the tigers observed in a particular region have yellow black stripes, therefore all the tigers native to this region have yellow stripes.” Example of weak inductive reasoning “I always jump the red light, therefore everybody jumps the red light.” More examples of inductive reasoning “Every time you eat shrimp, you get cramps. Therefore it can be said that you get cramps because you eat shrimp.” “Mikhail hails from Russia and Russians are tall, therefore Mikhail is tall.” “When chimpanzees are exposed to rage, they tend to become violent. Humans are similar to chimpanzees, and therefore they tend to get violent when exposed to rage.” “All men are mortal. Socrates is a man, and therefore he is mortal.” “The women in the neighboring apartment has a shrill voice. I can hear a shrill voice from outside, therefore the women in the neighboring apartment is shouting.” “All of the ice we have examined so far is cold. Therefore, all ice is cold.” “The person looks uncomfortable. Therefore, the person is uncomfortable.” In an argument, you might: Derive a general rule in an accepted area and then apply the rule in

the area where you want the person to behave, Give them lots of detail, then explain what it all means, Talk about the benefits of all the parts and only get to the overall benefits later, Take what has happened and give a plausible explanation for why it has happened. Inductive arguments can include: Part-to-whole: where the whole is assumed to be like individual parts (only bigger). Extrapolations: where areas beyond the area of study are assumed to be like the studied area. Predictions: where the future is assumed to be like the past. EXAMPLE Say this

Not this

Look at how those people are behaving. They must be mad.

Those people are all mad.

All of your friends are good. You can be good, too.

Be good.

The base costs is XXX. The extras are XXX, plus tax at XXX. Overall, it is great deal at YYY.

It will cost YYY. This includes XXX for base costs, XXX for extras and XXX for tax.

Heating was XXX, lighting was YYY, parts were ZZZ, which adds up to NNN. Yet revenue was RRR. This means we must cut costs!

We need to cut costs, as our expenditure is greater than our revenue.

Discussion Early proponents of induction, such as Francis Bacon, saw it as a way of understanding nature in an unbiased way, as it derives laws from neutral observation. In argument, starting with the detail anchors of your persuasions in reality, starting from immediate sensory data of what can be seen and touched and then going to the big picture of ideas, principles and general rules. Starting from the small and building up to the big can be less threatening than starting with the big stuff. Scientists create scientific laws by observing a number of phenomena, finding similarities and deriving a law which explains all things. A good

scientific law is highly generalised and may be applied in many situations to explain other phenomena. For example, the law of gravity was used to predict the movement of the planets. Inductive arguments are always open to question as, by definition, the conclusion is a bigger bag than the evidence on which it is based. In set theory, an inductively created rule is a superset of the members that are taken as the start point. The only way to prove the rule is to identify all members of the set. This is often impractical. It may, however, be possible to calculate the probability that the rule is true. In this way, inductive arguments can be made to be more valid and probable by adding evidence. Although if this evidence is selectively chosen, it may falsely hide contrary evidence. Inductive reasoning thus needs trust and demonstration of integrity more than deductive reasoning. Inductive reasoning is also called generalizing as it takes specific instances and creates a general rule. Inductive reasoning contrasts strongly with deductive reasoning in that, even in the best, or strongest, cases of inductive reasoning, the truth of the premises does not guarantee the truth of the conclusion. Instead, the conclusion of an inductive argument follows with some degree of probability. Relatedly, the conclusion of an inductive argument contains more information than is already contained in the premises. Thus, this method of reasoning is ampliative.

9.10 LANGUAGE AND THINKING Language is an aspect of cognition that provides the basis for much of the activity occurring in various cognitive processes discussed so far. It is primarily through language that we can share the results of our own cognition with others and receive similar input from them. Language plays a crucial role in almost all aspects of daily life, and its possession and high degree of development is perhaps the single most important defining characteristics of human beings. Humans communicate with one another using a dazzling array of languages, each differing from the next in innumerable ways. Language is a uniquely human gift, central to our experience of being human. Language is so fundamental to our experience, so deeply a part of being human, that it’s hard to imagine life without it. But are languages merely tools for expressing our thoughts, or do they actually shape our thoughts?

The problem of how thought and language are related is one of the major problems in cognitive psychology. The main reason for the difficulty is that we do not have a clear command of the concepts of thought and language. Consequently, different claims about their relation are possible—depending on how “thought” and “language” are understood. Language is, a system of symbols plus rules for combining them, and is used to communicate information. The study of thought and language is one of the areas of psychology in which a clear understanding of interfunctional relations is particularly important. As long as we do not understand the interrelation of thought and word, we cannot answer, or even correctly pose, any of the more specific questions in this area. Strange as it may seem, psychology has never investigated the relationship systematically and in detail. Interfunctional relations in general have not as yet received the attention they merit. For a long time, the idea that language might shape thought was considered at best untestable and more often simply wrong. What we have learned is that people who speak different languages do indeed think differently and that even flukes of grammar can profoundly affect how we see the world. One of the most important issues in cognitive psychology concerns the relationship between language and thought or thinking. Language and thought seem to be reasonably closely related. One of the earliest attempts by psychologists to provide a theoretical account of the relationship between language and thought was made by the behaviourists. Behaviourist John B. Watson, often regarded as the “father of behaviourism”, argued that thinking was nothing more than sub-vocal speech. Most people sometimes engage in inner speech when thinking about difficult problems. Experimental evidence against Watson’s theory was provided by Smith, Brown, Toman, and Goodman (1947). One of the most influential theorists on the relationship between thought and language is Benjamin Lee Whorf (1956). Whorf was much influenced by the fact that there are obvious differences between the world’s languages. Whorf was impressed by these differences between languages, and so proposed his hypothesis of linguistic relativity, according to which language determines, or has a major influence on, thinking. In other words, linguistic relativity hypothesis is the view that language shapes thought. According to

linguistic relativity, thinking is determined by language; weaker versions of this viewpoint assume that language has a strong influence on thinking. In other words, the particular language you speak affects the ideas you can have: the linguistic relativity hypothesis. Benjamin Whorf studied with Sapir at Yale and was deeply impressed with his mentor’s view of thought and language. Whorf extended Sapir’s idea and illustrated it with examples drawn from both his knowledge of American Indian languages and from his fireinvestigation work experience. The stronger form of the hypothesis proposed by Whorf is known as linguistic determinism. This hypothesis has become so closely associated with these two thinkers that it is often “lexicalized’ as either the Whorfian hypothesis or the Sapir-Whorf hypothesis. Most subsequent research has produced findings less favourable to Whorf’s hypothesis. Some evidence that language can have a modest effect on perception and/or memory was obtained by Carmichael, Hogan, and Walter (1932). Eleanor Rosch Heider (1972) reported that language does not have any major influence on the ways in which colour is perceived and remembered. The work of Bernstein (1973) is of relevance to the notion that language influences at least some aspects of thought. He argued that a child’s use of language is determined in part by the social environment in which it grows up. However, Bernstein claimed that there are class differences in the use of language, but that these differences do not extend to basic language competence or understanding of language. There is relatively little support for the view that thought is influenced by language. However, the opposite hypothesis, that is, language is influenced by thought makes some sense. Language develops as an instrument for communicating thoughts. Jean Piaget was a prominent supporter of the view that thought influences language. According to him, children unable to solve a particular linguistic problem would still be unable to do so, even if they were taught the relevant linguistic skills possessed by most children who can solve the problem. This prediction was confirmed by Sinclair-De-Zwart (1969). Psychology owes a great deal to Jean Piaget. It is not an exaggeration to say that he revolutionised the study of child language and thought. He developed the clinical method of exploring children’s ideas which has since been widely used. He was the first to investigate child perception and logic

systematically; moreover, he brought to his subject a fresh approach of unusual amplitude and boldness. Instead of listing the deficiencies of child reasoning compared with that of adults, Piaget concentrated on the distinctive characteristics of child thought, on what the child has rather than on what the child lacks. Through this positive approach he demonstrated that the difference between child and adult thinking was qualitative rather than quantitative. An alternative to the theories discussed so far was put forward by Lev Vygotsky (1934). According to him, language and thought have quite separate origins. Thinking develops because of the need to solve problems, whereas language arises because the child wants to communicate and to keep track of his or her internal thoughts. The child initially finds it difficult to distinguish between these two functions of language, but subsequently they become clearly separated as external and internal speech. External speech tends to be more coherent and complete than internal speech. As the child develops, so language and thought become less independent of each other. Their inter-dependence can be seen in what Vygotsky referred to as “verbal thought”. However, thought can occur without the intervention of language, as in using a tool. The opposite process that is language being used without active thought processes being involved can also happen. An example cited by Vygotsky is repeating a poem which has been thoroughly over-learned. There is some validity in Vygotsky’s claim that thought and language are partially independent of each other. The task of investigating the relationship between language and thought is so complex that no definite answers are available. However, it seems far more likely that language is the servant of thought rather than its master.

QUESTIONS Section A Answer the following in five lines or in 50 words: 1. 2. 3. 4.

Thinking Cognitive process Image or Images Symbol

5. 6. 7. 8. 9. 10. 11. 12. 13. 14. 15. 16. 17. 18. 19. 20. 21. 22. 23. 24. 25. 26. 27. 28. 29. 30.

Problem-solving Algorithm Functional fixedness Gestaltists Heuristic methods Incubation Insight Means-ends analysis Mental set Positive transfer effect Negative transfer effect Restructuring Trial and error Stages of problem-solving Functional fixidity Reasoning Define reasoning and enlist its types Types of reasoning Creative thinking Inductive reasoning Divergent thinking Concept or concepts Characteristics of a creative person Functions of language Concept attainment Creativity

Section B Answer the following questions up to two pages or in 500 words: 1. Define thinking and discuss its nature. 2. What are various tools of thinking? 3. What is a problem? Explain nature of problem-solving behaviour.

4. 5. 6. 7. 8. 9. 10. 11. 12. 13. 14. 15. 16. 17. 18. 19. 20.

Explain various stages of problem-solving. Write a note on language and thought. Discuss the nature of language and its main components. Explain the factors that help in concept attainment. What is the meaning of thinking? Discuss the role of language in thinking. What is concept attainment? Discuss different factors influencing concept formation. Describe the process of concept formation. Describe creative thinking. Discuss how it is different from problemsolving. Explain the stages involved in problem-solving. What is thinking? Discuss the use of images in human thought. What is problem-solving? Discuss the role of set in problem-solving. What are basic elements of thought? What are concepts? What are heuristics? How do psychologists define problem-solving? What are two general approaches to problem-solving? What role do heuristics play in problem-solving?

Section C Answer the following questions up to five pages or in 1000 words: 1. Define thinking. What are the chief characteristics of thinking? 2. When does past experience have a positive effect on problemsolving? When does it have a negative effect on problem-solving? 3. What is insight? What effects does it have on problem-solving? 4. Explain different methods of problem-solving. What factors interfere with effective problem-solving? 5. Define problem-solving and discuss its stages. 6. Discuss thinking as a problem-solving behaviour. 7. What are steps involved in problem-solving? Describe the strategies

8. 9. 10. 11. 12. 13. 14. 15. 16. 17. 18. 19. 20. 21. 22.

23.

of problem-solving. Explain problem-solving and discuss its stages. How do we solve problems? Describe. What are the stages of problem-solving? Discuss. Discuss the various problem-solving strategies. What are the factors that interfere with effective problem-solving? Concepts are one of the basic components of our thoughts. Explain. Define creative thinking. Explain the creative process and highlight the characteristics of creative thinkers. What is thinking process? Analyse the process of thinking in solving a problem with the help of a suitable example. What are the characteristics of concept? Explain developmental strategies in concept learning. Discuss the relationship of thinking with symbols, language and past experience. What is a concept? Describe some experiments on concept formation. Mention two main types of experiments in problem-solving. Explain the role of ‘transfer’ in problem-solving with the help of experiments. What is the process of reasoning? What forms of error and bias can lead to faulty reasoning? What factors can interfere with effective problem-solving? Answer briefly (i) Reasoning (ii) Tools of thinking Write brief notes on the following: (i) Percept (ii) Language and thought (iii) Development of concepts (iv) Incubation (v) Rigidity and thinking (vi) Thinking and images (vii) Tools of thinking (viii) Thinking as mental trial and error.

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Syllabus of B.A and T.D.C Part II (GURU NANAK DEV UNIVERSITY, AMRITSAR)

EXPERIMENTAL PSYCHOLOGY Paper A EXPERIMENTAL PSYCHOLOGY TIME: 3 HOURS MAX. MARKS: 75 Notes: 1. Use of non-programmable calculators and statistical tables is allowed in the examination. 2. The question paper may consist of three sections as follows:

Section A will consist of 10 very short answer type questions with answer to each question upto five lines in length. All questions will be compulsory. Each question will carry 1½ marks; total weightage of the section being 15 marks. Section B will consist of short answer type questions with answer to each question upto two pages in length. Six questions will be set by the examiner and four will be attempted by the candidates. Each question will carry 9 marks. The total weightage of the section being 36 marks. Section C will consist of essay type questions with answers to each question upto 5 pages in length. Four questions will be set by the examiner and the candidates will be required to attempt two. Each question will carry 12 marks, total weightage of the section being 24 marks. (The questions are to be set to judge the candidates basic understanding of the concepts.) EXPERIMENTAL METHOD: S—R framework & steps. VARIABLES: Types of Variables, Stimulus, Organismic and Response Variables, Process of experimentation; manipulation and control of variables, Concept of within and between Experimental Designs. SENSATION: Types of sensations, Visual sensation; structure and functions of the eye. Theories of colour vision (Young-Helmholtz, Opponent-Process & Evolutionary). Auditory sensation; Structure and functions of the Ear— Theories of hearing. Brief introduction to Cutaneous sensation, olfactory

sensation and gustatory sensation. PERCEPTUAL PROCESSES: Selective Attention—Nature and factors affecting perception, laws of perception; perception of form; contour and contrast, figure-ground differentiation, Gestalt grouping principles, perceptual set. PERCEPTION OF MOVEMENTS: Image-Retina and Eye-Head movement system, Apparent movement, Induced movement, Auto Kinetic movement. PERCEPTION OF SPACE: Monocular and Binocular cues for space perception. Perceptual constancies—lightness, brightness, size and shape. ILLUSIONS: Types, causes and theories. STATISTICS: Normal Probability Curve, Its nature and characteristics (Numericals of Areas under NPG only) Correlation, Nature and characteristics. Rank order and product moment methods (Numericals for individual data).

Paper B EXPERIMENTAL PSYCHOLOGY TIME: 3 HOURS MAX. MARKS: 75 Notes: Instructions for the paper-setters/examiners: Each question paper may consist of three sections as follows:

Section A will consist of 10 very short answer type questions with answer to each question upto five lines in length. All questions will be compulsory. Each question will carry 1½ marks; total weightage of the section being 15 marks. Section B will consist of short answer type questions with answer to each questions upto two pages in length. Six questions will be set by the examiner and four will be attempted by the candidates. Each question will carry 9 marks. The total weightage of the section being 36 marks. Section C will consist of essay type questions with answers to each question upto five pages in length. Four questions will be set by the examiner and the candidates will be required to attempt two. Each question will carry 12 marks, total weightage of the section being 24 marks. (The questions are to be set to judge the candidates basic understanding of the concept.) INTRODUCTION TO PSYCHOPHYSICS: Physical vs. psychological continua, Concept of Absolute and Differential Thresholds. Determination of AL and DL by Methods of limits, Methods of Constant Stimuli & Method of Average Error. LEARNING: Classical and operant conditioning, Basic Processes; Extinction, spontaneous recovery, Generalization and Discrimination, Factors influencing classical and instrumental conditioning. Concept of reinforcement, Types of reinforcement and Reinforcement Schedules. Transfer of Training and skill learning. MEMORY: An Introduction to the concept of Mnemonics, Constructive memory, Implicit memory & Eyewitness memory. Methods of Retention. FORGETTING: Decay, interference, retrieval failure, and motivated forgetting.

THINKING AND PROBLEM-SOLVING: Reasoning & Language and Thinking.

Concept

Attainment,

Index Absolute limen, 35 Absolute threshold, 179, 183 Accentuation, 92 Accommodation, 116 Accuracy, 28 Achromatic vision, 48 Acronym method, 246 Acrostic, 246 Active forgetting, 264 Adaptation, 37 Adequate stimulus, 34 Aerial perspective, 115 Algorithm, 306, 315 Ames room illusion, 128 Amplitude, 50 Anvil bone, 51, 52 Apparent movement, 108, 109 Appetitive conditioning, 208 Aqueous humour, 45 Arrowhead illusion, 125 Artificial concepts, 324 Atkinson-Shiffrin model, 238 Atmospheric perspective, 116 Attention, 86, 89 Attenuation, 88 Attributes, 292 Auricle, 51 Autobiographical memory, 240 Autokinesis, 110 Autokinetic effect, 109 Autokinetic movement, 110

Automatic encoding, 231 Aversive conditioning, 208 Avoidance instrumental conditioning, 208 Backward conditioning, 200 Basilar membrane, 53, 54 Behaviour variables, 28 Bell-shaped curve, 144 Between-subjects, 30 experimental design, 31 Binocular cues, 111, 116 disparity, 116, 117 Bipolar cells, 44 Bitter tastes, 68 Blind spot, 45 Brightness, 41 Categorical clustering, 236 Cause and effect, 11, 16, 29 Choroid, 44 Chunking, 232, 235, 246 Ciliary muscles, 44 Circles illusion, 127 Circumvallate, 65 papillae, 65, 66 Classical conditioning, 200, 201, 205, 207, 209, 213 Cochlea, 52, 53 Cocktail party effect, 86 phenomenon, 86 Coefficient of correlation, 158, 161 multiple, 160 simple, 160 Cognition, 83, 287 Cognitive structure, 320 Colour blindness, 44 Colour constancy, 101 Colour vision, 46, 47 Concept attainment, 323 Conditioned response, 203 Conditioned stimulus, 203 Conditioning, 199 Cones, 43, 44 Confirmation bias, 258, 311 Confounding variable, 16

Conscious memory, 235 Constancy, 118, 123 phenomenon, 119 Constant error, 191 method, 186, 187 Contour, 100 perception, 100 Contrast, 101 Control, 15, 17, 29 condition or group, 14 group, 309, 310 Convergence, 117, 118 Convergent thinking, 291, 312 Cornea, 42 Correlation, 157, 158, 160 research, 13, 30 Counterritation, 59 Creative individuals, 295 thinkers, 293, 294 thinking, 291, 293, 296 Creativity, 311 Critical thinking, 291, 294 Cue-dependent forgetting, 267 Cued recall, 233 Cutaneous sensation, 55 Declarative knowledge, 251 Declarative memory, 240 Deduction, 325, 326 Deductive reasoning, 325, 331 Deductive thinking, 292 Deep processing, 232 Delboeuf’s illusion, 130 Demerits of Karl Pearson’s product moment (r) method, 170 Demerits of rank order method, 167 Dependent variable (DV), 11, 13, 14, 28 Designs, 30 Difference threshold, 179, 180, 184, 188 Differenz Limen, 179 Difficulty level, 28 Discrimination, 204 Divergence, 149 Divergent thinking, 291, 312 Domain knowledge, 321 Drop method, 69

Duration, 35, 37, 38 Eardrum, 52 Ebbinghaus illusion, 127 Effortful encoding, 231 Einstellung, 319, 320 effect, 309 Elaboration, 237 Elaborative rehearsal, 232, 237, 239 Elements of thought, 292 Encoding, 36, 230, 231 failure, 266 specificity hypothesis, 248 specificity principle, 238, 248 strategies, 231 Endorphins, 58, 59 Entrenchment, 310 variables, 13 Episodic memory, 240, 251 Error of, 30 anticipation, 186 habituation, 184, 186 Errors in Muller-Lyre illusion experiment, 191 Event-based prospective memories, 241 Evolutionary theory, 47, 48 Ewald hering’s theory of colour vision, 47 Experimental condition or group, 14, 15, 309, 310 designs, 30 extinction, 204, 212 method, 11, 17 psychology, 3, 7, 9 Experimentation, 13, 29, 30 Explicit memory, 240, 252, 253, 255 Extensity, 37, 38 External ear, 51 Extinction, 196, 204 Extraneous variables, 15, 16, 30 Extrinsic motivation, 317 Eye, 41, 42 Eyeball, 42 Eye–head movement system, 108 Eye-lashes, 42 Eye-lids, 42 Eye movements, 108 Eyewitness memory or testimony, 256 Eyewitness testimony, 260

Factors affecting forgetting, 268 Factors affecting problem-solving, 317 Factors of instrumental conditioning, 209 Features, 324 Fenestra ovalis, 53 Field-dependence, 91 Figure and ground, 84, 104 differentiation, 35 Filiform papillae, 65 First letter technique, 246 Fixation, 311 Fixed interval schedule, 212 Fixed ratio schedule, 211 Foliate papillae, 65 Forgetting, 263, 264 Fovea, 45 Free recall, 233, 262 learning, 249 Frequency method, 186 Frequency theory, 53, 54, 55 Functional fixedness, 310, 311, 319 set, 310 Fungiform, 65 papillae, 65, 66 Ganglion cells, 44 Gate-control theory, 57 Gaussian distribution, 144 law, 144 General forgetting, 264 Generalization, 204 Generalizing, 330 Generate-test strategy, 306 Gestalt, 97, 102, 103 Gestalt laws of organisation, 100, 105 Gradient, 114 Ground, 85, 94, 100, 101, 102, 104 Gustation, 64 Gustatory sensation, 64 Gusto meter, 69 Habit strength, 27 Hammer bone, 51, 52 Hering, 128 illusion, 129

Heuristics, 306, 315 Horizontal learning, 198 Hue or colour, 41 Hypothesis, 11 Ill-defined problems, 305 Ill-structured problems, 298 Illusions, 123 Image–retina system, 108 Imagery, 245 Images, 292 Implicit memory, 240, 251, 252, 253, 254 Inactive conditioning, 208 Incubation, 316 Incus, 51, 52 Independent extraneous variables, 15 Independent variable (IV), 11, 12, 17, 27 Individual differences, 28 Induced movement, 109, 110 Induction, 328 Inductive reasoning, 328, 331 Inductive thinking, 291 Inference, 197 Information-gathering systems, 34, 38 Inhibition, 28 theory, 209 Inner ear, 52 Input, 27 Insight, 304, 307 Instrumental conditioning, 206, 207, 213 Intensity, 35, 37, 38 Interference, 268 theory, 209, 265 Interposition, 113 Intervening variables, 27 Intrinsic motivation, 317 Iris, 44 Irradiation generalization, 204 Just-noticeable difference, 3, 179 Karl Pearson’s product moment method of correlation, 169 Key word method, 245 Kurtosis, 149, 151 Language and thinking, 331

Laplace’s second law, 144 Latent learning, 197 Law of adaptability, 105 closure, 99 common fate, 99 connectivity, 103 contour, 104 contrast, 104 effect, 210 error, 144 facility of errors, 144 figure and ground relationship, 103 good continuation, 98 good figure, 104 grouping, 98, 103 nearness, 98 Pragnanz, 99, 100 primacy, 263 proximity, 98 similarity, 98 symmetry, 99 wholeness, 103 Leading questions, 257 Learning, 195, 196, 197 Lens, 44 Lepto-kurtic, 149, 151 Levels of processing, 239 theory, 237 Lightness constancy, 119 Limen, 178, 182 Linear perspective, 111 Linguistic determinism, 332 Linguistic relativity hypothesis, 332 Local sign, 38 Logical concepts, 293 Long-term memory, 233, 236, 237, 238, 239, 251, 266 Maintenance rehearsal, 232, 237 Malleus, 51, 52 Manipulation, 29, 30 Means-ends analysis, 307, 315 Measurement of implicit memory, 255 Memory, 228, 229, 241, 258, 270 Mental, 215 imagery, 244 set, 309, 310, 319

Merits of Karl Pearson’s product moment (r) method, 170 Merits of rank order method, 167 Mesokurtic distribution, 151 Method of average error, 190 Method of constant stimuli, 186 difference, 186 Method of correlation, 162 Method of equation, 190 Method of just noticeable difference, 182 Method of limits, 182 limitations of, 186 Method of loci, 243, 244 Method of minimal changes, 182 Method of PQRST, 247 Method of reproduction or adjustment, 190 Method of retention, 262 Method of right and wrong cases, 186 Method of serial exploration, 182 Middle ear, 52 Mindlessness, 308 Minimum-distance principle, 98 Mnemonic, 242, 245, 246, 249 devices, 242 Modality, 236 Modal model of memory, 230 Modelling, 220 Models of memory, 238 Monocular cues, 111 Moon illusion, 125 Motion parallax, 115 Motivated forgetting, 269 Movement, 108 error, 191 Muller-Lyre illusion, 125, 190 Multiple correlation, 160 Multi-store model, 237, 238 Mushroom-shaped, 65 Narrative chaining, 246, 247 Narrative technique, 246 Natural concepts, 293, 324 Negatively skewed curve, 150 Negative or inverse correlation, 160 Negative reinforcement, 208, 210, 211 Negative transfer, 214 effect, 318, 319 Neurotransmitters, 36, 58

Neutral stimulus, 202 Nonsense syllables, 230 Normal curve, 143 Normal distribution, 144, 147 curve, 144 Normal probability curve, 144, 145 Normal random variable, 144 Object constancy, 119 Observation, 13 Olfactory epithelium, 60, 63 Olfactory nerve, 59 Olfactory sensation, 59 Operant conditioning, 206, 209 Opponent-process theory, 47 Opportunity sampling, 16 Optical illusions, 124 Optic nerve, 45 Orbison illusion, 129 Organic forgetting, 264 Organic sensations, 38 Organisation, 236 Organisational device, 246 Organismic variables, 27 Organ of corti, 53 Orienting stimulus, 202 Oscillation, 28 Ossicles, 51 Outer, 51 Output variables, 28 O-variables, 27 Over-learning, 268 Paired-associate learning, 249 Papillae, 64, 65 Paradigm of classical conditioning, 202 Parallelogram illusion, 129 Parasonic rays, 49 Partial correlation, 160 coefficient, 160 Partist strategy, 328 Passive forgetting, 264 Pearson’s r, 167 Peg word method, 244 Perception, 34, 80, 81, 82, 83, 84, 85, 100 of movement, 108 of space, 110

Perceptual constancy, 118, 119 defence, 92 expectancy, 82 organisation, 97 set, 89, 90, 92, 105, 107 Permanent memory, 236 Phantom limb, 58 Phenomenal motion, 108 Phi-phenomena, 109 Physical stimulus, 34 Pinna, 51 Placebos, 30, 59 Place theory, 53, 54 Platykurtic, 149, 151 Poggendorff illusion, 127 Ponzo illusion, 111, 126 Positive or direct correlation, 159 Positive reinforcement, 208, 210 Positive skewness, 150 Positive transfer, 214 effect, 318 Potent learning, 197 Practice, 196 Pre-conscious, 236 Prejudices, 95 Primacy effect, 263 memory, 234 reinforcers, 210 Priming, 253 Principle of contour, 101 Principle of primacy, 263 Principle of recency, 263 Proactive interference, 265, 266, 268 Probability or frequency, 28 Probability ratios, 145 Problem, 296, 297 Problem-solving, 300, 301, 304, 308, 312, 313, 316, 318 Procedural knowledge, 251 Procedural memory, 240 Process of memorising, 230 Productive and reproductive thinking, 305 Product moment correlation coefficient, 167 Product moment method, 167, 168 Prospective memory, 241 Psychological forgetting, 264 Psychometry, 143

Psychophysical methods, 182 Psychophysics, 177, 178 Punishment, 208, 211 instrumental conditioning, 208 training, 211 Pupil, 43, 44 Purkinge-phenomenon, 43 Quality of sensation, 35 Quota sampling, 16 Random, 16 assignment, 15, 16 sampling, 16 Randomisation, 15 Randomness, 16 Rank, 163 difference method, 162 order method, 162, 163 Real movement, 108 Reasoning, 324, 325 Reasons for forgetting, 264 Recall, 232, 233 Recency effect, 263 Receptor cells, 34 Receptor potentials, 37 Recognition, 233, 263 Recollection, 232 Reconstructive memory, 249, 259 Reinforcement, 196, 207, 210 schedules, 211 Reiz Limen, 179 Relative clarity, 113 height, 112, 115 motion, 115 size, 113 Relatively permanent, 195 Repetition priming task, 255 Representative sample, 16 Repression, 269 Resonance, 53, 54 Respondent conditioning, 200 Response variables, 28 Restructuring, 304 Retention interval, 268 Retina, 43, 44

Retinal disparity, 116, 117 Retrieval, 232, 233 failure, 266 Retroactive, 266 inhibition, 265 interference, 268 Retrospective memory, 241 Reward, 207 instrumental conditioning, 208 Rods, 43, 44 Salty taste, 67 Sander illusion, 130 Sander parallelogram, 130 Saturation, 41 Schema(s), 248, 250, 293 Sclerotic coat, 42 Scripts, 249 Secondary cues, 111 memory, 234 reinforcers, 210 Selective attention, 82, 85, 87 Selective perception, 86, 88, 89, 96, 106 Self-effacement bias, 95 Self-enhancement bias, 95 Self-fulfilling prophecy, 96 Semantic memory, 240, 251 Sensation, 34, 35, 38, 81, 82, 83 of smell, 59 of taste, 64 Sense of touch, 55 Sensory adaptation, 177 memory, 233, 234 register, 233 systems, 34 transduction, 37 Separate-groups, 30, 31 Serial anticipation method, 262 Serial learning, 249, 262 Serial-position effect, 263 Set, 105, 107 Shallow processing, 232 Shape constancy, 121, 122 Short-term memory, 233, 235, 238, 239 Simple conditioning, 200

Simple correlation, 160 Single-group, 30 design, 31 Size constancy, 120 scaling, 125 Skewness, 149, 150, 151 Skill learning, 215 Skin sensation, 183 Slip method, 69 Socket, 41 S—O—R, 17, 18 Sour taste, 68 Space error, 191 Special sensations, 39 Specific forgetting, 264 Specific model of classical conditioning, 202 Speed or quickness, 28 Spontaneous recovery, 205 SQ3R method, 247, 248 Stages in problem-solving, 314 Stages of classical conditioning, 202 Stages of memory, 230 Standard normal distribution, 144 Standard normal variable, 153 Standard scores, 153 Stapes, 51, 52 Statistics, 143 Steps in problem-solving, 314 Steps of creative problem-solving process, 316 Stereochemical theory, 62 Stereopsis, 117 Stimulus discrimination, 204 generalization, 204 threshold, 179 variables, 27 Stimulus-stimulus (S-S) learning, 205 Stirrup, 52 bone, 51 Storage, 231 failure, 266 Strategies for problem-solving, 305 Strategy, 305 Strength, 38 Stroboscopic movement, 109 Structural knowledge, 320, 321 Subjective contours, 101 Subject variables, 13

Subliminal, 35 Sweet taste, 67 Syllogistic logic, 327 Symbols and signs, 293 Synapse, 36 Synaptic cleft, 36 Tabula rasa, 80, 93 Task variables, 13 Taste buds, 64, 65 Taste cells, 64 Techniques of improving memory, 242 Terminal threshold, 182 Texture, 114 gradient, 115 Theory of disuse or decay, 266 Theory of misapplied constancy, 124 Thinking, 287, 288, 289, 290, 292, 304 Threshold, 35, 178, 182 Throughput, 27 Time-based prospective memories, 241 Titchener circles, 127 Topographic memory, 240 Trace decay, 264 Trace-dependent forgetting, 267 Transduction, 36, 37, 234 Transfer of learning, 214, 217 Transfer of training, 214 Travelling wave theory, 54 Trial and error, 305 Trichromatic, 46 theory, 4 Tristimulus theory of colour vision, 46 Two-point threshold, 183 Type-E independent variable (IV), 13 Type-S independent variable (IV), 13 Types of forgetting, 264 Types of memory, 233 Ultrasonic rays, 49 Unconditioned stimulus, 202 Unconscious memory, 236 Upper limen, 182 Upper threshold, 182 Variable, 12, 26, 27 interval schedule, 212

ratio schedule, 212 Vertical–horizontal illusion, 124 Vertical learning, 198 Visible light, 40 Visual memory, 240 Visual sensation, 40 Vitreous humour, 45 Volley principle, 55 Walled-around, 65 Weber-Fechner law, 4, 80 Weber’s law, 4, 177, 180 Well-defined problems, 305 Well-structured problems, 297 Wholist strategy, 328 Within-subjects, 30 design, 30, 31 Word completion task, 255 Word-completion test, 254 Working memory, 235 model, 239 Yellow spot, 45 Young-Helmholtz’s theory, 46 Zero correlation, 159 Zero transfer, 215 Zollner illusion, 128