Chapter 7: Cognition, Intelligence and Human Potential

Learning Objectives

  • Describe how you would teach a child concepts of shape and number
  • Describe how prior learning can facilitate or interfere with problem-solving
  • Describe how the basic characteristics of the normal curve relate to individual differences
  • Describe how adaptive learning relates to performance on intelligence tests

Knowledge, Skills and Human Potential

I have described psychology as the science of human potential. It is through this lens that we view the different content areas. The biological evolutionary process, taking place over millions of years, resulted in our physical structure. In the “Mostly Nature” chapters, we examined how our physical structure, including our brain, permits and limits what humans can achieve. We saw how our genetic and physical features permit speech and the use of tools. Without these capabilities, humans could not have individually and socially evolved to the point where we could transform the planet over a relatively brief period of time. Recall how Manhattan appeared only 400 years ago.

In the previous two chapters of the “Mostly Nurture” section, we described how direct and indirect learning enables much of the animal kingdom to adapt to their specific environmental conditions. The extent to which we fulfill our individual potential depends on our environmental conditions and the types of learning experiences to which we are exposed. The Nukak survive under conditions requiring a nomadic lifestyle. This restriction impacts upon every level of Maslow’s human needs hierarchy. Hunting and gathering must be conducted daily in order for tribe members to survive. Shelters are temporary and unstable, providing little protection from the elements and predators. Most of a Nukak’s life is spent living with a small number of people, limiting opportunities for finding friends or potential mates. Activities related to survival consume much of the day, leaving little discretionary time for self-actualization (i.e., achieving one’s potential).

You probably found when you plotted your personal pie-chart that, in comparison to the Nukak, a relatively small part of your day is dedicated to survival. Instead, much of your time is spent on school-related work, perhaps a job, social activities, and recreation. At the end of the previous chapter we saw how soon after you learned to speak, you may have learned the ABCs and to count. This was followed by the acquisition of other knowledge and skills in preparation for you to attend school. Consider the importance of what you have learned in school to your ability to attain your personal goals and achieve your potential. This chapter completes the “Mostly Nurture” section. Here we will consider the types of knowledge and skills acquired in school and how they relate to human intelligence and to achieving our potential as individuals and a species.

Concept Learning

A stimulus class is a collection of objects sharing at least one common property. For example, all circles are geometric objects with all points on the circumference equally distant from the center. Concept learning is inferred when an individual responds in the same way to all instances of a stimulus class. Much of our knowledge base consists of concepts. For example “circle” and “boy” are qualitative concepts. In comparison, “middle-sized” and “tenth” are quantitative concepts. They differ in amount, not just in kind.

Parents usually try to teach such concepts soon after their children speak. How would a parent go about teaching the concept circle and know if the child understands? When I ask my students this question, they usually suggest that the parent say the word “circle” while pointing to circular objects in the environment. You may recall our discussion of the acquisition of word meaning under the topic of classical conditioning. In this instance, the word “circle” is associated with many different stimuli sharing the property. A discrimination learning procedure could also be used to establish and assess conceptual responding to circles. The child would receive an appetitive stimulus for saying the word “circle” while pointing to appropriate examples differing in size, color, etc. The child would never be reinforced for saying “circle” to other shaped stimuli. Eventually, the child should be able to appropriately generalize the response to new instances of circles.

The same procedure could be used with quantitative concepts. When I was a graduate student, the research literature on transposition (i.e., responding to stimuli on the basis of a relationship) suggested that other animals and young children were unable to apply the middle-size relation to physically dissimilar stimuli (Reese, 1968). In my doctoral dissertation (Levy, 1975), I demonstrated near-perfect middle-sized transposition on two very different sets of stimuli by nursery-school children. First they were taught to point to three small squares (such as those shown below in Figure 1) in the order of their height before being required to select the middle-sized one. The placement was changed over trials so the child had to change the pointing order in a manner consistent with the sizes. They were then asked to order and point to the middle-sized member of three much larger squares. The results supported the conclusion that middle-size transposition occurs only when a child sequentially orders the three stimuli in an array prior to choosing the middle-sized one. After being taught to count, it becomes possible to establish relational responding based on any quantity. For example, a child could be asked to point to the fifth-largest triangle. This would require ordering all the triangles in an array based on size, and then, starting from the smallest, counting to five.

Figure 7.1 Example of stimulus arrays presented on each trial of a middle-size problem. The three stimuli in an array appeared in random order on each trial.

Concept learning, perhaps surprisingly, occurs throughout the animal kingdom. For example, pigeons readily learn visual concepts such as “triangle” and “square” (Towe, 1954), can distinguish between letters of the alphabet (Blough, 1982), and respond to ordinal position (Terrace, 1986). Presenting slides in a Skinner box, it has been demonstrated that pigeons easily learn such abstract natural concepts as “tree”, “water”, and even “person” (Herrnstein and Loveland, 1964; Herrnstein, Loveland, and Cable, 1976). Apparently, excellent vision, not a large cortex (i.e., pigeons have “bird brains”) is necessary for learning such concepts. In a fascinating application of concept learning, Skinner (1960) humorously describes a previously- classified World War II project in which pigeons were taught to identify the defining characteristics of axis-power military ships. The objective was to respond to the invasion of Pearl Harbor with our own squadron of “kamikaze pigeons.” The pigeons became the brains behind the first non-human “smart missile”

We and the Nukak have in common many basic needs (e.g., food, water, shelter, temperature, danger, pain, etc.) and family relationships (e.g., mother, father, brother, sister, etc.). One strategy for describing and contrasting our distinct human conditions would be to study our linguistic concepts. For example, there is no doubt that the Nukak will have a much more extensive vocabulary for types of rain and types of forestry than we will. We will have more extensive vocabularies regarding planes, trains, and automobiles. When I was very young, my mother taught me “red car”, “blue car”, “green car”, etc. My father taught me “coupe”, “convertible”, and “sedan”, and eventually “Chevy”, “Chrysler”, “Ford”, etc.

Unlike the rain forest, some climates and geographies support domestication of plants and/or large animals. Such environmental conditions enabled the development of agriculture and animal husbandry, permitting humans to abandon the nomadic lifestyle. New vocabularies developed related to the essential concepts for these life-transforming activities. When humans were able to permanently settle in a location, larger and larger communities evolved. This created the need for concepts related to increasingly complex interpersonal relations. As food surpluses occurred, there were opportunities for people to dedicate their time and creative efforts to the development of new tools, technologies, and occupations. Eventually, communities, economic arrangements, governments, and formal religions evolved. Along with these developments, the collective human knowledge base and vocabulary expanded. It was after the last ice age, approximately 13,000 years ago, that the agricultural lifestyle became the predominant human condition (see Figures 7.2 and 7.3). For the great majority, this stage of human history probably had more in common with Stone-Age nomadic cultures than our contemporary conditions. Literacy was not essential and survival needs took up most of one’s daily activities. As noted previously, this changed with the industrial revolution and the institution of compulsory education.


Figure 7.2 Sickle from 3000 B.C.

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Figure 7.3 Ancient Egyptian hoe and plow.

We have seen how the ability to use speech to communicate a continually-expanding vocabulary of concepts has enabled humans to live very differently and control their fates far more than the rest of the animal kingdom. Until relatively recently, however, only the privileged acquired the ability to read, write, and perform mathematic operations (i.e., learn the 3 “R”s). This meant that the great majority of humans, even in the relatively-advanced western societies, were unable to profit from or contribute to the accumulating knowledge recorded on the written page. John Adams, one of America’s founding fathers, stated “A memorable change must be made in the system of education, and knowledge must become so general as to raise the lower ranks of society nearer to the higher. The education of a nation, instead of being confined to a few schools and universities for the instruction of the few, must become the national care and expense for the formation of the many” (McCullough, 2001, p. 364). As Adam’s call for universal education was eventually realized, an increasing number of people became literate over the past century. This created an expanding pool to contribute to the ever-evolving knowledge-base. The resulting technologies continue to transform the human condition at an accelerating pace.

Learning to Learn

The ability to transform the human condition involves more than the knowledge and skills acquired in school. This knowledge must be converted into the action necessary to solve problems and to create tools. We will begin our discussion of problem solving by describing Harlow’s (1949) classic research demonstrating chimpanzees’ acquisition of learning sets. The term “learning set” may be interpreted to refer to either an independent or dependent variable. It can refer to a number of experiences that have something in common or to the effect of those experiences (as in being “set up”). Harlow provided his chimpanzees with over 300 two-choice visual discrimination problems. For example, the first problem might require choosing between a circle and a square; the second problem, between a red triangle and a green triangle; the third problem, a large diamond and a small diamond, etc. Different stimuli and dimensions were relevant across the different problems. Since each problem includes only two possible choices, the likelihood of being correct on the first trial by chance was always 50 per cent. The result on the first trial provides the necessary information for an alert subject could be correct from trial two on. If correct, one would continue to choose the same stimulus; if incorrect, one would switch to the other possibility. Harlow and others described this ideal performance pattern as a “win-stay, lose-shift” strategy.

The chimps’ performance improved gradually over the first 30 problems, suggesting an incremental learning process. This appears qualitatively, rather than quantitatively different from the sudden, discrete win-stay, lose-shift strategy characteristic of human adults. However, over the remaining trials, the win-stay, lose-shift strategy emerged so that the performance of the chimps on the last 55 trials was human-like with perfect performance on the second trial. It appears that just as pigeons are able to learn concepts by “abstracting out” the common characteristics of a collection of visual stimuli, chimpanzees are able to “abstract out” an approach to solving two-choice visual discrimination problems regardless of the stimuli involved. They have been “set” (i.e., have learned how to learn) to solve a particular type of problem.


We frequently describe challenges in life as problems. A problem exists when there is a discrepancy between the way things are and the way one would like them to be. The solution consists of acquiring the information and ability to eliminate the discrepancy. As described in Chapter 3, many animals appear to engage in behaviors which do not appear survival-related. Kittens and infants play with toys for extended periods of time with no apparent external reward other than the sensory stimulation. Monkeys will learn a response in order to gain the opportunity to look through a window (Butler, 1953). Human adults appear to find intrinsic reinforcements in solving complex problems. How else could we understand the creation of crossword puzzles and recreational games such as chess?

Two-choice discriminations are as simple as problems get. One piece (i.e., bit) of information is all that is required to solve the problem and obtain the reward. Crossword puzzles and chess are far more complicated. Perhaps we seek complexity because such experience is adaptive. Unfortunately, many problems in life are extremely difficult to solve and to address. Issues related to health, interpersonal relationships, and finances often top the list. It would be good preparation to acquire skills and strategies that apply in such circumstances. Many have likened life to a game of chess, posing problems having many possible options and requiring extensive planning for future possibilities. In fact, some have described life as consisting of one problem followed by another.

Psychologists have studied problem-solving in humans and other animals almost since the founding of the discipline. As described previously, Thorndike studied a few different species in puzzle boxes, describing the problem-solving process as involving trial-and-error (or success) learning. In his classic, The Mentality of Apes (translated in 1925), the Gestalt psychologist Wolfgang Kohler argued that the puzzle-box, by its very nature, requires a “blind” (i.e., trial-and-error) learning process since the required behaviors cannot be determined by observing the environment. Kohler created a number of problems for his subjects, primarily chimpanzees, in which the solution could be grasped by observing the environment. He considered such problems to be more representative of those we confront on a day-to-day basis.

One famous example of Kohler’s problems required that the chimpanzee insert a thin bamboo stick within a wider one. This created a tool long enough to reach a banana outside the cage. Another problem required stacking boxes high enough to reach a banana. A third required combining sticks to reach a banana hanging from above. The following classic video of Kohler’s research demonstrates individual and collective (i.e., social) problem-solving by his chimps with these tasks. Kohler amusingly anthropomorphized, attributing human characteristics to his subjects. He described the chimp’s initial frustration resulting from unsuccessful attempts and attributed characterized it as involving “insight” when the chimps performs the behaviors necessary to obtain the banana.

Under circumstances where the necessary components of a solution are observable, Kohler characterized the problem-solving process as requiring “insight.” You may recall that Gestalt psychologists primarily studied perceptual phenomena (e.g., the phi phenomenon). It is not surprising that Kohler considered insight to be a perceptual process requiring reorganization of the perceptual field in order to attain “closure.” Presumably, the chimp continued to scan the environment until attaining the specific insight required to solve the current problem. Wertheimer (1945) later published a “how to” book based on Kohler’s work, extending Gestalt concepts to childhood education.

Facilitative Effects of Prior Experience

Other researchers believed that Gestalt psychologists under-emphasized the role of prior experience in problem-solving. The subjects in Kohler’s primate colony were reared in the wild, not in captivity. Since bamboo sticks were prevalent in that environment, it was likely that the chimpanzees had handled them previously, increasing the likelihood of solving the two-stick problem. Birch (1945) provided five previously unsuccessful chimps with sticks to play with for three days. They were observed to gradually use the sticks to poke, shovel, and pry objects. When again provided with the two-stick problem, all five chimps discovered the solution within 20 seconds, demonstrating the importance of prior experience.

Based on Harlow’s observation of learning to learn, one can imagine Kohler’s chimps entering their cages, looking for the banana, and asking themselves “OK, what does Kohler want me to do today?” In a humorous simulation of the box climbing problem (Epstein, R., Kirshnit, C. E., Lanza, R. P., & Rubin, 1984), pigeons needed to move a box under a plastic banana and then step on the box in order to peck the banana to receive food. Some pigeons were shaped to move the box to wherever a spot appeared on the floor, others were shaped to stand on the box and peck the plastic banana, and a third group was taught both responses. Only the group taught both components of the required behavior displayed “insight”, confirming the importance of prior learning experiences in problem-solving (see video).

Interference Effects of Prior Experience

Prior experience can impede, as well as facilitate, problem-solving. Luchins (1942) gave college students a series of arithmetic problems to solve (see Figure 7.4). They were asked to provide the most direct way of obtaining a certain amount of liquid from jars holding different quantities.

Problem Volume of jug A Volume of jug B Volume of jug C Amount to obtain
Example  29 3 20
1  21 127 3 100
2  14 163 25 99
3  18 43 10 5
4 9 42 6 21
5 20 59 4 31
6 20 49 3 20

Figure 7.4 Luchin’s water jar problems.

In an example, subjects were first shown how it was possible to obtain 20 units of water by filling a 29-unit container and spilling 3 units into a separate container, three times (i.e., 29–3*3, or A-3B). After the example, a control group was administered problem 6 that could be solved using two (the direct solution, A-C) or all three jars (the indirect solution, B-A-2C). An experimental group was provided with five problems that could be solved with the B-A-2C formula prior to being administered the last problem. The experimental subjects were much more likely than the control subjects to use the less-efficient indirect method. This sort of “rigidity” is counter-productive. Thus, although it is often helpful to rely upon past experience in approaching problems, there is also value in considering each problem separately. Otherwise, we may be very unlikely to “think outside the box.” Figure 7.5 shows the solution to the well-known 9-dot problem in which one is instructed “Without lifting your pencil from the paper, draw exactly four straight, connected lines that will go through all nine dots, but through each dot only once.” Here, the solution literally requires thinking outside the box.


Figure 7.5 “Think outside the box.”

A special case of being blinded by past experience has been demonstrated with the use of physical objects, a phenomenon called “functional fixedness.” Dunker was one of the pioneers investigating functional fixedness in humans. One of the tasks he created required using several common objects in an unfamiliar way to create a “candle box” (see Figure 7.3).

Figure 7.6 Functional fixedness.

In another example of functional fixedness, Maier and Janzen (1968) found that college students were much more likely to use some objects rather than others to tie strings suspended from the ceiling together. For example, they were more likely to tie a ruler to the bottom of a string than a bar of soap. Presumably, the usual function of soap interferes with consideration of it for another use, even within a different context. This effect was demonstrated experimentally by Birch and Rabinowitz (1951). Two groups of college students were provided experience using two different objects to complete electrical circuits. Subjects were far more likely to use the unfamiliar object as the weight when they were given the two-string problem to solve

The Gestalt psychologists emphasized the tendency to perceive objects as meaningful wholes. Functional fixedness appears to be an inevitable result of this tendency. An implication of this perspective is that requiring individuals to describe the parts of objects should reduce the likelihood of functional fixedness. This was found to be the case when college students were asked to engage in a task similar to the introspection procedure employed by the structuralists to analyze conscious experience (McCaffrey, 2012). Subjects were asked to break down objects into their component parts without consideration of how they were used. This reduced the occurrence of functional fixedness.

The Unusual Uses Test (Guilford, Merrifield, and Wilson, 1958; Guilford and Guilford, 1980) is a popular assessment of creativity based upon the concept of functional fixedness. One is asked to list as many uses as possible for different objects (e.g., “What can you do with a brick?”). Responses may be counted or scored for originality. It is conceivable that encouraging test-takers to break down objects into their component parts could increase creativity scores on this test.

The General Problem-Solving Process

A general problem-solving process including five distinct stages has been described. The stages are: (1) general orientation; (2) problem definition and formulation; (3) generation of alternatives; (4) decision making; (5) verification (Goldfried and Davison, 1976, p. 187). The general orientation stage encourages individuals to approach situations eliciting unpleasant emotions as problems. Problems relating to health, interpersonal, and financial matters can be devastating, possibly resulting in debilitating anxiety and/or depression.

Weight-control is a common health concern. When I consulted for a medically-supervised weight clinic, I encouraged a self-control approach to fitness and health. Frequently, emotionality related to unrealistic societal ideals for appearance interfered with a client’s adhering to a prudent lifestyle. It was helpful to reduce the emotionality related to one’s appearance by adopting a problem-solving approach to weight control and body shape (Stage 1). The problem was defined as a discrepancy between one’s current weight and dimensions and a more desired profile (Stage 2). This permitted a relatively-detached brainstorming discussion of different nutritional and exercise modifications designed to affect caloric input and output (Stage 3). The likely benefits and drawbacks of implementing the different approaches were discussed with the goal of deciding upon a strategy that could be sustained (Stage 4). The decided upon strategy was implemented, with objective (weight and measurements) and subjective (ease of implementation, satisfaction, etc.) progress consistently monitored (Stage 5). A TOTE (Test-Operate-Test-Exit) approach was implemented to determine the need for fine-tuning or changing the strategy (Miller, Galanter, and Pribram, 1960). Similar to a thermostat, the individual would test the environment (i.e., determine current weight and measurements), operate on the environment (i.e., “turn on” the nutritional and exercise program), and continue to assess progress until achieving the desired objective. This same process would be sustained in order to maintain the desired end state.

The same “thermostat” approach could be applied to financial matters. The problem could be defined as a discrepancy between a family’s income and expenditures. Brainstorming would be conducted to list possible ways to increase income or reduce costs. A strategy would be decided upon, implemented, and continually assessed. Adoption of a problem-solving approach is particularly helpful with interpersonal problems, which are almost always emotionally charged. It is difficult, but possible, to teach individuals or couples to respond objectively to the substance of what someone says while ignoring provocative language. Once this is achieved, difficulties and solutions can be mutually defined and strategies for addressing them can be negotiated prior to implementation and assessment (D’Zurilla and Goldfried, 1971).

Tools, Technology and the Human Condition

The Law of Accelerating Returns

The general problem-solving process represents a higher level of abstraction than the win-stay, lose-shift strategy that applies only to two-choice discrimination problems. This generic process emerges from learning-set type experiences with a variety of types of problems and may be applied to all others. For example, problems can occur in sense modalities other than vision, include more than two choices, and differ in complexity. The abilities to predict and control our environment, including problem-solving and creating tools, have enabled the transformation of the human condition. It is a mistake to believe that this occurred quickly or in a linear progression (i.e., equally spaced in time). To paraphrase Charles Dickens’ opening to A Tale of Two Cities (2003): It is the fastest of times, it is the slowest of times; it is the age of the internet, it is the age of the blowpipe.

Gordon Moore (1965) calculated that, since the invention of the integrated circuit in 1958, the number of transistors that could be contained on a computer chip doubled approximately every two years. Now known as Moore’s Law, this geometric relationship has been shown to also hold with computing speed and memory. Raymond Kurzweil (2001), inventor and futurist, proposed that Moore’s Law was simply one example of the generic Law of Accelerating Returns that applies to the pace of all evolutionary biological and technological change.

The Stone Age, Bronze Age, and Iron Age

Many archeologists divide the time period prior to recorded history into three stages. During the Stone Age, it took tens of thousands of years for the occurrence of such paradigm shifts (i.e., life transforming events) as the use of stone tools, the control of fire, and invention of the wheel. It took until the Bronze Age (3300-1200 BC) and Iron Age (1200-900 BC) for tools to be manufactured, as opposed to being handmade from items found in nature (see Figures 7.7 and 7.8). Skipping to the first millennium A.D., advances such as the use of paper for writing and toiletry, inventions such as the quill and fountain pens, guns and gunpowder, and the creation of the first public library, were occurring every hundred years or so.

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Figure 7.7 Ancient stone tools.

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Figure 7.8 Ancient stone wheel.

The Industrial Revolution and the Modern Era

In the nineteenth century, major advances occurred every few years. Toward the end, the industrial revolution increased the pace, laying the groundwork for our current human condition. The steam locomotive and automobile replaced the horse as the fastest way to travel on land, permitting travel across the continent (see Figures 7.9 and 7.10) and the airplane took travel to the skies (Figure 7.11); the steamboat and submarine enabled speedy travel on and beneath the sea. These technologies were enhanced and in instances, replaced, during the 20th century. Orville and Wilbur’s initial flight in 1903 was followed by the development of the airplane as a speedy mode of transportation connecting the continents. Cross-country trips that took months by horse, took days by train and hours by plane. Intercontinental flights replaced ships as the only possible way to traverse oceans. During the industrial revolution people left farms for employment in large cities. Highway development and the proliferation of cars reversed the trend and suburban living became a preferred lifestyle for many. The reaper, steel plow, and refrigerator improved the yield and storage of food. Improved agricultural and meat processing techniques led to large, highly-efficient industries. Within 150 years, people went from producing their own food, to shopping at small markets, to shopping at large supermarkets.

Figure 7.9 Early steam locomotive.

Figure 7.10 Early automobile.

Figure 7.11 Wright brothers airplane

The telegraph and telephone (see Figure 7.12) enabled instant communication over long distances. The light bulb prolonged work and recreation time, and phonographs and cameras enabled the recording of audio and visual media. The revolver, repeating rifle, and machine gun changed self-defense and warfare, altering the balance of power among cultures and nations.

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Figures 7.12 and 7.13 The telephone then and now.

Radio enabled everyone with electricity to listen to the same event at the same time, culminating in talk shows with audience participation. Television extended this phenomenon to the visual world and soon a common culture was being created consisting of news, sports, variety shows, comedies, soap operas, and reality shows (see Figures 7.14 and 7.15).

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Figures 7.14 and 7.15 TV then and now.

Digitization and computer technology transformed the speed and power of processing and communicating information (see Figures 7.16 and 7.17). Communication satellites in space and optical fibers beneath the oceans connected the continents, enabling and encouraging globalization.

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Figure 7.16 and 7.17 Computer then and now.

While foraging, the Nukak sometimes build small bridges to pass over small bodies of water. The bridge is a wonderful metaphor as well as a feat of engineering for connecting peoples and places. Think of where you are and how far it is possible to travel before reaching a bridge. One’s world is much smaller without them! The Nukak live in bands of approximately 15 individuals (usually the children and adults of 3 to 5 families). The tribe consists of approximately 20 bands living in different parts of a small region in the rain forest. That is their world. At the beginning of the 19th century, most human cultures lived on farms in small villages. That was their world. Technological innovations in transportation and communication have potentially connected every person on the planet. Within the span of 200 years, we have moved from communication by word of mouth and written letters to wireless phones and e-mail. We have landed a rocket ship on the moon and are currently exploring Mars for signs of life. These are our worlds!

The advances over the past two centuries have also led to a dramatic change in human life expectancy. “In the eighteenth century, we added a few days every year to human longevity; during the nineteenth century we added a couple of weeks each year; and now we’re adding almost a half a year every year. With the revolutions in genomics, proteomics, rational drug design, therapeutic cloning of our own organs and tissues, and related developments in bio-information sciences, we will be adding more than a year every year within ten years. So take care of yourself the old fashioned way for just a little while longer, and you may actually get to experience the next fundamental paradigm shift in our destiny” (Kurzweil, 2001).

The dramatic increases in human life expectancy over the past 1-1/2 centuries are primarily the result of improved sanitary conditions and inoculations against such diseases as smallpox, polio, rubella, diphtheria, and influenza. In current technologically-advanced cultures, the major reasons for loss of life are lifestyle related. For example, over 300,000 Americans die each year from smoking-related disorders. Heart disease and cancer, which combine for a half of all deaths on an annual basis, are significantly related to one’s nutritional and exercise habits. Health psychology has emerged as a sub-discipline of psychology dedicated to “the prevention and treatment of illness, and the identification of etiologic and diagnostic correlates of health, illness and related dysfunction” (Matarazzo, 1980). Hopefully, the knowledge acquired through this discipline will enable the development of lifestyle-related technologies essential to the continuation of the trend in human life expectancy.

Unfortunately, technology is a two-edged sword. It may be used to improve the human condition for the betterment of all or lead to our own extinction. The basic science of biology resulted in improvement in sanitary conditions and inoculations against major diseases. The same knowledge has been applied to create potentially devastating biological weapons. Chemistry has enabled the development of plastics and plastic explosives. Physics has enabled nuclear energy and nuclear weapons. Humans are the most creative and destructive force on this planet. It is the hope of this author that the science of psychology can contribute to our survival and enable us to realize the potential of our species.

Clearly, the automobile, airplane, telephone, radio, television, personal computer, cell phone, and World Wide Web have each transformed the human condition. How do we reconcile these advances occurring within such a short period of time with the concurrent Stone-Age existence of the Nukak? Once again, I will quote from Kurzweil’s extraordinary essay: “Technology goes beyond mere tool making; it is a process of creating ever more powerful technology using the tools from the previous round of innovation. In this way, human technology is distinguished from the tool making of other species. There is a record of each stage of technology, and each new stage of technology builds on the order of the previous stage (Kurzweil, 2001). The recording of progress is responsible for the distinction between tool-making in other species and human technological change, according to Kurzweil. This same explanation can be applied to the distinction between the human conditions for the Nukak and us. I have emphasized the speeding up of the pace of technological change during the past two centuries. It is easy to forget the glacial pace of change during the Stone Age. The Nukak survive under geographic and climatic conditions limited to a hunter-gatherer lifestyle. They have learned to make fires by rubbing sticks together, to make blowpipes from cane, and to tip darts with the paralyzing drug curare. The inability to store foods or domesticate large animals makes it impossible to produce food surpluses. Life is a day-to-day struggle for survival. There is no time or opportunity to create the technologies that transformed the human condition in cultures originating in the Fertile Crescent.

Individual Differences

Not all individuals contribute equally or in the same way to the human condition. It was necessary for a substantial number of people with exceptional knowledge, problem-solving ability, and skills to work as a team to transform Manhattan from a forest to a metropolis. Until now, we have been focusing on differences between Stone-Age and technologically-enhanced cultures in order to appreciate extreme variations of the human condition. We have not discussed differences between the individual members of a culture. Not every member of the Nukak is the same height and weight. Not all members of the Nukak are equally skilled in blowing darts or fashioning necklaces. Not all college students are the same height and weight. Not all college students are equally proficient at shooting free throws or playing a musical instrument.

Psychology can be described as the science of individual differences. In the prior examples, psychologists would look to hereditary and experiential variables as potential causes of behavioral variation. Before we consider some controversial issues, it should prove helpful to place these issues within the larger context of how to formulate useful questions regarding individual differences. Frequently, by being specific and clear when defining terms, it is possible to shed light and avoid heat, even with the most contentious of topics. The scientific method is our best strategy for obtaining useful information to address difficult theoretical and practical questions.

I will use the game of basketball as an example since it is an internationally popular sport among adult males and females. The objective of the game is to shoot a 9-1/2–inch diameter sphere through an 18-inch circular rim located ten feet off the ground. The easiest, and most certain way to accomplish this, is to hold the basketball in your hands and “dunk” (or “stuff”) it through the rim (“hoop”). Basketball is a game where “size matters” (especially height). It is an advantage to be as close to the rim as possible.

One has to be over seven feet tall to be able to dunk a basketball while still standing on the ground. How likely is it that a person grows to be over seven feet tall? To answer this question, it would be necessary to measure everyone’s height and divide the number of people who are seven feet or more by the total. A more analytic approach would be to create a frequency distribution of the number of people of different heights.


Figure 7.18 Normal curves for height.

Figure 7.18 is an example of frequency distributions for the heights of samples of American husbands and wives. The normal curve is a symmetrical bell-shaped curve characteristic of many variables in nature, including human characteristics and performance (e.g., height, reaction time, etc.). It is defined by a formula resulting in specific percentages of the area under the curve being related to distance along the X-axis. The distance is measured in standard deviation units, a statistical index of variability (i.e., consistency). The size of the standard deviation is based on the extent to which scores cluster around the mean. If scores tend to be close to the mean (i.e., are consistent), the standard deviation is low. If the scores vary widely from the mean, the standard deviation is high. The normal curve includes approximately two-thirds of the scores between plus and minus one standard deviation, and 95 percent of the scores between plus and minus two standard deviations.

One characteristic of any symmetrical curve is that the peak indicates the mean (i.e., average) score. Another characteristic of a symmetrical curve is how “spread out” it is. The male curve above seems more spread out than the “narrower” female curve. The narrowness of a curve indicates the extent to which the scores pile up close to the mean, that is, the consistency (or variability). The female scores are more consistent (i.e., less variable) in the figure. The average height for women in the figure is 65 inches with a standard deviation of 4, and the average for men is 71 inches with a standard deviation of 5. Assuming the distributions are normal, this would mean that approximately two-thirds of women are between 61 and 69 inches, and two-thirds of men are between 66 and 76 inches. A height of seven feet (84 inches) would be almost three standard deviations above the mean height for men. This would mean that only about one in five hundred men attain that height. No wonder extremely tall individuals tend to be favored draft picks in professional basketball. They are hard to find.

Sometimes a basketball scout remarks that a particular player “has what you can’t teach.” The implication is that height is entirely genetically determined. In fact, it has been reported that hundreds of genes influence human height (Lango, Estrada, and Lettre et al., 2010). Clearly, whether one does or does not possess the Y-chromosome matters. It needs to be emphasized, however, that even a physical characteristic such as height can be significantly affected by environmental factors. The Centers for Disease Control statistics (2012) indicate that overall, the average heights for American women and men have been stable for many years. However, the heights of recent immigrants show an increase. The apparent explanation is that those recently arriving react to the American diet. Those who have been exposed to this diet for extended periods have apparently approached their genetic potential.

If you cannot reach the basket while standing on the ground, it may still be possible to dunk the ball by jumping. An amusing basketball movie from several years ago was entitled “White Men Can’t Jump.” The implication of the title was that if one created frequency distributions for men of different races, one would see diverging curves similar to those for the height of women and men. Collecting such data and plotting the curves would determine the accuracy of the title. That is, it is an empirical question. Another empirical question would address the extent to which jumping is like height. Do you think nutrition might influence jumping ability? What about exercises designed to strengthen your leg muscles or improve flexibility? Is jumping something you can teach? Do you think there is such a thing as jumping technique? As you move further from the hoop, one’s height becomes less of an advantage and skill level increases in importance. Shooting ability is clearly a characteristic related to basketball performance which can be taught and practiced.

Intelligence Testing

We will now try to apply the approach used to address questions regarding basketball to issues related to human intelligence. Perhaps no term is more misunderstood or, as we shall see, more misused, than intelligence. It is common to describe ourselves or others as being “smart” (i.e., intelligent) or “not so smart.” A repeated lesson of this book is the need to be careful when labeling people. Labels can be used as pseudo-explanations, diverting us from searching for true explanations. Also, there is always the potential for self-fulfilling prophecies. When one attributes exceptionally good or poor performance to levels of “intelligence”, the search for another explanation ceases. Once one is labeled as intelligent or dull, this can have significant effects upon how they are treated by those with the best intentions.

Do you think people vary in intelligence the way they do with height, jumping ability, and shooting from a distance? If so, is intelligence more like height, jumping ability, or shooting from a distance? The first step in addressing this question requires defining what we mean by intelligence. Recall, an operational definition defines terms by the procedures used to measure them. For example, the definition of height would be the number of standardized units (e.g., inches) from the bottom of your feet to the top of your head when you are in an erect standing position. A person’s height is observable to someone else. We cannot directly observe intelligence as we do height. Intelligence is like learning, which is also not directly observable. Rather, it is operationally defined based on behavioral observations. Technically, we do not observe learning; we observe learned behavior. Applying this same approach to intelligence, we need to observe intelligent behavior.

At the beginning of the twentieth century, many of the countries experiencing the Industrial Revolution implemented compulsory education to increase the knowledge and skills of future workers. The French government asked Alfred Binet, a psychologist, to develop an easily administered test to identify children requiring special assistance to succeed in the public schools. Binet (1903) formulated an ordered list of 30 questions addressing basic skills such as memory, problem-solving, and vocabulary. Examples of simple items include asking a child to point to his/her nose and to name a food. Examples of difficult items would be to use three different words in a sentence and to provide the definition of an abstract word. Scoring was based on the concept of mental age as determined by the average number of items children of different ages got correct. It must be emphasized that Binet formulated his test to address a practical problem, school readiness, not to assess native ability. The test was designed to serve a supportive function; to diagnose the type of assistance a child needed to succeed. Binet anticipated the possibility of interpreting his test as measuring intelligence, but believed intelligence was multifaceted and fluid, rather than unitary and stable. He also believed intelligence was influenced by experience and that comparisons could only be made for people sharing similar environmental conditions (White, 2000).

Despite Binet’s (1903) stated reservations, the Stanford psychologist, Lewis Terman (1916), standardized his test on American children, calculated an IQ (intelligence quotient) score as proposed by William Stern (1912), and considered it to measure intelligence. The IQ score was obtained by dividing a child’s mental age by the child’s chronological age and multiplying by 100. For example, if a 4-year old tested at the level of an average 5-year old, the IQ score would equal 125 (5/4 X 100).

Unlike Binet, Terman believed his test items measured an inherited, unitary, and stable trait of intelligence. Based on this assumption, his standardization process produced IQ test results adhering to the normal curve with a mean of 100 and standard deviation of 15 (see Figure 7.19). This meant that a little more than 68 per cent of the scores were between 85 and 115 (i.e., from minus one to plus one standard deviation) and a little more than 95 per cent were between 70 and 130 (minus two to plus two standard deviations).

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Figure 7.19 Normal curve for IQ.

The Stanford-Binet became the most popular intelligence test for decades. It is ironic that a test developed to address a practical concern and considered by its founder to be inappropriate as an index of intelligence, became the basis for the first operational definition of intelligence (i.e., IQ test score). Having an operational definition for intelligence, it becomes possible to ask if the questions on the test appear to be measuring something clearly biological such as height, something probably having a strong biological component such as jumping ability, or something clearly requiring skill development such as shooting from a distance. Terman believed and acted as though IQ score, despite being inferred from behavioral observations, measured something akin to height. Arguably, a memory test such as digit span seems akin to height or jumping ability. The amount of items one is able to repeat back is limited by the capacity of short-term memory. However, the great majority of IQ test questions are obviously influenced by experience. Children are taught to label and point to different body parts. Vocabulary and grammatical rules are learned. As described in Chapter 1, children must be taught to follow instructions and work to the best of their ability in order for the test to provide meaningful results.

Would it make sense to visit the rainforest and administer the Stanford-Binet to a Nukak child in English? Based on the test results, would it make sense to make important life decisions for the child? It is unfortunate that so much controversy and harm was introduced by redefining a procedure designed to assess school readiness as a test of intelligence. Terman believed “There is nothing about an individual as important as his IQ” (Terman, 1922). It is true that, IQ score is a better predictor of school performance at all levels and of job performance than any other test result (Schmidt & Hunter, 1998). This should not be surprising. Binet and his colleagues spent 15 years developing items to determine which children would require special assistance to succeed in school. Many jobs in a technologically advanced culture are dependent on the skills and knowledge acquired in schools.

Unlike Binet, whose goal was to identify school children requiring special assistance, Terman proposed using IQ tests to classify children and place them on separate educational and career paths. This was frequently recommended despite the fact that the children were unschooled or English was not their native language. Terman became an advocate of eugenics, proposing that IQ test results should be used as a basis for controlling reproductive and educational practices. According to him, “High-grade or border-line deficiency… is very, very common among Spanish-Indian and Mexican families of the Southwest and also among Negroes. Their dullness seems to be racial, or at least inherent in the family stocks from which they come. Children of this group should be segregated into separate classes… They cannot master abstractions but they can often be made into efficient workers… from a eugenic point of view they constitute a grave problem because of their unusually prolific breeding” (Terman, 1916, pp. 91-92). Tragically, thousands of poor African-American women were involuntarily sterilized as the result of such positions (Larson, 1995, p. 74).

In 1974, Leon Kamin published The Science and Politics of IQ questioning the motivations behind the use of IQ test results as the basis for social policy recommendations. Other similar articles and books soon followed (c.f., Block & Dworkin, 1976; Cronback, 1975; Scarr, & Carter-Saltzman, 1982). In 1994, Herrnstein & Murray published The Bell Curve: Intelligence and Class Structure in American Life, sparking further controversy regarding the interpretation of research findings and their social implications. In reaction to the increasingly heated public and professional debates regarding intelligence testing, the American Psychological Association appointed a Task Force chaired by the respected cognitive scientist, Ulrich Neisser. The Task Force was charged with reviewing the findings of the voluminous research literature, reaching conclusions, and making recommendations. The authors of the report concluded:

In a field where so many issues are unresolved and so many questions unanswered, the confident tone that has characterized most of the debate on these topics is clearly out of place. The study of intelligence does not need politicized assertions and recriminations; it needs self-restraint, reflection, and a great deal more research. The questions that remain are socially as well as scientifically important. There is no reason to think them unanswerable, but finding the answers will require a shared and sustained effort as well as the commitment of substantial scientific resources. Just such a commitment is what we strongly recommend (Neisser et al., 1996).

In Chapter 1, we discussed the requirements of psychological explanations and the implications regarding nature/nurture controversies. Intelligence is frequently used in a circular manner as a pseudo-explanation for behavior. Why does someone obtain a high score on an IQ test? – Because she/he is intelligent. How do you know someone is intelligent? – Because she/he scores high on the IQ test. IQ cannot serve as both an independent and dependent variable. An IQ test consists of behavioral tasks presumed to require intelligence. As such, IQ test performance is something to be explained (i.e., a dependent variable), not in and of itself an explanation (i.e., an independent variable). As always, psychology looks to nature and nurture for its explanations. No single gene has consistently been reported to have a strong effect on IQ (Deary, Whalley, & Starr, 2009). Hundreds of genes have been found to impact upon human height (Lanktree et al., 2011). It is likely that thousands of the 17,000 or so human genes influence IQ test scores.

We described how pseudo-explanations can result in self-fulfilling prophecies. It might surprise you to know that such effects have been experimentally demonstrated to occur with regard to intelligence both in the laboratory and in the field. In one study, college students were told that they were given either “maze bright” or “maze dull” rats to run through a maze (Rosenthal & Fode, 1963). Even though the rats were randomly assigned to the categories, the “maze-bright” rats performed better than the “maze dull” rats. Presumably, the students’ expectancies influenced how they treated the rats and affected the results.

In an important book entitled Pygmalion in the Classroom, Rosenthal & Jacobson (1968) demonstrated the external validity of this finding with children in schools. After tests were administered to first- through sixth-grade students, teachers were told that the results indicated that some of their students would “bloom” that year. Randomly, 20 per cent of the students in each of the classes were designated as “bloomers.” Sure enough, upon re-testing at the end of the year, first- and second grade students designated as “bloomers” improved more than the control students. The same effect was not demonstrated in the students in the later grades. It was suggested that young children are especially sensitive to the types of behaviors related to teacher expectancies.

Rather than acting as though intelligence exists as a human characteristic akin to height, it is more accurate, as well as prescriptive, to consider intelligence akin to jumping or shooting a basketball from a distance. Research must be designed to analyze the specific genetic and experiential components of behaviors considered to be intelligent. For example, what genes and learning experiences are necessary for a child to respond to an instruction to touch his/her nose, or include three words in a sentence? This approach avoids unnecessary controversy concerning racial or ethnic differences in intelligence. Rather, research is conducted to determine the potential causal variables in the acquisition of culturally-defined intelligent behaviors. Such a strategy is grounded in the reality that both nature and nurture contribute to an individual’s responding to any item on an IQ test.

Analyzing Intelligence

Do you think there is a trait of athleticism that applies to all sports? Or, do you think that there are separate abilities and skills that apply to different sports? One of Alfred Binet’s initial suggestions was that intelligence is complicated and can be analyzed into separate abilities and skills. This differed from Terman’s belief that intelligence was a unitary aptitude applicable under all conditions. More than a century has passed since Binet implemented his test in the Paris school system. Since then, other more comprehensive tests permitting more analytic scoring and prescriptive applications, have been developed.

David Wechsler gained experience developing adult intelligence tests for the military during World War 1. While serving as Chief Psychologist at Bellevue Medical Center in New York City, he developed the Wechsler-Bellevue Intelligence Scale (1939). This was later published in 1955 as the Wechsler Adult Intelligence Scale (WAIS) and revised in 1981, 1997, and 2008. Wechsler agreed with Binet that intelligence was multi-faceted and included several diverse types of questions on his test. Wechsler also believed that the verbal abilities assessed on the Stanford-Binet were highly dependent on education and therefore culturally biased. He developed a combination of tasks which did not rely on verbal knowledge and that could produce a separate performance IQ score. Subsequent revisions of the WAIS included additional types of questions and more analytical scores.

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Figure 7.20 Subscales of the Wechsler Adult Intelligence Scale.

Figure 7.20 provides an overview of the different categories and types of test items and the different scores (indexes in the Figure) one can obtain with recent versions of the WAIS. The WAIS and WISC (Wechsler Intelligence Scale for Children) are presently the most frequently administered intelligence tests (Kaplan & Saccuzzo, 2009, pp 250-251). One of the reasons for this popularity is the prescriptive capability resulting from the subscale indexes and the scores for different item types comprising each subscale. For example, a low score on the vocabulary items of the Verbal Comprehension index could suggest the benefit of working with flashcards whereas a low score on the information items might suggest assignment of reading material. A similar analytic and prescriptive approach would apply to the other indexes and item types.

It is possible to use the statistical technique of factor analysis to analyze intelligent behavior based upon the results of empirical research studies. Citing more than six decades of research evaluating human cognition, John Carrol (1993) obtained results supporting a three-stratum model of cognitive ability (see Figure 7.21). The first stratum consisted of a General Intelligence factor, consistent with Terman’s unitary approach. However, the results also suggested the eight “Broad Ability” factors listed above as well as 69 narrow abilities. Analyzing intelligence test performance into different components in this way reduces the controversy resulting from a single global score. Rather than generating questions regarding differences in “intelligence”, questions regarding differences in performance on different types of tasks are generated. This requires examination of the specific broad and narrow abilities involved in answering test items. Ultimately, the genetic (nature – e.g., parts of the brain) and experiential (nurture – e.g., learning experiences)) variables influencing the abilities impacting upon specific test items need to be specified.

Figure 7.21 Carroll’s three-stratum model of cognitive ability. Key: fluid intelligence (Gf), crystallized intelligence (Gc), general memory and learning (Gy), broad visual perception (Gv), broad auditory perception (Gu), broad retrieval ability (Gr), broad cognitive speediness (Gs), and processing speed (Gt). Carroll regarded the broad abilities as different “flavors” of g.

Different Types of Intelligence

Do you think the same type of athleticism applies to all sports? Or, do you think there are different forms of athleticism applying to basketball players, baseball players, soccer players, etc.? Relating this to intelligence, it is common for people to distinguish between “school smarts” and “street smarts.” Does that distinction make sense to you? It does to Howard Gardner. Wechsler disagreed with Terman’s belief that intelligence was unitary as opposed to multi-faceted. Gardner (1983) disagreed with Terman’s belief that the Stanford-Binet test measured the only important form of intelligence and proposed a multiple intelligence model (see Figure 7.22).

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Figure 7.22 Howard Gardner’s Multiple Intelligence Model.

Verbal/linguistic intelligence, logical/mathematical intelligence, and to a lesser extent, visual spatial intelligence, are the domains emphasized on the majority of standardized tests. Again, this should not be surprising since Binet developed the original test to assess school readiness. Gardner believed it was necessary to also consider bodily/kinesthetic intelligence, musical/rhythmic intelligence, intra- and inter-personal intelligence, and naturalistic intelligence, in order to appreciate the full range of human intellectual ability and accomplishment.

Intelligence and Human Potential

I previously quipped that based on our DNA and the amount of brain space dedicated to our hands and speech-related body parts, the title of this book could be “Thumbs, Tongues, and Cortex.” Human potential and accomplishment is built upon this three-legged stool. Without the conceptual knowledge, problem-solving ability, imagination, and creativity permitted by our brains (i.e., what we usually consider “intelligence”), our speaking and tool-making capabilities would be very limited. Wechsler defined intelligence as “the global capacity of a person to act purposefully, to think rationally, and to deal effectively with his environment” (1939). Eat, survive, reproduce. When we examine the aptitudes and abilities required to obtain and prepare food, build and maintain shelters, establish and maintain cooperative relationships with relatives, friends, and significant others, and raise children, we can appreciate Gardner’s consideration of other, non-school related forms of intelligence. We had to be intelligent in order to survive on this planet for a very long time before we created schools. It is only in the past century that for many, adapting to the human condition became so related to the three “R”s and performing well on standardized and non-standardized tests. One can debate the appropriateness or inappropriateness of considering any of Garner’s eight “intelligences” as aptitudes, talents, skills, or traits. What cannot be debated is the essential role each has played in the totality of human achievement and the importance of each when considering our potential as individuals and a species. Much human achievement requires cooperation and teamwork. This is true in order to survive in the rainforest or to transform Manhattan Island. Our combined potential is greater than the sum of our individual potentials. The transformation of Manhattan required cooperation among diverse individuals possessing the different talents and skills required to plan, design, and create the impressive skyline. The best strategy for realizing our potential as a species is to act upon John Adam’s and Albert Binet’s desires to educate each and every individual.

Consideration of intelligence in this chapter is out of place with regard to the organization of the book. As described in Chapter 1 and in the material above, nature and nurture are involved in intelligent human behavior. This implies the Nature/Nurture section as being the appropriate location to include intelligence. Instead, I chose to discuss intelligence as a way of concluding the Mostly Nurture section.

The bottom line of Wechsler’s definition of intelligence is its adaptive nature. What is considered intelligent depends upon one’s physical and social environmental demands. Surviving in the rainforest requires very different behaviors than performing well in school. Performing well in school requires different behaviors than performing well on the job or in social contexts. It took millions of years of natural selection for the human being to evolve. The result was an animal capable of adapting to a wide range of environmental conditions. As social and communicating animals, humans profit from the experiences of others. Shared knowledge and skills have resulted in the accelerating development of life-transforming tools and technologies. There is no way to predict the environmental conditions humans will create in the future. We can predict the continued modification of and adaptation to a new world; perhaps even new worlds!

Intelligence and Self-Control

God, give me grace to accept with serenity the things that cannot be changed,

Courage to change the things which should be changed,

and the Wisdom to distinguish the one from the other.

Reinhold Neibuhr

Do you think you can be more intelligent? Your answer to the question may depend on whether you agree with Terman’s or Binet’s assumptions. If, like Terman, you believe intelligence is unitary, inherited, and fixed, a passive serenity is called for. If you agree with Binet, that intelligence is multi-faceted and affected by experience, a more active, courageous approach becomes possible. We have seen that the science of psychology has resulted in knowledge regarding procedures effecting behavior change. This makes it possible for you to apply the self-control process described in previous chapters to change the behaviors you consider to reflect intelligence and develop your potential.

At the beginning of this chapter we saw how much of our knowledge consists of concepts and that adaptation may often be described as problem-solving. A college education is designed to expand your knowledge base as well as improve and add to your problem-solving skills. Review of the types of items tested on Wechsler’s IQ test (see Figure 7.10) reveals how attending college could improve your performance on each of the sub-scale indexes. Succeeding in college will require a significant amount of reading in diverse content areas. Along the way you will acquire many new concepts and expand your vocabulary. You will take math courses requiring quantitative reasoning and humanities courses requiring comprehension and critical thinking. You can maximize the benefit of your formal education by being an active student. Constantly test yourself for mastery of the material. Try to integrate the information acquired in different courses and consider how to apply the knowledge and skills beyond the classroom. Time permitting, read for pleasure. Whether you enjoy fiction or non-fiction, reading will expose you to new information and ideas. The more you learn, the more informed and thoughtful you will become and the more likely to fulfill your potential.