Chapter 6: Indirect Learning and Human Potential

Observational Learning

Direct and Indirect Learning

In order to appreciate the differences between the lives of hunter-gatherer humans such as the Nukak, and technologically enhanced humans, it is necessary to consider the role and extent of social learning (i.e., involving others of the same species). Social learning can consist of simply observing how others behave under specific circumstances, or symbolic communication through the use of language. Usually, Introduction to Psychology textbooks cover observational learning in the same chapter as classical and instrumental conditioning, with language appearing in a different chapter. I prefer to combine these topics, using the previously mentioned distinction between direct and indirect learning.

In classical and instrumental conditioning, an individual interacts directly with environmental events. Pavlov’s dogs were exposed to the tone and food; Skinner’s rats could press the bar and receive food. In contrast, observational learning is indirect in the sense that someone (or something) else is interacting with the environment. An example of indirect classical conditioning might involve one child (the observer) witnessing another child (the model) being jumped upon by a dog and acting fearful. It is likely that even though the dog did not jump on the observer, he will be fearful in its presence. An example of indirect instrumental conditioning might involve a child witnessing another taking a cookie from a cookie jar. We all know what will happen next.

Language is a consensually agreed upon collection of arbitrary symbols representing objects, movements, properties, and relationships among objects and events. Through language, humans can provide similar information to that provided through observational means, thereby resulting in similar behaviors. For example, one can tell a child that a particular dog might jump on him, or that there are cookies in a cookie jar. Olsson and Phelps (2004) compared direct, observational, and linguistic learning of a fear of faces. Human subjects were either exposed to a shock (direct learning) in the presence of a picture of a face, observed another person’s emotional reaction to the face (indirect observational), or were told that the picture of the face would be followed by shock (indirect symbolic). All three groups subsequently demonstrated similar fear reactions to the picture of the face. The three types of experience represent different paths to the same adaptive learning (see also Kirsch, Lynn, Vigorito, and Miller, 2004). We will now consider each of the forms of indirect learning in greater depth.

Observational Learning

Figure 6.1 Albert Bandura.

Bandura’s Four-stage Model of Observational Learning

Albert Bandura is to the study of observational learning what Pavlov is to the study of predictive learning (classical conditioning) and what Thorndike and Skinner are to the study of control learning (instrumental or operant conditioning). Bandura conducted some of the pioneering research demonstrating observational learning in children and developed a comprehensive theory of social learning (Bandura, 1962, 1965, 1969, 1971, 1973, 1977a, 1977b, 1978, 1986; Bandura, Ross, & Ross, 1961, 1963a, b; Bandura & Walters, 1963). Much of his empirical research relates to the four-stage model of observational learning he proposed to analyze and organize the voluminous literature (see You Tube video). The four logically necessary observational learning processes include: attention, retention, production, and motivation. That is, in order for an observer to imitate a model it is essential that the observer attend to the model’s behavior, retain information regarding the important components, have the ability to produce the same actions, and be motivated to perform. This is a “chain as strong as its weakest link.” If any stage is missing, imitation (but not necessarily learning) does not occur. We will now review some of the major variables found to influence each of these stages.

Attention

Much of what we have learned about direct predictive and control learning applies to observational learning as well. Human beings predominantly rely upon the senses of vision and hearing to adapt to environmental demands. In order to imitate what we see or hear, we must be attending to critical elements of modeled behavior. Factors such as intensity, attractiveness, and emotionality will enhance the salience of a stimulus, increasing the likelihood of imitation (Waxler & Yarrow, 1975).

Prior learning experience, in the form of perceived similarity to self, significantly affects the probability of attending to different models in one’s environment. One is more likely to attend to individuals of the same sex, age, race, ethnicity, social class, and other variables. Girls and boys are universally treated very differently. Starting from birth, they are dressed differently, given different hair styles, and encouraged to engage in different behaviors. Girls are encouraged to “play house” and boys to “play ball.” When children first start to speak, they soon learn to categorize the world into “mama”, “dada”, boys and girls, and assign themselves gender and age identities. These assignments impact upon their choices of models throughout their lives. Selective indirect learning experiences influence family responsibilities in all cultures and education and career opportunities in technologically enhanced cultures.

In addition to those similar to them, people are most likely to attend to others designated as “authority figures” or “role models”, whether these designations are earned or assigned. In a Stone-Age culture such as the Nukak, there are very few potential models. Elders are most likely to be considered authority figures with special powers or abilities attributed to some. In our culture, every day we come into contact with a large number of potential models based on kinship, grade-level, occupation, organization-membership, friendship, etc. In addition to these “live” examples we are exposed to a countless number of potential models on the radio, TV, internet, etc. The likelihood of paying attention to a model can be based upon perceived functional value. For example, one may seek out a particular relative or friend or search for a particular website in order to obtain knowledge or skills that relate to a current problem. Sources of authority may include elders, teachers, clergy, “experts”, or celebrities. For example, it was demonstrated that 11- to 14-year old women performed better on a task modeled by a cheerleader as opposed to a lower-status female model (McCaullaugh, 1986).

In the previous chapter, we described Nukak foraging trips. Many of the skills required for hunting, gathering, and preparing food are acquired through observational learning. “Every Nukak knows how to make virtually everything he or she will need during his or her lifetime, and the basic material for making these items can be found within the band’s territory” (Politis, 2007, 229). The blowpipe, fashioned from cane, is the primary hunting tool. Darts made from palm trees are shaped, sharpened, and tipped with the paralyzing drug curare obtained from the bark of the parupi vine. Nukak men spend considerable time making 7- to 10-foot long blowpipes, caring for and maintaining them. Smaller blowpipes (less than 6-feet-long) are constructed for young boys to play with and acquire expertise. Male adolescents often accompany their fathers on foraging trips with scaled-down blowpipes.

Women and girls are responsible for grinding various fruit and seeds. The mortars are created from sections of tree trunks and the pestle is a straight stick with one end flattened. Women also fashion clay pots for the storage and transport of fruits and liquids, fiber hammocks, and baskets of different sizes made from vines (Politis, 2007, 210-217).

Figure 6.2 Children’s cooking class.

Retention

Bartlett (1932) conducted memory research with meaningful materials such as stories or fables. He found that in retelling stories, people tended to alter them in systematic ways. He concluded that memory is a reconstructive rather than a reproductive process involving leveling (simplification), sharpening (exaggeration of specific details), and assimilation (incorporation into existing schemas). Thus, when we observe a model, we are not storing a “videotape” of what we see and hear but rather encoding our observations in such a manner that we can reconstruct what occurred at a later time. For example, if someone is demonstrating how to open a combination lock, we will probably try to memorize verbal instructions (e.g., turn clockwise past 0 to 14, turn counter-clockwise past 0 to 28, etc.). It will decrease the likelihood of encoding errors if this complex behavior is broken down into manageable units. The instructions should be repeated at a slow pace, out loud or silently, to improve retention and increase the likelihood of opening the lock. Adults who verbally coded modeled events and actively rehearsed afterward were much better at imitating what they observed than adults who did not code the events or were prevented from rehearsing (Bandura & Jeffrey, 1973). Later in this chapter, we will review research related to memory and forgetting in more depth.

Response Production

When I was a child, I loved the TV character Superman. I would join my friends with a towel draped around my neck and try to fly. I have yet to take off. Obviously I had attended to Superman and remembered what he did. As I grew up, I continued to watch TV and have role models. Many of these, like Superman, possessed natural abilities that escaped my genes or skills that escaped my learning history. In the former case, I was forced to be serene. In the latter, with “courage”, I could acquire the component responses necessary to imitate the model. In Chapter 14, we will consider the topic of self-control and I will describe a research-based process for changing one’s behavior in a desired fashion. Still, I wouldn’t suggest trying to fly.

Motivation

We can see people doing pretty much anything on the internet. Fortunately, it is not necessarily the case that “people see, people do.” In our complicated, open, media-dominated world, we are constantly exposed to models performing undesirable, illegal, or dangerous acts. We do not automatically try to imitate everything we observe. Often, the outcome is an example of latent observational learning. The rats in Tolman and Honzik’s (1932) group that did not receive food at the end of the maze learned the correct route, but didn’t show it. We often attend to models, remember what they performed, and possess the ability to imitate their actions but do not in the absence of an incentive.

In a classic study, Bandura (1965) showed boys and girls a film depicting a child displaying unusually aggressive acts with a Bobo doll punching bag (e.g., hitting the doll with a hammer – see below). In one version of the film, an adult observed the child and punished his aggressive acts. In a second version, the adult praised and provided candy to the boy. There was no consequence in a third condition. Afterwards, the children were placed in a room with a Bobo doll and observed to see how often they displayed the unusual aggressive acts. The findings indicated that boys committed more of these aggressive acts than girls in all three conditions. Both boys and girls were more likely to imitate the model that was rewarded at the end of the film than the model that was punished. Afterwards, children in the 3 groups were offered treats to imitate what they observed in the film. As was true in Tolman and Honzik’s group that was switched from non-reward to reward, there was a dramatic increase in the number of aggressive acts. Clearly, the children had learned and retained what they observed. The likelihood of imitation was influenced by both the consequences displayed in the film as well as the contingencies implemented in the playroom (see Figure 6.2).

Figure 6.3 Children displaying observational aggression (Bandura, 1965).

Figure 6.4 Mean number of different matching responses reproduced by children as a function of response consequences to the model and positive incentives (Adapted from Bandura, 1965).

In a classic series of studies (Bandura, Grusec, & Menlove, 1967; Bandura and Menlove, 1968), children with fears of dogs were shown films of other children interacting with dogs exhibiting progressively-threatening behaviors. This indirect observational learning procedure was very successful in reducing or eliminating the children’s fears.

Speech and Language

Civilization began the first time an angry person cast a word instead of a rock.

Sigmund Freud

Observational learning has been evidenced in many species of animals including birds (Zentall, 2004) but approximations to speech appear practically unique to humans. Paul Revere famously ordered a lantern signal of “one if by land and two if by sea” during his Revolutionary War midnight ride through the streets of Massachusetts. This is not functionally different from the distinct alarm calls emitted by vervet monkeys in the presence of eagles, snakes, and leopards (Strushaker, 1967; Seyfarth and Cheney, 1980). Through observational learning, young vervets learn to respond to different screeches for “heads up”, “heads down”, and “look around!” Vervets hide under trees to the eagle warning, rear on their hind paws to the snake warning, and climb the nearest tree to the leopard warning. Recently, even more descriptive “speech” has been demonstrated in prairie dogs (Slobodchikoff, Perla, & Verdolin, 2009). These examples are the closest we see to social learning of speech in other animals. Slobodchikoff (2012) has written a fun and informative review of animal communication entitled Chasing Dr. Doolittle: Learning the Language of Animals.

Meltzoff and Moore (1977, 1983) demonstrated unambiguous examples of imitation in infant humans as young as 12- to 21-days of age, leading to the conclusion that humans normally do not need to be taught this mode of learning.

Skinner (1986) contributed an interesting but admittedly post-hoc speculative theoretical article describing possible evolutionary scenarios for the adaptive learning of imitation and speaking. An imitative prompt is more informative than an ordinary gestural prompt in that it specifies the specific characteristics of a desired response. Speech is preferable to signing as a means of communication since it is possible at long distances and other circumstances where individuals cannot see each other.

Hockett’s Features of Language

If we are to understand human behavior, we must understand how language is acquired and its impact upon subsequent adaptive learning. Before we proceed, we must consider what we mean by language. Charles Hockett (1960) listed 13 features that he considered essential to language:

1. Vocal-auditory channel – We saw in Chapter 1 that the human being’s brain, with its disproportional amount of space dedicated to the tongue, larynx, and voice box, facilitates the acquisition of speech. Sign language, involving a manual-visual channel, is mostly restricted to deaf people and those wishing to communicate with them.

2. Broadcast transmission and directional reception – Sound is sent out in all directions while being received in a single place. This provides an adaptive advantage in that people can communicate with others out of their line of sight.

3. Rapid fading (transitoriness) – Sounds are temporary. Writing and audio-recordings are techniques used to address this limitation of speech (and alas, lectures).

4. Interchangeability – One must be able to transmit and receive messages.

5. Total feedback – One must be able to monitor one’s own use of language.

6. Specialization – The organs used for language must be specially adapted to that task. Human lips, tongues and throats meet this criterion.

7. Semanticity – Specific signals can be matched with specific meanings. Different sounds exist for different words.

8. Arbitrariness – There is no necessary connection between a meaningful unit (e.g., word) and its reference.

10. Discreteness – There are distinct basic units of sound (phonemes) and meaning (words).
11. Displacement – One must be able to communicate about things that are not present. One must be able to symbolically represent the past and the future.

11. Productivity – The units of sound and meaning must be able to be combined to create new sounds and meaningful units (sentences).

12. Duality of patterning – The sequence of meaningful units must matter (i.e., there must be a syntax).

13. Traditional Transmission – Specific sounds and words must be learned from other language users.

Although all of Hockett’s features are frequently cited as the defining characteristics of language, the first 3 elements are restricted to speech. These features do not apply to sign language, letter writing, reading, and other examples of non-vocal/auditory modes of symbolic communication.

Language Acquisition

The principles of predictive and control learning help us understand the acquisition of language and the role it plays in subsequent human adaptation. At a few months old, infants start to babble and are able to make all the possible human sounds. Eventually, as the child is increasingly exposed to the sounds of her/his social unit, some of the sounds are “selected” and others removed from the repertoire. Routh (1969) demonstrated that infants are able to make subtle discriminations in sounds. The frequency of speaking either vowels or consonants could be increased if selectively reinforced with tickles and “coos.” It has been demonstrated that the mother’s vocal imitation of a child’s verbalizations is also an effective reinforcer (Pelaez, Virues-Ortega, and Gewirtz, 2011).

Children may learn their first word as early as 9 months. Usually the first words are names of important people (“mama”, “dada”), often followed by greetings (“hi”, “bye”) and favored foods. As described in Chapter 5, classical conditioning procedures may be used to establish word meaning. For example, the sound “papa” is consistently paired with a particular person. Children are encouraged to imitate the sound in the presence of the father. It may be the source of humor (or embarrassment) when a child over-generalizes and uses the word for another male adult. With experience, children learn to attend to the relevant dimensions and apply words consistently and exclusively to the appropriate stimuli or actions (e.g., “walk”, “run”, “eat”, etc.). Similarly, words are paired with the qualities of objects (e.g., “red”, “circle”, etc.) and actions (e.g., “fast”, “loud”, etc.). Children learn to abstract out the common properties through the process of concept formation. Words are also paired with quantities of objects. In the same way that “redness” may be a quality of diverse stimuli having little else in common, “three-ness” applies to a particular number of diverse stimuli.

Much of our vocabulary applies to non-observable objects or events. It is important to teach a child to indicate when “hurt” or “sick”, or “happy” or “sad.” In these instances, an adult must infer the child’s feelings from his/her behavior and surrounding circumstances. For example, if you see a child crying after bumping her head, you might ask if it hurts. As vocabulary size increases, meaning can be established through higher-order conditioning using only words. For example, if a child is taught that a jellyfish is a “yucky creature that lives in the sea and stings”, he/she will probably become fearful when swimming in the ocean.

Since different languages have different word orders for the parts of speech, syntax (i.e., grammatical order) must be learned. At about 18 months to 2 years of age, children usually start to combine words and by 2-1/2 they are forming brief (not always grammatical) sentences. With repeated examples of their native language, children are able to abstract out schemas (i.e., an organized set of rules) for forming grammatical sentences (e.g., “the car is blue”, “the square is big”, etc.). It is much easier to learn grammatical sequences of nonsense words (e.g., The maff vlems oothly um the glox nerfs) than non-grammatical sequences (e.g., maff vlem ooth um glox nerf). This indicates the role of schema learning in the acquisition of syntax (Osgood, 1957, p.88). Children usually acquire the intricacies of grammar by about 6 years of age. In the next chapter, we will describe the process of abstraction as it applies to concept learning, schema development, and problem-solving.

Vocabulary size has been found to be an important predictor of success in school (Anderson & Freebody, 1981). Major factors influencing vocabulary size include socio-economic status (SES) and the language proficiencies of significant others, particularly the mother. In a monumental project, Hart and Risley (1995) recorded the number of words spoken at home by parents and 7-month-to 36-month-old children in 42 families over a 3-year period. They found that differences in the children’s IQ scores, language abilities, and success in school were all related to how much their parents spoke to them. They also found significant differences in the manner in which low and high SES parents spoke to their children. Low SES parents were more likely to make demands and offer reprimands while high SES parents were more likely to engage in extended conversations, discussion, and problem-solving. Whereas the number of reprimands given for inappropriate behavior was about the same for low and high SES parents, high SES parents administered much more praise.

Speech becomes an important and efficient way of communicating one’s thoughts, wishes, and feelings. This is true for the Nukak as well as for us. Given the harshness of their living conditions and the limits of their experiences, the Nukak have much in common with low SES children within our society. Declarative statements (e.g., “the stick is sharp”, “the stove is hot”; “pick up the leaves”, “don’t fight with your sister”; “I am happy”, “you are tired”, become the primary basis for conducting much of the everyday chores and interactions.

Spoken language is observed in stone-age hunter/gatherer and technologically advanced cultures. There has been controversy concerning the role of nature and nurture in human language development (Chomsky, 1959; Skinner, 1957). Skinner, writing from a functionalist/behavioral perspective, tellingly entitled his book Verbal Behavior, not “Using Language.” Watson (1930) described thinking as “covert speech” while Skinner (1953) referred to “private behavior.” According to Vygotsky (originally published in 1934), children initially “think out loud” and eventually learn to “think to themselves.” Skinner suggested that speaking and thinking were not different in kind from other forms of behavior and that respondent conditioning (predictive learning) and operant conditioning (control learning) could provide the necessary experiential explanatory principles. There was no need to propose a separate “language acquisition device” to account for human speech.

We saw in Chapter 5, how predictive learning principles could be applied to the acquisition of word meaning. Basically, Skinner argued that words could serve as overt and covert substitutes for the control learning ABCs. As antecedents, words could function as discriminative stimuli and warning stimuli. For example, “Give mommy a kiss” or “Heads up!” As consequences, words can substitute for reinforcers and punishers (e.g., “Thank you.”, “Stop that!”). A rule is a common, useful, and important type of verbal statement including each of the control learning ABCs (Hayes, 1989). That is, a rule specifies the circumstances (antecedents) under which a particular act (behavior) is rewarded or punished (consequence). For example, a parent might instruct a child, “At dinner, if you eat your vegetables you can have your dessert” or, “When you get to the curb look both ways before crossing the street or you could get hit by a car.”

Chomsky, a psycholinguist, submitted a scathing critique of Skinner’s book, emphasizing how human genetics appears to include a “language acquisition device.” The Chapter 1 picture of the human homunculus, with its disproportional brain space dedicated to the body parts involved in speech, certainly suggests that the human being’s structure facilitates language acquisition. The homunculus also implies there is adaptive value to spoken language; otherwise these structures would not have evolved. Proposing a “language acquisition device”, similar to proposing an instinct to account for speech, is a circular pseudo-explanation. The language acquisition device is inferred from the observation of speech, it does not explain speech. Remember, a psychological explanation must specify specific hereditary and/or environmental causes. Chomsky does neither, whereas Skinner is quite specific about the types of experience that will foster different types of verbal behavior. It is not as though Skinner denies the role of human structure in the acquisition of speech or its importance as indicated in the following quote. “The human species took a crucial step forward when its vocal musculature came under operant control in the production of speech sounds. Indeed, it is possible that all the distinctive achievements of the species can be traced to that one genetic change” (Skinner, 1986). Neuroscientists and behavioral neuroscientists are actively engaged in research examining how our “all-purpose acquisition device” (i.e., brain) is involved in the learning of speech, reading, quantitative skills, problem-solving, etc.

Human beings may have started out under restricted geographic and climatic conditions in Africa, but we have spread all over the globe (Diamond, 2005). We developed different words and languages tailored to our environmental and social circumstances. There is much to be learned from the school of hard knocks, but it is limited to our direct experience and can be difficult or dangerous. Our verbal lives enormously expand learning opportunities beyond our immediate environment to anything that can be imagined. Indirect learning (i.e., observation or language) often speeds up adaptive learning and eliminates danger. It is not surprising that human parents universally dedicate a great deal of effort to teaching their children to speak. It makes life easier, safer, and better for them as well as their children.

MacCorquodale (1969) wrote a retrospective appreciation of Skinner’s book along with a comprehensive and well-reasoned response (1970) to Chomsky’s critique. Essentially, MacCorquodale described Chomsky as a structuralist and Skinner as a functionalist. That is, Chomsky attempted to describe how the structure of the mind enables language. Skinner was concerned with how language enables individuals to adapt to their environmental conditions. Paraphrasing Mark Twain, an article marking the 50th anniversary of its publication concluded that “Reports of the death of Verbal Behavior and behaviorism have been greatly exaggerated” (Schlinger, 2008).

Reading and Writing

It is language in written form that has enabled the rapid and widespread dissemination of knowledge within and between cultures. It is also the medium for recording our evolving advances in knowledge and technology. Early forms of Bronze Age writing were based on symbols or pictures etched in clay. Later Bronze Age writing started to include phonemic symbols that were precursors to the Iron Age Phoenician alphabet consisting of 22 characters representing consonants (but no vowels). The Phoenician alphabet was adopted by the Greeks and evolved into the modern Roman alphabet. The phonetic alphabet permitted written representation of any pronounceable word in a language.

The Arabic numbering system was originally invented in India before being transmitted to Europe in the Middle Ages. It permits written representation of any quantity, real or imagined, and is fundamental to mathematics and the scientific method, which rely on quantification and measurement. The alphabet and Arabic numbers permit words to become “permanent” in comparison to their transitory auditory form. This written permanence made it possible to communicate with more people over greater distances and eventually to build libraries. The first great library was established at Alexandria, Egypt in approximately 300 years B.C. Scrolls of parchment and papyrus were stored on the walled shelves of a huge concrete building (Figure 6.5). Gutenberg’s invention of the printing press in 1439 enabled mass publication of written material throughout Western Europe (Figure 6.6). Today, e-books are available on electronic readers that can be held in the palm of your hands (Figure 6.7)! It should not be surprising that college student differences in knowledge correlate with their amount of exposure to print (Stanovich and Cunningham, 1993).

Figure 6.5 The library at Alexandria.

Figure 6.6 Gutenberg’s printing press.

Figure 6.7 The library now.

Memory

An enormous amount of information is processed by our senses every day. As described, when discussing observational learning, some of it is attended to and some of it is ignored. Some of it is remembered and some is forgotten. Memory and forgetting have been important topics in psychology since the start of the discipline. Hermann Ebbinghaus (1885) invented the 3-letter nonsense syllable (e.g., GUX, VEC, etc.) in order to eliminate the effects of prior familiarity. He generated the first learning and forgetting curves for over 1,000 lists of nonsense syllables using himself as the subject. Whereas Ebbinghaus’ immediate recall was almost perfect, within nine hours retention dropped to less than 40 per cent. His performance continued to decline to about 25 per cent retention after six days and approximately 21 per cent after a month (see Figure 6.8).

Figure 6.8 Ebbinghaus’ forgetting curve.

Psychologists have tried to understand the mechanisms involved in memory and forgetting. An important question is whether forgetting is simply a function of the passage of time or the result of interference from other memories or activities. Since the time of Ebbinghaus, two significant sources of interference have been identified. Retroactive interference (i.e., working backwards) occurs when learning new materials reduces the ability to recall previously learned material. Proactive interference (i.e., working forwards) refers to the detrimental effect of previously learned material on the memory of new material (Slamecka & Ceraso, 1960). For example, if a student learned Spanish in high school and French in college, sometimes the new French vocabulary might interfere with remembering the former Spanish vocabulary. This is retroactive interference. If the prior learning of Spanish interfered with recalling the more recently learned French, this would be considered proactive interference. In the case of Ebbinghaus, as he learned more and more lists, he was increasing the buildup of both retroactive and proactive interference. That is, if he learned new lists before being asked to recall a previously learned list, this would result in retroactive interference. Proactive interference would occur when prior learning impeded learning a new list.

Starting in the late 1950s, researchers started distinguishing between different types (or stages) of memory. Sensory memory (sometimes referred to as very short-term memory) is basically a very brief continuation of sensation. Sensory memory exists immediately after presentation of a stimulus, is unconscious, and highly detailed (Sperling, 1960). Depending upon the variables previously considered under observational learning, some of the details will be attended to and others ignored. The attended to details may enter consciousness for further processing in the form of different rehearsal strategies. This longer-lasting, but still temporary stage, is usually referred to as working or short-term memory (Brown, 1958; Peterson and Peterson, 1959). Sometimes adapting to one’s environment only requires the use of currently available knowledge (e.g., after looking up a phone number). At other times, one may adapt by taking advantage of prior direct and indirect learning (e.g., when calling a family member or friend). Long-term memory refers to this much longer-lasting (perhaps permanent) stage.

Computers became information-processing models for human memory with sensory, short-term, and long-term memory linked in sequential stages. Atkinson and Shiffrin (1968, 1971) proposed the three-stage model of memory portrayed in Figure 6.9. Input (i.e., environmental sensory information) available in sensory memory had to be attended to in order to be available for rehearsal in short-term memory. There, the information had to be continually rehearsed in order to remain available. Then it needed to be elaborated upon and encoded in a manner which could be interpreted, stored, and retrieved at a later time from the more permanent long-term memory. As shown in Figure 6.4, information from long-term memory can be retrieved into short-term memory to address immediate adaptive needs. We will now elaborate on the methods and findings of the classic experiments which led to the Atkinson-Shiffrin information-processing model of human memory.

Figure 6.9 The Atkinson and Shiffrin Model of Memory.

Sensory Memory

George Sperling (1960) developed an ingenious procedure demonstrating that a great deal of information may be retrieved from a stimulus for a brief period of time after it is removed (1/20th of a second in Figure 6.10). If you show a person a matrix of twelve letters and ask them to recite as many of the letters as they can soon afterward (up to a second in the Figure), they usually are able to retrieve between four and five of the items.

Figure 6.10 Sperling’s partial-report procedure.

Sperling believed that the act of reporting what they remembered interfered with maintenance of the information, resulting in an inaccurate estimate of the actual amount retained. He developed a partial-recall procedure in which a high-, middle-, or low-frequency tone indicated which row of the array should be reported on an individual trial. It was demonstrated that up to about a quarter of a second, individuals were able to report twice as many of the items as with the full report method. In order for this to occur, the full array had to be available for processing. Visual sensory memory is often referred to as iconic memory. It has been determined that auditory sensory memory, often referred to as echoic memory, is more durable than visual information and can last several seconds (Cowan, Lichty, & Grove, 1990). This makes it possible to understand spoken sentences. Still, the limitations of auditory memory impact upon the ability to retain lecture material. A lecture requires processing the information contained in several sentences extending over lengthier time intervals.

Short-Term Memory

The information remaining in sensory memory is available for further processing through the conscious act of rehearsal. We have all had the experience of having to look up a phone number again if we are distracted before dialing. An important question raised by Brown (1958) and by Peterson and Peterson (1959) was how long information would remain consciously available in the absence of rehearsal. In order to determine this, it was necessary to ask people to recall information after different time intervals without rehearsing the material. This was accomplished by having them count backwards by three. You can try this yourself if you don’t think it would work. Look up a phone number and start counting backward from 1,000. See how long you can go before having to go back and look it up again. It was found that when rehearsal was prevented, retention of trigrams (i.e., three consonants) declined from 80 per cent after three seconds to 10 percent after 18 seconds. Thus, it is not surprising that if you are distracted soon after looking up a phone number, you will need to look it up again.

Keppel and Underwood (1962) reviewed Peterson’s and Peterson’s results and noted that memory was very good at all the intervals on the first few trials. Performance deteriorated, however, with additional trials. This raised the question of whether the decline in short-term memory as a function of interval length resulted from delay or proactive interference from prior trials. Waugh and Norman (1965) tested this by giving subjects lists of 16 numbers. After the last item, the subject was asked to report the number which appeared immediately after one of the numbers in the list. Digits were presented every second or every four seconds. By varying both the time interval and whether the target number appeared early or late in the list, it was possible to determine which variable was more important. If the time interval were more important, the position of the item in the list should not matter. If the number of items prior to the target was more important, the time interval should not matter. It turned out that the number of prior items had a much greater effect than the delay. Short-term memory loss is primarily the result of interference when someone is not actively rehearsing the material.

In addition to knowing the duration of short-term memory, it is important to know its capacity. That is, how much information can you maintain in consciousness if you are allowed to rehearse? Memory span tests are one way of addressing this question (Humpstone, 1917). You can be asked to repeat letters, words, or numerical digits in order. Items are added until you are correct on less than 50 per cent of the test trials. One of the most cited articles in the psychology literature is “The magical number seven, plus or minus two: Some limits on our capacity for processing information” by George Miller (1956). Miller examined the data from different types of short-term memory tasks, including memory span. He came to the conclusion that there is a relatively small amount of information we can retain in consciousness. He suggested that we are limited to between five and nine chunks of information. A chunk is similar to what we previously referred to as a gestalt; a meaningful unit. For example, study the following list of letters for about fifteen seconds and then look away and see how many you can correctly repeat:

mbicbnifbacbiac

Probably you were only able to correctly repeat about seven letters.

Now do the same with the same letters organized as follows:

ibmnbcfbiabccia

Now you may be able to repeat the entire list since they can be grouped into five chunks of three. Telephone companies try to help us out with our short-term memory limitations by grouping the numbers. Probably you have used mnemonics (i.e., memory enhancing techniques) to memorize different types of information. For example, the word HOMES might help you remember the five great lakes (Huron, Ontario, Michigan, Erie, Superior). Roy G Biv might help you recall the sequence of colors comprising the visual spectrum (red, orange yellow, green blue, indigo, violet). In the following chapter, we will review cognitive processes, including concept formation.

Long-Term Memory

Think of all the concepts you learned as children; the ABCs, numbers, names of relatives, types of food, names of feelings, etc. Think of all the skills you acquired; walking, talking, getting dressed and tying your shoes, riding a bike, etc. Think of different events in your life; birthday parties, fun with your siblings and friends, teachers in different grades, ball games and dances, graduations, etc. Think of how you feel when reading about a calm summer day, watching a close sporting contest, or hearing a buzzing bee. These are all examples of different types of long-term memory included in the overview provided in Figure 6.11 (Squire, 1986, 1993).

Figure 6.11 Types of long-term memory (adapted from Squire, 1986, 1993).

The first distinction in types of long-term memory relates to whether conscious effort is required for recall to occur. Explicit (declarative) memory requires conscious effort whereas implicit (non-declarative) memory does not. For example, recalling the name of a type of food you haven’t eaten for several years or when you met your best friend requires conscious effort. No effort is required to recall how to ride a bike or to feel relaxed when reading about a calm summer day.

Explicit memory can be sub-divided into sematic memory and episodic memory (Tulving, 1972). Semantic memory consists of your entire knowledge base including your vocabulary, concepts, and ideas. Episodic memory consists of your chronological listing of life events. A food type is an example of semantic memory. When you met your best friend is an example of episodic memory.

Implicit memory can be sub-divided into procedural memory and emotional memory. Procedural memory refers to all the motor skills you are able to execute. Emotional memory refers to the feelings experienced based on prior experience. Bike riding is an example of procedural memory whereas a fear of buzzing bees is an example of emotional memory.

We will now consider the factors influencing how these different types of information become stored in long-term memory. This has practical applications as you attempt to achieve your potential. Improving your long-term memory will help you adapt to many of the demands of your physical and social environment. It will help you learn your course material, not only to perform well on exams, but also to best apply the knowledge, skills, and attitudes you acquire to your future educational and career objectives.

Figure 6.9 indicates that maintenance rehearsal strategies, consisting of repeating information over and over again, are sufficient to retain information in short-term memory. More active elaborative rehearsal strategies related to the meaning of material, however, are far more effective for transferring information to long-term memory. Elaboration can be in the form of relating new information to previously acquired knowledge or to one’s personal experience. When studying for exams, rather than simply trying to memorize information through repetition, it is more effective to try to describe the information using your own words. You can try to apply the information by making up your own examples or describe how the information relates to other things you know. As described in Chapter 1, an extremely effective study strategy is to make up questions and then test yourself. The finding that this strategy improves recall and test results in college students (Roediger & Karpicke, 2006; Einstein, Mullet, & Harrison, 2012) and the elderly (Meyer & Logan, 2013) has been labeled the testing effect. Another effective way of determining if you understand information is to try to teach it to someone else. This is only possible when you have a thorough understanding of the material yourself.

One of the most important variables influencing your ability to learn, remember, and apply information is how it is organized. Effective lecturers and textbook writers attempt to use schemas (Rumelhart, 1980) and scripts (Mandler, 1984) in order to achieve their instructional objectives. Schemas organize information in a coherent way while scripts create a meaningful sequence. In the previous chapter, I described two schemas developed by Skinner to organize behavioral contingencies and intermittent schedules of reinforcement. Psychology studies how nature and nurture interact to influence the potential for human thought, feeling, and behavior. This description determined the schema for organizing the book. I hope this helps you see where each of the content areas (i.e., chapters) fit within the context of the entire discipline of psychology (see Figure 6.12).

Psychology: The Science of Human Potential

Mostly Nature Mostly Nurture Nature/Nurture

Biological Psychology Direct Learning Developmental

Sensation and Perception Indirect Learning Personality

Motivation and Emotion Cognition Social Psychology

Problem Behavior

Figure 6.12 Nature/nurture schema for organizing the textbook chapters.

I once read a review suggesting that starting a biological psychology textbook with a description of a neuron was like starting a book about airplanes with a description of a screw. When possible, it is helpful to create an overarching organizational schema (i.e., an “airplane”, “big picture” or “forest”) portraying the relationships between the different components (i.e., parts, little pictures, or trees). The nature/nurture schema for human potential was an attempt to create such an overview of the different content areas of psychology. Your potential is initially determined by your unique (assuming you are not an identical twin) genetically determined physical and biological characteristics, sensory capabilities, needs, and drives (i.e., “nature”). Ultimately, the direct and indirect learning experiences to which you are exposed (i.e., “nurture”) will impact upon your personality development and the extent to which you achieve your individual potential (“nature/nurture”).

Maslow’s human needs pyramid is a hierarchically organized script prioritizing categories of human needs. According to Maslow, one first needs to satisfy basic survival needs before being able to concentrate on interpersonal relationships, and so on. Atkinson and Schifrin’s three-stage memory model is another example of a script. Information sequentially flows from sensory, to short-term, to long-term memory. Another script, mentioned below as well as in Chapter 7, is the sequential development of technologies resulting from application of the scientific method. Such technological growth is rapidly transforming the human condition. Kurzweil (2001) attributed the accelerating pace of technological achievements to the recording of prior successes. Without this recording, individuals and cultures would not be able to profit from prior advances.

Preparing for School and the 3 “R”s

It is through indirect learning that the benefits of direct learning, including tool-making and technological change, are recorded and disseminated among humans. This is as true for the Nukak as it is for us. The Nukak use observational learning and language to socialize children and teach survival skills. Whereas the Nukak’s and our basic survival needs are the same, technologies have changed our physical conditions, population densities, and adaptive needs. The Nukak spend their time each day meeting their basic survival needs as individuals and a species.

Last chapter, we saw how verbal behavior can be understood through the application of basic learning principles. Once children speak, it is possible to use language to expand their knowledge and skills. Rather than acquiring hunting, gathering, and other survival skills, you have probably been acquiring school-related knowledge and skills since you were old enough to speak and prepare to attend school.

Children enjoy listening to rhymes. Children enjoy singing. Children REALLY enjoy singing rhymes! It is not unusual for adults to start singing the alphabet song to children as young as 2 years of age. The alphabet is an example of a serial list in which items always appear in a particular order. Serial learning was one of the first types of memory studied by Ebbinghaus. The serial-position effect (Hovland, 1938) refers to the finding that one learns the items at the beginnings and ends of lists before learning the items in the middle. The alphabet song divides the 26 letters into 4 manageable chunks based on rhyming sounds. This makes learning the entire sequence fun and relatively easy, even for a very young child. Once this is accomplished it is possible to match the sounds to their written forms, an important precursor to learning to read.

Counting represents another fundamental serial learning task for children. It is different from the alphabet in that the sequence of items is not arbitrary. That is, there is no reason “a” has to be the first letter of the alphabet and precede “b”, etc. However, “1” has to be first, and “2”, second, etc. Counting, therefore, requires additional learning in which the numbers are spoken in the presence of the appropriate quantities of different objects. Eventually, the child “abstracts out” the dimension of quantity and the different values. Similar to letters, the sounds are eventually associated with their written forms, an important precursor to learning arithmetic.

Implementation of compulsory education around the turn of the 20th century was an enabling factor for subsequent scientific and technological advances. In order for individuals and for a society to receive the full benefits of compulsory education, it is necessary that children be prepared for the first years of schooling. The richness of their experiences and extensive vocabularies provides many children with the basic knowledge and skills required to excel in pre-school and beyond. Unfortunately, as revealed in Hart and Risley’s (1995) findings, not all children currently receive the level of preparation necessary to immediately acquire the ability to read, write, and perform quantitative operations. Hopefully, parent education and pre-school programs such as Head Start, will reduce the continuing achievement gap between different segments of our population.

The phonetic alphabet, the basis for reading, has served as the major means of recording human knowledge since the time of the Phoenicians. There is certainly much truth to the statement that “reading is fundamental.” Learning to read is an excellent example of the importance of the Gestalt perspective. Reading may be broken down into a sequence of steps establishing larger and larger meaningful units (i.e., gestalts). Eye-movement recordings reveal that individual letters are not initially perceived as units. With increased experience, we are able to integrate the components into a relatively small number of distinct letters, followed by integration of letters into words. Mentioned previously, we perceive the letters of words simultaneously (i.e., as a “gestalt”), not sequentially (Adelman, Marquis, and Sabatos-DeVito, 2010). Eventually, we are able to read aloud fluently by scanning phrases and sentences (Rayner, 1998).

Learning to write requires establishing larger and larger behavioral units through shaping and chaining. As soon as a child is able to grasp a pencil or pen, parents often encourage her/him to “draw.” Once a certain level of proficiency is achieved, it is possible to teach the writing of letters and numbers. This may begin by having the child trace the appropriate signs and then fading them out so that eventually the appropriate symbol can be formed without visual assistance. Eventually fluency of writing letters, followed by words, followed by phrases and complete sentences is achieved. As children advance through the grades, they are assigned tasks requiring more extensive reading and writing.

Learning basic arithmetic is an extension of counting. It is possible to visually differentiate between small numbers of items (e.g., to tell the difference between 3 and 4). This is not possible once a threshold is passed (e.g., trying to see the difference between 10 and 11 items, or 20 and 21, or 120 and 121). It is necessary to accurately apply verbal counting to the actual number of objects in order to perform such tasks. Once a child is able to count objects, it is possible to begin teaching basic mathematics including: addition and subtraction; the base-10 system; multiplication and division; fractions, etc. For an early comprehensive treatment of the application of predictive and control learning principles to reading, writing, and arithmetic, I recommend Staat’s excellent book, Learning, Language, and Cognition (1968). One cannot overstate the fundamental importance of compulsory education to societal development and economic progress. Rindermann and Thompson (2011) conducted sophisticated statistical analyses demonstrating the powerful relationship of cognitive ability, particularly in the STEM fields (science, technology, engineering, and math), to wealth in 90 countries. The top 5% in cognitive ability contribute significantly, often in the form of scientific and technological advances.

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