From drooling dogs, running rats, and pecking pigeons, we have learned much about the basic processes of learning. But conditioning principles don’t tell us the whole story. Today’s learning theorists recognize that learning is the product of the interaction of biological, psychological, and social-cultural influences (FIGURE 7.12).

7-14 How do biological constraints affect classical and operant conditioning?

Ever since Charles Darwin, scientists have assumed that all animals share a common evolutionary history and thus share commonalities in their makeup and functioning. Pavlov and Watson, for example, believed the basic laws of learning were essentially similar in all animals. So it should make little difference whether one studied pigeons or people. Moreover, it seemed that any natural response could be conditioned to any neutral stimulus.

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In 1956, learning researcher Gregory Kimble proclaimed, “Just about any activity of which the organism is capable can be conditioned and … these responses can be conditioned to any stimulus that the organism can perceive” (p. 195). Twenty-five years later, he humbly acknowledged that “half a thousand” scientific reports had proven him wrong (Kimble, 1981). More than the early behaviorists realized, an animal’s capacity for conditioning is constrained by its biology. Each species’ predispositions prepare it to learn the associations that enhance its survival. Environments are not the whole story.

John Garcia was among those who challenged the prevailing idea that all associations can be learned equally well. While researching the effects of radiation on laboratory animals, Garcia and Robert Koelling (1966) noticed that rats began to avoid drinking water from the plastic bottles in radiation chambers. Could classical conditioning be the culprit? Might the rats have linked the plastic-tasting water (a CS) to the sickness (UR) triggered by the radiation (US)?

To test their hunch, Garcia and Koelling exposed the rats to a particular taste, sight, or sound (CS) and later also to radiation or drugs (US) that led to nausea and vomiting (UR). Two startling findings emerged: First, even if sickened as late as several hours after tasting a particular novel flavor, the rats thereafter avoided that flavor. This appeared to violate the notion that for conditioning to occur, the US must immediately follow the CS.

Second, the sickened rats developed aversions to tastes but not to sights or sounds. This contradicted the behaviorists’ idea that any perceivable stimulus could serve as a CS. But it made adaptive sense. For rats, the easiest way to identify tainted food is to taste it; if sickened after sampling a new food, they thereafter avoid it. This response, called taste aversion, makes it difficult to eradicate a population of “bait-shy” rats by poisoning.

Humans, too, seem biologically prepared to learn some associations rather than others. If you become violently ill four hours after eating contaminated mussels, you will probably develop an aversion to the taste of mussels but usually not to the sight of the associated restaurant, its plates, the people you were with, or the music you heard there. (In contrast, birds, which hunt by sight, appear biologically primed to develop aversions to the sight of tainted food [Nicolaus et al., 1983].)

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Garcia’s early findings on taste aversion were met with an onslaught of criticism. As the German philosopher Arthur Schopenhauer (1788–1860) once said, important ideas are first ridiculed, then attacked, and finally taken for granted. Leading journals refused to publish Garcia’s work: The findings are impossible, said some critics. But, as often happens in science, Garcia and Koelling’s taste-aversion research is now basic textbook material.

It is also a good example of experiments that begin with the discomfort of some laboratory animals and end by enhancing the welfare of many others. In one conditioned taste-aversion study, coyotes and wolves were tempted into eating sheep carcasses laced with a sickening poison. Thereafter, they developed an aversion to sheep meat; two wolves later penned with a live sheep seemed actually to fear it (Gustavson et al., 1974, 1976). These studies not only saved the sheep from their predators, but also saved the sheep-shunning coyotes and wolves from angry ranchers and farmers who had wanted to destroy them. Similar applications have prevented baboons from raiding African gardens, raccoons from attacking chickens, ravens and crows from feeding on crane eggs. In all these cases, research helped preserve both the prey and their predators, all of whom occupy an important ecological niche (Dingfelder, 2010; Garcia & Gustavson, 1997).

Such research supports Darwin’s principle that natural selection favors traits that aid survival. Our ancestors who readily learned taste aversions were unlikely to eat the same toxic food again and were more likely to survive and leave descendants. Nausea, like anxiety, pain, and other bad feelings, serves a good purpose. Like a low-oil warning on a car dashboard, each alerts the body to a threat (Neese, 1991).

And remember those Japanese quail that were conditioned to get sexually excited by a red light that signaled a receptive female’s arrival? Michael Domjan and his colleagues (2004) report that such conditioning is even speedier, stronger, and more durable when the CS is ecologically relevant—something similar to stimuli associated with sexual activity in the natural environment, such as the stuffed head of a female quail. In the real world, observes Domjan (2005), conditioned stimuli have a natural association with the unconditioned stimuli they predict.

The tendency to learn behaviors favored by natural selection may help explain why we humans seem naturally disposed to learn associations between the color red and sexuality. Female primates display red when nearing ovulation. In human females, enhanced bloodflow produces the red blush of flirtation and sexual excitation. Does the frequent pairing of red and sex—with Valentine’s hearts, red-light districts, and red lipstick—naturally enhance men’s attraction to women? Experiments (FIGURE 7.13) suggest that, without men’s awareness, it does (Elliot & Niesta, 2008). In follow-up studies,

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A genetic predisposition to associate a CS with a US that follows predictably and immediately is adaptive. Causes often immediately precede effects, so we may associate an effect with the event that preceded it. As we saw in the taste-aversion findings, however, these predispositions can trick us. When chemotherapy triggers nausea and vomiting more than an hour following treatment, cancer patients may over time develop classically conditioned nausea (and sometimes anxiety) to the sights, sounds, and smells associated with the clinic (FIGURE 7.14) (Hall, 1997). Merely returning to the clinic’s waiting room or seeing the nurses can provoke these conditioned feelings (Burish & Carey, 1986; Davey, 1992). Under normal circumstances, such revulsion to sickening stimuli would be adaptive.

As with classical conditioning, nature sets limits on each species’ capacity for operant conditioning. Science fiction writer Robert Heinlein (1907–1988) said it well: “Never try to teach a pig to sing; it wastes your time and annoys the pig.”

We most easily learn and retain behaviors that reflect our biological predispositions. Thus, using food as a reinforcer, you could easily condition a hamster to dig or to rear up, because these are among the animal’s natural food-searching behaviors. But you won’t be so successful if you use food as a reinforcer to shape face washing and other hamster behaviors that aren’t normally associated with food or hunger (Shettleworth, 1973). Similarly, you could easily teach pigeons to flap their wings to avoid being shocked, and to peck to obtain food: Fleeing with their wings and eating with their beaks are natural pigeon behaviors. However, pigeons would have a hard time learning to peck to avoid a shock, or to flap their wings to obtain food (Foree & LoLordo, 1973). The principle: Biological constraints predispose organisms to learn associations that are naturally adaptive.

In their early days of training animals, Marian and Keller Breland presumed that operant principles would work on almost any response an animal could make. But along the way, they too learned about biological constraints. In one act, pigs trained to pick up large wooden “dollars” and deposit them in a piggy bank began to drift back to their natural ways. They dropped the coin, pushed it with their snouts as pigs are prone to do, picked it up again, and then repeated the sequence—delaying their food reinforcer. This instinctive drift occurred as the animals reverted to their biologically predisposed patterns.

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7-15 How do cognitive processes affect classical and operant conditioning?

In their dismissal of “mentalistic” concepts such as consciousness, Pavlov and Watson underestimated the importance of not only biological constraints, but also the effects of cognitive processes (thoughts, perceptions, expectations). The early behaviorists believed that rats’ and dogs’ learned behaviors could be reduced to mindless mechanisms, so there was no need to consider cognition. But Robert Rescorla and Allan Wagner (1972) showed that an animal can learn the predictability of an event. If a shock always is preceded by a tone, and then may also be preceded by a light that accompanies the tone, a rat will react with fear to the tone but not to the light. Although the light is always followed by the shock, it adds no new information; the tone is a better predictor. The more predictable the association, the stronger the conditioned response. It’s as if the animal learns an expectancy, an awareness of how likely it is that the US will occur.

Associations can influence attitudes (Hofmann et al., 2010). When British children viewed novel cartoon characters alongside either ice cream (Yum!) or brussels sprouts (Yuk!), they came to like best the ice-cream-associated characters (Field, 2006). Other researchers have classically conditioned adults’ attitudes, using little-known Pokémon characters (Olson & Fazio, 2001). The participants, playing the role of a security guard monitoring a video screen, viewed a stream of words, images, and Pokémon characters. Their task, they were told, was to respond to one target Pokémon character by pressing a button. Unnoticed by the participants, when two other Pokémon characters appeared on the screen, one was consistently associated with various positive words and images (such as awesome or a hot fudge sundae); the other appeared with negative words and images (such as awful or a cockroach). Later, they evaluated the extra Pokémon characters. Without any conscious memory of the pairings, the participants formed more gut-level liking for the characters associated with the positive stimuli.

Follow-up studies indicate that conditioned likes and dislikes are even stronger when people notice and are aware of the associations they have learned (Shanks, 2010). Cognition matters.

Such experiments help explain why classical conditioning treatments that ignore cognition often have limited success. For example, people receiving therapy for alcohol use disorder may be given alcohol spiked with a nauseating drug. Will they then associate alcohol with sickness? If classical conditioning were merely a matter of “stamping in” stimulus associations, we might hope so, and to some extent this does occur. However, one’s awareness that the nausea is induced by the drug, not the alcohol, often weakens the association between drinking alcohol and feeling sick. So, even in classical conditioning, it is—especially with humans—not simply the CS-US association, but also the thought that counts.

B. F. Skinner acknowledged the biological underpinnings of behavior and the existence of private thought processes. Nevertheless, many psychologists criticized him for discounting cognition’s importance.

A mere eight days before dying of leukemia in 1990, Skinner stood before the American Psychological Association convention. In this final address, he again resisted the growing belief that cognitive processes (thoughts, perceptions, expectations) have a necessary place in the science of psychology and even in our understanding of conditioning. He viewed “cognitive science” as a throwback to early twentieth-century introspectionism. For Skinner, thoughts and emotions were behaviors that follow the same laws as other behaviors.

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Nevertheless, the evidence of cognitive processes cannot be ignored. For example, animals on a fixed-interval reinforcement schedule respond more and more frequently as the time approaches when a response will produce a reinforcer. Although a strict behaviorist would object to talk of “expectations,” the animals behave as if they expected that repeating the response would soon produce the reward.

Evidence of cognitive processes has also come from studying rats in mazes. Rats exploring a maze, given no obvious rewards, seem to develop a cognitive map, a mental representation of the maze. When an experimenter then places food in the maze’s goal box, these rats run the maze as quickly and efficiently as other rats that were previously reinforced with food for this result. Like people sightseeing in a new town, the exploring rats seemingly experienced latent learning during their earlier tours. That learning became apparent only when there was some incentive to demonstrate it. Children, too, may learn from watching a parent but demonstrate the learning only much later, as needed. The point to remember: There is more to learning than associating a response with a consequence; there is also cognition. In Chapter 9 we will encounter more striking evidence of animals’ cognitive abilities in solving problems and in using aspects of language.

The cognitive perspective has also shown us the limits of rewards: Promising people a reward for a task they already enjoy can backfire. Excessive rewards can destroy intrinsic motivation—the desire to perform a behavior effectively and for its own sake. In experiments, children have been promised a payoff for playing with an interesting puzzle or toy. Later, they played with the toy less than unpaid children (Deci et al., 1999; Tang & Hall, 1995). Likewise, rewarding children with toys or candy for reading diminishes the time they spend reading (Marinak & Gambrell, 2008). It is as if they think, “If I have to be bribed into doing this, it must not be worth doing for its own sake.”

To sense the difference between intrinsic motivation and extrinsic motivation (behaving in certain ways to gain external rewards or avoid threatened punishment), think about your experience in this course. Are you feeling pressured to finish this reading before a deadline? Worried about your grade? Eager for the credits that will count toward graduation? If Yes, then you are extrinsically motivated (as, to some extent, almost all students must be). Are you also finding the material interesting? Does learning it make you feel more competent? If there were no grade at stake, might you be curious enough to want to learn the material for its own sake? If Yes, intrinsic motivation also fuels your efforts.

Youth sports coaches who aim to promote enduring interest in an activity, not just to pressure players into winning, should focus on the intrinsic joys of playing and reaching one’s potential (Deci & Ryan, 1985, 2009). Doing so may also ultimately lead to greater rewards. Students who focus on learning (intrinsic reward) often get good grades and graduate (extrinsic rewards). Doctors who focus on healing (intrinsic) may make a good living (extrinsic). Indeed, research suggests that people who focus on their work’s meaning and significance not only do better work but ultimately enjoy more extrinsic rewards (Wrzesniewski et al., 2014). Giving people choices also enhances their intrinsic motivation (Patall et al., 2008).

Nevertheless, extrinsic rewards used to signal a job well done (rather than to bribe or control someone) can be effective (Boggiano et al., 1985). “Most improved player” awards, for example, can boost feelings of competence and increase enjoyment of a sport. Rightly administered, rewards can improve performance and spark creativity (Eisenberger & Aselage, 2009; Henderlong & Lepper, 2002). And the rewards that often follow academic achievement, such as scholarships and jobs, are here to stay.

TABLE 7.5 below compares the biological and cognitive influences on classical and operant conditioning.

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7-16 How does observational learning differ from associative learning? How may observational learning be enabled by mirror neurons?

Cognition is certainly a factor in observational learning, in which higher animals, especially humans, learn without direct experience, by watching and imitating others. A child who sees his sister burn her fingers on a hot stove learns not to touch it. We learn our native languages and various other specific behaviors by observing and imitating others, a process called modeling.

Picture this scene from an experiment by Albert Bandura, the pioneering researcher of observational learning (Bandura et al., 1961): A preschool child works on a drawing. An adult in another part of the room builds with Tinkertoys. As the child watches, the adult gets up and for nearly 10 minutes pounds, kicks, and throws around the room a large inflated Bobo doll, yelling, “Sock him in the nose…. Hit him down…. Kick him.”

The child is then taken to another room filled with appealing toys. Soon the experimenter returns and tells the child she has decided to save these good toys “for the other children.” She takes the now-frustrated child to a third room containing a few toys, including a Bobo doll. Left alone, what does the child do?

Compared with children not exposed to the adult model, those who viewed the model’s actions were more likely to lash out at the doll. Observing the aggressive outburst apparently lowered their inhibitions. But something more was also at work, for the children imitated the very acts they had observed and used the very words they had heard (FIGURE 7.15).

That “something more,” Bandura suggests, was this: By watching a model, we experience vicarious reinforcement or vicarious punishment, and we learn to anticipate a behavior’s consequences in situations like those we are observing. We are especially likely to learn from people we perceive as similar to ourselves, as successful, or as admirable. fMRI scans show that when people observe someone winning a reward (and especially when it’s someone likable and similar to themselves), their own brain reward systems activate, much as if they themselves had won the reward (Mobbs et al., 2009). When we identify with someone, we experience their outcomes vicariously. Even our learned fears may extinguish as we observe another safely navigating the feared situation (Golkar et al., 2013). Lord Chesterfield (1694–1773) had the idea: “We are, in truth, more than half what we are by imitation.”

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On a 1991 hot summer day in Parma, Italy, a lab monkey awaited its researchers’ return from lunch. The researchers had implanted wires next to its motor cortex, in a frontal lobe brain region that enabled the monkey to plan and enact movements. The monitoring device would alert the researchers to activity in that region of the monkey’s brain. When the monkey moved a peanut into its mouth, for example, the device would buzz. That day, as one of the researchers reentered the lab, ice cream cone in hand, the monkey stared at him. As the researcher raised the cone to lick it, the monkey’s monitor buzzed—as if the motionless monkey had itself moved (Blakeslee, 2006; Iacoboni, 2008, 2009).

The same buzzing had been heard earlier, when the monkey watched humans or other monkeys move peanuts to their mouths. The flabbergasted researchers, led by Giacomo Rizzolatti (2002, 2006), had, they believed, stumbled onto a previously unknown type of neuron. These presumed mirror neurons may provide a neural basis for everyday imitation and observational learning. When a monkey grasps, holds, or tears something, these neurons fire. And they likewise fire when the monkey observes another doing so. When one monkey sees, its neurons mirror what another monkey does. (For a debate regarding the importance of mirror neurons, which are sometimes overblown in the popular press, see Gallese et al., 2011; Hickok, 2014.)

Imitation is widespread in other species. In one experiment, a monkey watching another selecting certain pictures to gain treats learned to imitate the order of choices (FIGURE 7.16 below). In other research, rhesus macaque monkeys rarely made up quickly after a fight—unless they grew up with forgiving older macaques. Then, more often than not, their fights, too, were quickly followed by reconciliation (de Waal & Johanowicz, 1993). Rats, pigeons, crows, and gorillas all observe others and learn (Byrne et al., 2011; Dugatkin, 2002).

As we will see in Chapter 9, chimpanzees observe and imitate all sorts of novel foraging and tool use behaviors, which are then transmitted from generation to generation within their local culture (Hopper et al., 2008; Whiten et al., 2007). In one 27-year analysis of 73,790 humpback whale observations, a single whale in 1980 whacked the water to drive prey fish into a clump. In the years since, this “lobtail” technique spread among other whales (Allen et al., 2013). Humpback see, humpback do.

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So, too, with monkeys. Erica van de Waal and her co-researchers (2013) trained groups of vervet monkeys to prefer either blue or pink corn by soaking one color in a disgusting-tasting solution. Four to six months later, after a new generation of monkeys was born, the adults stuck with whatever color they had learned to prefer—and, on observing them, so did all but one of 27 infant monkeys. Moreover, when blue- (or pink-) preferring males migrated to the other group, they switched preferences and began eating as the other group did. Monkey see, monkey do.

In humans, imitation is pervasive. Our catchphrases, fashions, ceremonies, foods, traditions, morals, and fads all spread by one person copying another. Imitation shapes even very young humans’ behavior (Bates & Byrne, 2010). Shortly after birth, babies may imitate adults who stick out their tongue. By 8 to 16 months, infants imitate various novel gestures (Jones, 2007). By age 12 months (FIGURE 7.17), they look where an adult is looking (Meltzoff et al., 2009). And by age 14 months, children imitate acts modeled on TV (Meltzoff, 1988; Meltzoff & Moore, 1989, 1997). Even as 2½-year-olds, when many of their mental abilities are near those of adult chimpanzees, young humans surpass chimps at social tasks such as imitating another’s solution to a problem (Herrmann et al., 2007). Children see, children do.

So strong is the human predisposition to learn from watching adults that 2- to 5-year-old children overimitate. Whether living in urban Australia or rural Africa, they copy even irrelevant adult actions. Before reaching for a toy in a plastic jar, they will first stroke the jar with a feather if that’s what they have observed (Lyons et al., 2007). Or, imitating an adult, they will wave a stick over a box and then use the stick to push on a knob that opens the box—when all they needed to do to open the box was to push on the knob (Nielsen & Tomaselli, 2010).

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Humans, like monkeys, have brains that support empathy and imitation. Researchers cannot insert experimental electrodes in human brains, but they can use fMRI scans to see brain activity associated with performing and with observing actions. So, is the human capacity to simulate another’s action and to share in another’s experience due to specialized mirror neurons? Or is it due to distributed brain networks? That issue is currently being debated (Gallese et al. 2011; Iacoboni, 2008, 2009; Mukamel et al., 2010; Spaulding, 2013). Regardless, children’s brains do enable their empathy and their ability to infer another’s mental state, an ability known as theory of mind.

The brain’s response to observing others makes emotions contagious. Through its neurological echo, our brain simulates and vicariously experiences what we observe. So real are these mental instant replays that we may misremember an action we have observed as an action we have performed (Lindner et al., 2010). But through these reenactments, we grasp others’ states of mind. Observing others’ postures, faces, voices, and writing styles, we unconsciously synchronize our own to theirs—which helps us feel what they are feeling (Bernieri et al., 1994; Ireland & Pennebaker, 2010). We find ourselves yawning when they yawn, laughing when they laugh.

When observing movie characters smoking, smokers’ brains spontaneously simulate smoking, which helps explain their cravings (Wagner et al., 2011). Seeing a loved one’s pain, our faces mirror the other’s emotion. But as FIGURE 7.18 shows, so do our brains. In this fMRI scan, the pain imagined by an empathic romantic partner has triggered some of the same brain activity experienced by the loved one actually having the pain (Singer et al., 2004). Even fiction reading may trigger such activity, as we mentally simulate (and vicariously experience) the experiences described (Mar & Oatley, 2008; Speer et al., 2009). In one experiment, university students read (and vicariously experienced) a fictional fellow student’s description of overcoming obstacles to vote. A week later, those who read the first-person account were more likely to vote in a presidential primary election (Kaufman & Libby, 2012).

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So the big news from Bandura’s studies and the mirror-neuron research is that we look, we mentally imitate, and we learn. Models—in our family or neighborhood, or on TV—may have effects, good and bad.

Prosocial Effects

7-17 What is the impact of prosocial modeling and of antisocial modeling?

The good news is that prosocial (positive, helpful) models can have prosocial effects. Many business organizations effectively use behavior modeling to help new employees learn communications, sales, and customer service skills (Taylor et al., 2005). Trainees gain these skills faster when they are able to observe the skills being modeled effectively by experienced workers (or actors simulating them).

People who exemplify nonviolent, helpful behavior can also prompt similar behavior in others. India’s Mahatma Gandhi and America’s Martin Luther King, Jr. both drew on the power of modeling, making nonviolent action a powerful force for social change in both countries. The media offer models. One research team found that across seven countries, viewing prosocial media boosted later helping behavior (Prot et al., 2013).

Parents are also powerful models. European Christians who risked their lives to rescue Jews from the Nazis usually had a close relationship with at least one parent who modeled a strong moral or humanitarian concern; this was also true for U.S. civil rights activists in the 1960s (London, 1970; Oliner & Oliner, 1988). The observational learning of morality begins early. Socially responsive toddlers who readily imitate their parents tend to become preschoolers with a strong internalized conscience (Forman et al., 2004).

Models are most effective when their actions and words are consistent. Sometimes, however, models say one thing and do another. To encourage children to read, read to them and surround them with books and people who read. To increase the odds that your children will practice your religion, worship and attend religious activities with them. Many parents seem to operate according to the principle “Do as I say, not as I do.” Experiments suggest that children learn to do both (Rice & Grusec, 1975; Rushton, 1975). Exposed to a hypocrite, they tend to imitate the hypocrisy—by doing what the model did and saying what the model said.

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Antisocial Effects The bad news is that observational learning may have antisocial effects. This helps us understand why abusive parents might have aggressive children, and why many men who beat their wives had wife-battering fathers (Stith et al., 2000). Critics note that aggressiveness could be genetic. But with monkeys, we know it can be environmental. In study after study, young monkeys separated from their mothers and subjected to high levels of aggression grew up to be aggressive themselves (Chamove, 1980). The lessons we learn as children are not easily replaced as adults, and they are sometimes visited on future generations.

TV shows and Internet videos are powerful sources of observational learning. While watching TV and videos, children may “learn” that bullying is an effective way to control others, that free and easy sex brings pleasure without later misery or disease, or that men should be tough and women gentle. And they have ample time to learn such lessons. During their first 18 years, most children in developed countries spend more time watching TV than they spend in school. The average teen watches more than 4 hours a day; the average adult, 3 hours (Robinson & Martin, 2009; Strasburger et al., 2010).

TV viewers are learning about life from a rather peculiar storyteller, one that reflects the culture’s mythology but not its reality. Between 1998 and 2006, prime-time violence reportedly increased 75 percent (PTC, 2007). If we include cable programming and video rentals, the violence numbers escalate. An analysis of more than 3000 network and cable programs aired during one closely studied year revealed that nearly 6 in 10 featured violence, that 74 percent of the violence went unpunished, that 58 percent did not show the victims’ pain, that nearly half the incidents involved “justified” violence, and that nearly half involved an attractive perpetrator. These conditions define the recipe for the violence-viewing effect described in many studies (Donnerstein, 1998, 2011). To read more about this effect, see Thinking Critically About: Does Viewing Media Violence Trigger Violent Behavior? below.

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***

Our knowledge of learning principles comes from the work of hundreds of investigators. This chapter has focused on the ideas of a few pioneers—Ivan Pavlov, John Watson, B. F. Skinner, and Albert Bandura. They illustrate the impact that can result from single-minded devotion to a few well-defined problems and ideas. These researchers defined the issues and impressed on us the importance of learning. As their legacy demonstrates, intellectual history is often made by people who risk going to extremes in pushing ideas to their limits (Simonton, 2000).

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7-14 How do biological constraints affect classical and operant conditioning?

7-15 How do cognitive processes affect classical and operant conditioning?

7-16 How does observational learning differ from associative learning? How may observational learning be enabled by mirror neurons?

7-17 What is the impact of prosocial modeling and of antisocial modeling?

TERMS AND CONCEPTS TO REMEMBER

RETRIEVAL PRACTICE Match each of the terms on the left with its definition on the right. Click on the term first and then click on the matching definition. As you match them correctly they will move to the bottom of the activity.

Test yourself repeatedly throughout your studies. This will not only help you figure out what you know and don’t know; the testing itself will help you learn and remember the information more effectively thanks to the testing effect.

Basic Learning Concepts and Classical Conditioning

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Operant Conditioning

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Biology, Cognition, and Learning

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