What Sticks
The Science of Remembering What You Learn
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- Educational Psychology
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The book examines operant conditioning principles applied to education, including how rewards and punishments affect learning outcomes. It discusses the "make believe" approach to memory formation and presents evidence from research on Rex Briggs's work with children's learning patterns. Each chapter builds on previous findings about how people actually remember what they learn.
This practical guide explains why traditional study methods often fail while evidence-based techniques succeed. Readers will discover that learning styles don't matter, but retrieval practice does. Anyone who wants to improve their own learning or help others learn better will find this worth their time.
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Overview
The testing effect, also called retrieval practice, active recall, or test-enhanced learning, shows that remembering information from memory during study improves long-term retention. It’s not the same as the general practice effect, which is any improvement from repeating tasks. Cognitive psychologists are working with teachers to use tests less for grading and more for learning. Doing so helps students remember better than just reading or studying passively. Testing what you already know, especially when it's challenging, strengthens memory more effectively than other methods.
History
The idea that testing helps learning isn’t new. Francis Bacon noted it in 1620, saying it's better to read something ten times while trying to recall it than twenty times without effort. Later, John Locke wrote in 1689 that ideas refreshed often stay clearer in memory. In 1890, William James emphasized that active repetition—trying to remember rather than re-reading—leads to stronger learning. The first formal studies came in 1909 by Edwina E. Abbott, followed by more research. C. A. Mace wrote in 1932 that recalling information without looking at the text works far better than passive reading. Then in 1987, John L. Richards began studying retrieval practice, and since then, researchers like Hal Pashler and Henry Roediger have confirmed that testing produces better learning and retention than methods like re-reading or highlighting.
Retrieval practice
Retrieval practice boosts long-term memory more than simply restudying, with research showing that how well you can recall something improves over time, not just right after learning. Studies using brain scans indicate that testing strengthens memory by affecting both front and back parts of the hippocampus. This effect appears to help everyone equally, regardless of personality or working memory capacity, and may be especially helpful for those who struggle more with learning. Though some question whether testing helps transfer knowledge across subjects, evidence supports that applying theory to real situations—like in medical diagnosis—leads to stronger learning and retention, even for material not directly tested. Retrieval practice also reveals misconceptions and reduces forgetting compared to restudying, with benefits lasting years.
Repeated testing
Repeated testing produces stronger results than re-reading material, likely because it builds multiple pathways for recalling information, helping you make lasting connections and better organize what you learn. Spaced repetition enhances this effect, especially when there's a delay between studying and testing—though that gap might also lead to some forgetting or retrieval-induced forgetting. For example, if you study in the morning, test yourself in the evening; but if you study in the evening, test immediately, since sleep plays a role in memory consolidation. Surprisingly, divided attention doesn’t hurt the testing effect if it comes from a different source, and the speed of learning doesn't determine how quickly you forget—only the kind of practice you use matters.
Test difficulty
When you try to recall information, the effort you put in affects how well you remember it. Successful but challenging retrieval leads to stronger memory than easy recall, which is why finding the right level of difficulty matters. Studies show that learning a language improves when unfamiliar words are used instead of familiar ones, proving that harder material results in better retention. The more difficult it is to remember something, the more likely you are to keep it. This effort also supports deeper processing at the time of learning. Even failing to retrieve information can help if it prompts you to form the thought, thanks to the generation effect. Feedback increases learning, but combining it with appropriately challenging tests—like in the Read, Recite, Review method—boosts retention more than studying or testing alone.
Test format
The way you test yourself matters less than retrieving information, which strengthens learning. Transfer-appropriate processing shows matching study format with testing boosts results, though mismatched formats lead to lower performance. Still, short-answer and essay tests produce greater gains than multiple-choice ones. Cued recall helps short-term retrieval by lowering effort, but over time hurts long-term memory because retrieval isn't as demanding. While quick learning reduces forgetting temporarily, more effortful retrieval leads to longer-lasting results. Cueing happens when new material connects to prior knowledge or when visual/audio aids support recall. Prior knowledge enhances retrieval practice benefits, but people with both high and low prior knowledge benefit from it. Pre-testing improves outcomes, and post-testing helps solidify newly learned material, known as the forward testing effect. Importantly, pre-test performance doesn't predict later performance—time plays a role in forgetting.
Pre-testing effect
Pre-testing, also called errorful generation or pre-questioning, is a learning strategy where you test yourself on material before actually learning it, and then get feedback afterward. This method has been shown to improve learning in both lab and classroom settings. It's especially helpful in language learning, science classes, and with lower-ability students in Chemistry. Pre-testing can also be useful at the start of a lecture series and helps reduce mind-wandering. While some studies suggest it’s not quite as effective as post-testing overall, others show it’s just as good. The effect seems more focused on the specific material being learned rather than general curiosity. It works across different ages and subjects but is better suited for concrete information like facts and concepts. You can use it with reading, videos, or live lectures.
Practice methods
Retrieval practice works better than concept mapping alone, even though students don’t always see it as helpful. When used together, they improve learning, showing that concept mapping can support retrieval practice and other non-verbal techniques. Multimedia testing with flashcards helps, but taking cards away too soon hurts long-term memory. People sometimes misjudge how well their practice is going, which leads them to remove cards prematurely and forget more later. Experts recommend distributed retrieval practice with feedback for students, care unit residents, and teachers. Interleaved practice, self-explanation, and elaborative interrogation may help, but need more study. Summarization is useful if people know how to use it properly. Keyword mnemonics and imagery offer limited benefit, often fading quickly. But when these methods include retrieval elements, the testing effect becomes more likely to happen.
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Overview
Study skills are ways of learning that help you take in, keep, and use new information, whether you're preparing for a test or just trying to understand something better. These techniques can be learned quickly and applied across most subjects. They include things like mnemonics to remember lists, reading strategies, staying focused, and taking notes efficiently. Study skills are different from subject-specific methods, like those used in music or technology, or from personal traits like natural intelligence or personality. Before trying new approaches, it helps to understand how you usually study, so you can recognize what might be holding you back.
Historical context
Study skills have always been important for school success and lifelong learning, though they’re often left up to students and their families to figure out. These skills are now more commonly taught in high schools and universities. The term covers general learning approaches as well as subject-specific techniques. Manuals for students have been around since the 1940s. In the 1950s and 1960s, college instructors in psychology and education wrote guides based on their research and experience. Marvin Cohn drew from his work as a university reading clinic director when he wrote Helping Your Teen-Age Student in 1978. In 1986, Dr. Gary Gruber published The Essential Guide to Test Taking for Kids, a two-volume set aimed at elementary and middle school students, which included strategies for tests and schoolwork.
Rehearsal and rote learning
Memorization means learning something by repeating it, often without fully understanding it, and it’s one of the most basic ways to store information in your memory. You might read through notes or a textbook, or rewrite them, to help yourself remember facts, names, lists, stories, poems, music, or even pictures and maps. This kind of learning is sometimes called rote learning, and while it can be useful, it doesn’t always encourage deep thinking. Educators like John Dewey have argued that students should also learn how to question and evaluate what they’re studying, whether in a lecture or while reading a book.
Reading and listening
When you first engage with material, try the REAP method: Read to grasp the idea, Encode by restating it in your own words from the author's perspective, Annotate with critical notes and insights, and Ponder by reflecting, discussing, or exploring related content. This deepens understanding and builds on what you already know. Another approach is PQRST—Preview the topic, Formulate questions, Read to answer them, Write a Summary using diagrams or mnemonics, and Test yourself without adding distractions. Research shows that students who self-test perform better on exams than those who just re-read. Peer study groups also boost performance, with one survey showing a 73% average score increase among participants. Creating personal memory cues—like phrases or songs—helps recall more than using others' cues. And while speed reading can be trained, it often leads to lower comprehension. Studies from 2006 found that students who tested themselves retained information longer and better than those who only reviewed their notes. Even taking notes on a computer can hurt learning if you just transcribe lectures word for word instead of processing ideas in your own terms.
Flashcards
Flashcards are visual tools made from cards that help with learning and revision. Students often make their own, or use index cards—usually A5 size—with short summaries written on them. Because each card is separate, they can be reordered, picked through randomly, or used for self-testing. Software versions of flashcards are also available to help with studying.
Summary methods
Summary methods help you take large amounts of information and distill them into smaller, more manageable notes. These can be organized outlines with keywords, definitions, and relationships laid out in a tree structure. Another popular approach is using spider diagrams or mind maps, which visually connect ideas and show how they relate to one another. These tools are especially helpful when planning essays or answering exam questions. They keep the logical flow of a topic clear while making it easier to review and remember key points.
Visual imagery
Visual memory can help you learn better, and one well-known method is called the method of loci. That’s where you picture information in specific places, like around a room. Drawing diagrams is another useful tool, even though many don’t realize how powerful they are. They help bring everything together and let you practice reorganizing what you’ve studied into something practical. If you make the diagram while learning, it helps you remember faster. You can also turn those pictures into flashcards, which work great for last-minute review instead of re-reading text.
Examination strategies
When it comes to exams and essays, students can use the Black-Red-Green method, a technique developed through the Royal Literary Fund, to make sure they cover every part of a question. They underline the question in three colors: black for clear instructions that must be followed, red for key terms, definitions, or references like cited authors or theories, and green for subtle clues or hints that point toward how to approach the answer or where to focus emphasis. Another helpful strategy is the PEE method—Point, Evidence, and Explain—which breaks down exam questions so students can give strong responses and score higher. Some schools also promote practicing the P.E. BEing method before tests.
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Overview
Active learning means students aren't just sitting and listening—they're doing something like working in groups or role-playing, and that involvement makes a difference. Bonwell and Eison from 1991 describe it as a method where students participate by doing more than passively hearing information. Research shows that when teachers use active techniques, students do better academically. Hanson and Moser in 2003 found this to be true. Scheyvens, Griffin, Jocoy, Liu, and Bradford in 2008 added that these methods help students become more interested and motivated while building skills like critical thinking and problem-solving. According to a report from the Association for the Study of Higher Education, students need to read, write, talk, and solve problems to really learn. This process connects to what's called the knowledge, skills, and attitudes (KSA) framework, which outlines learning goals. Students must engage in higher-order thinking tasks such as analysis, synthesis, and evaluation.
Teacher's characteristics in active learning
In a study by Jerome I. Rotgans and Henk G. Schmidt, researchers found that three teacher traits boost students' situational interest in active learning. That kind of interest, according to Hidi and Renninger, is "focused attention and an affective reaction that is triggered in the moment by environmental stimuli." The first trait is social congruence—when teachers interact harmoniously with students, it encourages participation and open questions. Subject-matter expertise matters too; when teachers know their field well, students are more motivated and learning becomes more effective. Lastly, cognitive congruence means simplifying complex ideas so students can follow along, ask questions, and build confidence in their own thinking.
Ensuring that all students are actively learning
When teachers want all students to stay engaged, they can use two key strategies. The first is asking higher-order questions, which push students beyond simple recall and help them connect ideas to real life, making learning stick. In contrast, lower-order questions only ask for facts or predictions, offering little room for deep thinking or lasting memory. The second method is called "The Ripple." It gives every student time to think on their own, then share with others, and finally contribute to a class discussion. This approach ensures that even quieter students get a chance to participate, something traditional methods often miss.
Science of active learning
Active learning works because it taps into how the brain actually learns, and scientists have studied this for years. Thousands of studies, like one by Smith and Kosslyn in 2011, show that certain principles help people remember better. These ideas can guide teachers in creating lessons that stick. When these methods are used well, as Stephen Kosslyn noted in 2017, students can end up learning effectively—sometimes without even trying to learn.
The principles of learning
Learning and memory research has led to a set of principles that help us understand how we absorb and keep information. One way to organize this knowledge involves 16 specific ideas grouped under two main goals. The first goal, “Think it Through,” includes strategies for focusing attention and deeply processing new material. The second goal, “Make and Use Associations,” centers on methods for organizing and recalling information. These principles offer a framework for effective studying and long-term retention.
Maxim I: Think it through
When you want to really learn something, you've got to think it through—don't just read or listen passively. Research shows that learning gets stronger when you connect new ideas to what you already know and dig deeper than surface-level understanding. That means making things challenging enough to push your brain, but not so hard it gives up. One way to do this is by actively recalling information instead of just re-reading it, which improves memory through something called the generation effect. You also benefit from deliberate practice—focusing on mistakes and repeating efforts with purpose. Mixing up different kinds of problems or tasks while studying helps too, a method known as interleaving. Presenting ideas both visually and verbally, called dual coding, can boost comprehension. And let's not forget that emotionally engaging content sticks better than neutral material.
Effective strategies in large classes
In large university classes with over 200 students, keeping everyone engaged can be tough. Some students may struggle academically, think less critically, and become less active in learning. Professors often find their feedback gets lost in the crowd. But there are ways to help. One strategy is using software that lets students participate without revealing their identities, easing discomfort. Another is the “one minute paper,” where students write answers to a question related to what was taught, within 60 seconds. The “think-pair-share” method also works well, guiding students through three steps: first, individual thinking; then sharing with a peer; and finally, discussing as a whole class.
Research evidence
Active learning produces measurable improvements in student performance, with research showing students learn significantly more when engaged in interactive instruction than in traditional lectures. A meta-analysis of 225 studies found that active learning reduced failure rates from 32% to 21% and boosted assessment scores by 0.47 standard deviations. Richard Hake's review of 62 introductory physics courses showed students using active learning techniques improved 25 percentage points on the Force Concept Inventory, while another study found gains of 38 percentage points when switching from lecture to active methods. Prince's 2004 review confirmed broad support for active learning in engineering education, and Michael's 2006 study highlighted its growing validation in physiology teaching. A 2012 report by the U.S. President's Council of Advisors on Science and Technology emphasized that active learning increases retention and performance, particularly in STEM fields. Studies also show benefits for international students, who often prefer active learning and may benefit more from it. Research indicates that active learning can reduce faculty-student contact by two-thirds while maintaining or improving outcomes, and that students' perceptions of their learning improve as well. A 2019 study noted that students initially misjudge active learning's effectiveness, but this bias can be corrected with early preparation and consistent communication. In a 2021 study, students taught by an active-learning instructor outperformed those in traditional classes, even though the active-learning instructor was new to teaching.
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Overview
In 1970, psychologist Walter Mischel at Stanford University ran a study on delayed gratification using the Stanford marshmallow experiment. Children were given a choice between one small reward immediately or two small rewards if they waited. A researcher left a child alone with a marshmallow for about fifteen minutes. Follow-up studies showed that kids who waited longer tended to do better in life, including higher SAT scores and lower BMI. But a later replication with a much larger and more diverse group found only half the original effect, suggesting economic background, not willpower, played a role. In 2020, research questioned whether the marshmallow test reliably predicts adult outcomes.
Original Stanford experiment
In 1970, Walter Mischel and Ebbe B. Ebbesen ran a delayed gratification experiment at Stanford University to see when kids learn to wait for bigger rewards. They gave children a choice between one treat—either two animal cookies or five pretzel sticks—and told them that if they waited 15 minutes without eating it, they’d get a second treat. Some kids tried to distract themselves, covering their eyes or singing to themselves, and even falling asleep while waiting. The researchers were testing whether making the reward more noticeable would help children wait longer.
Participants
Thirty-two children took part in the Stanford marshmallow experiment, evenly split between sixteen boys and sixteen girls. They came from the Bing Nursery School at Stanford University and were between three years six months and five years eight months old, with the average age being four years and six months. During the study, three children didn’t make it through the initial trials because they couldn’t understand what was being asked of them.
Detailed procedure
Two experimenters conducted the test in a room where a table held an opaque cake tin containing five pretzels and two animal cookies. A child sat in front of the table with a chair beside it, on which rested an empty cardboard box. On the floor near that chair were four battery-operated toys. Before the child could play, the experimenter pointed them out and briefly demonstrated each one, explaining they would return to play later. Each toy was then placed inside the box and hidden from view. The experimenter told the child he had to leave the room; if the child ate a pretzel while waiting, the experimenter would come back. This process was repeated four times until the child clearly understood. Then the experimenter exited and waited for the child to eat a pretzel. When returning, the experimenter opened the cake tin to reveal two sets of rewards — five pretzels and two animal crackers — and asked the child which they preferred. If the child chose to wait, they could receive the more preferred reward after the experimenter returned or stop waiting and take the less preferred one instead. Depending on the choice, the experimenter brought back either nothing, one reward, or both. He returned either immediately upon signal or after 15 minutes.
Results
The results of the Stanford marshmallow experiment turned out completely differently than anyone expected. Researchers had thought that showing children rewards would help them focus on waiting for a better reward later. But instead, the very presence of the rewards made kids more frustrated and less able to wait. It seemed the act of focusing on the treat actually hurt their ability to delay gratification. The findings suggested that not thinking about the reward—rather than fixating on it—actually helped children resist temptation.
Purpose
In 1972, Mischel, Ebbesen, and Zeiss conducted a study that became known as the Stanford marshmallow experiment, using marshmallows as a reward to test self-control in children. Building on earlier research, they hypothesized that distracting participants from the anticipated reward would help them wait longer. They tested three settings: overt activity, covert activity, or no activity at all. The researchers expected delay of gratification to increase under the first two conditions and decrease when there was no activity. To make sure kids understood what was asked of them, they were given three comprehension questions. Three separate experiments were carried out under different conditions.
Participants
The study included 50 children, evenly split between boys and girls, all from the Bing Nursery School at Stanford University. Their ages ranged from three years six months to five years six months, with a median age of four years six months. Six of the participants were removed from the results because they didn’t understand the experiment’s instructions. One of the children in the study was Whitney Tilson, who went on to become a hedge fund manager, philanthropist, author, and Democratic political activist.
Procedures
The procedures were carried out by a male and a female experimenter, with the male working with three boys and two girls, while the female worked with three girls and two boys. The testing took place in a small room containing a table with a barrier between child and experimenter. Behind the barrier sat a slinky toy, a cake tin holding a marshmallow and a pretzel stick. Next to that table was another one with battery- and hand-operated toys visible to the child. Against one wall were a chair, a desk bell, and another table. In Experiment 1, children were tested under five conditions: waiting for a delayed reward with an external distractor, waiting with an internal distractor, waiting without any distractor, just an external distractor without delay, or just an internal distractor without delay.
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Overview
Recall is how your mind brings back information you've learned before, and it's one of the three main processes of memory, along with encoding and storage. There are three main kinds of recall: free recall, where you retrieve information on your own; cued recall, where a hint helps you remember; and serial recall, which involves remembering items in a specific order. Scientists study these types by testing humans and animals to better understand how memory works. Two major theories try to explain how recall happens: the two-stage theory and the theory of encoding specificity.
Two-stage theory
The two-stage theory explains how we bring information back from memory. First comes a search and retrieval process, where the brain looks for stored details. Then, a second stage involves recognizing or choosing the correct information from what was retrieved. Recognition relies only on that final decision step, which is why it's often seen as easier than recall. Recall, however, uses both stages and can actually outperform recognition in some situations—like when someone fails to recognize a word but later recalls it. Another version of this theory says that when we try to freely remember a list, we start with what’s in working memory and then search associations to retrieve the rest.
Encoding specificity
The theory of encoding specificity explains how memory works by linking what we learn with the environment we're in when we remember it. It says that recall is better when the conditions during learning match those during retrieval. For instance, if you study in one place and take an exam somewhere else, your recall suffers because the context doesn’t align. This principle shows why context cues matter so much—because memory relies on both the information stored and the situation in which it's retrieved. It also helps explain that recognition doesn't always beat recall, since both depend heavily on matching circumstances.
History
The study of memory and learning began with philosophical questions about knowledge acquisition, and recall reflects that history. In 1885, Hermann Ebbinghaus used nonsense syllables to test his own recall, discovering rapid initial memory loss followed by slower decline, and showing that repeated learning and spaced study improve retention. British psychologist Frederic Bartlett studied how people recall stories, notably using North American Native folk tales like The War of the Ghosts, finding that recall was shaped by current knowledge, which he called "schematic intrusions." In the 1950s, the cognitive revolution redefined memory as an information-processing system, with key works like Plans and Structures of Behavior and Cognitive Psychology. Lloyd and Margaret Peterson studied short-term memory loss, and Atkinson and Shiffrin later developed a model for it. Endel Tulving introduced episodic and semantic memory and the encoding specificity principle in 1983. Allan Paivio's research in the 1960s showed that vivid words are better recalled. Since the 1980s, this field has continued to grow and evolve.
Free recall
When you try to remember a list of items, free recall lets you pull them back out in any order you choose. Often, people tend to remember the first few items better than the middle ones — that’s called the primacy effect. They also often recall the last items more easily — the recency effect. But here's what's interesting: when someone starts trying to remember a long list, they usually begin with the end and work their way back toward the beginning and middle. That pattern shows up again and again in how our minds organize and retrieve information.
Cued recall
Cued recall tests memory by giving people word pairs to study, then presenting one word as a cue to recall its partner. In the study-test method, participants see pairs and are later asked to recall the second word after being given the first. The anticipation method has participants try to guess the paired word before seeing it. Researcher Irvin Rock and Walter Heimer tested whether learning happens gradually or all at once using repeated word pairs, finding little difference between groups, though their experiment had some limitations. Other studies have shown forward recall—like recalling B when given A—is generally easier than backward recall. Experiments by S.E. Asch and S.M. Ebenholtz found that backward associations were weaker unless the recall strength was similar for both directions. A 1992 study by Mark Carrier and Harold Pashler showed that testing during learning, rather than just restudying, leads to better long-term recall, a finding known as the testing effect.
Serial recall
Serial recall is your ability to remember things in order, like sentence words or daily events, helping with language and autobiographical memory, not unique to humans—non-human primates and some other animals show it too. In long-term memory, you store sequences by repeating until they become whole units, but in short-term memory, immediate serial recall happens differently. Some research points to item-position associations or chaining, though the latter seems unlikely. A more accepted idea is that activation levels across positions explain recall, and that similar items hurt performance. Alan Baddeley found lists of same category are easier to remember than mixed ones. Rhythm and motor activity affect recall, with finger tapping disrupting memory more than background sounds. Eight key patterns emerge: list length affects recall, early and recent items remembered better, transposition errors happen more often for meaning than order, repetition errors rare, fill-in effects occur when errors shift later items, protrusion effects bring old items into new lists, and shorter words recalled more accurately.
Neuroanatomy
When we recall information, several brain parts light up more than during recognition, including the anterior cingulate cortex, globus pallidus, thalamus, and cerebellum. Neuroimaging studies have found six regions consistently show increased activity during recall: the right prefrontal cortex, hippocampal and parahippocampal areas, anterior cingulate cortex, posterior midline region including posterior cingulate and precuneus, inferior parietal cortex, and left cerebellum. While their exact roles are still being studied, the right prefrontal cortex seems linked to retrieving memories, medial temporal lobes to conscious recollection, anterior cingulate to choosing responses, posterior midline region to mental imagery, inferior parietal to spatial awareness, and cerebellum to initiating recall. Research by Fernandez et al. found that brain activity patterns—specifically a negative deflection in the rhinal cortex and positive signal from the hippocampus—occur milliseconds before we actually recall something, suggesting recall only happens when these two regions activate together.
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Overview
Make believe, or pretend play, is a kind of loose, creative activity involving role-playing, using objects in new ways, and behaving without taking things literally. Unlike everyday tasks focused on survival, pretend play helps children work through fears and desires in safe space while strengthening existing learning. Research shows kids good at make believe tend to be better at understanding others, solving problems, and connecting socially. For it to count as pretend play, children must know they're not really doing what they're acting out - if they think it's real, then it's misunderstanding rather than pretending. Whether or not children act out fantasies depends on whether they choose to bring imagination into the moment.
History
Pretend play has been part of human experience since early times, something kids do naturally without needing a name for it. In the 1920s and 1930s, interest in play grew, though research at the time offered little evidence about make-believe itself. That changed in the late 1940s, when researchers began focusing on how pretend play connected to a child’s personality. One idea was that role-playing showed inner feelings and daily experiences. By the 1970s, the third stage had begun, shaped strongly by Jean Piaget's theories, with studies either supporting or challenging his work. Though cultural terms may vary, the roots of imaginative play might go back to the very start of human consciousness.
Critical period
Pretending is something humans seem to do naturally, starting around 18 to 24 months old, according to Lillard, Pinkham & Smith (2011). By the time kids are between one and a half and two and a half years old, pretend play becomes more frequent. At first, it begins with simple object substitution, like using a block as a phone. By age three, children understand the difference between real life and pretend. Around four to five, they start playing roles beyond just being a child—like pretending to be a doctor or a parent. Their play becomes more complex, involving different social relationships and roles from everyday life.
Role-play
When kids engage in role-play, they're acting out the identity or traits of someone else, whether that's a person they know or a character from their imagination. This kind of play, called sociodramatic play, starts around age three and often comes earlier for children with older siblings. At first, it's very structured, following set roles and scripts, with kids playing alongside each other rather than together. By age five, they begin to add more creativity, building on each other's ideas instead of sticking to strict patterns. There are three types of role-play: relational, which reflects relationships like mother and child; functional, focusing on jobs or actions; and character-based, showing how society sees certain roles. Pretend play helps all children develop important skills, no matter their economic background, because it only requires imagination. Around age five, kids also start to understand another person's point of view through role-play, which strengthens their ability to cooperate and connect with others.
Nonliteral actions
Pretend play involves five key behaviors that show it’s not real. First, kids do tasks without the right tools—like making a call without a phone. Second, they substitute one object for another, such as using a block as a telephone. Third, they take on roles, pretending to be someone else like a firefighter putting out a fire. Fourth, actions lead to impossible results, like cleaning a room by snapping a finger. Fifth, children give inanimate objects human traits, such as talking or drinking tea. All of this happens within a pretend world that’s separate from reality. When play ends, those imaginary rules stop too. One common form of pretend play is having an imaginary companion, which many young children experience, though the reason behind it isn’t fully known.
Substitution
Around age two, children begin to understand substitution, when one object stands in for another during pretend play. At first, they can only swap objects that look or work similarly—like using a pen as a toothbrush because they have similar shape, or a remote control as a telephone because buttons function comparably. By age three, kids start mastering this skill without needing physical similarities. They begin substituting using just imagination, like pretending their palm is a phone. The ability to hold multiple substitutions at once also grows, so a child might simultaneously pretend to be on the phone, walking a dog, and drinking juice. There are two kinds of substitution: symbolic, where one object represents another—such as sticks used by a coach to stand in for players—and hypothetical, where an object is treated "as-if" it actually is something else, like imagining a pen works like a toothbrush.
Doll play
Pretend play with dolls starts when a child begins acting out self-actions on a doll. At first, a child might feed themselves, then extend that behavior to a doll. As the play develops, the child gives the doll a more active role—like having it reach for a spoon and feed itself. Eventually, the child adds emotional and sensory traits, making the doll feel happy, sad, or hurt. By around three and a half years old, children can give their dolls thinking abilities too. One key difference between doll play and social play is that in doll play, the child controls everything.
Influencing factors
Pretend play shows up across nearly all cultures, but attitudes toward it vary widely. Some cultures see it as inappropriate, even linking it to communication with spirits or devils. These views affect how much time kids get to play imaginatively and what themes they explore. Still, pretend play persists universally, suggesting it comes from within — not from outside influences or what children observe. It’s an internal cognitive drive that emerges no matter the culture.
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Overview
Operant conditioning, sometimes called instrumental conditioning, is a way we learn through the consequences of our actions. It involves changing voluntary behaviors by pairing them with rewards or punishments. When something good happens after a behavior, like getting a treat, that action is more likely to happen again. But if something bad follows, like a loud noise or pain, the behavior usually stops. This kind of learning can increase or decrease how often we do something, depending on what comes after. The behavior changes based on whether it's followed by something pleasant or unpleasant.
Origins
Operant conditioning began with Edward Thorndike, who proposed the law of effect, suggesting that behaviors are shaped by whether their outcomes feel satisfying or discomforting. In the 20th century, behavioral psychologists expanded on this idea, seeing much of human behavior as the result of environmental conditioning. They found that reinforcements—stimuli that increase a behavior—and punishments—stimuli that decrease it—can be either positive or negative, depending on whether they involve adding or removing something from the environment. Unlike classical conditioning, which pairs stimuli to trigger automatic responses like salivating at the smell of food, operant conditioning focuses on how consequences shape voluntary actions. Behaviors followed by rewards are more likely to be repeated, while those followed by negative outcomes tend to fade. These two types of learning remained central to behavior analysis throughout the century and even influenced studies in social psychology.
Thorndike's law of effect
Edward L. Thorndike studied how animals learn through trial and error, using puzzle boxes with cats. He found that cats learned to escape more quickly over time, as unsuccessful actions faded and successful ones repeated. This led him to formulate what he called the law of effect: behaviors followed by satisfying results tend to be repeated, while those followed by unpleasant outcomes are less likely to be repeated. By charting the time it took cats to escape across trials, Thorndike created one of the first animal learning curves. The same principle applies to human behavior—responses stick when they work and fade when they don’t. Parents have unknowingly used this kind of learning for thousands of years, teaching children through consequences without formal instruction.
B. F. Skinner
B.F. Skinner, known as the Father of operant conditioning, began his lifelong study with his 1938 book The Behavior of Organisms: An Experimental Analysis. Influenced by Ernst Mach, he rejected earlier ideas that relied on unobservable mental states, instead focusing on behavior and its consequences. He believed operant conditioning better explained human behavior than classical conditioning because it looked at intentional actions and their results. To study this, Skinner created the “Skinner Box,” a chamber where animals like pigeons and rats could perform simple, repeatable actions. Using a device called the cumulative recorder, he tracked how often these responses occurred under different reinforcement schedules. These schedules, defined as rules for delivering reinforcement, became central to his findings. In 1948, he published Walden Two, a fictional depiction of a society built on his principles. Ten years later, in Verbal Behavior, he applied operant conditioning to language, defining terms like “mands” and “tacts” without introducing new principles—treating verbal behavior as any other consequence-driven action.
Origins of operant behavior: operant variability
Operant behavior starts with actions that aren’t triggered by a specific stimulus—these are "emitted" rather than "elicited." So why do they happen? The explanation is similar to Darwin’s answer about how new bodily structures come into being: through variation and selection. In this case, an individual's behavior changes from moment to moment in ways like the exact movements made, the force used, or when the action occurs. If certain variations lead to rewards, those behaviors get stronger. And if the reward keeps coming, the behavior becomes more stable. But the amount of variation itself can be changed by adjusting other factors.
Shaping
Shaping is a method of conditioning used in animal training and with nonverbal humans, relying on operant variability and reinforcement. The trainer begins by defining the final behavior they want to achieve. Then, they select a behavior the subject already performs to some degree. Over time, the trainer reinforces versions of that behavior that come closer to the target. Each step moves the subject gradually toward the desired action. Once the target behavior is reached, it can be strengthened and kept going through a reinforcement schedule.
Noncontingent reinforcement
Noncontingent reinforcement is when a rewarding stimulus is given whether or not the person or animal does a particular behavior. This method is sometimes used to decrease an unwanted behavior by giving rewards for many different actions instead, which can cause the unwanted behavior to stop. Because no specific behavior is being strengthened, some people question whether it's accurate to call it "reinforcement" at all.
Stimulus control of operant behavior
At first, the actions we take don’t rely on any specific trigger, but as we learn through operant conditioning, certain cues start to control our behavior. When a behavior is followed by a reward or punishment, the stimuli present at that moment begin to influence when and how often we repeat it. These cues are called "discriminative stimuli." Together with the behavior and its consequence, they form what’s known as a "three-term contingency." For instance, a rat learns to press a lever only when a light turns on; a dog runs to the kitchen at the sound of a food bag; a child grabs candy when it's visible on a table.
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Overview
Rex Briggs, born in 1971, is an author and marketing researcher who gained recognition for his work with Generation X minorities while at Yankelovich Partners, where he also developed a theory called “The Psychology of disenfranchisement.” He was among the first to study the Internet. In 1995, Briggs joined Wired as Director of Research for their digital brand HotWired, where he created the first study measuring Web banner advertising effectiveness using random sampling online and design of experiments. His team also pioneered one-to-one web marketing, delivering personalized content, and introduced real-time web analytics known as “HotStats.”
Online Advertising Measurement
In 1997, Rex Briggs started a company called MBInteractive with Joshua Grossnickle and Oliver Raskin, which was owned by WPP plc. At MBInteractive, he kept working on marketing effectiveness and created the well-known IAB Advertising Effectiveness Study from that year. He also developed an early version of behavior targeting using leading online ad servers. During this time, Briggs introduced two marketing terms that stuck: “brand impact” and "Surround sound marketing."
Marketing ROI Measurement
In 2000, Briggs founded Marketing Evolution and developed a new kind of research called cross-media research, later known as multi-touch attribution and unified measurement. The approach began with The Dove Nutrium Bar study, which showed the return on investment for online advertising compared to television and magazine ads, helping determine how much of a budget should go toward digital versus other media. This work expanded to other brands and was shared globally by the IAB and Microsoft, with Briggs presenting the findings alongside Bill Gates and Steve Ballmer. In 2006, BusinessWeek featured his ROI marketing analysis in a cover story titled “Math Will Rock Your World.” That same year, he extended the research to connect online advertising with offline sales, publishing cross-media measurement for the Ford F-150 campaign launch.
Book: What Sticks
In 2006, Rex Briggs co-authored a book called What Sticks, which became the #1 marketing book according to Ad Age. That publication also named Briggs one of the 10 people who made their mark that year. The magazine devoted a cover story to the book and cited it as an answer to John Wanamaker’s famous question about advertising waste. Briggs, along with co-author Greg Stuart, studied three-dozen major brand campaigns and found that 37 percent of ad spending was wasted. They identified reasons like misunderstanding customer motivations, weak messages, and poor media choices. Their findings were supported by Bob Liodice of the Association of National Advertisers and reinforced by Mark Renshaw’s piece on the “70/20/10 Rule.” What Sticks is now required reading at top universities like Wharton and Harvard.
Social Media ROI
In 2007, Rex Briggs pushed forward the field of social media marketing while working with MySpace, Adidas, and Electronic Arts. At Marketing Evolution, he and his team identified what they called "The Momentum Effect"—how people share messages within their social networks. His findings were referenced in several books, including Emmanuel Rosen's The Anatomy of Buzz Revisited, Charlene Li and Josh Bernoff’s Groundswell, and Bob Garfield’s The Chaos Scenario. By 2011, Briggs claimed that the impact of social media could be predicted and measured just like traditional advertising.
Marketing Technology
Rex Briggs has been writing about marketing technology and automation since the year 2000, back when he published a paper that earned him an Excellence in International Research award from ESOMAR. In 2011, he described how software designed to optimize budget planning could function like a collective brain. He suggested this kind of technology might also be used to automatically share marketing best practices throughout the process. Briggs believes that SIRFs, or Spend to Impact Response Functions, will come to represent the "Face of Marketing," and that integrating them into software will be "transformative."
Book: SIRFs-Up: The Story of How Spend To Impact Response Functions (SIRFs), Algorithms And Software Are Changing The Face of Marketing
In 2012, Briggs published SIRFs-Up, a book exploring how marketing spend can be optimized using Spend To Impact Response Functions, or SIRFs. Ad Age covered the release. The first part outlines how SIRFs are being used by marketers, with examples from Victoria's Secret in the U.S. and AB-InBev in Latin America. Briggs explains that SIRFs show diminishing returns, where each additional dollar spent yields less value. He details the math behind measuring SIRFs and their application in ROI, media planning, and business strategy, using examples from well-known brands. The second part introduces a customer-insights-centered marketing framework, including content development and amplification strategies. Briggs discusses his research on social media, known as the Momentum Effect, and its importance to marketers. Part three focuses on marketing and media planning, introducing an audit process for advocacy and awareness, along with a brand's core purpose. Briggs argues that different business types require distinct marketing approaches, offering a tool called the Briggs-Matthews business typing system that considers factors like customer base size, whether a business is sales-led or marketing-led, and whether its products are purchased frequently or infrequently. The fourth part explains how to use SIRFs by either renting them from companies with benchmarks or gathering your own through research such as multi-touch attribution analysis. In the fifth section, Briggs predicts that marketing will be transformed by technology, especially as Business Intelligence, Marketing Resource Management, and Enterprise Marketing Management merge, integrating consumer intelligence data and SIRFs into all business operations. He also considers how humans will adapt in this increasingly tech-driven field. The final part offers a series of case studies demonstrating how all these concepts work together in practice.
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