In 2002 I was invited to give a talk to 500 school teachers. The invitation puzzled me, as my research at the time had nothing to do with education; I was a psychologist studying how different parts of the brain support different types of human learning. I mentioned this to the person who invited me, and she said, “We know. We want you to tell us about cognitive psychology. We think our teachers would be interested.” I shrugged, accepted the invitation, and forgot about it. Six months later (and days before I was to give the talk) I was wondering what had possessed me to say yes. Surely teachers would already know anything I could tell them about human memory, or attention, or motivation that would be relevant to teaching. I felt anxious and was sure the presentation would be a disaster.

But it wasn’t. Teachers thought it was interesting and relevant to their practice. Most surprising to me, they were unfamiliar with the content, even though it came from the very first class in human cognition a college student would take. I wondered: how could teachers not know the ABCs of cognition?

Yet the following 15 years have shown that experience was not a fluke. I’ve written four books and dozens of articles and have delivered scores of talks for teachers on the basics of cognition. In so doing, I’ve addressed what teachers saw as a need; what I haven’t done is think about why the need exists. Shouldn’t teachers learn how children think during their training? In this essay I consider why they don’t, and what we might do about it.

What Should Teachers Know?

Is my experience representative? Are most teachers unaware of the latest findings from basic science—in particular, psychology—about how children think and learn? Research is limited, but a 2006 study by Arthur Levine indicated that teachers were, for the most part, confident about their knowledge: 81 percent said they understood “moderately well” or “very well” how students learn. But just 54 percent of school principals rated the understanding of their teachers that high. And a more recent study of 598 American educators by Kelly Macdonald and colleagues showed that both assessments may be too optimistic. A majority of the respondents held misconceptions about learning—erroneously believing, for example, that children have learning styles dominated by one of the senses, that short bouts of motor-coordination exercises can improve the integration of the brain’s left and right hemispheres, and that children are less attentive after consuming sugary drinks or snacks.

But perhaps when teachers say they “know how children learn,” they are not talking about learning from a scientific perspective but about craft knowledge. They take the question to mean, “Do you know how to ensure that children in your classroom learn?” which is not the same as understanding the theoretical principles of psychology. In fact, in a 2012 study of 500 new teachers by the American Federation of Teachers (AFT), respondents said that their training was too theoretical and didn’t prepare them for teaching “in the real world.” Maybe they have a point. Perhaps teachers don’t need generalized theories and abstractions, but rather ready-to-go strategies—not information about how children learn, but the best way to teach fractions; not how children process negative emotion, but what to say to a 3rd grader who is dejected about his reading.

Most education researchers disagree, and they offer a reasonable argument. Some situations a teacher will encounter are predictable—a future teacher of 4th graders knows she will teach fractions—but many other situations are not. All teachers face problems for which their education leaves them unprepared: a 2nd grader goes to a corner of the room and spins, or a group of 6th graders laughs at a classmate because he whispers to himself when he reads. At these unpredictable moments, the teacher must improvise. How she responds to a child in a novel situation will depend, in part, on her beliefs about the cognitions, emotions, and motivations of children. In fact, future teachers have views about how children learn even before they begin their teacher-education programs. One goal of teacher education, then, is to ensure that these beliefs are as accurate as possible.

Whether for this reason or others, most teacher-education programs require some coursework in educational psychology. More important, every state requires that teachers pass an exam as part of the licensing process, and psychological content appears on most of these tests. For example, the publisher’s study guide for the Praxis II exam (used in more than 30 states) includes a list of psychological principles that test-takers should know (such as “how knowledge is constructed”), as well as the work of theorists (such as Bandura, Piaget, Bruner) and psychological terms (such as schema, zone of proximal development, operant conditioning). Two sample questions from this exam appear in the sidebar.

In sum, many U.S. teachers report that their education is overly theoretical and not of great utility. It’s clear that they are required to learn some basic principles of psychology as part of that education, but it is not clear that practicing teachers remember what they were taught.

Reform in Teacher Education

If a large percentage of teachers forget what they learn, that might be taken as evidence for the weakness of teacher preparation. Certainly, teachers’ lack of retention is consistent with the finding that teacher coursework predicts student outcomes poorly. Likewise, some research indicates that licensure test scores are associated with student outcomes, but those scores may simply be a proxy for a teacher’s cognitive ability. More generally, the lack of data showing the effectiveness of traditional teacher education might be viewed as support for policies that limit or eliminate the requirement that teachers undergo traditional teacher preparation. If we suspect teachers forget important aspects of their training and we know teachers without this preparation are mostly indistinguishable from those who get it, why set this meaningless hurdle? Requiring the coursework and a passing grade on a licensure test serves only to incur costs in time and money to future teachers, potentially closing the profession to some candidates. Given that some groups (such as African American men) are underrepresented in the profession, and that there are teacher shortages in certain geographic regions and subject areas, the requirement seems counterproductive.

Other observers have suggested that teacher education shouldn’t be eliminated, but it should be refocused. Current programs emphasize abstract theory at the expense of practical knowledge. There is, by this argument, only so much that can be learned from textbooks and lectures. Teaching is a skill, like tennis, that requires doing to gain proficiency. No one would think of teaching a child to play tennis by starting with a couple of years of book learning and no court time. Little wonder that teachers say their education overemphasized theory. These considerations point to greater emphasis on student-teaching placements, although existing research does not show that such apprenticeships necessarily lead to better student outcomes.

I suggest a third point of view. There’s reason for optimism that knowledge of the basic science of learning can improve teaching, and ultimately, student outcomes. Optimism, not confidence, because there is little direct evidence bearing on the question. Nevertheless, research does show that teacher beliefs influence their classroom decisions, so it is not a wild notion to suppose that accurate beliefs about how children learn will lead to better classroom decisions than inaccurate beliefs will.

The problem, I suggest, is twofold, and lies in the details of what future teachers learn, and how they learn it. Teachers are asked to learn content that is appropriate for future scientists, not future practitioners. And future teachers do not get sufficient practice with the concepts they are taught.

Science versus Application

What must scientists know? Scientists develop theories to account for observations. Observations come from the inspection and measurement of the world, inside the laboratory and out. A theory is a small set of statements that summarizes a large set of observations. Newton observed the movement of objects in many different circumstances, and summarized how they move with three laws of motion.

Scientists have recorded many observations of children’s cognition, motivation, and emotion over the last 100 years. Naturally, observations can be idiosyncratic, even if they are collected under controlled laboratory conditions. The observations that really matter are those that are observed consistently. Consider Piaget’s concept of conservation of number. In his famous demonstration, a four-year-old child will agree with you that two lines, each composed of eight buttons, contain the same number of buttons. But if, as the child watches, you elongate one of the rows by increasing the distance between the buttons, the child will now insist that the longer row has more buttons. Very young children do not yet recognize that rearranging a number of objects does not change their quantity.

Scientists have developed theories to account for these observations. For example, Piaget proposed that cognition develops in four stages. The second stage (ages two to seven) is characterized by difficulty in thinking abstractly and a focus on what is perceptually salient. Hence, a child in this stage cannot fathom that her mother was once her grandmother’s little girl, because her mother is so obviously grown. In the case of the buttons, the abstract idea of number is beyond the child, but the perceptual characteristic “bigger” is obvious to the child, and equates to “more.”

It seems self-evident that future scientists need to learn both observations (what children usually do) and theories to account for the observations. That’s the stuff of science. K–12 teachers, I will argue, have little use for psychological theory, but could benefit from knowing the observations—developmental patterns and consistencies in children’s cognition, motivation, and emotion. Such knowledge roughly equates to “understanding children.”

How can teachers use scientific observations about children? Some have direct classroom application. For example, around 4th grade, most children develop a more sophisticated understanding of how their own memories work; even without instruction on the principles of memory, children learn that some types of repetition help them to remember things more than others. A 5th-grade teacher who wants to ask students to work more independently would benefit from this knowledge: she could make a more informed bet that asking her 10-year-old students to commit things to memory will mostly work out. (For examples of scientific observations and classroom applications, see sidebar.)

Of course, not all scientific observations are equally useful to teachers. Some features of children’s minds have little prospect for classroom application. For example, if you lift two objects that are the same mass but different sizes, the larger one will feel lighter. That’s the size-weight illusion, and it is extremely reliable, but it’s hard to see how teachers would find it useful.

And the observations that do hold promise for education cannot be applied blindly. A teacher who learns that practice helps memory should not have 1st graders drilling a small set of math facts for two straight hours; practice helps memory, but under the wrong circumstances it can harm motivation.

The usefulness of scientific observations of children’s behaviors for teachers is widely appreciated, if textbooks for future teachers are any indicator. And these same books discuss the challenges involved in translating scientific findings into teaching practice. But teacher education misses the mark by emphasizing theory.

In contrast to observations, theoretical statements—for example, Piaget’s proposal that the thinking of children from ages two to seven tends to be concrete rather than abstract—are not helpful to teachers. On the positive side, a theoretical statement could provide a tidy summary of a large collection of observations, making them easy to understand, coordinate, and remember. But overall, theories have significant drawbacks when applied to practice.

First, scientific theories do more than summarize observations; they are meant to push science forward, to prompt new research. Thus, they go beyond existing data to make novel predictions about as-yet-unobserved phenomena. In the case of Piaget, many predictions derived from his theory were wrong, including the prediction about young children’s limited ability to think abstractly. Teachers guided by Piagetian theory, rather than by direct observation of children’s success in learning, will underestimate what young students can learn. More generally, when pre-service teachers learn the latest scientific theories, they are almost certainly learning content that will later be shown to be at least partially wrong.

A second problem with focusing on theory is that teachers are often taught multiple theories meant to account for the same phenomena. Again, that’s central to the purpose of the scientific enterprise: we refine and improve our theories for a set of observations by proposing multiple theories and setting one against the other. So, future researchers should learn multiple theories because they need to understand how theories are compared and evaluated. But for future teachers, the competition among theories can lead to a narrowing of perspective.

For example, a teacher reading any of the popular educational-psychology textbooks will encounter two wildly different theoretical accounts of student motivation. The behaviorist account emphasizes children’s motivation to earn rewards and avoid punishments. Classroom applications of this theory focus on systems that reward students for various behaviors or incremental achievements. Humanist theories, by contrast, emphasize students’ sense of autonomy, stressing that they are motivated to undertake tasks they see as under their control. Classroom applications of this perspective focus on ways to offer students greater choice.

The classroom practices—rewards and choice—are not incompatible, but the theories are. Each explicitly discounts what the other highlights, and both are incomplete. Professors of education introduce pre-service teachers to both theories, presumably because doing so exposes these future practitioners to a wider range of tools they might use in their classrooms. But because the theories are incompatible, one might presume that the classroom applications are incompatible as well. If you’re a behaviorist, you use one approach; if you’re a humanist, the other. Whichever choice teachers make, though, they all have classrooms with students who respond to rewards and to choice.

The presentation of multiple theoretical accounts is the rule rather than the exception in teacher education. The concept of intelligence provides another example. Again, many empirical observations could prove useful to teachers—for example, that intelligence can be improved with sustained cognitive work—but there is no single accepted theory of intelligence. It is variously described as having three relatively independent components, eight relatively independent components, or many, many non-independent components. Learning provides another example: educational theorists variously describe learning in terms of overt behavior, as mental symbols, or as a social construction. Teachers could hardly be blamed for thinking that scientists have some theories but have not yet figured out how learning works.

We see why teachers feel that much of their education is of low utility: much of it is. Teachers are taught (and via licensing exams, tested on) empirical observations (how kids think and act) as well as psychological theories. But only the former holds the promise of improving the practice of teaching.

The Need for Practice

The second reason teachers find their education impractical is that they do not get enough practice with the principles they learn to fully absorb them and thus make them useful.

I’ve suggested that teachers’ study of psychology ought to focus on consistencies in children’s cognitive, emotional, and motivational makeup, and that future teachers be asked to learn some of these consistencies. It’s important to note that these consistencies are abstractions. Consider “thinking fails when people try to keep too many things in mind at once.” That’s clear enough, but it can manifest in observable behavior quite differently, depending on the student’s age, the task he is performing, his emotional state, and other factors. A shy 3rd grader who is mentally overloaded by a rapid series of five instructions may just look blank. A 10th grader who is mentally overloaded by stereotype threat during a math test may respond with anger. Or with resignation. Teachers need to learn not just the abstract generalizations that scientists have described but how they play out in particular contexts.

This problem has been targeted in the past. A committee of educational psychologists, under the auspices of the American Psychological Association (APA), met in the mid-1990s to consider how future teachers might learn abstract principles of science in ways that could apply to classroom practice. The committee report recommended that authors of educational-psychology textbooks offer examples of how these principles play out in school, and provide more classroom scenarios for pre-service teachers to interpret. Another APA committee revisited the issue in 2011 and concluded that textbooks had improved along the lines suggested.

It was a sound strategy, but it didn’t solve the problem, as evidenced by the AFT’s 2012 survey showing that teachers still considered their education overly theoretical. The problem cannot be solved just by tying scientific abstractions to classroom examples; education students need sustained practice in making those connections. A single semester—the duration of a typical educational-psychology course—won’t do it.

In a landmark study of this issue by Patricia Cheng and colleagues, the researchers examined the problem-solving abilities of college students who had taken a course in deductive logic. Although they had successfully solved logic problems on course examinations, when they were given a standard logical form disguised as a “brain teaser” they were no better at solving it than students who had not taken the course (see Figure 1).

By definition, abstractions—a deductive logical form or a principle of children’s thinking—can look different, depending on context. Recognizing the underlying structure takes practice, but practice does the trick. Students who had taken more than one logic course were much more successful at solving the brain teaser.

If such theories are to be useful in the long term, what’s learned in an educational psychology course must be reinforced in other coursework and in fieldwork. The teacher specializing in adolescent literacy would learn about the limitations of attention in that context, while the teacher specializing in elementary math would learn different consequences of the same observation about children’s thinking. That would require coordination across the teacher-education curriculum. Beyond the classroom, pre-service teachers should continue to learn about and apply this content during their student-teaching placements, which would, of course, require that their mentors be able and willing to incorporate relevant feedback into their coaching.

Next Steps

I began this article by highlighting two prominent ideas for the reform of teacher education: eliminating the traditional requirements for a teaching career, or radically changing those requirements to maximize student-teaching experience and minimize coursework. Here I’ve suggested a third way: change the content of education-degree coursework to focus on consistencies in children’s thinking, and greatly curtail how much scientific theory we ask future teachers to learn. What are the logical next steps toward implementing this third way?

I should note that important data are missing from my analysis. We have only spotty evidence as to what practicing teachers actually know about child psychology. Neither do we have solid evidence that teaching that aligns with scientists’ understanding of children is more effective than teaching that does not. Although many would suspect they could predict the outcomes of this missing research, we would be wise to test these assumptions empirically before undertaking a wholesale reform of teacher education.

The changes would not be minor. Textbooks would need to be revised, and courses would need to be overhauled—and not just courses in educational psychology, but (to a lesser extent) courses throughout the curriculum, to ensure that they coordinate with the new content. The difficulty of persuading professors to change their courses should not be underestimated. Faculty in higher education are used to autonomy in the classroom, and we surrender it with great reluctance. Given the scale of this change, the easiest way forward would be to create a pilot program within a college of education rather than attempting schoolwide reform. Faculty will be much easier to persuade if a small-scale trial shows promising results.

That leads us to the question: how do we define and measure “promising results”? Naturally, the ultimate aim would be improved student learning, but I would suggest that three other types of measurement be collected in parallel. First, we must be sure teachers retain the psychological principles they are taught. Second, we must be confident that they not only know the principles, but they also know how to use them in lesson plans. Third, we must be confident that they actually do use the principles in their teaching. And then we would need to gauge whether the students of teachers who use these principles in lesson plans have better educational outcomes than students whose teachers do not.

The financial commitment, then, is probably high. But the benefits could be substantial and the investment would pay dividends long into the future.

Daniel T. Willingham is professor of psychology at the University of Virginia. His most recent book is The Reading Mind: A Cognitive Approach to Understanding How the Mind Reads.

Peak: Secrets from the New Science of Expertise
by Anders Ericsson and Robert Pool
Eamon Dolan/Houghton Mifflin Harcourt, 2016, $28; 336 pages.

As reviewed by Daniel T. Willingham

Since the early 1990s, Anders Ericsson has done more than any other psychologist in modern times to further our understanding of how people—especially those who become experts—learn and master skills. As the old adage puts it, practice makes perfect. But if practice is all there is to it, why has my typing improved so little in the last 40 years?

Ericsson’s research clarifies the difference between what he calls deliberate practice and other activities that call for repetition. Even though I type every day, my typing is not really practicing, because I’m not purposefully or systematically trying to improve it. Given that I have not formally studied typing, I may even be reinforcing bad technique.

In Ericsson’s formulation, deliberate practice has several components: evaluating what needs improvement, selecting one small aspect of the skill to work on, developing a strategy, and then evaluating the results of the revised performance. And if you plan to become really good, you need to practice: a lot. Exactly how long? That depends on the skill—10,000 hours is the popular author Malcolm Gladwell’s magic number, not Ericsson’s—but plan on years.

In the book’s first four chapters, Ericsson and his adept co-author, the science writer Robert Pool, take the reader through the science of expertise, building toward the idea that “memory representations” lie at the heart of skill. People who are superb at something have an enormous stock of memories related to what happens in their domain of skill, and how to act on it.

If reading a lot of detail about memory sounds formidable, fear not. The authors keep the material lively by using stories to illustrate scientific points. Over the course of the book, you’ll meet the Navy’s Top Gun pilots, a violinist so skilled that when a string breaks during a performance he simply completes the piece on the remaining strings, and the eccentric Hungarian psychologist who was so confident in his theory of genius that he sought a wife who would collaborate with him in raising a child to be a chess prodigy (it worked).

Good science writing requires not just clarity but energy and compelling narrative. Peak delivers, and is a pleasure to read. After reviewing the science, the authors explain how we can apply the principles of deliberate practice to our own personal and professional learning. In the profession of medicine, for example, we could “make” better doctors if we provided them with opportunities to systematically practice medicine rather than simply “doing” it.

What lessons, then, does the book hold for educators and policymakers? Surely the world’s expert on expertise has something to say about the process of learning math, for example. In one respect, the book is an excellent companion to Carol Dweck’s Mindset. Dweck emphasizes the importance of children believing they can get smarter if they work hard on the right things. Ericsson offers specifics about how they need to work if their efforts are to bear fruit.

And if Dweck doesn’t want you to focus on talent, lest you believe that your innate ability matters more than your concerted action, Ericsson takes this principle a step further, and in fact further than most psychologists would go. Ericsson has little use for talent at all. In his estimation, innate abilities matter only before people have practiced much. The kid with a high IQ will play better chess than the kid with a low IQ, but only because neither knows much about chess. If they both practice, the influence of IQ will disappear, and whoever practices more will be the better player.

Many people would contend that practice theory cannot fully explain how we reach the peak of performance, especially in certain domains, such as athletics. We tend to see a standout like LeBron James as having been “born great,” no matter how hard he had to work to fulfill his talent. Ericsson concedes that physical characteristics do influence achievement in sports and other physical activities and cannot be modified by practice.

But in most spheres, Ericsson holds that the role of innate ability, as in the chess example, only provides an advantage at the beginning of the learning curve. It is far from clear that Ericsson is completely right about that, but his underlying message—“Damn the talent, full practice ahead!”—is one that most psychologists (and educators) could support.

What are the practical implications of Ericsson’s features of deliberate practice for K–12 education? Ericsson writes that Nobel laureate physicist Carl Wieman uses teaching methods that embody the principles of deliberate practice. Wieman, who is known for his method of teaching large lecture courses via small-group student discussions of carefully selected questions, emphasizes that such discussion requires that students stay mentally active, whereas the more common lecture format encourages mentally passive note-taking. Ericsson agrees, but also highlights Wieman’s careful delineation of learning objectives and meticulous sequencing of small mental steps toward those objectives—hallmarks of the deliberate practice method.

Even if a teacher isn’t drawn to Wieman’s methods, I’d argue that principles of deliberate practice are well worth knowing. The mere distinction between experience and deliberate practice can help guide educators in imparting certain skills. For example, many schools want students to work well with others, so they assign group projects. But working in a group is simply experience. If you want students to become better group members, they need to practice being a group member. They must be explicitly taught how to work in groups, and that’s something few schools do.

What’s more, deliberate practice calls for working on one aspect of the skill at a time. Ericsson would suggest that the complex of skills required for working in a group or writing a research paper should not be tackled at once but should be broken down into smaller tasks, each of which would be practiced on its own. For writing a research paper, one could imagine subtasks such as using a database to locate research, evaluating the relevance of sources, creating an annotated bibliography, writing a rough outline and then a detailed one, and perhaps as many as four or five substeps in the writing of effective expository prose.

Even more than the teaching of students, Peak set me thinking about the training of teachers. Most teachers have no opportunity for deliberate practice of their craft. It’s long been noted that, by most measures, the average teacher improves enormously in the first several years on the job, after which student-achievement gains (one gauge of teacher effectiveness) level off. It’s reasonable to speculate that this drastic slowing of improvement is due to a lack of purposeful practice. But if teachers are to deliberately practice, they need to be given time in their schedules to do so.

Another challenge here is rooted in the way some teachers view their profession. Practice is only possible if practitioners agree on who the experts are, so the goals of practice can be articulated. In addition, educators will need to define the sequence of subskills to be acquired on the way to expertise. Practitioners need to know that “once you’ve mastered X, you move on to Y.” For those who see teaching as more art than craft, such dissection is not feasible.

Enabling practice in the teaching profession will not be simple, but Ericsson and Pool’s Peak offers a stark wake-up call, pointing up that we can’t expect teachers to improve in the absence of real practice. The book also provides an excellent resource for those who want to take action and begin integrating the principles of deliberate practice into K–12 education.

Daniel T. Willingham is a professor of psychology at the University of Virginia. His most recent book is Raising Kids Who Read: What Teachers and Parents Can Do.

Frames of Mind: The Theory of Multiple Intelligences
(Basic Books, 1983)

Multiple Intelligences: The Theory into Practice
(Basic Books, 1993)

Intelligence Reframed: Multiple Intelligences for the 21st Century
(Basic Books, 1999)

By Howard Gardner

Checked by Daniel T. Willingham

What would you think if your child came home from school and reported that the language-arts lesson of the day included using twigs and leaves to spell words? The typical parent might react with curiosity tinged with suspicion: Is working with twigs and leaves supposed to help my child learn to spell? Yes, according to Thomas Armstrong, author of Multiple Intelligences in the Classroom, especially if your child is high in “naturalist” intelligence–one of eight distinct intelligences that Harvard University scholar Howard Gardner claims to have identified. However, if your child possesses a high degree of what Gardner terms “bodily-kinesthetic” intelligence, Armstrong suggests associating movement with spelling. For example, a teacher might try to connect sitting with consonants and standing with vowels.

Armstrong is far from alone in placing faith in Gardner’s theory of “multiple intelligences.” Gardner’s ideas have been a significant force in education for the past 20 years–significant enough that they bear close study. How does the scientific community regard the theory of multiple intelligences, and what impact should the theory have on education?

Central Claims

Gardner first proposed his theory in 1983. Since then, it has undergone incremental but not fundamental change, including the addition of one intelligence (bringing the total to eight), the rejection of others, and consideration of the theory’s applications. The theory rests on three core claims:

• Gardner says that most psychometricians, those who devise and interpret tests as a way of probing the nature of intelligence, conceive of intelligence as unitary. In Intelligence Reframed, Gardner’s most recent restatement of his general theory, he writes, “In the ongoing debate among psychologists about this issue, the psychometric majority favors a general intelligence perspective.”

This is not an accurate characterization of the position taken by most psychometricians. As will be shown, the vast majority regard intelligence not as a single unified entity, but as a multifaceted phenomenon with a hierarchical structure.

• There are multiple, independent intelligences. There are three parts to this claim, and it is important to appreciate all three. First, Gardner offers a new definition of intelligence, describing it as “a biopsychological potential to process information that can be activated in a cultural setting to solve problems or create products that are of value in a culture.” Previous definitions were limited to cognition or thought; one was intelligent to the extent that one could solve problems and adapt effectively to one’s environment using thinking skills. Gardner self-consciously broadens the definition to include effective use of the body and thinking skills relevant to the social world. He also extends the functionality of intelligence to include the crafting of useful products, not just the solving of problems. Second, Gardner claims to have identified some (but not all) of the several types of intelligence, which I describe below. Third, he claims that these multiple intelligences operate independently of one another.

• The multiple intelligences theory has applications to education. Gardner has been careful to say that he has proposed a scientific theory that should not be mistaken for a prescription for schooling. He makes clear that the educational implications of children’s possessing multiple intelligences can and should be drawn, but he believes that many possible curricula and methods could be consistent with the theory. The sole general implication he supports is that children’s minds are different, and an education system should take account of those differences, a point developed in diverse ways by his many followers.

One Intelligence or Many?

Let’s evaluate each of Gardner’s claims in turn, beginning with how psychometricians view intelligence. In the early 20th century, many psychometricians did in fact think of intelligence as a unitary trait, just as Gardner now claims. The thinking at that time was articulated by Charles Spearman, who suggested that a single factor (he called it g, for general) underlay all intelligent behavior. If you had a lot of g, you were smart; if you didn’t, you weren’t. However, by the 1930s some researchers (notably Louis L. Thurstone) were already arguing for a multifaceted view of intelligence. One might be intelligent in the use of words, for example, but unintelligent mathematically. From the 1950s on, many psychometricians proposed hierarchical models, which may be thought of as a mixture of the single-factor and multiple-factor models. Except for a few holdouts, most psychologists now favor the hierarchical model.

How can one use data from tests of cognitive ability to evaluate the number of intelligences? A straightforward approach entails administering a number of separate tests thought to rely on different hypothesized intelligences. Suppose tests 1 and 2 are different tests of verbal ability (for example, vocabulary and spelling), and tests 3 and 4 are different tests of mathematical ability. If there is one intelligence, g, then g should support performance on all four tests, as shown in diagram A of Figure 1 (this page). A high score on test 1 would indicate that the test-taker is high in g, and he or she should perform well on all of the other tests.

Suppose, however, that there are two intelligences–one verbal and one mathematical, as shown in diagram B of Figure 1. In that case, a high score on test 1 would predict a high score on test 2, but would tell us nothing about the individual’s performance on the math tests, 3 and 4. Performance on those tests would depend on mathematical intelligence, which is separate and independent of verbal intelligence.

The data support neither of these views. To continue with our hypothetical example, the data show that all of the test scores, 1 through 4, are somewhat related to one another, which is consistent with the existence of g. But scores from tests of math ability are more related to one another than they are to verbal scores; the same goes for verbal scores. A hierarchical model, shown in diagram C of Figure 1, fits this pattern. In this model, g influences both mathematical and verbal cognitive processes, so performance on math and verbal tests will be somewhat related. But mathematical competence is supported not just by g, but by the efficacy of a mathematical intelligence that is separate and independent of a verbal intelligence. That’s why math scores are more related to each other than they are to verbal scores. It also explains how it is possible for someone to be quite good in math, but just mediocre verbally. This logic applies not only to the restricted example used here (math and verbal) but also to a broad spectrum of tests of intellectual ability.

The hierarchical view of intelligence received a strong boost from a landmark review of the published data collected over the course of 60 years from some 130,000 people around the world. That massive review, performed by the late University of North Carolina scholar John Carroll, concluded that the hierarchical view best fits the data. Researchers still debate the exact organization of the hierarchy, but there is a general consensus around the hierarchical view of intelligence. Thus Gardner’s first claim–that most psychometricians believe that intelligence is unitary–is inaccurate.

What Are the Intelligences?

Gardner’s second claim is that individuals possess at least eight independent types of intelligence. The following list includes a definition of each along with examples Gardner has provided of professions that draw heavily on that particular intelligence.

• Linguistic: facility with verbal materials (writer, attorney).

• Logico-mathematical: the ability to use logical methods and to solve mathematical problems (mathematician, scientist).

• Spatial: the ability to use and manipulate space (sculptor,

architect).

• Musical: the ability to create, perform, and appreciate music (performer, composer).

• Bodily-kinesthetic: the ability to use one’s body (athlete, dancer).

• Interpersonal: the ability to understand others’ needs, intentions, and motivations (salesperson, politician).

• Intrapersonal: the ability to understand one’s own motivations and emotions (novelist, therapist with self-insight).

• Naturalist: the ability to recognize, identify, and classify flora and fauna or other classes of objects (naturalist, cook).

Gardner claims that everyone has all eight intelligences to some degree, but each individual has his or her own pattern of stronger and weaker intelligences. Gardner also argues that most tasks require more than one intelligence working together. For example, the conductor of a symphony obviously uses musical intelligence, but also must use interpersonal intelligence as a group leader and bodily-kinesthetic intelligence to move in a way that is informative to the orchestra. The claim of separate and independent intelligences is, of course, central to Gardner’s theory. How do we know that these intelligences are independent?

It is important to bear in mind that the hierarchical model described in the previous section is not a theory, but a pattern of data. It is a description of how test scores are correlated. A theory of intelligence must be consistent with these data; the pattern of data is not itself a theory. For example, the data do not tell us what g is or how it works. The data tell us only that there is some factor that contributes to many intellectual tasks, and if your theory does not include such a factor, it is inconsistent with existing data. Gardner’s theory has that problem.

Setting g aside, the claim of independence among the eight intelligences is also a problem. Data collected over the past 100 years consistently show that performances on intellectual tasks are correlated. Even if Gardner’s theory did not include some general factor, it should at least provide a way to account for this correlation. The theory did not, and it was widely criticized for this failure. In some later writings, Gardner has said that he questions the explanatory power of g, not whether it exists–in other words, he doubts whether g makes much of a contribution to abilities Gardner deems important. He has also deemphasized the importance in his theory of whether the intelligences are truly independent.

Let’s allow, then, that the intelligences Gardner has identified are not independent, but that there are a number of distinguishable (but correlated) intellectual capabilities in addition to g. Has Gardner done a good job of cataloguing them? It is instructive to examine the criteria by which Gardner determines whether an ability is an intelligence. The criteria are shown in the table on page 22.

Gardner’s eight criteria appear to be quite rigorous: the psychometric criterion described in the previous section and seven others that span different domains of investigation. But Gardner weakens them by demanding that only a majority be satisfied, and some are rather easy to satisfy. The psychometric criterion is the most rigorous of the eight, but Gardner has largely ignored it. The remaining criteria are so weak that they cannot restrain a researcher with a zest for discovering new intelligences.

For instance, a humor intelligence and a memory intelligence certainly meet a majority of the criteria. Humor and memory can be used to solve problems and create valued products in many cultures and so meet Gardner’s definition of intelligence. Both can be isolated by brain damage, each has a distinct developmental history, and there is evidence for the psychological separability of each. Some individuals show exceptional memory or sense of humor but no other remarkable mental abilities. The evolutionary plausibility of each intelligence is easy to defend as well. Humor would certainly be adaptive in a social species such as ours, and the adaptive nature of memory should be self-evident.

By these criteria I am also prepared to defend an olfactory intelligence and a spelling intelligence and to subdivide Gardner’s spatial intelligence into near-space intelligence and far-space intelligence, thus bringing the total number of intelligences to 13. (Gardner, for reasons that are not clear to me, excludes sensory systems as potential intelligences, but not action systems such as bodily-kinesthetic.)

The issue of criteria by which new intelligences are posited is crucial, and it is in the selection of criteria that Gardner has made a fundamental mistake. Gardner’s criteria make sense if one assumes extreme modularity in the mind, meaning that the mind is a confederation of largely independent, self-sufficient processes. Gardner argues that neuroscience bears out this assumption, but that is an oversimplification.

For example, suppose that mathematical and spatial intelligence have the structure depicted in Figure 2, where each letter represents a cognitive process. Mathematical reasoning requires the cognitive processes A through E. Spatial reasoning requires the processes B through F. Are math and spatial reasoning separate?

Most people would agree that they are not identical, but they are largely overlapping and don’t merit being called separate. By Gardner’s criteria, however, they likely would be. If we assume that each process (A through F) is localized in a different part of the brain, then if the part of the brain supporting process A were damaged, math ability would be compromised, but spatial ability would not, so the brain criterion would be met. If process A or process F had a different developmental progression than the others, the developmental criterion would be met. If A and F differ in their need for attentional resources, the experimental psychological criterion would be met. The criteria that Gardner mentions can be useful, but they do not signal necessarily separate systems. In fact, the one criterion that Gardner has routinely ignored–the psychometric–is the one best suited to the question posed: Are cognitive processes underlying a putative intelligence independent of other cognitive processes?

Gardner’s second claim–that he has described multiple, independent varieties of intelligence–is not true. Intellectual abilities are correlated, not independent. Distinguishable abilities do exist, but Gardner’s description of them is not well supported.

Should Theory Become Practice?

For the educator this debate may be, as Shakespeare wrote, sound and fury, signifying nothing. What matters is whether and how the theory inspires changes in teaching methods or curriculum. The extent to which multiple intelligence ideas are applied is difficult to determine because few hard data exist to describe what teachers actually do in the classroom. Even statements of schools’ missions are of limited usefulness, although dozens of schools claim to center their curriculum on the theory. An administrator might insert multiple intelligences language in an effort to seem progressive. Or an administrator’s enthusiasm may be sincere, but if the teachers are not supportive, the classroom impact will be minimal.

We are left with indirect measures. Textbooks for teachers in training generally offer extensive coverage of the theory, with little or no criticism. Furthermore, the ready availability of multiple intelligences classroom materials (books, lesson plans, and activities) leaves the impression that there is a market for such materials. The applications they suggest generally fall into two broad categories: curricular expansion and pedagogical stratagem.

Curriculum expansion suggests that schools should appeal to all of the intelligences. Some educators have called for a more inclusive approach that does not glorify any one of the intelligences at the expense of the others. The theory has also been viewed as providing a pedagogical stratagem–namely, to teach content by tapping all of the intelligences. For example, to help students learn punctuation, a teacher might have them form punctuation marks with their bodies (bodily-kinesthetic intelligence), assign an animal sound to each punctuation mark (naturalist intelligence), and sort sentences according to the required punctuation (logical-mathematical intelligence). The motive may be that students will most enjoy or appreciate the material when it is embedded in an intelligence that is their strength. In this sense, intelligences may be translatable. The student who is linguistically weak but musically strong may improve his spelling through a musical presentation.

Gardner has criticized both ideas. Regarding curriculum, Gardner argues that the goals of education should be set independently of the multiple intelligences theory, and the theory should be used to help reach those goals. In other words, he does not believe that status as an “intelligence” necessarily means that that intelligence should be schooled. This objection is doubly true if you doubt that Gardner has categorized the intelligences correctly.

On the subject of pedagogy, Gardner sees no benefit in attempting to teach all subjects using all of the intelligences. He also expresses concern that some educators have a shallow understanding of what it takes to really engage an intelligence. Gardner writes, “It may well be easier to remember a list if one sings it (or dances to it). However, these uses of the ‘materials’ of an intelligence are essentially trivial. What is not trivial is the capacity to think musically.” It is therefore surprising that Gardner wrote the preface for Thomas Armstrong’s book, Multiple Intelligences in the Classroom, which includes many such trivial ideas, such as singing spellings and spelling with leaves and twigs, as mentioned earlier. In the preface Gardner says that Armstrong provides “a reliable and readable account of my work.” The inconsistency in Gardner’s views is difficult to understand, but I believe he is right in calling some applications trivial.

Gardner also writes that intelligences are not fungible; the individual low in logico-mathematical intelligence but high in musical intelligence cannot somehow substitute the latter for the former and understand math through music. An alternative presentation may serve as a helpful metaphor, but the musically minded student must eventually use the appropriate representation to understand math. Gardner is on solid ground here. There is no evidence that subject-matter substitution is possible.

Gardner offers his own ideas of how multiple intelligences theory might be applied to education. Teachers should introduce a topic with different entry points, each of which taps primarily one intelligence. For example, the narrational entry point uses a story (and taps linguistic intelligence), whereas the logical entry point encourages the use of deductive logic in first thinking about a topic. Entry points are designed to intrigue the student via a presentation in an intelligence that is a particular strength for him or her. Gardner also believes that a thorough understanding of a topic is achieved only through multiple representations using different intelligences. Hence significant time must be invested to approach a topic from many different perspectives, and topics should be important enough to merit close study.

How effective are Gardner’s suggested applications? Again, hard data are scarce. The most comprehensive study was a three-year examination of 41 schools that claim to use multiple intelligences. It was conducted by Mindy Kornhaber, a long-time Gardner collaborator. The results, unfortunately, are difficult to interpret. They reported that standardized test scores increased in 78 percent of the schools, but they failed to indicate whether the increase in each school was statistically significant. If not, then we would expect scores to increase in half the schools by chance. Moreover, there was no control group, and thus no basis for comparison with other schools in their districts. Furthermore, there is no way of knowing to what extent changes in the school are due to the implementation of ideas of multiple intelligences rather than, for example, the energizing thrill of adopting a new schoolwide program, new statewide standards, or some other unknown factor.

What is perhaps most surprising about Gardner’s view of education is that it is not more surprising. Many experienced educators probably suspected that different materials (songs, stories) engage different students and that sustained study using different materials engenders deep knowledge.

Multiple Talents

One may wonder how educators got so confused by Gardner’s theory. Why do they believe that intelligences are interchangeable or that all intelligences should be taught? The answer is traceable to the same thing that made the theory so successful: the naming of various abilities as intelligences.

Why, indeed, are we referring to musical, athletic, and interpersonal skills as intelligences? Gardner was certainly not the first psychologist to point out that humans have these abilities. Great intelligence researchers–Cyril Burt, Raymond Cattell, Louis Thurstone–discussed many human abilities, including aesthetic, athletic, musical, and so on. The difference was that they called them talents or abilities, whereas Gardner has renamed them intelligences. Gardner has pointed out on several occasions that the success of his book turned, in part, on this new label: “I am quite confident that if I had written a book called ‘Seven Talents’ it would not have received the attention that Frames of Mind received.” Educators who embraced the theory might well have been indifferent to a theory outlining different talents–who didn’t know that some kids are good musicians, some are good athletes, and they may not be the same kids?

Gardner protests that there is no reason to differentiate–he would say aggrandize–linguistic and logico-mathematical intelligences by giving them a different label; either label will do, but they should be the same. He has written, “Call them all ‘talents’ if you wish; or call them all ‘intelligences.'” By this Gardner means that the mind has many processing capabilities, of which those enabling linguistic, logical, and mathematical thought are just three examples. There is no compelling reason to “honor” them with a special name, in his view.

Gardner has ignored, however, the connotation of the term intelligence, which has led to confusion among his readers. The term intelligence has always connoted the kind of thinking skills that make one successful in school, perhaps because the first intelligence test was devised to predict likely success in school; if it was important in school, it was on the intelligence test. Readers made the natural assumption that Gardner’s new intelligences had roughly the same meaning and so drew the conclusion that if humans have a type of intelligence, then schools should teach it.

It is also understandable that readers believed that some of the intelligences must be at least partially interchangeable. No one would think that the musically talented child would necessarily be good at math. But refer to the child as possessing “high musical intelligence,” and it’s a short step to the upbeat idea that the mathematics deficit can be circumvented by the intelligence in another area–after all, both are intelligences.

In the end, Gardner’s theory is simply not all that helpful. For scientists, the theory of the mind is almost certainly incorrect. For educators, the daring applications forwarded by others in Gardner’s name (and of which he apparently disapproves) are unlikely to help students. Gardner’s applications are relatively uncontroversial, although hard data on their effects are lacking. The fact that the theory is an inaccurate description of the mind makes it likely that the more closely an application draws on the theory, the less likely the application is to be effective. All in all, educators would likely do well to turn their time and attention elsewhere.

-Daniel T. Willingham is a professor of psychology at the University of Virginia.

Checked:
The Myth of Laziness
(Simon & Schuster, 2003)
A Mind at a Time
(Simon & Schuster, 2002)
By Mel Levine

Checked by Daniel T. Willingham

Mel Levine writes about learning disabilities in a way that sometimes invites satire. The premise of his 2003 book, The Myth of Laziness, for example, is that a child who appears lazy probably doesn’t lack motivation, but rather suffers from “output failure.” It is tempting to have a good laugh and say, “Where were you when I was in school, Doc?”

But writing Levine off as a gooey, feel-good lightweight will not do. Indeed, Levine, a professor of pediatrics at the University of North Carolina Medical School and director of UNC’s Clinical Center for the Study of Development and Learning, is that rare author whose work affects not only millions of parents, but hundreds of school systems as well. While The Myth of Laziness had some success, his 2002 book, A Mind at a Time, reached #1 on the New York Times best-seller list and brought coverage by the national media, including (every publisher’s happiest hope) an appearance on Oprah. And in 2005, Levine added a third work, Ready or Not, Here Life Comes, which tackles the transition from adolescence to adulthood. By this time, his second book’s success had already given a significant boost to All Kinds of Minds, a nonprofit organization Levine cofounded in 1995 to promote his theories. A subsidiary program, Schools Attuned, trains teachers to recognize and address learning problems in children. So far eight training centers have been set up in North America.

Levine’s project got a push when state legislatures in North Carolina and Oklahoma allocated funds allowing any public school K-12 teacher to attend the course with substantial or complete remission of the $1,500 tuition. Then in May 2004, the New York City Department of Education signed a five-year contract with All Kinds of Minds worth about $12.5 million to train 20,000 city teachers. By the time 60 Minutes aired a story on the children of baby boomers last fall, Levine was called “one of the foremost authorities in the country on how children learn.”

There are two questions that parents and educators should ask about Levine’s program. First, Is his theory of how the mind works correct? Theories of learning disabilities (including Levine’s) are theories of what happens when learning abilities have gone wrong. If you mischaracterize the abilities, your description of potential problems is inaccurate. As I’ll describe, Levine’s broad-strokes account of the mind agrees with that of most researchers (and for that matter, with the observant layman): there is a memory system, an attention system, and so on. But it’s the detailed structure Levine claims to see within each of those systems that really drives his proposed treatments for disabled children, and on those details Levine is often wrong. The second question one should ask is, Does the evidence indicate that his proposed treatments help? The answer is that there is no evidence, positive or negative, as to whether or not the program helps kids. Given the inaccurate description of the mind on which it is based, however, it seems unlikely that it will prove particularly effective.

Old Ideas in a New Package

Levine proposes that the human mind has eight major cognitive systems-and many more subsystems (see Figure 1). Much of A Mind at a Time describes, through case studies, what happens when one or more of these systems or subsystems fails. For example, he tells the story of Vance, who dropped out of the 9th grade. According to Levine, Vance was strong in reading and math, but he could not remember facts. Levine diagnosed Vance’s problem as a deficit in long-term memory, one of the subsystems of memory. Despite a mind that worked well in most respects, this one glitch left Vance an academic failure, frustrated and shamed. The case typifies those described in the book: an able mind is foiled by a single weak link, and the child is failed by the school system’s inability to identify and address the problem.

Levine suggests a number of measures to help kids like Vance, some of which are standard practice in the field-for example, accommodations or workarounds in the classroom. The child with a long-term memory problem might be permitted to use notes during a test; the idea is that with this long-term memory support, Vance will be able to show his cognitive strengths such as analytic skills or effective writing. Levine also suggests that teachers take care not to accidentally embarrass children with learning disabilities. For example, Vance’s teacher should ensure that other children don’t know that he has any accommodation.

In fact, the same common treatment practices that Levine suggests are rooted in assumptions about the nature of learning disabilities. For example, the strategy of allowing accommodations is based on the widely accepted belief among educational and cognitive psychologists that learning disabilities may strike a specific cognitive process, like memory, but leave others, like attention, intact. As to the emphasis on the students’ dignity, that too is based on the consensus view that learning disabilities are inborn and specific. The disabled child is not stupid or lazy and should not be blamed for his or her problem.

Levine argues forcefully that learning disabilities are inborn and specific. Both propositions, however, are already well known to those in the field. In 2002, the same year that Levine published A Mind at a Time, ten different national organizations, including the Department of Education and the Learning Disabilities Association of America, released a report describing points of consensus about learning disabilities. These two points-and others that Levine proposes-were among them. One could argue, on Levine’s behalf, that some parents and teachers do not share these beliefs and that A Mind at a Time is meant to bring important research conclusions to a broader public. The problem, however, is that Levine departs from these consensus conclusions to make a host of claims about learning disabilities that are not supported by solid research.

Levine’s Theory

Let’s examine the architecture of the mind that Levine proposes, which serves as the theoretical backdrop for his analysis of learning disabilities. Most researchers in cognitive science (and of learning disabilities) would agree with the top level of the hierarchy in Figure 1: attention, memory, and motor control are separate, though interactive, systems. The separability is important because it implies that if a system is faulty, the other systems might still operate well. But these systems do interact; it’s obvious that if you don’t pay attention in class (due to a faulty attention system), you don’t learn, even if your memory system works well. (I will return to the question of interactions below.)

Although the top level of the hierarchy is standard stuff, the second and third levels of the hierarchy he proposes are anything but. And that’s the part of the theory that Levine puts to work. Children are diagnosed and treated using concepts at the second and third level of the hierarchy. In some cases, the specific subsystems Levine identifies arguably exist-there are probably different levels of language processing much like those mentioned by Levine-but there is no research, for example, to support the existence of his 5 subprocesses of “higher order thinking” nor his 14 subprocesses of attention.

Levine’s view of sequential ordering is also inconsistent with the evidence. He appears to assign any function involving time to this process, from dribbling a basketball to punctuality. In fact, although dribbling a basketball entails timing, it is an unusual case of sequencing because the movement is largely repetitive. And there is no reason to think that keeping appointments calls on sequencing-it calls on a type of memory scientists call prospective memory. In another odd distinction, Levine argues that “automatic” language (informal speech used with peers) differs fundamentally from “literate” language (formal speech used in the classroom). These types of speech do not differ in kind, as Levine claims, but differ because the latter is more demanding than the former-formal speech is more explicit and uses a wider vocabulary. That’s why, as Levine notes, some kids can speak fluently to their friends, but are inarticulate in class. If the subsystems were separate, as he claims, one should also see the opposite pattern: kids who speak articulately in the classroom, but cannot speak informally to their parents and peers.

Seeing Is Believing

How did Levine come to his particular theory of the mind?

Since A Mind at a Time contains few references to the scientific literature, I telephoned All Kinds of Minds and asked the associate director of research if there was a more research-oriented publication that I might read. She directed me to the web site of Schools Attuned, the teacher training program Levine established to promote his prescriptions for handling learning-disabled students, which lists the “research base” for the program. This research base consists of eight works, all by Levine and coauthors, none of which appeared in a peer-reviewed journal.

A review of these works reveals that they do not marshal research evidence to support their conclusions. Instead, they present the same ideas contained in A Mind at a Time, citing a few references that support well-accepted ideas-or example, that attention capacity is limited-but none to shore up Levine’s particular views. Sometimes the citation makes no sense whatever, as when Levine and coauthor Martha Reed cite a 1993 paper by Richard McKee and Larry Squire for the idea that declarative knowledge is consolidated in categories, enabling growth in knowledge as the child gets older. In fact, the McKee and Squire study had nothing to do with the categorization of declarative knowledge-it was an investigation of the neural basis of a memory paradigm often used in infants.

Since Levine makes little use of existing research on the mind’s function, it would appear that he leans heavily on his interpretations of clinical cases that he sees in his practice. Clinical case studies are always dangerous sources of evidence because there is a tendency to “see” in these cases what one’s theory leads one to expect. Even setting that problem aside, Levine makes some mistakes in interpreting his clinical observations.

One problem lies in Levine’s moving from children’s symptoms to the hypothetical disabled cognitive systems underlying them. A classic mistake in neuropsychology is assuming that the intact mind is a mirror reflection of the impaired mind. To use a well-known analogy, if you damage a transistor in a radio and the sound becomes fuzzy, it would be a mistake to assume that a normally functioning transistor is a fuzz suppressor. In the same way, it is a mistake to assume that a cognitive subsystem must lie behind every observed clinical symptom. Levine relies on such logic, however, to validate the subsystems in his theory. According to Levine, a faulty “previewing control” subsystem makes a child impulsive. A faulty “quality control” subsystem makes a child careless in monitoring how well a task is going. These behaviors are not proof of different cognitive subsystems; they are symptoms of attention deficit hyperactivity disorder (ADHD).

Levine disagrees, and he points to the fact that different children show different symptoms. If the same cognitive subsystem were impaired, he reasons, one would observe the same symptoms, but since kids have different symptoms, different cognitive subsystems must be impaired. But variability in symptoms need not indicate different disorders. For example, patients with clinical depression may show many or few of these symptoms: change in appetite, change in sleep pattern, restlessness, difficulty concentrating, and fatigue. We do not differentiate a different type of depression for each pattern of symptoms because the underlying causes of depression are the same. Similarly, there is no clear evidence for Levine’s distinctions among different types of attention disorders, which he bases on different symptom patterns.

Levine also makes an error in logic when he considers motivation. He believes that all children want to succeed (which is easy to believe), but he takes that to mean that there is no variation in motivation (which is not easy to believe). In The Myth of Laziness, where he argues that people who appear lazy actually have “output failure,” Levine says that the subsystems supporting overt behavior are faulty. Levine describes a student who had a memory problem that led to poor spelling and writing (among other problems), which in turn made his work look careless. Levine’s sensitivity is to be applauded-no doubt some students who appear lazy have a learning disability. But it is just as certain that children vary in their motivation to succeed, due to a myriad of factors, including their home environment. It is a logical error to assert that because some children’s apparent laziness is due to a learning disability, all children who appear to lack motivation must have a learning disability.

Another mistake of interpretation that Levine makes is diminishing the importance of the interaction of cognitive systems. Most of the systems and subsystems Levine identifies depend on attention: it is necessary for the successful deployment of memory, problem solving, reasoning, language, and so on. Similarly, a limited working memory capacity-the “workbench of the mind,” where complex thought occurs-reduces one’s reasoning ability, while problem solving is profoundly influenced by long-term memory, and so on. Levine acknowledges such interactions here and there, but he never comes close to giving these effects their due in specifying the implications for diagnosis and intervention.

Doubts about Diagnosis and Treatment

Learning disabilities are far from completely understood, but some facts are relatively clear. Levine’s approach leads him to take a contrarian view of two of them: diagnostic categories and the effectiveness of medications for ADHD.

Levine goes into some detail on the pitfalls that diagnoses (he calls them “labels”) may elicit-for example, they may be used as an excuse to prescribe medication. He argues that kids should not be “labeled,” but overlooks the fact that categories are useful (or not) to the extent that they mean something. A good category allows us to make inferences about nonobvious properties: for example, categorizing an object as a dog (based on observable features such as the shape of the head, the tail) allows the inference of nonobservable features (for instance, it has lungs, it may bite). In the same way, diagnostic categories are based on observable features of the child (that is, symptoms) and tell us something about nonobservable features (such as the neural basis or associated risk factors). Refusing to use diagnostic categories is refusing to benefit from experience to infer nonobservable features. In fact, we can surmise that Levine must use diagnostic categories to some extent.

If a clinician did not generalize from past cases to current patients, he or she would have to approach each case as totally novel and as though experience had no bearing on the treatment of the case. Thus what does it mean not to use “labels”? Levine does not simply mean that one should not tell the child, “You have disorder X.” His comment in A Mind at a Time, “I have seen no convincing scientific evidence that [Asperger’s syndrome] exists as a discrete disorder of some kind like a strep throat” indicates a belief that a diagnostic category must have a clear boundary of symptoms and that the relationship between the cognitive, neural, behavioral, and genetic factors must be understood before the category is useful. Psychiatry and neurology make use of diagnostic categories that initially did not meet these criteria or still do not (for example, schizophrenia, depression, Alzheimer’s disease), but nevertheless prove useful. By demanding that diagnostic categories either be simple and clear or go unused, Levine throws the diagnostic baby out with the bathwater.

Levine also takes an odd position on the use of stimulant medications for kids with ADHD. Their use has been intensively studied, and the best research shows that they are more effective than behavioral therapies and that adding behavioral therapy to medication does not seem to work better than medication alone. It is also important to remember that untreated ADHD is associated with increased risks of substance abuse, teen pregnancy, school dropout, and other behavioral problems. These risk factors are significantly reduced by medication. You would not be aware of these facts if you read A Mind at a Time. Levine allows that “some children” “may benefit” from medications, and, elsewhere, that they “can have a dramatic positive impact on many.” But he adds a list of eight caveats to the use of medication, ending with this one: “After a thorough evaluation, it is often possible to avoid or at least delay the use of medication, as other therapeutic possibilities present themselves.” Trying behavioral therapy first is sensible, and it is of course appropriate to be cautious in prescribing any medication, but given existing data (and the medical community’s consensus), Levine is simply too sunny in his predictions.

Do Levine’s Interventions Work?

How effective is Schools Attuned, Levine’s teacher training program? As of this writing, the evaluation effort is in its infancy. Several research reports exist, but none is peer reviewed, and most offer qualitative, not quantitative, data with small sample sizes. All Kinds of Minds has provided grant money to independent researchers to evaluate the effectiveness of Schools Attuned, and that research is ongoing. It is worth pausing to dwell on this fact: there are virtually no data with which to evaluate the efficacy of this program, yet the program has been embraced by two states and by the largest city in the United States. Instead of reviewing studies that evaluate the program, we are left to guess at its likely effect on children.

As noted, Levine suggests that teachers make accommodations for students-for example, that the student who is slow in recalling facts be given extra time on an exam. Levine adds another prescription that is not commonplace; he suggests practice on the cognitive subsystem that is impaired. That is, some practice is directed at the faulty subsystem itself in an effort to improve its workings, practice that need not be centered on schoolwork. The child who cannot express himself well verbally, for example, is to tell stories at every opportunity and to play word games such as Scrabble. This strategy gives rise to two concerns.

First, such intervention depends on an accurate diagnosis. If Levine’s theory of the mind and how it fails is incorrect, some percentage of children will be diagnosed incorrectly and the remediation misdirected.

Second, Levine assumes that cognitive processes are open to direct change through practice. Some of Levine’s subsystems likely don’t exist, but those that do are known to be more or less open to practice effects. For example, long-term memory cannot be changed, but students can learn tricks and strategies (such as using visual images) that will maximize the efficiency of even a poor memory system. Such strategy instruction is a typical intervention for learning-disabled children; properly applied, it can be effective. Levine offers some good suggestions in this vein, but he also makes suggestions that are known to be wrong. For example, he argues that memory would be improved if school classes were longer, when in fact study that is distributed in time is known to be superior.

But other cognitive processes are very likely resistant to remediation. Working memory can improve with practice, but the improvement is quite specific to the practiced task and does not generalize. Levine’s suggestion to exercise it with increasingly long arithmetic problems will yield little benefit. Also, problem solving or other higher-level thinking skills are very difficult to practice in any direct sense, in part because they are so closely tied to background knowledge. There are no general-purpose tricks to be learned that can improve them as there are with long-term memory.

Some of Levine’s interventions are designed to help the child’s emotional life, and those are both simple to implement and likely to be effective. As noted, Levine suggests that teachers avoid revealing to the student’s peers that the child has a deficit. Levine also emphasizes explaining to the child why she is having trouble in school and emphasizing that the problem is self-contained; the child should not think of herself as stupid. I suspect that many sensitive teachers are already following these guidelines. Still, Levine does well to assume that they are not and to emphasize their importance.

Other Levine ideas are more novel but still deserve consideration. Students should not take the identification of a learning disability as an excuse for poor performance, Levine argues, but rather as a reason to work all the harder. Further, Levine suggests that teachers should request “payback” from the student for the accommodation. Payback could bring several benefits: it not only represents fairness to the rest of the class, but also communicates to the student that she is as responsible as anyone else in the class to work hard and that she has talents to draw on. These prescriptions strike me as insightful, powerful, and uncommon. Levine is at his best when he considers the emotional life of learning-disabled children.

A Final Analysis

I began by asking whether Levine’s theory is accurate and whether there is evidence that his program will help children. The answer to the first question should be clear; in scientific terms, A Mind at a Time and The Myth of Laziness are riddled with error. Even worse, there is currently no evidence regarding the effectiveness of the Schools Attuned program, and the inaccuracy of the theory makes it inevitable that some kids are going to be misdiagnosed and some interventions are going to be misapplied or faulty. Further, Levine does not acknowledge that a sizable fraction of the kids in special-education classes identified as learning disabled don’t have a cognitive problem; they have an emotional disturbance or a chaotic home life.

These problems don’t mean that Schools Attuned will be a disaster. The program calls for teachers to provide more individual attention, for parents to change the student’s home environment, or for other professionals to be brought in to work with the child. Such emotional support and care may well have beneficial effects on the child’s attitude toward school and subsequent effort. But I suspect that another program able to recruit the same resources from parents, teachers, and other professionals but based on solid research evidence would prove more effective.

The obstacles to recruiting these resources are not trivial. Levine is a clinician, meaning he deals with parents who care enough to bring their child in to be evaluated and therefore are probably invested enough to take on the extra work with their children that Levine prescribes. Special-education teachers in schools more often deal with parents who are not so invested. Still, motivating others may be Levine’s greatest strength; he writes positively and passionately about the potential in every child.

Perhaps the greatest testimony to Levine’s passion and power of persuasion is that decisionmakers in North Carolina, Oklahoma, and New York City have invested good money and staked the learning of vulnerable children on Schools Attuned, not with solid evidence of efficacy, but because it sounded good to them-they didn’t have anything else to go on.

Daniel T. Willingham is a professor of psychology at the University of Virginia. Willingham thanks Rick Brigham for help in the preparation of this article.

The unabridged version of this article may be found at www.educationnext.org.