The PIRLS Reading Result–Better than You May Realize

by Dan Willingham
December 17th, 2012

This was written by cognitive scientist Daniel Willingham, professor of psychology at the University of Virginia and author of  “When Can You Trust The Experts? How to tell good science from bad in education.” This appeared on his Science and Education blog.

The PIRLS results are better than you may realize.

Last week, the results of the 2011 Progress in International Reading Literacy Study (PIRLS) were published. This test compared reading ability in 4th grade children.

U.S. fourth-graders ranked 6th among 45 participating countries. Even better, US kids scored significantly better than the last time the test was administered in 2006.

There’s a small but decisive factor that is often forgotten in these discussions: differences in orthography across languages.

Lots of factors go into learning to read. The most obvious is learning to decode–learning the relationship between letters and (in most languages) sounds. Decode is an apt term. The correspondence of letters and sound is a code that must be cracked.

In some languages the correspondence is relatively straightforward, meaning that a given letter or combination of letters reliably corresponds to a given sound. Such languages are said to have a shallow orthography. Examples include Finnish, Italian, and Spanish.

In other languages, the correspondence is less consistent. English is one such language. Consider the letter sequence “ough.” How should that be pronounced? It depends on whether it’s part of the word “cough,” “through,” “although,” or “plough.” In these languages, there are more multi-letter sound units, more context-dependent rules and more out and out quirks.

Another factor is syllabic structure. Syllables in languages with simple structures typically (or exclusively) have the form CV (i.e., a consonant, then a vowel as in “ba”) or VC (as in “ab.”) Slightly more complex forms include CVC (“bat”) and CCV (“pla”). As the number of permissible combinations of vowels and consonants that may form a single syllable increases, so does the complexity. In English, it’s not uncommon to see forms like CCCVCC (.e.g., “splint.”)

Here’s a figure (Seymour et al., 2003) showing the relative orthographic depth of 13 languages, as well as the complexity of their syllabic structure.

From Seymour, et. al. (2003)

Orthographic depth correlates with incidence of dyslexia (e.g., Wolf et al, 1994) and with word and nonword reading in typically developing children (Seymour et al. 2003). Syllabic complexity correlates with word decoding (Seymour et al, 2003).

This highlights two points, in my mind.

First, when people trumpet the fact that Finland doesn’t begin reading instruction until age 7 we should bear in mind that the task confronting Finnish children is easier than that confronting English-speaking children. The late start might be just fine for Finnish children; it’s not obvious it would work well for English-speakers.

Of course, a shallow orthography doesn’t guarantee excellent reading performance, at least as measured by the PIRLS. Children in Greece, Italy, and Spain had mediocre scores, on average. Good instruction is obviously still important.

But good instruction is more difficult in languages with deep orthography, and that’s the second point. The conclusion from the PIRLS should not just be “Early elementary teachers in the US are doing a good job with reading.” It should be “Early elementary teachers in the US are doing a good job with reading despite teaching reading in a language that is difficult to learn.”

References

Seymour, P. H. K., Aro, M., & Erskine, J. M. (2003). Foundation literacy acquisition in European orthographies. British Journal of Psychology, 94, 143-174.

Wolf, M., Pfeil, C., Lotz, R., & Biddle, K. (1994). Towarsd a more universal understanding of the developmental dyslexias: The contribution of orthographic factors. In Berninger, V. W. (Ed), The varieties of orthographic knowledge, 1: Theoretical and developmental issues.Neuropsychology and cognition, Vol. 8., (pp. 137-171). New York, NY, US: Kluwer

Why Great Teachers Are Story Tellers

by Dan Willingham
March 28th, 2009

Just about every teacher at some point tries to trick their students into learning something by making it “relevant” to students’ interests.   You might be surprised to learn that I don’t think much of this technique.   I love cognitive psychology, so you might think, “Well, to get Willingham to pay attention to this math problem, we’ll wrap it up in a cognitive psychology example.” But Willingham is quite capable of being bored by cognitive psychology, as has been proved repeatedly at professional conferences I’ve attended.   Trying to make problems “relevant” can also feel forced and artificial, and students see right through the ruse. 

So if content isn’t the way to engage students, how about your teaching style? Students often refer to good teachers as those who “make the stuff interesting.” It’s not that the teacher relates the material to students’ interests-rather, the teacher has a way of interacting with students that they find engaging.

When we think of a good teacher, we tend to focus on personality and on the way the teacher presents himself or herself. But that’s only half of good teaching. The jokes, the stories, and the warm manner all generate goodwill and get students to pay attention. But then how do we make sure they think about meaning? That is where the second property of being a good teacher comes in-organizing the ideas in a lesson plan in a coherent way so that students will understand and remember. Cognitive psychology cannot tell us how to be personable and likable to our students, but I can tell you about one set of principles that cognitive psychologists know about to help students think about the meaning of a lesson.

The human mind seems exquisitely tuned to understand and remember stories-so much so that psychologists sometimes refer to stories as “psychologically privileged,” meaning that they are treated differently in memory than other types of material. I’m going to suggest that organizing a lesson plan like a story is an effective way to help students comprehend and remember.   

First, stories are easy to comprehend, because the audience knows the structure, which helps to interpret the action. For example, the audience knows that events don’t happen randomly in stories.  Second, stories are interesting and engage listeners more readily that other formats, even if the same information is presented.  Lastly, stories are easy to remember.

I’m not suggesting that teachers simply tell stories, although there’s nothing wrong with doing so. Rather, I’m suggesting something one step removed from that. Structure your lessons the way stories are structured, using the four Cs: causality, conflict, complications, and character. This doesn’t mean you must do most of the talking. Small group work or projects or any other method may be used. The story structure applies to the way you organize the material that you encourage your students to think about, not to the methods you use to teach the material.

Daniel T. Willingham is a professor of psychology at the University of Virginia and the author of Why Students Don’t Like School: A Cognitive Scientist Answers Questions About How the Mind Works and What it Means for the Classroom (Jossey-Bass, 2009) from which this post was adapted. 

How Can I Help Slow Learners?

by Dan Willingham
March 27th, 2009

We’ve all heard anecdotes about accomplished people who struggled in school: Albert Einstein failed his first college entrance exam.  William Faulkner won a Nobel Prize for Literature without ever having accumulated enough credits to finish high school.  And Charles Schultz, the creator of the Peanuts comics had his illustrations rejected by his high school yearbook.  Doing well in school is not an absolute prerequisite for later success.  Still, teachers naturally want all students to get as much as they can from school.  How can we optimize school for students who don’t have the raw intelligence of other students?

Americans tend to view intelligence as a fixed attribute, like eye color. If you win the genetic lottery, you’re smart; but if you lose, you’re not. In China, Japan, and other Eastern countries, intelligence is more often viewed as malleable. If students fail a test or don’t understand a concept, it’s not that they’re stupid-they just haven’t worked hard enough yet. There is some truth in both.   Children do differ in intelligence, but intelligence can be changed through sustained hard work.   This belief in the malleable intelligence for students has many implications for classroom teachers and should play a role in how you administer praise and talk to students about their successes and failures.

 There is overwhelming evidence that there is a general intelligence.  It’s usually called g, short for general intelligence.  What exactly is g? It’s not known. People suggest it might be related to the speed or the capacity of working memory, or even that it’s a reflection of how quickly the neurons in our brains can fire. Knowing what underlies g is less important than knowing that g is real.  Having a lot of g predicts that we will do well in school and well in the workplace.

Still, if intelligence were all a matter of one’s genetic inheritance, then there wouldn’t be much point in trying to make kids smarter. Instead, we’d try to get students to do the best they could given the genetically determined intelligence they have. We’d also think seriously about trying to steer the not-so-smart kids toward intellectually undemanding tracks in schools, figuring that they are destined for low-level jobs anyway. But that’s not the way things are. Intelligence is malleable. It can be improved.

Slow learners are not dumb.  They probably differ little from other students in terms of their potential.   This should not be taken to mean that these students can easily catch up. Slow students have the same potential as bright students, but they probably differ in what they know, in their motivation, in their persistence in the face of academic setbacks, and in their self-image as students. I fully believe that these students can catch up, but it must be acknowledged that they are far behind, and that catching up will take enormous effort. How can we help? To help slow learners catch up, we must first be sure they believe that they can improve, and next we must try to persuade them that it will be worth it.

I have several suggestions in my book, including 1) praise effort, not ability; 2) tell students that hard work pays off; and 3) treat failure as a natural part of learning.  Points 2 and 3 are nicely made in this You Tube video titled Famous Failures:

Try to create a classroom atmosphere in which failure, while not desirable, is neither embarrassing nor wholly negative. Failure means you’re about to learn something. You’re going to find out that there’s something you didn’t understand or didn’t know how to do. Most important, model this attitude for your students. When you fail-and who doesn’t?-let them see you take a positive, learning attitude.

 Tomorrow:  Great teachers are story tellers.

Daniel T. Willingham is a professor of psychology at the University of Virginia and the author of Why Students Don’t Like School: A Cognitive Scientist Answers Questions About How the Mind Works and What it Means for the Classroom (Jossey-Bass, 2009) from which this post was adapted. 

How Can We Get Students to Think Like Experts?

by Dan Willingham
March 26th, 2009

“How can we expect to train the next generation of scientists if we are not training them to do what scientists actually do?”  This sounds sensible, even insightful,  but students are not cognitively capable of doing what scientists (or historians, writers, mathematicians, etc.) do.   It’s not just that students know less than experts.  As I’ll describe, what experts know is organized differently in their memory.

Even the greatest scientists do not think like experts when they start out. They think like novices. It’s not possible to think like a scientist or a historian without a great deal of training. Does this mean we shouldn’t ask students to write a poem or conduct a scientific experiment?  Of course not. (Some great examples and ideas for history can be found at the National History Education Clearninghouse). But we should understand the difference between the thought processes of experts and novices. 

Accomplished mathematicians, scientists, and historians have worked in their field for years, and the knowledge and experience they have accumulated enables them to think in ways that are not open to the rest of us. Thus, trying to get your students to think like them is not a realistic goal. “Well, sure,” you might be thinking. ” I never really expected that my students are going to win the Nobel Prize! I just want them to understand some science.” That’s a worthy goal, but it is very different than the goal of students thinking like experts.

Real scientists are experts. They have worked at science for forty hours (or more) each week for years. Those years of practice make a qualitative–not quantitative–difference in the way they think compared to how even a well-informed amateur thinks.  It will surely not surprise you to learn that experts have lots of background knowledge in their area of expertise. But the expert mind has another edge over the rest of us. The information in long-term memory is organized differently than the information in working memory.  We can generalize by saying that experts think abstractly.  When confronted with a classroom management problem, for example, novice teachers typically jump right into trying to solve the problem, but experts first seek to define the problem, gathering more information if necessary. Thus expert teachers have knowledge of different types of classroom management problem. Not surprisingly, expert teachers more often solve these problems in ways that address root causes and not just the behavioral incident. For example, an expert is more likely than a novice to make a permanent change in seating assignments.

Seeing things abstractly enables experts to home in on important details among a flood of information, to produce solutions that are always sensible and consistent (even if they are not always right), and to show some transfer of their knowledge to related fields. In addition, many of the routine tasks that experts perform have become automatic through practice.

Sounds great. How can we teach students to do that? Unfortunately, the answer to this question is not exactly cheering. The only path to expertise, as far as anyone knows, is practice.  One other interesting factor:  Great scientists are almost always workaholics. They have incredible persistence, and their threshold for mental exhaustion is very high. 

So if we can’t get students to think like experts what’s a reasonable goal?  Drawing a distinction between knowledge understanding and knowledge creation may help. Experts create. For example, scientists create and test theories of natural phenomena, historians create narrative interpretations of historical events, and mathematicians create proofs and descriptions of complex patterns. Experts not only understand their field, they also add new knowledge to it.  A more modest and realistic goal for students is knowledge comprehension. Student may not be able to develop their own scientific theory, but they can develop a deep understanding of existing theory.  A student may not be able to write a new narrative of historical fact, but she can follow and understand a narrative that someone else has written.

Tomorrow: How can I help slow learners?

Daniel T. Willingham is a professor of psychology at the University of Virginia and the author of Why Students Don’t Like School: A Cognitive Scientist Answers Questions About How the Mind Works and What it Means for the Classroom (Jossey-Bass, 2009) from which this post was adapted. 

In Defense of Practice

by Dan Willingham
March 25th, 2009

“Drill and kill” are dirty words in education.  The teacher drills the students, which is said to kill their innate motivation to learn.  The word drill conjures up military imagery not associated with the more neutral term practice, which means the same thing.  On the other side of this debate are educational traditionalists who argue that students must practice in order to learn some facts and skills they need at their fingertips-for example, math facts. 

For teachers, the important question is whether the cognitive benefit of automaticity make it worth the potential cost to motivation.  The answer is that it is sometimes worth it, and even necessary. The question is how to get the benefits of practice while minimizing the costs.

Why do I say that practice is necessary? One benefit of practice is to gain a minimum level of competence. A child practices tying her shoelaces with a parent or teacher’s help until she can reliably tie them without supervision.  Less obvious are the reasons to practice skills when it appears you have mastered something and it’s not obvious that practice is making you any better. Odd as it may seem, that sort of practice is essential to schooling. It yields three important benefits: it reinforces the basic skills that are required for the learning of more advanced skills, it protects against forgetting, and it improves transfer-the ability to apply what we know in different circumstances. 

Working memory is the where thinking occurs   A critical feature of working memory is that it has limited space.  There are, however, ways to cheat this limitation. The first way is through factual knowledge, as I discussed yesterday. A second way is to make the processes that manipulate information in working memory more efficient.  In fact, you can make them so efficient that they are virtually cost free. Think about learning to tie your shoes. Initially it requires your full attention and thus absorbs all of working memory, but with practice you can tie your shoes without thinking about it. 

Likewise, beginning readers slowly and painstakingly sound out each letter and then combine the sounds into words, so there is no room left in working memory to think about meaning.  When students are first introduced to arithmetic, they often solve problems by using counting strategies until they gain command of basic math facts.  Learning to write or keyboard letters is laborious and consumes all of working memory, leaving you unable to think of the content of what you’re trying to write until it becomes automatic. 

What’s true of reading, writing and math is true of most or all school subjects, and of the skills we want our students to have. They are hierarchical. There are basic processes (like retrieving math facts or using deductive logic in science) that initially are demanding of working memory but with practice become automatic. Those processes must become automatic in order for students to advance their thinking to the next level.

So now we get to the payoff: What is required to make these processes shrink, that is, to get them to become automatized? You know the answer: practice. There may be a workaround, a cheat, whereby you can reap the benefits of automaticity without paying the price of practicing, but if there is, neither science nor the collected wisdom of the world’s cultures has revealed it. As far as anyone knows, the only way to develop mental facility is to repeat the target process again and again and again.

If practice makes mental processes automatic, we can then ask, which processes need to become automatic? Retrieving number facts from memory seems to be a good candidate, as does retrieving letter sounds from memory. A science teacher may decide that his students need to have at their fingertips basic facts about elements. In general, the processes that need to become automatic are probably the building blocks of skills that will provide the most benefit if they are automatized. Building blocks are the things one does again and again in a subject area, and they are the prerequisites for more advanced work.

Tomorrow:  How Can We Get Students to Think Like Experts?

Daniel T. Willingham is a professor of psychology at the University of Virginia and the author of Why Students Don’t Like School: A Cognitive Scientist Answers Questions About How the Mind Works and What it Means for the Classroom (Jossey-Bass, 2009) from which this post was adapted. 

 

Understanding is Remembering in Disguise

by Dan Willingham
March 24th, 2009

In today’s world, is there a reason to memorize anything? You can find any factual information you need in seconds via the Internet.  Perhaps instead of learning facts, some teachers believe it’s better to practice critical thinking, to have students work at evaluating all the information available on the Internet rather than trying to commit some small part of it to memory.

Data from the last thirty years lead to a conclusion that is not scientifically challengeable: thinking well requires knowing facts, and that’s true not simply because you need something to think about. The very processes that teachers care about most-critical thinking processes such as reasoning and problem solving-are intimately intertwined with factual knowledge that is stored in long-term memory (not just found in the environment). 

Much of the time when we see someone apparently engaged in thinking, he or she is actually engaged in memory retrieval.   As I described yesterday, memory is the cognitive process of first resort. When faced with a problem, you will first search for a solution in memory, and if you find one you will very likely use it.  For example, you might have a friend who can walk into someone else’s kitchen and produce a nice dinner from whatever food is around.  When your friend looks in a cupboard, she doesn’t see ingredients, she see recipes. She’s drawing on her extensive background knowledge about food and cooking.  Take her to the garage instead, give her a box of auto parts and she will not be able to rebuild your carburetor. 

It’s often difficult for students to understand new ideas, especially ones that are really novel, meaning they aren’t related to other things they have already learned.  That’s because people understand new ideas (things we don’t know) by relating them to old ideas (things we do know).

Teachers put this idea to work all the time when they use analogies, which help us understand something new by relating it to something we already know about.  Science textbooks, for example, usually compare electricity to the movement of water. Electrons moving along a wire are like water moving through a pipe.

So, understanding new ideas is mostly a matter of getting the right old ideas into working memory and then rearranging them-making comparisons we hadn’t made before, or thinking about a feature we had previously ignored.

This is why understanding is remembering in disguise. No one can pour new ideas into a student’s head directly. Every new idea must build on ideas that the student already knows. To get a student to understand, a teacher (or a parent or book or television program) must ensure that the right ideas from the student’s long-term memory are pulled up and put into working memory.

Even this is easy to say but hard to accomplish.  Give a student an explanation and a set of examples, and they probably still don’t understand right away.  Even when students “understand,” there are really degrees of comprehension. One student’s understanding can be shallow while another’s is deep. Second, even if students understand in the classroom, this knowledge may not transfer well to the world outside the classroom. That is, when students see a new version of what is at heart an old problem, they may think they are stumped, even though they recently solved the same problem. They don’t know that they know the answer!  I elaborate in detail on these two issues – shallow knowledge and lack of transfer – in my book. 

Tomorrow:  In defense of practice

Daniel T. Willingham is a professor of psychology at the University of Virginia and the author of Why Students Don’t Like School: A Cognitive Scientist Answers Questions About How the Mind Works and What it Means for the Classroom (Jossey-Bass, 2009) from which this post was adapted. 

Why Don’t Students Like School?

by Dan Willingham
March 23rd, 2009

I have been writing about cognitive science and education for about six years now, and teachers have thrown a lot of questions at me. Many I did not feel comfortable answering-I felt that cognitive science didn’t have much to contribute. But for othersI felt that scientists did have some relevant knowledge that might apply to the classroom. When I heard such a question, I tucked it away.

After several years of saving questions, I collected nine that I thought were really central to teaching. The result was a book, Why Don’t Students Like School? This week I will post one entry each day that describes one question posed in the book and a highly abridged version of my answer.

The title-Why Don’t Students Like School? is not the question that I have been asked most often, but it is, to me, the most important. After I gave a talk at a conference, a ninth grade teacher asked me this question, obviously disappointed and frustrated. As she noted, almost everyone says that they like to learn new things; so why don’t students like school more?

It usually surprises people – and depresses teachers — when I tell them the brain is not designed for thinking. It’s designed to keep you from having to think. In fact, the brain is actually not very good at thinking.

Your brain serves many purposes, and thinking is not the one it serves best. Your brain supports the ability to see and to move, for example, and these functions operate much more efficiently and reliably than your ability to think. It’s no accident that most of your brain’s real estate is devoted to these activities. Compared to your ability to see and move, thinking is slow, effortful, and uncertain.

 About now you’re probably asking yourself, “Well, if we’re so bad at thinking, how do we function at all? How do we find our way to work or spot a bargain at the grocery store? How does a teacher make the hundreds of decisions necessary to get through her day?” The answer is that when we can get away with it, we don’t think.  We rely on memory, which is much more reliable than thinking.  Most of the problems we face are ones we’ve solved before, so we just do what we’ve done in the past.  We think of “memory” as storing personal events and facts, but it also stores strategies to guide what we should do: where to turn when driving home, how to handle a minor dispute when monitoring recess, what to do when a pot on the stove starts to boil over.  For the vast majority of decisions we make, we don’t stop to consider what we might do, reason about it, anticipate possible consequences, and so on. We just do what we always do. 

Saying we’re not very good at thinking sounds grim for educators.  But don’t despair. 

Despite the fact that we’re not that good at it, we actually like to think. We are naturally curious, and we look for opportunities to engage in certain types of thought. But because thinking is so hard, the conditions have to be right for this curiosity to thrive, and we quit thinking rather readily.  Solving problems – which I define as cognitive work that succeeds – makes us feel good.   

 From a cognitive perspective, an important consideration for educators is whether or not a student consistently experiences the pleasurable rush of solving a problem. What can teachers do to ensure that each student gets that pleasure?  I describe several practical applications in my book, but for now, I’ll focus on just one:  view schoolwork as a series of answers.  Sometimes I think that we, as teachers, are so eager to get to the answers that we do not devote sufficient time to developing the question. But it’s the question that piques people’s interest. Being told an answer doesn’t do anything for you.  When you plan a lesson, start with the information you want students to know by its end.  As a next step, consider what the key question for that lesson might be and how you can frame that question so it will have the right level of difficulty to engage your students.  

Lastly some practical advice:  Finding the sweet spot of difficulty is not easy. Your experience in the classroom is your best guide-if it works, do it again; if it doesn’t, discard it. But don’t expect that you will really remember how well a lesson worked a year later. Whether a lesson goes brilliantly well or down in flames, it feels at the time that we’ll never forget what happened, but the ravages of memory can surprise us, so write it down.  It’s worth making a habit of recording your success in gauging the level of difficulty in the problems you pose for your students.

Tomorrow: Why understanding is remembering in disguise.

 Daniel T. Willingham is a professor of psychology at the University of Virginia and the author of Why Students Don’t Like School: A Cognitive Scientist Answers Questions About How the Mind Works and What it Means for the Classroom (Jossey-Bass, 2009) from which this post was adapted. 

Why Nature (and Recess) Might Help Kids Learn

by Dan Willingham
January 8th, 2009

A few months back Robert posted an entry on “Nature Deficit Disorder“–the idea that children today don’t get enough time outdoors. The concern, according to Richard Louv, author of “Last Child in the Woods” is that interaction with nature helps develop important cognitive abilities. I said at the time that I was unaware of any research supporting the idea. I have since learned that there are data supporting something like this claim, at least.

The basic finding is not that interaction with nature is important for development, but that it is “restorative.” Several studies published in the last few years have shown that people do better on certain attention-demanding tasks after a brief interaction with nature. A recent study (Berman et al, 2008, Psychological Science, 19, 1207-1212) provides a convincing argument for what is behind the effect.

Here’s the basic idea: there are two ways that attention can be directed. In one case, attention is directed to something that you find inherently intriguing, e.g., a beautiful painting, or the flames in a fireplace.  In the other case, you direct attention to something that you want to think about (and you suppress attention going elsewhere).  This latter type of attention is more fatiguing.  This distinction between kinds of attention has been around for over 100 years, and a good deal of behavioral and neural data collected in the last thirty years supports it.

Interaction with nature provides, for most of us, lots of stimuli of inherent interest. We like to look at birds, flowers, and trees. Urban environments, in contrast, provide too many stimuli to which we direct attention–for example, the car that you’re afraid won’t slow down at the intersection–and also pelts us with so many stimuli that we must do a lot of suppression to avoid being overwhelmed. So interaction with nature is restorative because it provides a rest for the directive attention system.  Interestingly, the experimenters observed a difference in cognitive performance even after watching slides of nature vs. slides of urban environments. So it’s not just the peace and quiet of nature that’s behind the effect.

This directive type of attention is, many people believe, especially important to schooling. This finding fits well with other data showing that recess does provide a cognitive boost for students.

Would it help to project slides of natural scenes at urban schools during recess? It might be worth a try. The size of the effect reported in this experiment was not small.

Reading Strategies: A Little Goes a Long Way

by Dan Willingham
August 28th, 2008

Yesterday I argued that the knowledge readers bring to a text is essential to reading comprehension. But does even a knowledgeable reader comprehend automatically? Mustn’t the reader apply comprehension strategies to extract meaning from the text? The short answer is that teaching students comprehension strategies does help, but too much time is currently devoted to them.

Reading comprehension strategies include things like question generation (students are taught to generate questions about a text and then answer them) comprehension monitoring (students are taught to become aware of when they do not understand), and summarization (students are taught techniques to summarize meaning). Often, multiple strategies are taught.

The National Reading Panel  reviewed 205 studies examining the effectiveness of teaching students reading strategies, and there is little doubt that they help, and that the effect is sizable.

There are two aspects of the data which deserve special attention because they hold implications for classroom application. First, the effects of teaching students reading strategies are weak or absent before the third grade.  This finding is readily understandable—students are still learning to decode, and simply can’t juggle in mind the tasks of decoding, comprehending, and trying to implement a strategy. It’s only when decoding has become fluid so that the reader doesn’t need to think about it much that enough mental space is free to accommodate a strategy.

Second, when it comes to teaching students to use reading strategies, shorter programs seem just as effective as longer programs. This finding is crucial, because it ought to make us think differently about what reading strategies actually do. It’s natural to think that strategies improve the reader’s skill in extracting meaning from a text. But if that were true then more practice ought to make you better at it. Instead, comprehension strategies feel less like a skill and more like a trick—something like “check your work” in mathematics. It’s a very smart thing to do, and students should be explicitly taught to do it, but it doesn’t require extensive practice.

What might the trick of comprehension strategies be? A good guess is that they encourage students to think differently about reading. There is so much emphasis on decoding in early reading instruction (as there must be) that it is understandable that a student might think “If I’ve decoded, then I’ve read it.” But an adult knows that if you get to the bottom of a page and don’t know what you’ve read, you haven’t really read it, even if you’ve decoded everything. That conception of reading—that the point is communication—must click for students, and comprehension strategies may have most of their impact in getting students to think about reading as something they do to understand. Once they understand that, most of what comprehension strategies advise is something that students will do naturally: try to find the main idea, check your own comprehension, and so on.

The bottom line is that teaching comprehension strategies is a good idea, but it appears to be a one-time boost. There is no evidence that more practice yields more benefit. More information on this subject can be found here: http://www.aft.org/pubs-reports/american_educator/issues/winter06-07/CogSci.pdf

On Reading: Why Content Knowledge Matters

by Dan Willingham
August 27th, 2008

Why is content knowledge so important to reading? A couple of reasons are obvious: (1) you can’t comprehend if you’re missing some of the vocabulary, and (2) the text might use vocabulary you know, but reference ideas that you don’t know. For example, the sentence “Gosh, it’s January 5th-I’ve got to go get some wheatberries and raisins!” doesn’t use unusual vocabulary words, but it’s not sensible unless you know that the speaker is Armenian, and that a traditional dish for January 6 (Armenian Christmas) is a pudding that includes those ingredients.

But content knowledge serves reading in more subtle ways. A key feature of all writing (and speaking) is that information is omitted. For example, suppose you read the following sentence:

John said ‘look Dave, I would stand in line with you for the tickets, but I’ve used up all my sick days.’ 

There are two key ideas in the sentence: (1)  John wants to stand in line for the tickets but can’t and (2) John has used up his sick days. The second idea is offered as an explanation for the first.  But notice that a good deal of information that is necessary for the right interpretation is actually missing from the text. You need to know that (1) people may wait hours in line for tickets to entertainment events; (2) people may use sick days to avoid work even when they are not sick and (3) people are reluctant or unwilling to skip work when they have used all their sick days because their pay may be docked.  The writer has omitted this information, gambling that the reader already knows it, and can fill the logical gap in the sentence.  If the reader does not have the requisite background knowledge, he or she doesn’t comprehend the sentence.

Writers must omit some information-if they didn’t, writing would be impossibly repetitive and tedious. So readers must bring background knowledge to the task of reading so that they are ready to fill the gaps that writers will leave.  Small wonder that students who score poorly on reading tests suddenly look like terrific readers when given a passage on a topic that they know a lot about.

 I’ve described just one of the more subtle ways that background knowledge helps reading comprehension. There are others, described here http://www.aft.org/pubs-reports/american_educator/issues/spring06/willingham.htm.