This piece first appeared on RealClearEducation.com on April 16, 2014.
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A recent article in the Washington Post sounds a warning klaxon for our ability to read deeply. You’ve probably heard this argument elsewhere, made most forcefully by Nick Carr in the The Shallows: frequent users of the Web (i.e., most of us) are so in the habit of skittering from page to page, scanning for juicy bits of information but not really reading, that they have lost the ability to sit down and read prose from start to finish. I think the suggestion is probably wrong.

The first thing to make clear is that anyone who comments on this issue (including me) is guessing. There are simply not any data that address it directly. We might predict, for example, that scores on standardized reading tests would have dropped in the last fifteen years or so (they haven’t) but such data are hardly definitive, as reading comprehension test scores are a product of many factors.

The Post article cites studies comparing reading on paper versus reading on screens, but that won’t address the issue, which concerns the long-term consequences of a particular type of reading. The Post also incorrectly says that paper is superior. Most studies indicate no difference between screens and paper for pleasure reading. For textbook reading, students take longer to read on screens, although comprehension is about the same. (Daniel & Willingham, 2012).

The article, like all the pieces I’ve seen on this topic, is short on data and long on individual’s impressions. For example, teachers aver that students can no longer read long novels. Well, if we’re swapping stories, I (and most of my classmates) had a hard time with Faulkner and Joyce back in the early ‘80’s, when I was an English major.

The truth is probably that the brain is simply not adaptable enough for such a radical change. Yes, the brain changes as a consequence of experience, but there are likely limits to this change, a point made by both Steve Pinker and Roger Schank when commenting on this issue. If our ability to deploy attention or to comprehend language processes were to undergo substantial change, the consequences would cascade through the entire cognitive system, and so the brain is probably too conservative for large-scale change.

For example, there’s a lot of overlap in the processes of reading and the processes used for understanding spoken speech—processes that assign syntactic roles to words. Do we see any evidence that people are having a harder time understanding spoken language? Or does the problem lie in the mental processes that build understanding of larger blocks of language, as when we’re comprehending a story? If so, habitual Web users should have a hard time understanding complex narratives not just when they read, but in television and movies. No one should have watched The Sopranos, with its complicated, interweaving plotlines.

A more plausible possibility is that we’re not less capable of reading complex prose, but less willing to put in the work. Our criterion for concluding “this is boring. This is not paying off” has been lowered because the Web makes it so easy to find something else to read, watch, or listen to. (I explore the possibility in some detail in my upcoming book, Raising a Reader in an Age of Distraction.) If I’m right, there’s good news and bad news. The good news is that our brains are not being deep-fried by the Web; we can still read deeply and think carefully. The bad news is that we don’t want to.

Reference

Daniel, D. B. & Willingham, D. T. (2012). Electronic textbooks: Why the rush? Science, 335, 1569-1571.

This post first appeared at RealClearEducation on April 1, 2014.

Our scientific understanding is always evolving, changing. Thus, one of the ongoing puzzles in education research is how confident one must be in a set of findings before one concludes it ought to be the basis of educational practice. If the data show that X is true, but X seems really peculiar, do we assume X is probably true, or do we assume that we just don't understand things very well yet? A new study provides something of an object lesson in this problem; in this case "X" was "parents teaching reading at home doesn't help much after kindergarten."

Here's the background on that counterintuitive finding. The work was inspired by the home literacy model (Senechal & LeFevre, 2000). It posits two dimensions of home literacy experience: formal experiences are those in which the parent focuses the child's attention on print, for example by teaching letters of the alphabet, or pointing out that two words look the same, or that we read from left to right.

Informal experiences are those for which print is present, but is not the focus of attention; reading aloud to one's child would be an example. Children usually look at pictures, not print, during a read-aloud.

Previous research from this research team, and others, has shown that formal and informal experiences have different effects. Formal experiences are associated with early literacy skills like knowing letters, and later, with word reading. Informal experiences, in contrast, are associated with growth in vocabulary and general knowledge.

But data supporting the home literacy model have usually been concurrent, not predictive, and have been limited to preschool, kindergarten, and early 1st grade. That is, the research shows an association between the relevant factors measured now, as opposed to showing that the home factors at, say, kindergarten, predict growth in reading outcomes for the 1st grade and beyond. That's peculiar.

There are at least two possible reasons. One is that the home literacy environment does have an impact on literacy growth, but researchers have been looking for the effect in 1st grade - just at the time that school instruction is so heavy. So perhaps the impact of home literacy environment on literacy growth is overwhelmed by the effect of school instruction. A second possible reason is that the home literacy environment may change as a consequence of how the parents perceive their child is doing in school.

A new study (Senechal & LeFevre, 2014) used a clever design to examine both possibilities. Subjects were 84 children in Quebec who spoke English at home, but for whom the language of instruction at school was French. So researchers could test progress in English, and thereby examine the impact of the home literacy environment independent of schooling. The research measured various aspects of children's literacy -- reading and oral language -- from kindergarten until spring of second grade. In addition, researchers used a number of measures to characterize their formal and informal literacy experiences at home.

The results provided strong support for the Home Literacy Model. Formal literacy activities at home were linked not only to performance in reading English, but, in contrast to prior work, a relationship was observed with growth in reading English from kindergarten to 1st Grade. Thus, there is some support of the idea that previous studies failed to observe the relationship because the experiences at school overwhelmed any effect that home experiences might have had.

But that can't be the whole story, because the relationship was no longer observed in 2nd grade. This is where parental responsiveness comes in. English instruction, one hour daily, began in 2nd grade, and so parents began to get feedback from schools about their child's English reading at that time.

Researchers found that the degree to which parents taught their children English at home was positively associated with student outcomes in kindergarten and 1st grade. But there was a negative association in 2nd grade. A straightforward interpretation is that many parents engaged in some English teaching at home during kindergarten and 1st grade, and the more of it they did, the better for their kids. Then in 2nd grade, parents get feedback from the school about their child's reading in English. If their child is doing well, parents ease off on the teaching at home. If their child is doing poorly, they increase reading. Indeed, researchers found that most parents -- 76 percent -- changed their formal literacy practices in response to their child's reading performance in 2nd grade. So you end up with a negative correlation of parental instruction and child performance in 2nd grade. The kids who are doing the worst in reading are the ones whose parents are teaching them the most.

The impact of informal literacy activities like read-alouds did not change; they were consistently linked to growth in vocabulary and other measures of oral language from kindergarten through second grade.

It should be noted that the parents in this study had greater than average education - more than half had a university degree. It's a good bet then, that the baseline home literacy environment was atypically high and that these parents may have been more responsive to their child's literacy outcomes than others would have been. We should not generalize these findings broadly.

Still, in this case, "X" turned out to be explicable and sensible. It appeared that parents teaching literacy at home did not help children's literacy because other variables had gone uncontrolled. This study doesn't solve the broader problem - we never know if our understanding of an issue is incomplete to the point of inaccuracy - but that's one issue on which we are at least closer to the truth. 

References:

Senechal, M., & LeFevre, J. (2002). Parental involvement in the development of children’s reading skill: A 5-year longitudinal study. Child Development, 73, 445–460.

Senechal M. & Lefevre, J. (in press). Continuity and change in the home literacy environment as predictors of growth in vocabulary and reading. Child Development.

This piece first appeared on RealClearEducation.com on March 26.

How do you know that whether a book is at the right level of difficulty for a particular child? Or when thinking about learning standards for a state or district, how do we make a judgment about the text difficulty that, say, a sixth-grader ought to be able to handle?

It would seem obvious that an experienced teacher would use her judgment to make such decisions. But naturally such judgments will vary from individual to individual. Hence the apparent need for something more objective. Readability formulas are intended as just such a solution. You plug some characteristics of a text into a formula and it combines them into a number, a point on a reading difficulty scale. Sounds like an easy way to set grade-level standards and to pick appropriate texts for kids.

Of course, we’d like to know that the numbers generated are meaningful, that they really reflect “difficulty.”

Educators are often uneasy with readability formulas; the text characteristics are things like “words per sentence,” and “word frequency” (i.e., how many rare words are in the text). These seem far removed from the comprehension processes that would actually make a text more appropriate for third grade rather than fourth.

To put it another way, there’s more to reading than simple properties of words and sentences. There’s building meaning across sentences, and connecting meaning of whole paragraphs into arguments, and into themes. Readability formulas represent a gamble. The gamble is that the word- and sentence-level metrics will be highly correlated with the other, more important characteristics.

It’s not a crazy gamble, but a new study (Begeny & Greene, 2014) offers discouraging data to those who have been banking on it.

The authors evaluated 9 metrics, summarized in this table:

The dependent measure was student oral reading fluency, which boils down to number of words correctly read per minute. Oral fluency is sometimes used as a convenient proxy for overall reading skill. Although it obviously depends heavily on decoding fluency, there is also a contribution from higher-level meaning processing; if you are understanding what you’re reading, that primes expectations as you read, which makes reading more fluent.

In this experiment, second, third, fourth, and fifth graders each read six passages taken from the DIBELS test: two passages each from below, at, and above their grade level, for a total of six passages. 

Previous research has shown that the various readability formulas actually disagree about grade levels (e.g., Ardoin et al, 2005). In this experiment, oral reading fluency was to referee the disagreement. Suppose that according to PSK, passage A is appropriate for second graders and passage B is appropriate for third graders. Meanwhile Spache says both are third-grade passages. If oral reading fluency is better for passage A than passage B, that supports the PSK. (“Faster” was not evaluated only in absolute terms, but accounted for the standard error of the mean).

The researchers used an analytic scheme to evaluate how good a job each metric did of predicting the patterns of student oral reading fluency. Each prediction was considered binary: the grade level assignment predicted that there should be a difference (or not) in oral reading fluency: was a difference observed?  Chance, therefore, would be 50%. The data are summarized in the Table

All of the readability formulas were more accurate for higher ability than lower ability students. But only one—the Dale-Chall—was consistently above chance.

So (excepting the Dale-Chall), this study offers no evidence that standard readability formulas provide reliable information for teachers as they select appropriate texts for their students. As always, one study is not definitive, least of all for a broad and complex issue. This work ought to be replicated with other students, and with outcome measures other than fluency. Still, it contributes to what is, overall, a discouraging picture.

References

Ardoin, S. P., Suldo, S. M., Witt, J., Aldrich, S., & McDonald, E. (2005). Accuracy of readability estimates’ predictions of CBM performance. School Psychology Quarterly, 20, 1 – 22.

Begeny, J. C., & Greene, D. J. (2014). Can readability formuas be used to successfully gauge difficulty of reading materials? Psychology in the Schools, 51(2), 198-215.

I’ve often written that it’s hard to bring neuroscientific data to bear on issues in education (example here). Hard, but not impossible.  Dorothy Bishop offered similar concerns on her blog Saturday. A study from Guinevere Eden’s lab provides a great example of how it can be done.

It concerns the magnocellular theory of dyslexia (Stein, 2001). According to this theory, many varieties of reading disability have, at their core, a problem in the functioning of the magnocellular layer of the lateral geniculate nucleus of the thalamus. This layer of cells is known to be important in the processing of rapid motion, and people with developmental dyslexia are impaired on certain visual tasks entailing motion, such detecting coherent motion amongst a subset of randomly moving dots, or discriminating speeds of objects.

The most widely accepted theory of reading disability points to a problem in phonological awareness—hearing individual speech sounds. The magnocellular theory emphasizes that phonological processing does not explain all of the data. There are visual problems in dyslexia as well. Proponents point to problems like letter transpositions and word substitutions while reading, and to visuo-motor coordination problems (Stein & Walsh, 1997; see Figure below) although the pervasiveness of these symptoms are not uncontested.

 Consistent with this hypothesis are post-mortem findings of cell volume differences in the magnocellular layer of dyslexics (Livingstone et al, 2001), deficits in motion detection process in individuals with dyslexia (Cornelissen, et al., 1997) and brain imaging studies showing reduced activity in cortical motion detection areas that are closely linked to the magnocellular system (e.g., Demb et al, 1997).

It’s certainly an interesting hypothesis, but the data have been correlational. Maybe learning to read somehow steps up magnocellular function. That’s where Eden and her team come in.

They compared kids with dyslexia to kids with typical reading development and found (as others have), reduced processing in motion detection cortical area V5. But then they compared kids with dyslexia to kids who were matched for reading achievement (and were therefore younger). Now there were no V5 differences between groups. These data are inconsistent with the idea that kids with dyslexia have an impaired magnocellular system. They are consistent with the idea that reading improves magnocellular function. (Why? A reasonable guess would be that reading requires rapid shifts of visual attention).

In a second experiment, the researchers trained kids with dyslexia with a standard treatment protocol that focused on phonological awareness. V5 activity—which, again, is a cortical area concerned with motion processing--increased after the training! This result too, is consistent with the interpretation that reading prompts changes in magnocellular function.

These are pretty compelling data indicating that reading disability is not caused by a congenital problem in magnocellular functioning. We see differences in motion detection between kids with and without dyslexia because reading improves the system’s functioning.

The finding is interesting enough on its own, but I also want to point out that it’s a great example of how neuroscientific data can inform problems of interest to educators. About a year ago I wrote a series of blogs about techniques to solve this difficult problem.

Eden’s group used a technique where brain activation is basically used as a dependent measure. Based on prior findings, researchers confidently interpreted  V5 activity as a proxy for cognitive activity for motion processing. Indistinguishable V5 activity (compared to reading-matched controls) was interpreted as a normally operating system to detect motion. And therefore, not the cause of reading disability.

I’m going out of my way to point out this success because I’ve so often said in the past that neuroscience applied to education has mostly been empty speculation, or the coopting of behavioral science with neuro-window-dressing.

And I don’t want educators to start abbreviating “brain science” as BS.

References:
Cornelissen, P., Richardson, A., Mason, A., Fowler, S., and Stein, J. (1995). Contrast sensitivity and coherent motion detection measured at photopic luminance levels in dyslexics and controls. Vision Research, 35, 1483–1494.

Demb, J.B., Boynton, G.M., and Heeger, D.J. (1997). Brain activity in visual cortex predicts individual differences in reading performance. PNAS, 94, 13363–13366.

Livingstone, M.S., Rosen, G.D., Drislane, F.W., and Galaburda, A.M. (1991). Physiological and anatomical evidence for a magnocellular defect in develop-mental dyslexia. PNAS, 88, 7943–7947

Stein, J. (2001). The magnocellular theory of developmental dyslexia. Dyslexia, 7, 12-36.

Stein, J. & Walsh, V. (1997). To see but not to read: The magnocellular theory of dyslexia. Trends in Neurosciences, 20, 147-152.

We all know that most Americans don't read much. A recent poll showed that a common reason they don't read is "lack of time." Fifty-one percent suggested that was a major factor that kept them from reading more books.

It's tempting to quote Sir John Lubbock: "In truth, people can generally make time for what they choose to do; it is not really the time but the will that is lacking." That's the line of thinking taken in this Atlantic blog, noting that many of us spend plenty of time watching television.

This line of argument is true enough, but probably won't help much. So without scolding, here are some ideas on how to think about reading and time differently.

1) Don't assume that that you have to have a long block of time to read. Bit and pieces add up. If you think "I need at least thirty minutes of uninterrupted time to get into the book," well, try fitting reading into the bits and pieces of time in your day. You're ready to go out and your spouse isn't? There's five minutes. Long line in the grocery store? There's five minutes. 

2) Be prepared. To make use of these times, keep books in places where you find yourself with a few minutes. Bathroom. (Let's not deny it.) Kitchen (if you eat alone). Car (also useful when you're not driving, but at your destination. B. F. Skinner noted he read Thoreau's Walden, which he kept in his glove box, in snippets when waiting for late-comers.) Get audio books for your commute.
3) The best preparation is on your phone. It's not my favorite way to read, but you always have your phone with you. Get Kindle for your iPhone or Android. Reading emergencies--e.g., my kid was supposed to play but isn't and now I'm stuck watching other people's kids play pee-wee soccer--reading emergencies happen.
3) Don't assume that you can only read one book at a time. If you've got books distributed in different spots, won't you get mixed up? Probably not. But if you are really worried about that, start with books that have lots of short stuff: Uncle John's bathroom reader in the car, Chekhov short stories in your purse, etc.
4) You don't you have to finish what you start. For a long time I assumed that if I started a book I was in some way obligated to finish it. Or maybe that if I didn't, I had wasted my time in starting it. This attitude makes no sense. Don't fail to start a book because you're afraid it might turn out too challenging or emotionally hard, or whatever. If you don't like the book, abandon it.
5) No, seriously, I'm too busy. When was the last time you were bored? If you really can't remember, then okay, you're too busy. If you can name a time, then you could have been reading instead of being bored.

Does music training improve other academic skills?

One sometimes hears the inclusion of music in the curriculum justified by the claim that it improves mathematics, or reading.

I’ve never cared for this justification because I think students should study music for its own sake, whether or not it boosts other skills. And it seems a chancy argument; if it turns out that music doesn’t help other academic work, does that mean it should be dumped?

Setting that argument aside, it’s certainly of interest from a cognitive point of view to know whether musical training has an impact on reading or math. There are a good number of correlational studies showing a positive effect, but few experimental data.

Now a new experimental study (Rautenberg, in press) shows that music training does have some positive effect for reading.

159 German 1st graders participated. The music training lasted 8 months and focused on three areas: rhythmic skills training, tonal/melodic skills training and auditory discrimination of timbre and sound intensity. There were two control groups: one received no training. The other was an active control receiving  training in art.

The results were fairly robust, as shown in the graph of single word reading accuracy at the beginning and end of the year.

What’s behind the benefit? Language does have a musical aspect to it, referred to as prosody. And indeed, children’s ability to appreciate the rhythmic aspect of speech is correlated with the ease with which they learn to read, even when controlling for phonemic awareness. In German (and in English) certain letter combinations signal certain stress patterns, so there is a signal in the written language that children can learn. The ideas is that children are less likely to learn the association of certain written letter patterns and their corresponding rhythms in speech if they don’t perceive the rhythms of speech very well.

That’s the argument. More fine-grained analyses of the data partially support it.

The argument predicts that it’s rhythm that’s important, not tonality, and the data do show significant correlations of reading with ability in the former, but not the latter.

The argument further predicts that the training ought to reduce a particular type of error: one in which a child reads the phonetic sounds correctly but gets the rhythm wrong; they segment the word into syllables incorrectly, or they accent the wrong syllable. This prediction was not supported.

All in all, this study seems to be an important addition--although certainly not a conclusive one--to the argument that some types of music training aids children's learning to read, at least in certain languages.

Reference
Rautenberg, I. (in press). The effects of musical training on the decoding skills of German-speaking primary school children. Journal of Research in Reading.

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-depenent 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.

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

One finding (from Seymour, Aro & Erskine, 2003) illustrated in one figure (Figure 5.3 from Stan Dehaene's marvelous book,Reading in the Brain.).  The figure shows errors in word reading at the end of first grade, by country.

Are we to conclude that the differences are due to educational practice? The vaunted Finnish system shows smashing results even at this early age, whereas the degenerate British system can't get it right?

Countrywide differences in instruction could play a role, but Dehaene emphasize that the countries in which children make a lot of errors--Portugal, France, Denmark, and especially Britain--just happen to have deeper orthographies.

A shallow orthography means that there is a straightforward correspondence between letters and phonemes. English, in contrast, has one of the deepest (most complex) orthographies among the alphabetic languages: for example, the letter combination "gh" if pronounced differently in in "ghost," "eight," and "enough."

In short, children learning to read English have a difficult task in front of them--and so too, therefore, do teachers.

Is there a lesson to be drawn here?

To me, the difficult orthography of English highlights the importance of careful sequencing in the learning of grapheme-phoneme pairs, along with a limited number of sight words--sequencing that exploits the regularities that exist, and bring children as swiftly as possible to the point that they can read texts and so feel a sense of accomplishment.

In Italy, for example, the order in which grapheme-phoneme pairs are taught would matter much less because there simply is not that much to learn. Several months of instruction is sufficient for most children to reach a point that they can decode most texts.

The deep orthography of English also sheds light on why American schools spends as much time on English-language arts (ELA) as they do: something like two-third of instructional time in the first grade (NICHD Early Child Care Research Network, 2002).

One might draw the conclusion that the difficulty of the task in reading requires enormous amounts of time. Another point of view--one I share--is that this practice places too much emphasis on ELA at the expense of other content, and runs a high risk of discouraging kids who might become passionate about science, or history, or geography, but won't because the early elementary years contain so little content beyond ELA and mathematics.

I think it would worth our accepting slower progress in reading in exchange for broader subject-matter coverage in early grades--coverage that will actually pay dividends for reading comprehension in later grades.


Dehaene, S. (2009). Reading in the Brain. New York: Viking.

National Institute of Child Health and Human Development Early Child Care Research Network (2002). The Relation of Global First-Grade Classroom Environment to Structural Classroom Features and Teacher and Student Behaviors. The Elementary School Journal, 102, 367-387

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

I was just at a reading conference and gave a talk on reading comprehension strategies.

I’ve written about them before (article here). The next paragraph provides just a brief summary of what I’ve written. The figure below shows the strategies themselves, if you’re not familiar with them (click the image for a larger version).

The short version of my conclusion is that they don’t really improve the comprehension process per se. Rather, they help kids who have become good decoders to realize that the point of reading is communication. And that if they can successfully say written words aloud but cannot understand what they’ve read, that’s a problem. Evidence for this point of view include data that kids don’t benefit much from reading comprehension instruction after 7th grade, likely because they’ve all drawn this conclusion, and that increased practice with reading comprehension strategies doesn’t bring any improved benefit. It’s a one-time increment.

How much time is devoted to reading comprehension strategy instruction? I can’t find good (or poor) data on this question, and I doubt it exists. There is so much variation among districts (and probably even classrooms) on this issue, it’s hard to draw a conclusion with much confidence. Any time I talk about reading, a lot of teachers, coaches, and administrators tell me that enormous amounts of time go to reading comprehension strategy instruction in their district—but I’m sure the people who make sure to mention this to me are not a random sample. 

Whatever the proportion of time, much of it is wasted, at least if educators think it’s improving comprehension, because the one-time boost to comprehension can be had for perhaps five or ten sessions of 20 or 30 minutes each.

Some reading comprehension strategies might be useful for other reasons. For example, a teacher might want her class create a graphic organizer as a way of understanding how an author builds narrative arc

The wasted time obviously represents a significant opportunity cost. But has anyone ever considered that implementing these strategies make reading REALLY BORING? Everyone agrees that one of our long-term goals in reading instruction is to get kids to love reading. We hope that more kids will spend more time reading and less time playing video games, watching TV, etc.

How can you get lost in a narrative world if you think you’re supposed to be posing questions to yourself all the time? How can a child get really absorbed in a book about ants or meteorology if she thinks that reading means pausing every now and then to anticipate what will happen next, or to question the author’s purpose?

To me, reading comprehension strategies seem to take a process that could bring joy, and turn it into work.

A lot of people have been tweeting or posting to Facebook a link to a graph which was posted to the Atlantic Monthly website on April 6, with this provocative headline:

And here's the chart you are urged to show, derived from Gallup poll numbers over the years.

We're invited to conclude that because the percentage of readers increased after the advent of the Internet, the Internet did not have a negative impact on book reading.

All of the postings I've seen have apparently taken this conclusion at face value, so it seems like it's worth going through why this conclusion is not justified.

First, lots of stuff happened between 1949 and 2005. For example, household income increased for middle- and high-income families. It could be that the internet has negatively affected book reading, but a number of other factors have increased it, so overall we see an increase. The idea that other factors are having a big impact on reading seems legitimate, given the big increase in reading from 1957 to 1990, a year in which very few people had internet access. So perhaps those factors are continuing to boost reading, despite the negative impact of the internet.

The type of analysis we're being asked to perform implicitly is a variety of time series analysis. It's useful in situations where one can't conduct an experiment with a control group. For example, I might track classroom behavior daily for one month using a scale that runs from 1-10. I find that it ranges from 4 to 6 every day. The teacher implements a new classroom management scheme, and from that day forward, classroom behavior ranges from 7 to 9 every day.

Interpreting the new classroom management scheme as the cause of the change is still not certain--some outside-of-class-factor could have just happened to have occurred on that same day that prompted the change in classroom behavior. But the fact that the change in behavior happened over such a narrow time window makes us more confident that such a coincidence is unlikely.

And of course it helps my confidence that it's the same class. In the chart above, we're looking at events that happened over years, with different people who we hope had similar characteristics.

To really get at the effect of the internet on reading habits, you need more finely controlled data. A number of studies were done in the 1950s, examining the effect of television on reading habits. The best of these (see Coffin, 1955) measured reading habits in a city that did not have a television station but was poised to get one, and then measured reading habit again after people in the city had access to television. (The results showed an impact on reading, especially light fiction. Newspaper reading was mostly unaffected, as television news was still in its infancy. Radio listening took a big hit.)

Second, we might note that the most recent year on the chart is 2005. According to the Pew Internet and American Life Project, only 55% of Americans had internet access at that point, and only 30% had broadband. So perhaps the negative impact wouldn't be observed until more people had internet access.

This brings us to more serious studies of whether use of the Internet displaces other activities. The studies I know of (e.g., Robinson, 2010) conclude that Internet use does not displace other activities, but rather enhances them. The data are actually a bit weird--IT use is associated with more of everything: more leisure reading, more newspaper reading, more visits to museums, playing music, volunteering, and participating in sports.

The obvious explanation would be that heavy IT users have higher incomes and more leisure time, but the relationships held after the author controlled for education, age, race, gender, and income--though most of these effects were much attenuated.

This research is really just getting going, and I don't think we're very close to understanding problem.

In sum, the question of what people do with their leisure time and how one activity influences another is complicated. One chart will not settle it.




Coffin, T. E. (1955) Television's impact on society. American Psychologist, 10, 630-641.
Robinson, J. P. (2011) Arts and leisure participation among IT users: Further evidence of time enhancement over time displacement. Social Science Computer Review, 29,  470-480.