Once children are fluent decoders, the most frequent problem in reading is poor comprehension due to a failure to make inferences. Even seemingly straightforward anaphoric inferences can elude these students: they might read “Bob gave Tamisa some of his snack because she was hungry” and still be unsure of the referent for “she.” Other inferences require bridging information from long term memory, and these are still more challenging. For example, “Kevin said he was cold. Zeke gave him his coat.” Even if these two sentences are understood, each on its own, deeper comprehension entails making the (probably accurate) inference that Zeke gave Kevin the coat because Kevin said he was cold, which requires knowing that putting on a coat is something one does when cold.

Educators have sought to improve inferencing. In some cases they can teach students reading comprehension strategies: create a summary, for example, or create a graphic organizer. The task provides some structure that will prompt the student to make the necessary inferences. Alternatively, students might be taught more directly to make inferences, usually by instruction to elaborate on what they read in the text,  to use cues in the text that provide clues to inferencing (e.g., words like “because,” or “so,”), and to monitor their comprehension.

​A new meta-analysis of inference instruction (Elleman, 2017) shows that it’s quite effective, but carries some important caveats…ones that I’ve mentioned before.

The overall mean effect size on comprehension of inference instruction was a healthy g = .58. Elleman also evaluated separately comprehension due to inferences, and literal comprehension, and observed a difference moderated by ability. 

As the figure shows, both skilled and less skilled readers improve in inference-making ability, but inference instruction provides a boost to understanding of things stated explicitly in the text only for less skilled readers.
​
Still more interesting to me was the report that the amount of instructional time had no impact on the effectiveness of the intervention, which I’ve shown in the graph below, compiled from a data table in the paper.

Each dot represents a study condition. Two things are notable: first, most studies entail rather little practice, but nevertheless show a large effect. Second, more practice does not lead to a larger effect.

​This finding is important because it provides an important clue to the mechanism by which this instruction helps. Practice usually helps, especially early in training. The curve looks like this

Performance improves with practice, and the curve is negatively accelerating. You get the most bang for the buck from practice early in training. The data from this meta-analysis don’t show either effect. It’s true that the range is relatively small…most studies use very little practice, so it’s harder to observe any effect of practice. That still doesn’t explain why you get such a big effect with very little practice.

​This failure to observe a practice effect is more understandable if the relationship of practice and performance for inference generation look more like this: 

The plot would look like this if what kids learn during inference instruction is easy to learn, and easy to implement, but carries a one-time benefit. For example, this instruction might prompt children to better understand the importance of making the effort to coordinate meaning across sentences. It might teach them to look for cues to inference possibilities like the word “because,” or time cues like “later.”

As Elleman notes, theories of reading have centered on the knowledge from long-term memory needed to make inferences (Kintsch, 1998) and/or the working memory capacity needed to hold information in mind simultaneously so meanings can be compared (Daneman & Carpenter, 1980). Neither of these is going to change over the course of 10 hours of instruction.

And that’s the practical implication of this meta-analysis. There’s a big benefit to inference instruction, but all of the benefit accrues rapidly. There seems to be no point in spending extended classroom time on the practice.

Similar results have been observed in meta-analyses of studies examining the impact of reading comprehension strategy instruction. Gail Lovette and I (2014) reported on nine meta-analyses of typically developing readers and of readers either identified with a reading disability, or at risk. In each case, the pattern was the same: a large effect with few hours of instruction, and no benefit to more instruction. (This piece was published as a commentary in Teachers College Record and seems to have disappeared from the website. Email me if you’d like a copy.)

This interpretation is also consistent with theories of reading comprehension. Inferences are situation specific: you can’t really teach how to make inferences because the inference to be made depends on the content of the text. Rather, you can teach them to seek and use some cues (probably a causal connection here) and you can teach them that it’s important to make inferences. But making them requires broad background knowledge in long term memory.

That is an essential goal to improve reading comprehension, but it is a goal requiring years of planning, not hours. 

Tomorrow, March 18, is Trisomy-18 awareness day. It’s important to me because one of my daughters, Esprit, has Trisomy-18. In the spirit of the day I’m going to offer just a little background for those who are unfamiliar with it, but focus mostly on one interaction small children typically have with Esprit—staring at her.

By way of background, Trisomy-18 is a chromosome disorder. Each cell in the human body has 23 pairs of chromosomes, strands of DNA. Trisomy means that there are three copies, not two, of one of the pairs. Three copies of the 21st chromosome is Trisomy-21, also called Downs Syndrome. Three copies of the 18th chromosome give you Trisomy-18, also called Edwards Syndrome. (So now you know why they picked the eighteenth of March—3/18—as Trisomy-18 awareness day. )

There’s no particular cause—it’s a fluke. There’s also no cure, and over 90% of the children born with Trisomy-18 die within the first year.

Esprit is unusual for still being here at age 13, but her profile is typical of Trisomy-18 in other ways. She cannot walk or speak, and she learned to sit upright about a year ago. Cognitively, she’s like a one-year old on many dimensions. 

My goal here is not to raise awareness about the medical side of Trisomy-18—if you’ve read to this point, you’ve come close to the end of my knowledge—but rather to consider the manner in which you are most likely to encounter a child with Trisomy-18; out and about with your own child. Older kids (and their parents) will sneak a surreptitious glance at Esprit. Many adults will smile and some will approach her, always with warmth.

But kids aged two to six are generally flummoxed and show it. Parents are usually not prepared to respond to their child’s curiosity and bafflement.

​Your five-year-old will notice that Esprit doesn’t look like other children. She has facial features typical of Trisomy-18 kids. Her head is small, her ears low-set, her chin recedes, and her eyelids droop, so she usually looks sleepy. 

But your child wouldn’t be paying attention to these facial features, because others are much more noticeable. Esprit is tiny for her age, weighing just fifty pounds, and she’s usually in a large wheelchair that provides support for her back. She also wears a TLSO around her midsection, and orthotics on her feet.

To a five-year old, this is a sight.

So usually he stares. (I'll call the child "he" to keep pronouns unambiguous, cf Esprit.) That makes the parent uncomfortable, and they try to call the child away, distract him, so he’ll unlock his gaze. The parent doesn’t say “don’t stare;” doing so would acknowledge that he’s staring, and that there’s something to stare at. Eventually, the parent might drag or chivy the child away, with the child looking back the whole time, staring.

I appreciate that you don’t want your child to stare, but ignoring his interest or trying to get the hell away doesn’t work well and sends your child the message that there’s something wrong here. And admonishing the child “it’s not nice to stare” once out of earshot will not make him accept a disabled kid as part of the shopping mall crowd next time he sees one. Kids this age are too young for that. (If there's any effect, it will be to make him a sneakier starer.)

Here’s an alternative. Encourage your child to add a social element to the staring. It’s natural and unobjectionable that he’s curious about a child who looks different. Staring feels wrong because interaction with another person demands some outward acknowledgement that there is a fellow human in front of you. You can gape at a skyscraper or a sunset, but no matter how interesting another person is to behold and for whatever reason, you must give social signals that you recognize that they are not an object.

Once you add social signals, staring doesn’t feel like staring. Staring while smiling, for example, seems perfectly appropriate. Sure, a five-year old’s voluntary smile is comically phony, but who cares? It’s the thought that counts. Or encourage your child to say “hi,” or to wave. Any of these changes the dynamic from “observation of a spectacle” to a bid for social interaction. (It will also thrill Esprit.)

More outgoing kids will ask questions, usually of my wife or I rather than Esprit. Please don’t shush them, and please don’t worry about what they will ask. Parents (and strangers) don’t expect social graces at this age, so we know we’ll hear “what’s wrong with her?” or “what’s that? (pointing to her orthotic). We’re very used to talking with children about Esprit’s disability. Questions are a way of initiating social interaction. They’re great.

​Every family’s experience is different, of course, and I’d never claim to speak for all parents of disabled children. But the next time your little one stares at someone different, give the social signal strategy a try. Let me know how it goes. 

​Everyone knows that it’s dangerous to use a cell phone while driving. The danger lies in distraction; even with a hands-free phone, the conversation saps attentional resources that should be devoted to the road.

But what if you’re not driving? Suppose you’re a student working a multi-step math problem and an announcement comes in over the school PA system. 

Lab studies provide some disquieting answers. Coming back to your main task after an interruption carries a cost both in time lag and in error rates…in one field study errors were observed where the main task was the administration of medication.

In a new study Erik Altmann and his colleagues investigated the effect of the duration of the interruption. They were especially interested in duration because delay is known to have a robust effect on memory, but is likely to have an effect on attention. (The importance of delay is explained below.)

​In this experiment, the multi-step main task involved a display of a digit and a letter, about which subjects had to make seven judgments, in a particular sequence. The graphic below explains the task. 

​Interruptions occurred randomly, on average every 6 trials (but with a lag of at least three trials). Subjects saw a letter string that they were to type on the computer keyboard. Duration of the interruption was controlled by the number of strings and the number of characters in each string. 

Let’s return to the importance of the interruption delay. Suppose you’re executing a multi-step procedure and you’re interrupted. When you return to your main task any problems you have might be due to memory or attention. If the problem is one of memory (but your attention is fully back on task) we’d expect that you might forget where you are in the sequence, e.g., you were supposed to the “R” task in the UNRAVEL sequence, but you forget and repeat the “N” task. But we wouldn’t expect you’d necessarily make a mistake when answering the “N” task, because attention is fully back on task.

But if the problem is that your distracted, we’d think that both types of problems would be more likely—an interruption would make you lose your place in the sequence (sequence errors) and make you more prone to mistakes in when answering (answer errors).

​The results were quite clear, as shown in the figure

The interruption made subjects forget where they were in the sequence, but it did not seem to affect attention much once they returned to the task, because the interruption didn’t make them more error prone.

​As in other experiments, this one showed that an interruption incurred a cost to response time upon return to the main task. In this experiment, this cost increased with delay, and in light of the error data, we’d interpret this effect as being due to subjects struggling to remember where they were in the sequence. 

This memory-based account of the effect of interruptions on sequential tasks is consistent with decades of experimental work showing that the contents of short term memory is compromised by delay.  These results don’t mean attention is not a relevant factor in interruptions, but they do speak to the relative roles of memory and attention in sequenced tasks.

So administrators...if you haven't set a policy that the PA system is silent during class, think about doing so!

I’m leery of value-added measures as a metric of individual teacher quality. Aside from the straight psychometric challenges, I’ve always worried that there’s too much that teachers give students that a VAM would miss. For example, I think of a LAUSD high school teacher who told me with considerable excitement that he had managed to get one of his kids who was near to dropping out to come to his class for five days in a row. The student wasn’t really participating in any way yet, but the teacher had a plan in mind for how to try to coax this student back to trying to engage with math just one more time, after many years of difficulty and frustration.

Who would tell this teacher “that child is a bad investment of your time?” Yet where is the VAM that will measure the value the teacher is adding to this student?

A recent paper (Master, Loeb & Wyckoff, 2017; preprint here) tried to shed light on this problem. The authors note that the short-term effects of ELA teachers are usually smaller than those of math teachers (as measured by VAM). This outcome is easy to understand from a cognitive perspective—students learn more outside of school that can be applicable to ELA tests (compared to math), and thus the contribution of a teacher and school will be relatively smaller. But the contribution of ELA and math teachers to long-term outcomes (e.g., graduation) is equivalent. Why?

One possibility is that students learn different kinds of things from each. They may learn more subject-specific content from math teachers that persist to math performance next year. But a good ELA teacher may be more likely to impart different, more persistent skills to students—they may improve their self-image as students, for example.

To examine this possibility the authors compared VAMs across years in ELA and math both within subjects and between them. In other words, if an ELA teacher was really effective, we know that effect will be observable in English class the next year. Will it be observable in math class as well?

The authors had two enormous data sets with which to investigate this question: standardized test scores from 3rd through 8th students in New York City and Miami-Dade County from 2003/04 to 2011/12.

This study, like previous studies, found that about 25 or 30% of VAM persists into the next year. In this study, those quantities were similar in math and in ELA. The startling result came when investigators used VAM in one subject to predict VAM in the other subject in subsequent years. (More precisely, they examined student achievement in year 2 in subject A, accounting for achievement in year 1 in subjects A and B, and the VAM estimates of the teachers in subjects A and B in year 1.)

As noted, about ¼ to 1/3 of the VAM in ELA from one year carried over to ELA achievement the following year. And about 46% of that effect also carried over to math achievement in Miami-Dade. In New York City, it was 70%.

But having a really effective math teacher had very little impact on ELA achievement the following year. In both districts, this carryover was around 5%.

There was good evidence that these effects persist into a third year in New York City, but in Miami-Dade the results were inconclusive, according to the researchers because measurements there were less precise.

The results point to three conclusions, given the caveats typical to this work (and often forgotten): subjects other than ELA and math were not measured, and students were not randomly assigned to teachers (and in fact, there is likely systematic bias in assignment)

First, these results help us to understand why ELA short-term VAMs are smaller than math short-term VAMs, yet the predictive value for long-run outcomes (like graduation) is the same. The ELA short-term VAMs may typically be smaller, but they contribute across subjects (which the math do not). And these cross-subject effects may last years.

Second, the authors don’t speculate much on the mechanism of transfer, but at least two routes seem plausible. First, ELA teachers may, on average, provide a bigger boost to what are usually called non-cognitive skills: self-regulation, persistence, seeing oneself as belonging in school, and so on. Second, better ELA skills—especially better reading skills like decoding, fluency, deployment of comprehension strategies, and self-monitoring of comprehension—seem likely to pay dividends in many subjects.

​Third, when it comes to policy, I’ll leave the conclusion to the authors: “educators and policymakers may miss valuable information if they rely only on short-term within-subject student learning to evaluate teachers’ “value added” to student achievement.” Student achievement gains prompted by teacher X could easily be misattributed to another teacher in another subject, years later.  

Over the weekend I posted a link to a new study (Singer & Alexander, 2017) comparing reading comprehension when reading from a screen and reading from paper. Ninety undergraduates read four texts each: two book excerpts and two newspaper articles, all on various topics concerning childhood ailments. Two were read digitally, and two on paper. The results showed that subjects reading from a screen or from paper were equally proficient in identifying the main idea, but subjects reading paper did a better job when asked to list key points of the text, and to describe how it related to the main idea. Despite this pattern, 69% of subjects thought they performed better on the screen-based texts, and just 18% thought they had done better with paper.

I didn’t think all that much about this study because there have been lots of comparable studies. But my tweet garnered more comments and retweets than mine typically do, so I figured this finding must be news to some of my Twitter followers.

That’s when I decided to write a blog post flagging some of the relevant studies.

The following studies compared reading comprehension from a screen and paper, and concluded paper is better:

• Chen et al, 2014;
• Jeong, 2012;
• Lauterman & Ackerman (2014);
• Kim & Kim, 2013;
• Mangen et al, 2013; 
• Rasmusson et al , 2015;

The following studies reported no difference in comprehension, but a difference in reading time. The common-sense interpretation is that if comprehension is more difficult on screen, the reader has the option to trade time for accuracy, and that’s’ what these readers; 

• Ackerman & Lauterman, 2012;
• Connell et al, 2012;
• Daniel & Woody, 2013;

That makes it more difficult to interpret the following three studies. The experimenters report no difference in reading comprehension, but they did not measure reading time:

• Margolin et al 2013;
• Rockinson-Szapkiw, 2013; 
• Subrahmanyam et al, 2013;  

One exception is Porion et al 2016 who report no difference in comprehension, but did restrict reading time.

So ten studies report that paper is superior and four call it a draw, but three of these did not measure reading time. Other researchers reviewing the literature draw same conclusion that I do: comprehension is better when reading from paper: Tees, 2010; Sidi 2016; Zucker et al, 2009;  Walsh, 2016 concludes that reading from paper is better only for complex documents.

I doubt I’ve captured all of the extant literature. These studies tend to be published in far-flung places, and quite honestly, not always in top-drawer journals. I think that’s because it seems like the same question is being posed over and over…but actually there are a lot of potentially important modifying variables: four obvious ones would be subject matter knowledge, reader age, the purpose of reading (textbook vs leisure, for example) and experience with e-readers. So when you read any one of these articles, you can’t help but think “hmm. How generalizable is this?”

The other caveat to this conclusion is that it’s almost certainly a moving target. The fifth important variable is the interface used by the e-book. It’s my hunch that that’s the vital factor in this (small) screen decrement. Software engineers are working on it, as hardware engineers have made great improvements in the brightness and contrast of screens. I think it’s just a matter of time before ereaders are as easy to read as paper.

​​That college grades have risen over the last fifty years is not in dispute. The average course grade in college was 2.5 in 1960 (on a 4.0 grading scale) and had risen to 3.1 in 2006.

I often hear two reasons offered for the increase. During the 1960s, Professors ​were eager to help students stay in the school, so as to avoid the draft and the Vietnam war. (The lax standards were extended to female students for verisimilitude.)

In more recent years, increases in grades are attributed to the consumer era of higher education. Students see college courses as a commodity they purchase, and professors, hoping for high enrollements and good course evaluations to boost their tenure prospects, hand out the A's.

This student-as-consumer account seems to be bolstered by the fact that grade inflation has been higher at private colleges and universities than at public ones. 

Both accounts propose that grade inflation is solely due to changes in professors' grading policies, and that students have not changed. A recent paper challenges that assumption, and offers some persuasive data. 

​Rey Hernández-Julián and Adam Looney brought economic models of inflation to bear on the question. As they point out, higher prices don't always signal inflation. For example, price may increase as quality increases. 

They examined 20 years of transcript data from 90,000 students at Clemson University over the years 1982-2001. During that time grades increased from 2.67 to 2.99, comparable to the increase observed elsewhere. They also had data on the characteristics of these students. 

The researchers observed shifts in student characteristics and course-taking behavior that accounted for a little more than half of the increase in grades.

First, the students coming to Clemson were better prepared, as measured by the SAT. Math scores increased by 29 points over the period, and Verbal scores by 15 points.

Second, student enrollment drifted towards departments that tend to assign higher grades. More students took courses in Speech and Communication, Spanish, Graphic Communications, and yes, Education; all these department assign average grades above the means of other departments. Tough-grading departments--Math, Accounting, Physics, Mechanical Engineering--saw drops in enrollment.

Third, the percentage of women at Clemson increased, and women earn higher grades than men do. This increase was modest (4% points) and accounts for little of the grade increase, but the authors point out that the increase in women enrollment is high nationwide (from 41% to 56% between 1970 and 2000) and so may account for more of the grade increase at other institutions. 

The upshot is that a little less than half of the increase in grades is attributable to grade inflation. The authors identify possible contributors to grade increase, and whatever they cannot account for is labeled "inflation." They point out that the actual value of grade inflation could be lower.

I would add that the actual value could, in theory, also be higher. Unobserved variables like course difficulty and student effort could be decreasing. Obviously measuring such variables at broad scale is difficult if not impossible. 

A prominent theory of the difference in cognition between those with Autism Spectrum Disorder and typical adults has it that the former have difficulty understanding and predicting what others think. This ability is often called Theory of Mind. A recent experiment indicated that, at least in one task, this process is not difficult for adults on the Autism spectrum (Pantelis & Kennedy, 2017).

The authors used a task called the Beauty Contest game. It’s deceptively simple. You’re told that a large group of people will each pick one number from 1 to 100. Whoever picks the number closest to 2/3 the value of the mean guess is the winner.

So consider why this is a theory of mind task.

• One possibility is that a player will say to himself “this is complicated, I have no idea how to be strategic, so I’ll pick a random number between 1 and 100. Call this a “0th order” player.
• A 1st order player assumes that others will be 0th order players. They will choose randomly, so the mean of their choices will be 50, so the 1st order player chooses a value of 2/3*50 or 33.
• A 2nd order player assumes that some of the other players will be 0th order, but some will figure out how to be 1st order players, and will choose numbers accordingly. The 2nd order players chooses her number according to how many 1st order and how many 0th order players she expects to be among her opponents.
• A 3rd order player assumes some other players will be 2nd order, as well as 1st and 0th order…and in principle it can continue from there.

You can see how this theory of mind task is recursive. You might start by asking “what will my opponent think?” They you can ask “will my opponent guess what I’m thinking he’ll think?” and so on. You can also see that thinking through what others might do leads you to pick a lower number.

(It’s called the Beauty Contest because the idea was first forwarded by John Maynard Keynes in the form of a newspaper beauty contest, where entrants were to select the six most attractive faces from 100 pictures, with the best pickers getting a prize. Keynes pointed out that entrants might simply pick the ones they thought most attractive, but their choices might also be informed by what they thought others would do.)

Pantelis & Kennedy first gave this task to 250 undergraduates; each was also asked to complete the Autism-Spectrum Quotient questionnaire (AQ), which is meant to measure sub-clinical personality traits consistent with autism. There was no correlation between guesses and scores on the AQ.

There is also a method of estimating the “depth” of recursive thinking in a large group of subjects. The experimenters separated the 250 subjects into those scoring relatively high on the AQ and those scoring relatively low. They observed no difference in the depth of recursive thinking in the two groups.

More telling, experiment 2 tested 30 adults with autism or Asperger’s, all of whom were described as high-functioning and of typical to high intelligence (as measured by a standard IQ test). The researchers observed no difference between this group and typical controls in the mean number guessed, nor in the model’s estimate of the depth of theory-of-mind thinking.

The researchers are appropriately cautious in drawing conclusions from this research. As they note, theory of mind is complex and it’s easy to believe that it has multiple components. The beauty contest likely taps just one. Then too, autism spectrum disorder is likely complex, with a constellation of abilities and challenges which may vary considerably from person to person. And that is perhaps the main point of this experiment: the simple characterization: “autism is mainly a theory of mind problem” won’t do. 

Students come to school to learn, but that doesn’t mean they begin school devoid of knowledge. As much as policymakers have focused in recent years on the potential richness of the home environment (and the edge that may give children) it’s equally true that children come to school with erroneous beliefs—beliefs that teachers have long recognized can be an obstacle to learning.

That’s especially true in some areas of science. Humans must know how to interact with their world, and that necessity appears to have led to a set of intrinsic, intuitive beliefs about the nature of objects in the world which have some utility for individuals, but also conflict with important principles of biology. Researchers have, in the last ten years or so, documented some of these. A new report (Coley et al, 2017) is perhaps the most thorough in doing so.

Researchers administered a series of measures to three groups of subjects (total N = 211) : 8th grade students, college biology majors, and college non-biology majors. The measures focused three intuitive beliefs:

​Anthropocentric thinking: Using humans as the basis for reasoning about other biological species (i.e., thinking of humans as the norm to which others are compared) and seeing humans as biologically unique and discontinuous compared to other species. For example, adults are slower to confirm that plants are living things, consistent with the idea that organisms that seem more distant from humans must not share other qualities with humans.

Teleological thinking: believing that the apparent goal or function of an object or event is the cause of the event. Hence, a young child might reason that lions exist so that they can be in zoos for us to see. An older child might reason that it rains in order that plants grow.

Essentialist thinking: the belief that objects have a fundamental essence that specifies their category membership, and that all members of this category share this essence. For example, an animal is either a bird or not a bird—there’s no degree of “birdiness” in the final analysis, and all birds share the bird essence. Young children believe that parents and their offspring tend to share not only physical characteristics (e.g., eye color) but also preferences (e.g., liking sweets).  
​
The researchers wanted to examine (1) whether these intuitive beliefs change in late adolescence and (2) whether training in biology affected the prevalence or depth of these beliefs. There was an effect for both factors, but in both cases, smaller than the researchers expected. The graphs below show results for one question type from each category—the final analysis used a composite of questions from each category, but these are representative. 

At left, responses to a anthropocentric question. Students were given a number of organisms and asked whether each shared a common ancestor and any point in evolution with humans. Higher bars reflect better performance.
At center, responses to a teleological question. Students read an "explanation" of a biological phenomenon that appealed to causality (e.g., "worms exist to aerate the soil, which benefit plants"). Shorter bars reflect better performance.
At right, responses to an essentialist question. Students were asked questions about absolute category membership (e.g., something is either a mammal or it isn't, and there's never an in-between). Shorter bars reflect better performance. 

All in all there are effects of age (and associated effects like further general education) as well as effects of training in biology. But all three groups show the same trend for anthropocentric and teleological thinking. Curiously, essentialist thinking grows stronger with development. The authors suggest a few possible interpretations of this finding the most plausible of which is that it is broadly consistent with how biology is frequently taught.

The core finding---that these intuitive ways of thinking are quite resistant to education—matches the findings regarding naïve  physics (e.g., Potvin et al., 2015) and highlights the challenges science teachers face. 

The BBC has a website which (based on the title) I gather is to help students prepare for the GCSE. The "science" area has a section on "Brain and Memory" which, unfortunately, has several inaccuracies. 

This figure appears on page 1. Some of the functions attributed to some brain areas are roughly correct--motor cortex is shown as more toward the front of the brain than sensory cortex, which is right, and vision is where it ought to be. But it's hard to tell what's what because the brain is simply drawn wrong (see below) so localization is hard to pinpoint (e.g., there's no central sulcus, which would separate motor and somatosensory areas).

Some functions--reading--are not localized in one spot. "Speech" is misleading--do they mean producing speech? Or language overall? Whatever, it's wrong.

Things don't improve on the next two pages, which cover some cognitive aspects of memory. I've annotated them.

This is not advanced material. This is stuff I teach in my Introduction to Cognition course. 
Come on, BBC. The American election is hard enough on us. Don't add to our misery.

Printing Nicholson Baker’s article in yesterday’s Magazine was a terrible, terrible decision.

The decision deserves two “terribles” because it was a double mistake.

First, you published an article on a topic that entails conflicting priorities in setting goals for public good, policy constraints in achieving these goals, the science of learning, distribution of wealth, and doubtless other complexities that I’m too exhausted to identify and enumerate. The author of the article has no expertise on any of these matters. That he appears to believe his 28 days as a substitute teacher gives him much insight into schooling only makes him less credible. The most fundamental limitations of his experience—for example, that teachers might choose a lesson for the substitute because it is easy to teach, even if it’s less interesting for the students—seem to have escaped him.

The second “terrible” is, unsurprisingly, the content. The author commits the common education newcomer blunder: “The school that would have been perfect for me, would be perfect for everyone.” He cannot understand why high school must be so stifling and soulless. Part of the blame goes to curriculum, where otherwise interesting topics are made dull, but there’s no mistaking that the teachers who inflict this boring stuff on students deserve blame as well. Baker reminisces fondly about his own experience at an alternative high school, where students studied what they wished. 

To be more specific, NYTimes editors, here’s a probably incomplete list of problems in Baker’s argument:
                1. There is actually evidence regarding classroom instructional quality in this country (e.g., here). He might have made use of it. (It shows, by the way, that the emotional tone is, on average, much more positive than he lets on. Instructional quality, however, is not much better.)
                2. Baker is not the first to suppose that much greater freedom for students would lead to greater motivation and better outcomes. The lesson over the last hundred years seems to be that such schools are wonderful when they work, but reproducing the successes has proven more difficult than most observers would guess.
                3. Some parents prefer a lot of structure. The private schools in  my town do not all follow the lots-of-choice model, a al Waldorf, Montessori, or Reggio Emilia. More parents pay to send their children to highly structured, traditional schools.
                4. There are good arguments in favor of a common curriculum.

While I have your attention, please don’t publish similarly one-note, blinkered pieces centering on the ideas like these:
1) Technology is poised to revolutionize learning and schools.
2) Competition would solve all problems in American education.
3) American education is the best in the world and all challenges in educational outcomes are due to poverty.
4) Teachers are fools, and the teacher’s unions are organized crime syndicates dedicated to protecting them.
5) All of America’s problems in education can be traced to standardized tests and if teachers were simply allowed to teach as they wished, all would be well.

Thanks,
Dan