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.

Most of us don't put a lot of thought into our Facebook status updates--we broadcast bits of daily news to our friends. Here are a few from my feed as I write this:

• "I now have a tattoo."
• "It's kind of sad that we are wasting valuable time paying a babysitter to buy a new TV."
• "Neat do it yourself Ideas in this link."
• "Stunning sunset off the deck!"

I'm guessing most people don't think more than a few seconds about the snippet of prose they offer their friends. But even if a lot of thought doesn't go into an update, do they, in aggregate, say something about our personalities, our relationships, our lives?

Looking at the status updates above, do you think you could guess the age of each writer? The sex?

Researchers at the University of Pennsylvania and Cambridge University thought status updates might prove useful to social science, a new way to use "big" data. They call their method "differential language analysis."

First, software searches for words (including emoticons and hashtags) and phrases (e.g., "happy birthday," or "like about you"). Researchers then analyze which words and phrases tend to differentiate groups of people--"groups" in this case might be defined in any number of ways: sex, gender, religion, politics, etc.

Researchers also took note of when certain words and phrases tended to cluster together within individuals, forming a category. For example, the words "university," "professor," and "campus" might co-occur, obviously demonstrating some connectedness of experience.

The researchers applied the method to 70,000 Facebook users who had previously consented to have their status updates and some other data anonymously available for research purposes.

The researchers present their results mostly visually (and in fact claim that visualization is critical to help make sense of the many positive correlations obtained) in the familiar word cloud format.

Here's a much more detailed version, separated by age and gender. (Click to expand.)

What do we make of this sort of data? Well, there's certainly face validity. The words match our stereotypes (or at least, mine) of the sort of thing we'd expect from these age groups. But can this method do anything beyond a cute demonstration?

The authors suggest it can be a tool to test hypotheses. They provide the example of the "age positivity effect": older people are generally happier than younger people, even though both young and old view old age negatively (Carstensen & Mikels, 2005). This phenomenon has already been tested via other methods.

The graph below shows word frequency in status updates as a function of age.

Could this method be put to good use in education? If we view it as a another window, however imperfect, into the mind of users, it would certainly seem so. What is on the minds of students who succeed in school? Of those who don't succeed in school, but succeed in life? Of those who love mathematics but hate school?

References
Carstensen, L. L., & Mikels, J. A. (2005). At the intersection of emotion
and cognition: Aging and the positivity effect. Current Directions in
Psychological Science, 14,117–121.

Kern, M. L. et al (2013) From "Sooo excited!!! to "So proud": Using language to study development. Developmental Psychology. Advance online publication. doi: 10.1037/a0035048

What does it mean for an administrator to be an instructional leader? As often as this phrase is repeated, you'd think there would be well-researched techniques with proven effectiveness. There is no shortage of authors offering protips: Amazon has over a thousand titles that include the phrase.

But there is less research on the topic than you'd think, and much of it (e.g., May, Huff, & Goldring, 2012) actually shows a weak or non-existent relationship between student achievement and the priority administrators place on instructional leadership (as opposed to other aspects of a principal's job, e.g., close attention to administrative matters, inspirational leadership, focus on school culture, etc.).

A terrific new study by Jason Grissom, Susanna Loeb, and Ben Master shed light on the role of instructional leadership. It's the method that sets this study apart. Instead of simply asking principals "how important is instructional leadership to you?" or having them complete time diaries, researchers actually followed 100 principals  around for a full school day, recording what they did.

The researchers also had access to administrative data from the district (Miami-Dade county) about principals, teachers, and students that could be linked to the observational data. The outcome measure of interest was student learning gains, as measured by standardized tests.

The results showed that principals spent, on average, 12.6 percent of their time on activities related to instruction. The most common was classroom walkthroughs (5.4%) and the second was formal teacher evaluation (2.4%).

Some school characteristics were associated with variations in the amount of time principals devoted to instructional leadership. More time was spent in schools with lower-achieving students, with students from lower-income homes, and with a higher percentage of students of color.

As to the primary question of the study, time spent on instructional leadership was NOT associated with student learning outcomes.

But once "instructional leadership" was made more fine-grained, the picture changed.

Time spent coaching teachers--especially in math--was associated with better student outcomes. So was time spent evaluating teachers and curriculum.

But informal classroom walkthroughs--the most common activity--were negatively associated with student achievement. This was especially true in high schools.

In a follow-up analysis, the researchers evaluated these data in light of what the principals said about how teachers view classroom walkthroughs. The negative association with student achievement was most evident where principals believed that teachers did not view walkthroughs as opportunities for professional development.  (Other reasons for walkthroughs might be to ensure that a teacher is following a curriculum, or to be more visible to faculty.)

Although the researchers suggest that their results should be considered exploratory, they do suggest a general principle of instructional leadership that fits well with one overarching principle of learning: feedback is essential. Instructional leadership activities that offer meaningful feedback to teachers may help. Those that don't, will not.

Grissom, J. A., Loeb, S., & Master, B. (2013). Effective instructional time use for school leaders: Longitudinal evidence from observations of principals. Educational Researcher, 42,  433-444.

May, H., Huff, J., & Goldring, E. (2012). A longitudinal study of principals' activities and student performance. School Effectiveness and School Improvement, 23, 417-439.

Diane Ravitch posted a comment from a reader on her blog yesterday, which drew this comparison:

"But both CCSS and standardized testing are trying to make teachers into KAPOs, a Nazi concentration camp prisoner who was given privileges if they would supervise work gangs."

Diane later noted that there was an "outpouring of rage on Twitter" against this post. She went on to say

"Several people said I should not have allowed it on the blog or words to that effect. I find this argument to be a form of political correctness that is used to censor opinion. If anyone wants to use an analogy to make a point, that is their choice."

Diane has continued to defend the posting on Twitter today, Dec. 27. I think this defense is off target in three ways.

First, I would not call this a case of political correctness. Diane has not said that the analogy is not offensive, but she has suggested that objecting to it is tantamount to political correctness. This will always be a judgment call, but I am on the other side of the fence on this one. There are certain events that are so important, so sensitive to the people in whose culture it is enmeshed that I find it unfeeling and insensitive to draw on that event for ones own purposes. That is especially true when the comparison minimizes the trauma and suffering associated with the event. Test-takers are not comparable to Holocaust victims, nor are students asked to perform public service comparable to slaves. This is a far cry from the hypersensitivity documented in The Language Police in which, for example, an elderly person could never be depicted as doing something stereotypically associated with the elderly.

Second, I disagree with Diane's characterization of people's objections. If you agree that some speech is ill-considered and offensive, telling people that is not censoring their opinion. It's just not the same thing. It's telling them you think their analogy is ill-considered and objectionable, and you are asking them to rethink. You're not forbidding them from saying it, obviously.

Third, more specific to Diane, if she had asked the author to change the analogy or had refused to post the piece because of the analogy, I would not call that censorship. The author does not have a guaranteed right to post what she likes in Diane's blog, a right that Diane would have been infringing. Diane was a offering a platform for this author's voice, and obviously she offers that platform to voices she thinks are worth amplifying. This situation is not comparable to that documented in The Language Police, in which enormous power was concentrated in the hands of few publishers. If an author wanted to publish a textbook they had to toe the line drawn by the publishers or give up on publishing the book. That power relationship does not exist in this case. This is the internet, for crying out loud.

Diane, I respectfully ask that you rethink your position on this matter. I don't think it was a good call and I don't think your defense of it holds up.

EDIT: 1:28 p.m EST. I referred The Language Police as Left Back.

Pop quiz: What’s the earliest age that children think abstractly?

• 2 years
• 4 years
• 7 years
• 9 years

In truth, it’s a bad question because the answer depends on the type of abstraction. If the subtext of the question is “what’s the earliest age at which children show understanding of an abstraction?” the best choice from those offered above is “2 years.” And very likely earlier. Here’s one example.

Caren Walker and Alison Gopnik (2013) examined toddlers ability to understand a higher order relation, namely, causality triggered by the concept “same.”

The experimental paradigm worked like this. The toddler was shown a white box and told “some things make my toy play music and some things do not make my toy play music.” The child then observed three pairs of blocks that made the box play music, as shown below. On the fourth trial, the experimenter put one block on the box and asked the child to select another that would make the toy play music. There were three choices: a block that looked the same as the one already on the toy, a block that had previously been part of a pair that made the toy play music, and a completely novel block.

Toddlers (21 to 24 months old) selected the identical block most often (61% of the time).

Further experiments showed that children as young as 18 months got the task right, and showed that children this age can use the concept “different” as well as they understand “same. “

What’s interesting about this finding? It would be easy to believe that children so young would fix attention on features of an individual block, rather than relations among blocks (i.e., red blocks make it work). Importantly, the child is not just appreciating sameness—he or she is using that property by understanding its causal role. And the child ignores other properties (e.g., shape or color) that are more salient. Furthermore, children learn this property readily, after exposure to just three trials. This finding may speak to the importance to our species of understanding causality.

I want to use this experiment to illustrate a broader point.

A dominant theme within cognitive developmental psychology over the last thirty years has been that children look more clever in proportion to the cleverness of experimenters. That is, as experimenters develop more subtle ways to evaluate children, it becomes clear that children understand more at a younger age than we appreciated. They were capable of learning it all the time. The problem lay in how we were looking.

The same applies to the concept explored by Walker & Gopnik. Dedre Gentner (Christie & Gentner, 2010) has reported data showing that even preschoolers seem to have trouble with reasoning tasks that call for higher-order relations—they seem to need scaffolding in which the important relation is labelled. Walker and Gopnik point out that Gentner used a task requiring verbal labeling, whereas their task merely called for an action. Seemingly small differences in what look like conceptually similar tasks can make a big difference in whether the child seems to understand.

This is one (but not the only) reason that I think it’s important to be cautious in making claims about what children are and are not ready for. The extent to which they appear ready to understand an abstraction depends partly on how we measure knowledge.

It is the normal state of developmental affairs that a child’s initial understanding of a concept looks fragile, fragmented, and uncertain. The child shows understanding on one task but is stumped by a conceptually similar task with (seemingly) trivial differences in format. He seems to understand one day, but not the next (e.g., Flynn & Sielger, 2007).

In fact, I’d suggest that complete mastery of concept across materials, types of query, and times is a good indication that the concept was introduced at a developmentally inappropriate time. We waited too long--the child probably already knew the concept.

Reference

Christie, S., & Gentner, D. (2010). Where hypotheses come from: Learning new relations by structural alignment. Journal of Cognition and Development, 11, 356–373.

Flynn, E., & Siegler, R. (2007). Measuring change: Current trends and future directions in microgenetic research. Infant and Child Development, 16, 135-149.

Walker, C. M. & Gopnik, A. (2013). Toddlers infer higher-order relational principles in causal learning. Psychological Science, published online doi: 10.1177/0956797613502983

A New York Times editorial on December 6 called for improved math instruction, calling the current system “broken.” Although I agree we could be doing a better job of teaching math, the suggestions in the editorial showed a striking naiveté about what it will take to improve.

The editors of the Times offered four suggestions:

1. A more flexible curriculum (especially better integration of engineering)
2. Very early exposure to numbers
3. Better teacher preparation
4. Experience in the real world (perhaps via collaborations with industry)

The editorial ignores the fact that 1 and 4 will be meaningless without 2 and 3. And it grossly underestimates the difficulty of implementing 2 and 3.

The editors’ idea regarding how to implement “early exposure to numbers” is to ensure better access to preschool. But that won’t do it because “exposure” won’t do it. Math is not learned like a language. Children can learn vocabulary and more complex syntax by mere exposure. They can’t learn math that way.

Still, the editorial is right to argue that very early learning is important. I’d argue it’s the key to math reform.

That National Math Panel concluded that three things need to be in place for students to be proficient in math: (1) you need to have memorized a small number of math facts to automaticity; (2) you need to know standard algorithms that apply to standard problems and; (3) you need a conceptual understanding of number, and of what algorithms do.

American kids are okay (not great) on math facts and okay (not great) on algorithms. On conceptual understanding, they are terrible. A student can get by for a time by memorizing algorithms and when they are to be applied, but eventually, not understanding what you’re doing catches up with you, meaning it affects your success in math.

But lacking conceptual understanding makes people hate math long before that. What could be more boring than executing algorithms you don’t understand? And if you don't understand what you're doing, why wouldn't you conclude "I'm not really good at math?"

This conceptual understanding ought to start in preschool with ideas like cardinality and equality. “Very early exposure to numbers” is not going to do it. That doesn’t mean taking what we had been doing in first grade and asking kids in pre-K to do it. That means putting activities into pre-K (e.g., games and puzzles that emphasize the use of space) that will provide a foundation for conceptual understanding so that first-graders will be in a better position to understand what they are doing. (Though first grade math will also have to change for that happen.)

The other recommendation that the editors of the Times get wrong is “Better teacher preparation.” They focus on high school, noting that many teachers of physical sciences did not major in these subjects. That may be a problem, but it ignores a much more serious teacher problem.

Most American teachers—like most American adults, including me--don’t have a deep conceptual understanding of math. They are a product of the system we are trying to change. You cannot teach what you don’t know.

So what’s my recommendation for American mathematics?

We need to pay much closer attention to preschool and to early elementary grades. That will entail developing methods of helping children understand the conceptual side of math—methods we now lack. It will also entail professional development to train teachers in the conceptual side of math.

The size of this undertaking is massive. But it directly addresses the issue encapsulated in the editorial’s title: “Who Says Math Has to Be Boring?” The editorial focuses on the idea that it’s boring to do things without knowing why you’re doing them. So the proffered solution is real-world application. But I think a worse problem is not understanding how math works, being asked to execute algorithms with no understanding of what is really happening. That’s a heavier lift but will ultimately be more rewarding.

On a scale of 1 to 10, how much do you think Pearson publishing cares about the efficacy of their products?

Now now, I asked for a numerical rating, not invective or expletives.

My own rating might be a three or a four. I'm guessing that the folks at Pearson care about effectiveness to some extent because it affects how much things sell.

But the bottom line is that what matters is the bottom line. The success and failure of particular marketing strategies are followed closely, I'm guessing, as are sales of particular products. Learning outcomes from the product? Well, the customer can track them if they are interested.

So what are we to make of it when Pearson says "We are putting the pursuit of efficacy and learning outcomes at the centre of our new global education strategy."

Wut?

Educators have every right to be cynical. It's not just that Pearson has shown little inclination in this direction in the past, but also that it's a publicly traded company that shareholders ought to expect will put profits first.

Ironically, the path Pearson plans to effect this change is mostly about inputs: hiring people who care about efficacy, developing a global research network to gather evidence, that sort of thing.

But crucially they also promise to track outcomes, namely "to report audited learning outcomes, measures, and targets alongside its financial accounts, covering its whole business by 2018."

That's an enormous commitment and if they really follow through, it gives me some confidence that this is not merely a marketing ploy. Or if it is, the marketing team has concluded that to make this ploy appear not to be a ploy, they need to put some teeth in the plan.

A significant aspect of the success of this step turns on that small adjective "audited." It's not that hard to cook the learning outcome books. For this new effort to be persuasive, Pearson will need to have disinterested parties weigh in on the efficacy measures used, and their interpretation.


A person knowledgeable about testing, yet wholly disinterested? Does Pearson have Diogenes on staff?

There's another aspect of this plan that I find even more interesting, and potentially useful. Pearson has published a do-it-yourself efficacy review tool. It's a series of questions you are to consider to help you think about the effectiveness of a product you are currently using, or are contemplating using. There's an online version as well as a downloadable pdf.

The tool encourages you to consider four factors (listed here in my own phrasing):

1. What am I trying to achieve?
2. What evidence is there that this product will help with my goal?
3. What's my plan to use this tool?
   
4. Do I have what I need to make my plan work?

These simple, sensible questions are elaborated in the framework, but working through the details should still take less than an hour. The tool includes sample ratings to help the user think through the rating scheme.

I think this tool is great, and not just because it aligns well with a similar tool I offered in When Can You Trust the Experts?

I think it offers Pearson a way to gain credibility as the company that cares about efficacy. If I were to hear that Pearson's sales force made a habit of encouraging district decision-makers to apply this efficacy framework to the educational products of Pearson (and others) that would be a huge step forward.

I would be even more impressed if Pearson warned users about the difficulty of overcoming the confirmation bias, and making these judgments objectively.

Still, this is a start. There might be some satisfaction in greeting this move with cynicism, but I think it's better to start with skepticism--skepticism that will prompt action and help to encourage educators to think effectively about efficacy. 

Is there a critical period of brain plasticity for literacy? We know that brain development progresses with age. If a child does not learn to read at the right age, has the brain lost its plasticity such that learning to read will be more difficult?  

For at least one aspect of brain plasticity, we now have data indicating that the answer is “no.”

That aspect of plasticity that bears on reading is the loss of mirror invariance in visual perception.

Mirror invariance means recognizing a mirror image as the same object. It makes good sense for visual recognition to be set up this way. If I recognize a dog facing to my left, I ought to recognize the same dog facing to my right as the same object.

But mirror invariance is a problem when children are learning to read, because for that task one must NOT treat mirror-reversed objects as identical: b and d must be treated differently. Anyone who has observed children learning to read and write cannot help but notice that they initially make a lot of mirror reversal errors. The errors disappear with practice.

In a recent study Felipe Pegado and colleagues (2013) set out to investigate whether literacy changes mirror invariance not just for letters of the alphabet, but for other visual stimuli as well. Does the process of learning to read actually change this aspect of vision?

The researchers simply showed subjects pairs of stimuli, to which they were to respond “same” or “different” via button press. Mirror images were to be judged “same.”

The experimenters used three different types of stimuli: pictures, letter strings, and false fonts (that is, letter-like stimuli that were not actually letters.

Of most interest, they tested three groups of subjects: illiterate adults (“il” in the graph below), ex-illiterates (i.e, those who learned to read as adults; “ex” in the graph below) and literate adults (that is, those who learned to read at a typical age; “li” in the graph below). 

The solid line shows reaction times to mirror reversed images, and the dashed line is reaction time to the non-reversed images. Look first at the data for the illiterate subjects for the pictures, strings, and false fonts: they respond equally quickly for mirror reversed and same stimuli.  

But the ex-illiterate (ex) and the literate (li) subjects have trouble with the mirror reversed images. They have BIG trouble with the letter strings, but they are slower even with the pictures.

What does this result mean?

A straightforward interpretation is that lots of practice with visual stimuli that are not mirror-reversible—that is, learning to read—changes the visual system. The natural state of the visual system is that mirror-reversed objects are treated as equivalent. Literate people can treat them as equivalent, but it takes a little extra time.

I find two aspects of these findings interesting: that that visual system changes in this way and that the “ex-illiterate” subjects show the same phenomenon. Thus (at least for this process) it’s not that case that, once brain development is finished the visual system is no longer open to change.

This visual process is not the only one that is changed by learning to read, but this one at least is not subject to a critical period of development.

Reference:
Pegado, F., Nakamura, K., Braga, L. W., Ventura, P., Filho, G. N., Pallier, C., Jobert, A., Morais, J., Cohen, L., Kolinsky, R., & Dehaene, S. (2013, June 17). Literacy Breaks Mirror Invariance for Visual Stimuli: A Behavioral Study With Adult Illiterates. Journal of Experimental Psychology: General. doi: 10.1037/a0033198

"Stereotype threat" refers to a phenomenon in which people perform worse on tasks (especially mental tasks) in line with stereotypes, if they are are reminded of this stereotype.

Hence, the stereotype for women (in American culture) is that they are not as good at math as men; for older people, that they are more forgetful than the young; and for African-Americans, that they are less proficient at academic tasks. Members of each group do indeed perform worse at that type of task if the stereotype is made salient just before they undertake it (e.g. Appel & Kronberger, 2012).

Why does it happen? Most researchers have thought that the mechanism is via working memory. When the stereotype becomes active, people are concerned that they will verify the stereotype. These fears occupy working memory, thereby reducing task performance (e.g., Hutchison, Smith & Ferris, 2013).

But a new experiment offers an alternative account. Sarah Barber & Mara Mather (2013) suggests that stereotype threat might operate through a mechanism called regulatory fit. That's a theory of how people pursue goals. If the way you conceive of task goals matches the goal structure of the task, you're more likely to do well than if it's a poor fit.

Stereotype threat makes you focus on prevention; you don't want to make mistakes (and thus confirm the stereotype). But, Barber & Mather argue, most experiments emphasize doing well, not avoiding mistakes. Thus, you'd be better off with a promotion focus, not a prevention one.

To test this idea, Barber & Mather tested fifty-six older (around age 70) subjects on a combined memory/working memory task. Subjects read sentences, some of which made sense, others which were nonsensical either syntactically or semantically.

Subjects indicated with a button press whether the sentence made sense or not. In addition, they were told to remember the last word of the sentence for as many of the sentences as they could. Task performance was measured by a combined score: how many sentences were correctly identified (sensible/nonsensical) and how many final words were remembered.

Next, subjects read one of two fictitious news articles. The one meant to invoke stereotype threat described the loss of memory due to aging. The control article described preservation of memory with aging.

Then, subjects performed the sentence task again. We would expect that stereotype threat would lead to worse performance.

BUT the experimenters also varied the reward structure of the task. Some subjects were told they would get a monetary reward for good performance. Others were told they were starting with a set amount of money, and that each memory error would incur a penalty. 

The instructions made a big difference in the outcome. As shown in the graph, framing in terms of costs for errors didn't just remove stereotype threat; it actually lead to an improvement.

This outcome makes sense, according to the regulatory fit hypothesis. Subjects were worried about errors, and the task rewarded them for avoiding errors.

These data are the first to test this new hypothesis as to the mechanism of stereotype threat, and should not be seen as definitive.

But if this new explanation holds up (and if it applies to other groups) it should have significant implications for how threat can be avoided.

References:
Appel, M., & Kronberger, N. (2012). Stereotypes and the achievement gap: Stereotype threat prior to test taking. Educational Psychology Review, 24(4), 609-635.

Barber, S. J., & Mather, M. (2013). Stereotype Threat Can Both Enhance and Impair Older Adults’ Memory. Psychological science, published online Oct. 22, 2013. DOI: 10.1177/0956797613497023.
Hutchison, K. A., Smith, J. L., & Ferris, A. (2013). Goals Can Be Threatened to Extinction Using the Stroop Task to Clarify Working Memory Depletion Under Stereotype Threat. Social Psychological and Personality Science, 4(1), 74-81.

I finally got around to reading Paul Tough's How Children Succeed. If you haven't read it yet, I recommend that you do.

You probably know by now the main message: what really counts for academic success is conscientiousness (or its close cousins, grit, or character or non-cognitive skills).

Tough intersperses explanations of the science behind these concepts with stories of students that he's met and followed. The stories add texture and clarity, and Tough is among a very small number of reporters who gets complex science right consistently. He takes you through attachment theory, the HPA axis, and executive control functions, all without losing his footing nor prompting glazing in the reader's eyes.

Tough also devotes considerable space to a fascinating inside look at how charter school mavens have thought about self-control, how their thinking has changed over time, and how their views square with the science.

The only flaws I see in the book concern a couple of big-picture conclusions that Tough draws.

First, there's what Tough calls the cognitive hypothesis--that academic success is driven primarily (perhaps even solely) by cognitive skills. The book suggests that this premise may be in error. What really counts is self-control.

But of course, you do need cognitive skills for academic success. In fact, Tough describes in detail the story of a boy who is very gritty indeed when it comes to chess, and who scales great heights in that world. But he's not doing all that well in school, and a teacher who tries to tutor him is appalled by what he does not know.

Self-control predicts academic success because it makes you more likely to do the work to develop cognitive skills. I'm sure Tough understands this point, but a reader could easily miss it.

Second, Tough closes the book with some thoughts on education reform. This section, though brief, struck me as unnecessary and in fact ill-advised. The whole book is about individual children and what makes them tick. Jumping to another level of analysis--policy--can only make this speculation seem hasty.

But these two minor problems are mere quibbles. If you have heard about "non-cognitive skill," or "self-control" or "grit" and wonder whether there's anything to it, you'd be hard put to find a better summary than How Children Succeed.