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.