Over at The Anova, Freddie deBoer has a knack for writing about statistical questions and making them not just readable but interesting.
Case in point: he recently explored the New York Times feature about school choice.
Although careful to praise the Times authors for their genuine concern and dedication, he thoughtfully explicates the numerous ways in which their article gets important questions wrong because it doesn’t think its way through statistics carefully enough.
For example: when we say we want students to do better, does that mean we want individual students to rise above the average, or that we want to raise the average for students overall?
As deBoer sees the field, we typically say we want the latter, but focus on (and tell stories about) the former.
DeBoer’s article doesn’t express an opinion about school choice (I’m sure he has one, but he doesn’t tip his hand here). But, it’s an excellent reminder that statistics can help us only so long as we are clear-minded about what they really measure.
As he glumly says in his final paragraph:
It’s not just that we can’t get what we want. It’s that nobody really knows what they’re trying to accomplish.
Maria Montessori described observing children in a traditional classroom as being tantamount to an entomologist observing dead insects pinned to a board, “where the spontaneous expression of a child’s personality is so suppressed that he is almost like a corpse, and where he is so fixed to his place at a desk that he resembles a butterfly mounted to a pin” (Montessori, 1967b).
Despite her observations taking place around the turn of the 20th century, they sound eerily familiar. Even over a century ago, she acknowledged that in order to best learn, children need a certain freedom in order to explore their interests and take ownership over what they are doing.
Presumably motivated by the discrepancy between reality and practice, she developed an approach to education. Initially working with children with learning difficulties, and later with children between the ages of 3 and 6, Maria Montessori–who first studied medicine–developed her approach almost completely through careful observation of the way in which children interacted with their environment.
Montessori’s insights about the way children learn and develop were not confirmed by science until many years later. In a book, Montessori: The Science Behind the Genius, Angeline Stoll Lillard (2005) outlines the eight principles incorporated into Montessori Education and provides the evidence base supporting each one. The principles are:
movement and cognition are intertwined
students should have a sense of control
interest improves learning
extrinsic rewards hinder intrinsic motivation
learning from and with peers
learning should be contextualized
optimal adult-child interactions
order in the environment
While there are many examples of each of these embedded in the Montessori classroom, and separately each one of these concepts now brings with it an immense amount of research, for each principle I cherry-pick just one or two examples from the classroom.
I also provide a brief mention of some supporting research to help give you a sense of the science that now reinforces the Montessori approach to education, developed over a century ago.
This blog post will address the first four principles listed above, part 2 will be posted at a later date and will address the latter four.
Movement and Cognition are Intertwined
Montessori activities and materials purposefully incorporate movement into learning activities. Let’s take the Sandpaper Letters, for example, used to introduce preschool-aged children to letter sounds. (Children are not taught the names of the letters nor the order of the alphabet at this point). The Sandpaper Letters are lowercase letters, about five inches in height, made out of sandpaper and affixed to thin piece of painted wood.
When introduced, children are simultaneously shown how to trace the letter and produce the sound that the letter makes. The child is then free to use the Sandpaper letters to practice producing the letter sounds and tracing the letters.
Research has since underscored many instances of the interconnected nature of movement and cognition, including the improvement of memory when movement is involved at the moment when something is learned. For example, students who acted out actions described by sentences remembered the sentences better than students who did not act them out (*Cohen, 1989; *Engelkamp, Zimmer, Mohr & Sellen, 1994).
In the same way, when children simultaneously trace a letter and produce its sound, they are better able to remember it.
Students should have a sense of control
In the Montessori classroom, this sense of control is brought about by giving children the choice of activities they wish to pursue, from among the options that have been laid out by the teacher; the Montessori m.o. is freedom within limits.
So if Thomas wants to pick up where he left off on a mathematics activity, he may do so. Or, if he wishes to take out the Knobbed Cylinder work from the Sensorial area (which, unbeknownst to him, will help him to develop his pincer grip necessary to later begin writing), he may do that as well. Thomas has a choice over what activity he wants to do, and how long he wants to do it for.
Researchers carried out a simple experiment which highlighted the importance of choice in activities. Children aged seven to nine years were presented with six categories of anagrams to work on. While all of the children in reality had the same choices, one group was told to choose from among the six categories, a second group was told that the experimenter chose the categories for them, and a third group was told that their mothers had made the choice of categories for them.
Children in the first group who “chose their own work” solved twice as many anagrams as the other two groups in the same amount of time. Additionally, during an optional free-play period after the time allotted to work on the anagrams, children in the first group elected to spend more time continuing to solve anagrams (*Iyengar & Lepper, 1999).
When children in a Montessori classroom have the freedom to choose, they have a sense of control, they take ownership over what they are doing, and their performance and their persistence improve. The freedom to choose also fosters independence in young children.
Interest improves learning
In a previous post, I talk about the importance of emotion in learning. The Montessori method is yet another approach to learning which capitalizes on this notion.
Making the most of student interest can be seen from many different levels in the Montessori approach:
the design of materials in which young children tend to be naturally interested,
the introduction of language activities at a time when, developmentally, children take an interest in learning their language,
allowing children to pursue activities that they find interesting at a given moment.
It only makes sense that people will better learn something in which they are interested. All else held constant, if two people are given piano lessons, one who has pined for professional instruction for some time, and the other whose parents forced it on him, the former will most certainly learn how to play better more quickly. Interest matters.
There are numerous studies that confirm this common sense conclusion. (I won’t delve into them here, but they’re out there.) Let me instead present you with the psychological definition of the word: being in a state of interest involves, “focused attention, increased cognitive functioning, persistence, and affective [emotional] involvement” (*Hidi, 2000, p. 311). In capitalizing on student interest, the Montessori approach encourages all of these things.
Extrinsic rewards hinder intrinsic motivation
Depending on the circumstances, extrinsic rewards can get fast (though not necessarily long-lasting) results. Extrinsic rewards have their place, though when it comes to one’s learning, the Montessori approach views extrinsic rewards as a hinderance to concentration and intrinsic drive: the characteristics that Montessori herself sought to instill in individuals.
Instead of extrinsic motivators, Montessori education relies on children’s natural curiosity for motivation, and does all that it can to get out of the way of children and their learning. By giving children extended time to pursue the activities that interest them, Montessori teachers let students focus on an activity for as long as they wish, in order to complete it as many times as desired. This freedom allows children to obtain for themselves a strong sense of accomplishment and satisfaction.
These feelings, not gold stars, provide the impetus and motivation for more challenging pursuits.
One study in particular (*Lepper, Greene & Nisbett, 1973) highlights particularly well the detrimental effect that extrinsic rewards can have on individuals–even with activities individuals otherwise would enjoy.
In this study, researchers put out markers available for use in classrooms of 3- to 5-year-old children. They noted which children were heavy marker users. One at a time, the heavy marker users were pulled aside and shown a “Good Player Award” (a card with a gold star and ribbon), and when asked, all the children said they would like to receive one. These children were told that all they had to do was draw with the markers.
In one condition, children were told they would receive a “Good Player Award” after drawing with the markers for six minutes. In another condition, the children were allowed to draw for six minutes and were unexpectedly given the award on the board. And in a third condition, the children drew for six minutes and no award was ever mentioned.
A panel of judges blind to each child’s condition rated the drawings of the children who expected the reward as being much lower in creative quality than those of the children in the two other conditions.
They researchers also found that a few weeks after the experiment, the children conditioned to expect a reward for using the markers used markers far less than the other children, and about half as much as the other children in the class.
In an activity that children otherwise enjoyed, the introduction of extrinsic rewards decreased children’s creativity, in addition to later decreasing their voluntary participation once the possibility of getting a reward was removed.
(For a recent LatB blog article about intrinsic and extrinsic motivation, click here.)
Conclusion
Developing curricula around these four principles would be powerful. I wish that my own education had better leveraged these four insights, I’m sure I’d be all the better for it.
What I continue to find intriguing is that these were developed simply through the meticulous observation of young children over time, carried out by one person. No scientific experiments necessary.
More recent studies have revealed that these principles are in line with the way we learn. Designing her approach with the way children learn and develop better enables them to engage with and take ownership of their learning. This, I believe, is a major oversight with the way children are currently educated.
Look out for part two where I will delve into the other four principles, and discuss what this can look like in the classroom.
Reference
Lillard, A. S. (2005). Montessori: The science behind the genius. New York, NY: Oxford University Press.
Montessori, M. (1967b). The discovery of the child. New York, NY: Ballantine Books.
*References marked with an asterisk are cited in Lillard, 2005.
Oxytocin is often described as the “love hormone.” Apparently lots of oxtyocin is swirling around when mothers interact with their babies, and so its role in maternal affection is much trumpeted.
You may well hear people say that, in schools, we need to be sure that our students have more oxytocin in their lives.
However, folks giving this advice may be unsettled to hear that recent research describes oxytocin as “the relationship crisis hormone.”
Researchers in the US and Norway have found that, in romantic relationships, discrepancies in romantic interest lead to higher levels of oxytocin production.
In my mind, this news underlines an important general conclusion.
a) The study of psychology is complicated.
b) The study of neuroscience is really complicated.
c) The study of hormones is absurdly complicated. I mean, just, you cannot believe how complicated this stuff gets.
As a result, I encourage you to be wary when someone frames teaching advice within a simple hormonal framework. If you read teaching advice saying “your goal is to increase dopamine flow,” it’s highly likely that the person giving that advice doesn’t know enough about dopamine.
(BTW: it’s possible that the author’s teaching advice is sound, and that this teaching advice will result in more dopamine. But, dopamine is a result of the teaching practice–and of a thousand other variables–but not the goal of the teaching practice. The goal of the teaching is more learning. Adding the word “dopamine” to the advice doesn’t make it any better.)
In brief: if teaching advice comes to you dressed in the language of hormones, you’ll get a real dopamine rush by walking away…
Loyal blog readers know that Austin Matte is our local expert on Head Start. To follow up on his recent article, I want to highlight study published in Child Development.
Studying records of nearly 3000 students, the authors find that attendance matters. Head Starters who miss class don’t make as much progress in math and literacy as those who do.
That news might not sound surprising–of course attendance matters!–but it contributes to an important debate about the value of Head Start in the first place.
The Argument, Part I
We’ve got some good research showing that, although Head Start produces impressive gains among its participants, those gains just don’t last. This review, for example, finds that–by 3rd grade–Head Start participants no longer stand out from their non-Head-Start peers.
In the biz, they call this result “fadeout.” Some people argue that fadeout suggests we should give up on Head Start altogether. After all, given that its results don’t last, we should spend our money elsewhere.
Austin’s response to this argument (a response I find persuasive, by the way) is that fadeout in fact demonstrates the benefits of Head Start.
Here’s an analogy:
I’m overweight and my cholesterol is high. My doctor tells me to exercise and eat right. I start jogging four times a week and eating like Tom Brady. A year later–voila!–my doctor reports that I’m the picture of health.
So, I stop with the jogging, and go back to potato chips and lard burgers. Fairly soon, I’m back to my old weight and cholesterol level.
Now: do you blame the jogging? Or, do you blame the end of the jogging?
People who say that “Head Start” doesn’t work are blaming the jogging. But, it just seems obvious that the jogging helped. It was my decision to stop–not to start–jogging that caused the problems.
Isn’t the straightforward conclusion that we should add more years to Head-Start, not eliminate the program that’s clearly working?
The Argument, Part II
Today’s study gets at the same question a different way. If Head Start programs didn’t really help, then doing less of them wouldn’t matter. Gaps in attendance shouldn’t be a problem, because the program being attended wouldn’t actually accomplishing anything.
This research, however, gives the lie to that logic. Clearly, less time in Head Start leads to less learning; or–said the other way around–moretime produces more learning.
(In the biz, they call this “the dosing effect.” A higher dose of something–in this case, Head Start–leads to greater benefits–in this case, greater learning.)
Given that we see a dosing effect, we can have confidence that Head Start does, in fact, cause the changes it claims to cause.
I + II = Yes
Austin’s argument about “fadeout” helps us see the long-term benefits of Head Start. And today’s study about “dosing” helps us see the short-term effects of Head Start.
As the promise of spring and summer days rolls in, the increase in sunshine can mean only one thing for students: assignments, exams, papers, and projects are due.
Not surprisingly, this time of year arrives with no shortage of stress for those with tight deadlines, writer’s block, computer glitches, or myriad other dilemmas inherent to the academic world.
And for those faced with the daunting sight of a blank page needing to be filled, I like to offer the charming words of Sylvia Plath: “let me live, love, and say it well in good sentences.”
Of course, taken from Plath’s novel The Bell Jar, the quote’s implied ease of eloquent composition belies much of the strife of writing. Which brings us to an important question: where do good writers come from? Or, better yet, how do children acquire the words that will eventually be put on paper to make them good writers (and to ace those finals)?
Given that language and literacy skills are ubiquitous, their development has been an interest of researchers for years. And it turns out that early language exposure has long-lasting implications for childhood skill growth.
Let’s Talk about School Talk
Hoping to better understand if the amount and type of vocabulary that preschool teachers use around their students would predict children’s language skills at kindergarten and beyond, Dickinson & Porche (2011) conducted a longitudinal study. [1]
The researchers observed and videotaped classroom interactions in a number of Head Start preschools. Teacher-child talk was then separated into several categories:
teacher extending utterances were those times when teachers tried to keep conversation going by encouraging children to talk further;
sophisticated vocabulary reflected the number of low-frequency or sophisticated words used by teachers;
attention-related utterances were those times when teachers tried to gain or hold their students’ attention;
correcting utterances arose when teachers corrected the accuracy of what students said;
and analytic utterances during book reading happened when teachers prompted their students to explore reasons for characters’ actions or discussed the meanings of words.
The researchers also examined children’s literacy skills. To do this, the children completed tests targeting storytelling, receptive vocabulary, reading comprehension, and word recognition at both kindergarten and 4th grade.
Analyses showed that reading comprehension in 4th grade was positively related to preschool teachers’ use of sophisticated vocabulary and attention-related utterances.
As well, preschool teachers’ use of sophisticated vocabulary positively influenced 4th grade decoding skills.
Finally, a mediation model, or an indirect chain effect, emerged among preschool teachers’ sophisticated vocabulary, children’s kindergarten decoding skills, and children’s 4th grade reading comprehension. That is, students who had a preschool teacher that used more sophisticated vocabulary were better able to decode words in kindergarten, and in turn had better reading comprehension skills in 4th grade.
So, in essence, preschool teachers who used more varied words, and maintained their students’ attention to these words, seemed to provide more opportunities for their students’ language skills to grow.
Let’s Talk about Home Talk
Of course, no discussion of schooling’s impact on early skill development is complete without a look toward the home’s impact.
One such home-based study investigated the relation between socioeconomic status (SES) and children’s early language development. [2]
There were two primary hypotheses here:
that SES-related differences in children’s vocabulary could be the result of SES-related differences in language-learning experiences;
that maternal speech would mediate the relation between SES and child vocabulary development
33 high-SES families and 30 mid-SES families agreed to video record daily activities in their home and allowed researchers to transcribe them. Parent-child interactions were recorded twice, 10 weeks apart, and included such activities as getting dressed, eating breakfast, and playing with toys.
The researchers then used a variety of measures to analyze maternal speech.
They tallied word tokens (i.e., the number of different words used), word types (i.e., the number of root words used, such that using both ‘run’ and ‘running’ counted as one use), and word totals (i.e., the total number of words, even if some were used more than once).
They also counted the number of times the parent built upon something the child said (topic-continuing replies).
Finally, children’s vocabulary skill was assessed as a measure of productive vocabulary, or the number of word types used in an average 90-utterance speech sample.
These data showed that SES was significantly associated with both child vocabulary and maternal speech: high-SES mothers produced more utterances, more word tokens, more word types, spoke for longer periods of time, and produced more topic-continuing replies than did mid-SES mothers.
The average length of the mothers’ speech significantly predicted child vocabulary. And, the association between SES and child vocabulary became statistically weaker once the researchers subtracted maternal speech from the equation. In other words, the difference in vocabulary that the researchers found between the high-SES and mid-SES children was due (almost fully) to the differences seen in their mothers’ speech.
It seems, then, that SES-related differences in child-directed speech may arise from more general SES-related differences in language use. That is, the style of language use among higher-SES mothers appears to influence the way they talk to their children, which in turn affects the rate at which their children build their vocabularies.
Small Steps toward Big Words
These studies contribute to a large literature that suggests early language experiences have a substantial long-term impact on children’s language and literacy skill development.
So should parents and teachers grab the thesaurus in hopes that that their children will fast-track to the Dean’s List?
Probably not.
But a little mindfulness about how we (as parents, teachers, and/or caregivers) use our words around our youngest learners will probably go a long way.
In fact, studies have shown that even small increases in the richness of language that children are exposed to can have a lasting positive effect. [3]
So here and there, we can ask ourselves:
The next time I ask her to put her toys away, can I say it in a new way?
How can I push them to think about why the story character feels both happy and sad at the same time?
And my personal favorite: Am I saying this well, in good sentences?
References:
Connor, C.M., Morrison, F.J., & Slominski, L. (2006). Preschool instruction and children’s emergent literacy skills. Journal of Educational Psychology, 98, 665-689. [link]
Dickinson, D. K., & Porche, M. V. (2011). Relation between language experiences in preschool classrooms and children’s kindergarten and fourth-grade language and reading abilities. Child Development, 82, 870-886. [link]
Hoff, E. (2003). The specificity of environmental influence: Socioeconomic status affects early vocabulary development via maternal speech. Child Development, 74, 1368-1378. [link]
Exciting news: my book was published at the beginning of April. (I’m resisting the temptation to put in an exclamation point.)
Learning Begins explores the science of working memory and attention, and offers practical strategies for putting this research to work in our classrooms.
Here’s what the first Amazon reviewer wrote:
“This book feels more like a personal discussion with the author. Andrew shares stories with meaning, current useful research, and provides clear suggestions to better teaching methods and student supports. A quick and easy read! Andrew is a proficient educator himself who knows his audience and uses humor and story telling to reach them!”
I hope you’ll read it, and let me know what you think! (Okay, I gave in. There’s the exclamation point.)
(BTW: if you email me–[email protected]–I’ll give you a code for a 20% discount from the publisher.)
Should 9th graders start music classes–even if they’ve never played an instrument before? Are there academic benefits to studying music? Is 9th grade too late a start to get those benefits? Should my school’s STEM program become a STEAM program?
A recent study by Adam T. Tierney offers some answers to these compelling questions.
The Short Version
Tierney & Co. followed 19 high school students who enrolled in a high school music ensemble, and compared them to 21 students at the same school who started a JROTC program.
These groups started off nicely matched in various academic and linguistic measures. However, at the end of 4 years, the group that had studied music improved in some suggestive ways.
First, the neural signatures of their response to speech changed meaningfully; oversimplifying a bit here, they were “more mature.”
Second, the musicians improved more than the JROTC participants in their ability to distinguish between and manipulate language sounds.
Reasons to be Excited
Tierney’s study gives us several reasons to perk right up.
For example: we’ve known for a long time that life-long musicians have these language processing benefits. Now we have good reason to think that even those who pick up an instrument later in life get them as well.
Another example: this study compares the musicians to the JROTC participants. That is, it does not compare them just to some random collection of non-musicians. Like these new musicians, the JROTC students had a highly disciplined practice schedule, had to function in a structured group, and so forth.
Because the study includes this “active control group,” we can be sure the results don’t come from–say–just being part of an organized school activity.
Most exciting: the students’ improvement in their ability to process language sounds.
This ability–called “phonemic awareness”–gets a lot of research attention, because it can predict success in several essential language skills: reading and writing, to name two.
We test phonemic awareness in many ways. For instance:
“Which one of these words does not rhyme with the others: bell, swell, full, tell.”
“Say the word ‘boat.’ Now, say that again without the ‘b’ sound.”
“How many syllables are there in the word ‘ventricle’?”
If music practice–even music practice begun in high school–can improve students’ phonemic awareness, it just might be able to help them do well in other courses where they have to process language–which is to say: all of them.
Reasons to Remain Calm
Tierney’s study is exciting, but we shouldn’t require all of our students to join band just yet. Here are a few important gaps in this research:
The students enrolled in music class improved their phonemic awareness, but Tierney didn’t measure if that improvement had any impact on, say, their performance in English class; or, perhaps, their ability to learn a new language. That effect is plausible, but not demonstrated here.
Also, Tierney & Co. measured two other linguistic abilities beyond phonemic awareness: phonological memory, and rapid naming. They found no statistically significant difference between the music students and the JROTC students in these two measures.
If one measure out of three shows improvement, that’s good. But it’s not a home run.
And, a point about the research methodology here. These students chose to join band or JROTC; they were not–in the “gold standard” of research–randomly assigned to do so. (Of course: there are many good reasons to let students choose, rather than forcing them into one group or another.)
The differences we see, therefore, might not have to do with the experience of band vs. JROTC. Instead, they might be differences in the kind of 9th grader who wants to be in band vs. the kind of 9th grader who wants to be in JROTC.
In other words: perhaps those band students were always a little better at discriminating among sounds, which is why they were drawn to music in the first place. Tierney’s team did try to rule that out with their various pre-study measures, but perhaps those differences are not captured by the tests we have.
We just don’t know. (Or, better said: we don’t “know” in the way that scientists want to know things.)
A Final Point
I understand why people are attracted to this argument: “students should do art because it makes them better at other things we do in school.”
I am more attracted to this argument: “students should make art because it’s an essential expression of human joy, sorrow, love, solitude, fun, reverence, and hope.”
In other words: I don’t think schools should foster art because it makes people better at STEM. I think schools should champion art because it makes people better at being people.
A just-published study asks about the effect of schooling on the brain. (A chatty, readable summary by one of the authors can be found here.)
More specifically, it looks at a young child’s ability to self-regulate: a skill that early schooling emphasizes–and, of course, one that’s highly necessary for sustained success in almost any meaningful activity or relationship.
The authors take advantage of the arbitrary cut-off date for schooling, and look at brain development for children who were just old enough–or not quite old enough–to enroll in 1st grade.
The research question was: can we find meaningful differences in self-regulatory areas of the brain after a year of 1st grade (children just within the cut-off date) compared to a year of kindergarten (children just beyond the cut-off date)? Did these brains develop alike over the course of this year, as part of typical human development? Or, did the more academic structure of 1st grade influence brains to develop differently than the more playful freedom of kindergarten?
The result:
The research team found meaningful developmental differences in a specific region of the prefrontal cortex, and also in the posterior parietal cortex. Earlier work has shown both regions to be parts of neural networks that participate in self-regulation.
In other words: the greater structure of 1st grade seemed to bulk up neural regions often used for self-regulation.
In quite predictable ways, that is, schooling changes brains.
The Bigger Picture
I was drawn to this study because of a headline: “How does going to school change your brain?”
In the current world of education, we hear this phrasing quite often:
Taxi drivers in London–who must learn very complex street maps–have different brains from people who don’t learn those maps. Map learning changes your brain!
Learning a foreign language actually changes your brain!
Playing the bagpipes not only makes you sexy, but it also changes your brain!
You may well have heard this claim quite often in the world of education. It’s an especially popular point among folks who have something to sell.
So here’s an important secret: if you do something often, practically everything changes your brain.
If you nap regularly at 3, I suspect your brain is different from the brains of people who don’t. If you run marathons, doing so changes your brain. Or, juggling. Or, learning calculus.
Or–I don’t know–walking up stairs backwards.
Brains change. Often. It’s what they do.
I honestly don’t quite understand the reverence with which people utter the words “collecting chia pets actually changes your brain!” Over a decade ago, neuroscientists believed that brains didn’t change much once they were fully formed, so I understand why they are still awestruck by this fairly recent discovery.
But the rest of us? I’m surprised most non-neuroscientists are invested enough in the changelessness of brains to care one way or the other.
Here’s a test I occasionally use: when I hear the words “actually changes your brain,” I mentally substitute the words “happens while you’re breathing.” If that second sentence would surprise me, then I’ll be surprised by the first.
So, for example: “Ball-room dancing classes actually change your brain!” becomes “Ball-room dancing classes happen while you’re breathing.” Nope, not surprised.
Back to Where We Started
If it’s not surprising that a structured academic environment (1st grade) affects brains differently than a playful environment (kindergarten), what should we do with this study?
For teachers, the answer is: not much. This research result is interesting, but not at all surprising. When one group of students spends a year in a somewhat different environment than another group, those groups develop differently–both in their behavior and in their neural structures.
Put differently, we might summarize the research result this way: at the neural level, 1st grade works. It creates the changes we want it to change. (Or, more precisely: the changes we see in neural networks make sense given what we know about their behavioral correlates.)
For neuroscientists, the answer is: celebrate. Given that neuroplasticity is a relatively recent finding, it’s quite amazing that specialists can now predict where brain changes might happen, and then find those very changes after 9 months. 20 years ago, all of this would have been impossible. Today, it’s not only doable–it’s been done.
In other words: I don’t think you and I will teach any differently because of these findings. But, this study gives us even more confidence that neuroscience and education will come to inform each other more and more often.
As another April has come and gone, so has another World Autism Month. The Light It Up Blue campaign celebrates each spring with a renewed push for greater understanding and acceptance of individuals with autism spectrum disorder.
And with greater attention to autism (hopefully) comes greater attention to learning and developmental disabilities more broadly. In the context of education, this means greater attention to the who, what, and why of special education (SPED) services.
Special education provides a public education, generally through implementation of individualized curricula, to students with intellectual, learning, developmental, and/or physical disabilities. [1]
Or does it? In the last decade, researchers and policymakers have begun to take a closer look at the students enrolled in SPED. Red flags have emerged, to say the least.
The Numbers Don’t Add Up
At the forefront of concern is evidence of substantial disproportionality in SPED enrollment. Disproportionality arises when a group, such as a racial or ethnic minority, is represented in SPED at a greater rate than they comprise within their school, community, or nation. For example, if a school is comprised of around 65% white students, we should expect that the SPED classrooms are also comprised of around 65% white students.
Yet in nearly every state, rates of SPED enrollment show evidence of overrepresentation of minority groups. [2]
Now, before delving into the possible factors contributing to such disproportionality, it is worth noting that special education is still relatively new to U.S. public education. SPED was first enacted in 1973 and has gone through several policy iterations to reach its current form: the Individuals with Disabilities Education Act (IDEA).
IDEA mandates that education services for children with disabilities must meet students’ individual needs and must take place in the least restrictive environment possible (ideally with non-disabled students). As well, and perhaps most important for the current discussion, is the mandate that SPED assignment can happen only after appropriate enrollment procedures have concluded. These procedures include aptitude and achievement tests, teacher recommendations, and considerations of the student’s cultural background. [1]
Despite IDEA’s requirements, however, SPED services do not appear to be distributed equitably. [3] Enrollment data show that students of color consistently experience disproportionate inclusion in SPED, and this issue has actually come to the attention of Congress more than once. During both the 19thand 22nd Annual Reports to Congress, the Office of Special Education Programs (OSEP) and the Office of Civil Rights (OCR) reported that students of color may be being misclassified or inappropriately placed in SPED, that such placement may be a form of discrimination, and that SPED students may be receiving services that do not meet their needs. [4]
Red Flags
What kind of disproportionality are we talking about? Let’s look at a snapshot of some of the numbers and contexts that researchers have been tracking:
despite Black children constituting only 17% of total school enrollment, they comprise 33% of children diagnosed with mental retardation (now referred to as intellectual disability, ID) [5]
Black boys are, on average, 5.5 times more likely to be diagnosed as emotionally disturbed (ED) than are white girls [6]
American-Indian boys are, on average, nearly three times more likely than white girls to be diagnosed with a learning disability (LD) [6]
among students with disabilities, 57% of Hispanics are educated in partially separate or substantially separate settings and denied access to inclusive settings, compared to 45% of whites [7]
English language learners (ELL) are 27% more likely to be placed in special education during the elementary school grades [8]
Where to Begin?
Those are some pretty troubling statistics, and researchers have endeavored to get to the bottom of them. But as one might expect, disproportionality is a complex, layered issue.
And a potentially misleading one. For example, a natural response to reading the numbers above might be that disproportionate overrepresentation is worse than disproportionate underrepresentation. We would be remiss to take that thought as a blanket statement, though. After all, while overrepresentation may reflect heightened disapproval of minority students’ behavioral or academic performance, underrepresentation may reflect minority students’ struggles going unnoticed. And that latter possibility isn’t any better than the former.
For example, the diagnosis of Intellectual Disability in Black students has been shown to decline as poverty increases. [2] In other words, the poorest Black students may be the least likely to be identified as having ID. But, there is still a disproportionately high rate of Black children in SPED who are diagnosed with ID overall.
Such nuanced findings may suggest that Black students are being over- and under-monitored based on their socioeconomic background in addition to, or in lieu of, their academic profile.
Thus, the story that needs to be uncovered is not only the extent of disproportionality (i.e., the raw numbers) but also the forms (i.e., the diagnoses) and the causes.
What’s Happening with SPED Assessment?
Turning to causality in particular, some researchers have hypothesized that the assessment procedures required by IDEA for SPED enrollment may be less rigorous in practice than on paper. In an investigation of how qualitative factors, such as personal beliefs, may affect the rigor of psychological/educational evaluation, Harry, Klinger, Sturges, & Moore (2005) investigated community perceptions of the validity of SPED referrals throughout urban schools in Southern Florida. [9] Extensive interviews with teachers, administrators, and families uncovered a high level of confidence in school-ordered assessments.
That is, the interviewees believed that students would be referred for, and enrolled in, SPED only after a true need for such services was found. Which sounds good! But, paradoxically, this high level of confidence may actually lead to harmful results.
Because from the get-go, students may be vulnerable to inappropriate SPED placement if members of their family, school, and community are unlikely to examine a referral critically. Further, given that studies have found Limited English-Proficient students to be more likely to be placed in SPED, families that experience a language or cultural barrier to their child’s school may face particular disadvantage in advocating for their child.
These same researchers also found that teachers’ perceptions of a student’s learning difficulties, as well as their perception of dysfunction existing within a student’s family, predicted their students’ SPED assessment results. This may indicate a complex process through which a teacher’s perception of a student influences the nature of their interactions (e.g., challenging the student less due to lower expectations), which in turn contributes to lower levels of student achievement and, eventually, consideration for SPED.
Other researchers, however, have suggested that psycho-educational assessment is not the main event in SPED placement at all. [8] Rather, disproportionate referrals may arise from the ongoing failure of regular education classrooms to serve racial and ethnic minority students. They argue that it is the quality of a student’s classroom instruction, and the level of management within the classroom, that should be most emphasized during student assessment. This emphasis would allow for underachievement to be seen as the result of a poor learning environment rather than individual student failure.
What Other Factors Underlie Disproportionate Representation?
Overall, most researchers have concluded that disproportionality in SPED is the result of:
subjective student identification practices (e.g., teachers’ interpretation of the same behaviors differently depending on the student);
blatant violations of IDEA’s guidelines;
and antiquated systems of SPED funding based on category of disability (i.e., schools receive more money if a student is diagnosed with Intellectual Disability than if diagnosed with Dyslexia). [10]
Yet other studies have begun to take a new, ecological approach in their investigations. For example, based on the assumption that low-income students are more likely to be students of color, several researchers have asked: is poverty is associated with increased risk for SPED enrollment?
In one such study, Strand & Geoff (2009) analyzed the 2005 Pupil Level Annual School Census – a data set of 6.5 million students in England. [11] The authors found that poverty and gender explained more disproportionality in SPED enrollment than did ethnicity; but, the overrepresentation of students of color in SPED was still significant even after controlling for poverty. It appears, then, that some degree of interplay between individual (e.g., academic strengths and weaknesses, learning support at home) and environmental (e.g., socioeconomic conditions, teacher and societal beliefs) factors significantly contribute to placement in SPED classrooms.
Getting to the Bottom of it
So far, researchers seem to have a lot of pieces of the disproportionality puzzle in a lot of places. How do we put them all together–at least enough so that we can begin to do something about it?
To start, Oswald, Coutinho, & Best (2005) recommend a new research agenda. They advocate for disproportionality studies to focus specifically on disentangling social factors (such as systemic bias) from individual factors (such as differential susceptibility) as an underlying cause of over- or underrepresentation in SPED. [6]
These authors argue that studies should investigate whether students of certain racial or ethnic groups are differently susceptible to schooling contexts such as low-quality instruction, loose classroom management, or particular academic interventions. Under the theory of differential susceptibility, it is perhaps so that some students fare better in special education classrooms than others, making them more likely to be placed back into regular education.
They also advocate for assessment procedures that compare an individual’s performance to the performance of students of similar characteristics. For example, the achievement of a Hispanic female youth should be compared to the average performance of similar female students within their school or district (i.e., not their non-Hispanic classmates). If differential susceptibility to an aspect of the educational environment exists for some racial or ethnic minorities, assessment procedures that compare similar students may provide the most accurate depiction of an individual successes or challenges.
No Time Like the Present
It is clear that disproportionality exists within SPED. But what it less clear is why, or how to fix it. Given that it is a relatively new addition to public education, however, we can hope that the inequity currently seen in SPED may not yet be as deeply rooted as some of the challenges that regular education faces (e.g., school segregation).
Nonetheless, time is of the essence for new research! It is only with a better understanding of the roles that various factors play in SPED disproportionality that the development (and enforcement) of policy interventions can commence.
[Editor’s note: this post was written by Lindsay Clements. The initial byline, saying that it had been written by me, was incorrect. My apologies for the mistake.]
References
[1] U.S. Department of Education Office for Civil Rights (2010). Free Appropriate Public Education for Students With Disabilities: Requirements Under Section 504 of the Rehabilitation Act of 1973, Washington, D.C.
[2] Parrish, T. (2005). Racial disparities in the identification, funding, and provision of Special Education. In D.J. Losen & G. Orfield (Eds.), Racial Inequity in Special Education (pp.15-37). Cambridge, MA: Harvard Education Press.
[3] McDonald, K.E., Keys, C.B., & Balcazar, F.E. (2007). Disability, race/ethnicity and gender: Themes of cultural oppression, acts of individual resistance. American Journal of Community Psychology, 39, 145-161. doi:10.1007/s10464-007-9094-3 [link]
[4] U.S. Department of Education (1997). Nineteenth annual report to Congress. Washington, DC: Author.; U.S. Department of Education (2000). Twenty-second annual report to Congress. Washington, DC: Author.
[5] Losen, D.J. & Orfield, G. (2005). Racial inequity in special education. In D.J. Losen & G. Orfield (Eds.), Racial Inequity in Special Education (pp.xv-xxxvii). Cambridge, MA: Harvard Education Press.
[6] Oswald, D.P., Coutinho, M.J., & Best, A.L.M. (2005). Community and school predictors of overrepresentation of minority children in Special Education. In D.J. Losen & G. Orfield (Eds.), Racial Inequity in Special Education (pp.1-13). Cambridge, MA: Harvard Education Press.
[7] Garcia Ferros, E. & Conroy, J.W. (2005). Double jeopardy: An exploration of restrictiveness and race in special education. In D.J. Losen & G. Orfield (Eds.), Racial Inequity in Special Education (pp.39.70). Cambridge, MA: Harvard Education Press.
[8] Artiles, A.J., Rueda, R., Salazar, J.J. & Higareda, I. (2005). Within-group diversity in minority disproportionate representation: English language learners in urban school districts. Exceptional Children, 71(3), 283-300. [link]
[9] Harry, B., Klinger, J.K., Sturges, K.M., & Moore, R.F. (2005). Of rocks and soft places: Using qualitative methods to investigate disproportionality. In D.J. Losen & G. Orfield (Eds.), Racial Inequity in Special Education (pp.71-92). Cambridge, MA: Harvard Education Press.
[10] Reschly, D.J. (2000). IQ and Special Education: History, current status, and alternatives. Unpublished paper, National Academy of Sciences, National Research Council, Washington, DC.
[11] Strand, S., Geoff, L. (2009). Evidence of ethnic disproportionality in special education in an english population.The Journal of Special Education, 43(3), 174-190. [link]
In recent weeks, this blog has written about the dangerous assumption that students can just get all their information from The Google, and the implication that they therefore don’t need to know much factual knowledge. (Those posts are here and here.)
In yesterday’s New York Times, Daniel Willingham took up the same topic. If you don’t know Willingham’s work, a) you should, and b) this article will be a lovely introduction to his thoughtfulness and clarity.
