Could a similar strategy work before we go to bed?
Michael Scullin and colleagues hypothesized that students might stress about upcoming tasks. If so, they might feel less stress if they could somehow get a handle on those tasks.
Perhaps, to get that handle, students could make a to-do list of upcoming responsibilities.
To test his hypothesis, Scullin worked with adults (18-30) right before bed. Half of them wrote specific lists of their accomplishments during the day. The other half wrote specific lists of impending to-dos.
So, What Happened?
Of course, it’s possible this technique might backfire. If I write down tomorrow’s responsibilities, then I might ramp up my stress level as I worry about getting them done.
In this case, however, that’s not what happened.
On average, students who wrote to-do lists fell asleep ten minutes faster than those who cataloged their accomplishments.
(These results conceptually mirror those pre-exam stress studies, which show that “dumping” before an exam increases exam performance.)
I particularly like Scullin’s technique, because it’s so gosh-darn practical. Simply put, students can do this. It took only five minutes. And, it helped!
Because this is the first study looking at this technique, we don’t know about boundary conditions. I myself assume that, at some age, children are too young to be kept awake by their mental list of tomorrow’s responsibilities. If that’s true, perhaps some alternate form of writing might help.
Until we know about those boundary conditions, we should use our best judgment in recommending this strategy to students and parents.
h/t to Christine Martin for pointing out this study to me.
With teaching as with baking, sometimes you should follow steps in a very particular order. If you don’t do this, and thenthat, and then the other, you don’t get the best results.
Two researchers in Germany wanted to know if, and when, and how, students should study incorrect answers.
To explore this question, they worked with 5th graders learning about fractions. Specifically, they taught a lesson about comparing fractions with different denominators.
(When studying this topic, students can’t rely on their instincts about whole numbers. For that reason, it’s a good subject to understand how students update conceptual models.)
They followed three different recipes.
One group of 5th graders saw only correct answers.
A second group saw both correct and incorrect answers.
A third group saw correct and incorrect answers, and were specifically instructed to compare correct and incorrect ones.
Which recipe produced the best results?
The Judges Have Made Their Decision
As the researchers predicted, the third group learned the most. That is: they made the most progress in updating their conceptual models.
In fact: the group prompted to compare right and wrong answers learned more than the group that saw only the right answers. AND they learned more than the group that saw (but were not prompted to compare) right and wrong answers.
In other words: the recipe is very specific. For this technique to work, students should first get both kinds of information, and second be instructed to compare them.
Important Context
I’ve held off on mentioning an important part of this research: it comes in the context of problem-based learning. Before these 5th graders got these three kinds of feedback, they first wrestled with some fraction problems on their own.
In fact, those problems had been specifically designed to go well beyond the students’ mathematical understanding.
The goal of this strategy: to make students curious about the real-world benefits of learning about fractions with different denominators in the first place.
If they want to know the answer, and can’t figure it out on their own, presumably they’ll be more curious about learning when they start seeing all those correct (and incorrect) answers.
As we’ve discussed before, debates about direct instruction and problem-based learning (or inquiry learning) often turn heated.
Advocates of both methods can point to successes in “their own” pedagogy, and failures in the “opposing” method.
My own inclination: teachers should focusthe on relevant specifics.
In the link above, for example, one study shows that PBL helps 8thgraders think about deep structures of ratio. And, another study shows that it doesn’t help 4th graders understand potential and kinetic energy.
These German researchers add another important twist: giving the right kind of instruction and feedback after the inquiry phase might also influence the lesson’s success.
Rather than conclude one method always works and the other never does, we should ask: which approach best helps my particular students learn this particular lesson? And: how can I execute that approach most effectively?
By keeping our focus narrow and specific, we can stay out of the heated debates that ask us to take sides.
When we see alarming statistics about gender disparities in STEM disciplines, we quite naturally wonder how to fix this imbalance.
(This hope – by the way – isn’t simply a do-goody desire to sing “It’s a Small World After All.” If we believe that men and women can contribute equally to a scientific understanding of our world, then every girl discouraged is a contribution lost.
In other words: we ALL benefit if boys and girls contribute to science.)
So, how can we encourage girls to participate in science?
To answer this question, we might first answer a related question: what discourages girls in the first place.
If we can undo the discouragement, we are – indirectly but effectively – encouraging.
So, what discourages girls?
Is Science Education Itself the Problem?
Here’s a disturbing possibility.
When students learn about genetics, and specifically about the genetics of sex differences, they might infer that genders have a fixed, absolute quality. All boys (and no girls) are this way; all girls (and no boys) are that way.
It’s in the genes, see?
This set of beliefs, in turn, might reinforce a fixed mindset about gender and ability.
Through this causal chain, a particular science curriculum might itself discourage girls from pursuing science.
Yikes!
Researcher Brian Donovan and his team explored this question in a recent study. To do so, they asked students to read different lessons about genes and sexual dimorphism.
Some 8th – 10th graders learned about the genetics of human sexual difference.
Others learned about the genetics of plant sexual differences.
Others read a curriculum that explicitly contradicted the notion that genetic sex differences directly cause differences in intelligence and academic ability.
Did these curricular differences have an effect?
The Results Envelope Please
Unsurprisingly, students who learned that we can’t draw a straight line from genes to gender roles and abilities believed that lesson.
To make the same point in reverse: students who studied a seemingly “neutral” scientific curriculum – “we’re just talking about genes here” – drew unsupported conclusions about absolute differences between men and women.
Amazingly, this finding held true both for the students who studied the genetics of human sexual differences AND those who studied plant sexual differences.
WOW.
Perhaps surprisingly, students who learned that genetic sex differences don’t cause gendered ability differences also expressed a greater interest in science.
In particular, the girls who studied the “genetics only” lesson expressed meaningfully less interest in a science major than those who got the alternative lesson. (The two lessons neither encouraged nor discouraged the boys.)
But, Why?
Here’s the likely causal chain:
A science curriculum that focused “purely” on genetics seemed to suggest that men and women are utterly different beings.
Students who read this “pure” lesson inferred that some human abilities – like, say, scientific competence – might differ between genders.
This inference, in turn, made gender stereotypes (e.g., “men do better at science than women”) more plausible.
And so, the women who got that seemingly neutral science lesson, discouraged by the stereotype it reinforced, felt less inclined to pursue science.
By this roundabout route, a traditional science lesson might itself discourage students from learning science.
Alternative Explanations
Of course, the topic of gender differences – especially in the realms of math and science – can generate lots of energetic debate.
When I asked Donovan for alternative explanations for his findings, he was quick to emphasize that we need lots more research in this field. His is the first study done on this specific question. As always, teachers shouldn’t assume that any one study has found THE answer.
Some people do in fact argue that math and science ability (or interest) differ by gender because of genes. (Dr. Donovan explicitly rejects an explanation that moves directly from genes to gender differences.)
Here’s a recent book review by Lise Eliot, emphasizing that gender differences in brain regions
a) are often exaggerated and mis-reported, and
b) result from societies that emphasize gender differences.
Donovan’s research suggests that teachers can and should do more to be sure we’re not discouraging some students from particular academic interests and career paths.
For one set of practical suggestions, this interview with Sapna Cheryan outlines several ways we can promote “ambient belonging” in our classrooms.
Young people with Autism Spectrum Disorder (ASD) typically want social relationships but have trouble building them. Extensive social skills training research has been conducted with young children with ASD, but research about social skills training for young adults with ASD is scant. Elizabeth A. Laugeson has designed an evidence-based method of group training for young adults with ASD and other social challenges and their parents/caregivers. This training is designed to help the young adults with ASD develop skills and learn social rules to help them build the social and romantic relationships they seek.
Her book, PEERS® for Young Adults: Social Skills Training for Adults with Autism Spectrum Disorder and Other Social Challenges, is the product of years of research and clinical practice with this population. Laugeson is a clinical psychologist and assistant clinical professor at the University of California, Los Angeles Semel Institute for Neuroscience and Human Behavior. She also directs an ASD research alliance and an outpatient program to provide social skills training for people with ASD. She and colleagues have conducted and published rigorous randomized clinical trials of the Program for the Education and Enrichment of Relational Skills (PEERS®). The book, PEERS® for Young Adults,serves as a detailed manual for clinicians and educators about how to lead these coaching sessions so that they can support groups of young people (i.e., ideally 18- 24 years old) with ASD who wish to improve their social relations.
The program is designed around common social errors that people with ASD make. It is meant to be administered in its entirety and in the order described. It is likely to be most effective when the young adult participants want to be part of the program and seek more fulfilling social relations. Laugeson provides a thorough explanation of what to do in each session. That is, each chapter presents the rationale for the session, explains how to review homework, describes a didactic lesson, and presents a new homework assignment. These assignments include tasks like having a phone conversation and enrolling in activities related to the young adult’s interest. A key feature of the program is that it involves concurrent sessions with social coaching training for the parents/caregivers and active training for the young people with ASD. Parent/caregiver involvement is important so that the parents know how they can help their young adult. Each session concludes with the young adults and caregivers reuniting to debrief and plan for the next session together.
The group training program progresses through teaching how to: start and maintain conversations, find sources of friends, communicate electronically, use humor appropriately, enter and exit group conversations, hanging out with friends, indicate romantic interest, ask someone on a date, go on a date, and handle disagreements and bullies. There are numerous helpful and ideas in these sessions. For example, young adult participants should learn friendship is a choice, finding common interests with another person is a good way to start a conversation, trading information is key to social interactions, and remaining flexible to changes that may occur during social gatherings is necessary.
The guide is thorough in including behavioral management techniques, tools to help young adults and their caregivers assess progress and practice skills, role play demonstration descriptions with accompanying videos available online, perspective-taking questions, and a related mobile app called FriendMaker.
Laugeson’s research has shown that many young people with ASD have benefited from PEERS®training. This book makes it possible and practical for clinicians and educators to run PEERS®training on their own so that many more young people can learn these critical lessons and begin living happier, more socially-fulfilled lives.
Laugeson, E. A. (2017). PEERS® for young adults: Social skills training for adults with autism spectrum disorder and other social challenges. New York, NY: Routledge.
You have, no doubt, heard about this research before.
Walter Mischel tested preschoolers on self-control. In the famous “marshmallow test,” they got either one marshmallow right now, or twoif they waited for fifteen minutes.
(I have to include an adorable video of children resisting marshmallows.)
Here’s the blockbuster part: the preschoolers’ performance on that test predicted their adult performance on similar self-control measures — four DECADES later.
And, as Roy Baumeister has shown, self-control influences … say … adult financial success. Or, likelihood of addiction. Or, even the odds that I’ll wind up in jail.
These paragraphs add up to a scary story. If self-control a) can be predicted in early childhood, and b) meaningfully shapes core adult behaviors and abilities, then we might worry about an individual’s capacity to determine his or her life’s direction.
And, we might particularly worry about a teacher’s ability to provide meaningful long-term help.
Here’s the headline: Y.E. Willems and others ran a meta-analysis on the heritability of self-control. Looking at 31 twin studies that included over 30,000 individuals, they conclude that overall heritabililty of self-control is 60%.
But what, precisely, does that mean?
For two reasons, I think this finding defeats the “scary story” I told a few paragraphs ago.
First reason: however you interpret “heritability,” we see that plenty of self-control isn’t determined by it. And, if self-control isn’t fully heritable, then the environment can influence it.
“Heritabililty” Isn’t (At ALL) What We Think It Is
The second reason this research can calm our fears about the scary story gets technical.
“Heritability” sounds like it answers this question: “how much of a particular trait is determined by genes?”
In other words: how much does genetic variety explain dyslexia? Or, propensity for violence? Or, working memory capacity?
That’s not what heritabililty means.
Instead, heritabililty measures the amount of variation in a particular trait explained by genes.
This difference takes a long time to explain. Happily, we’ve got an expert ready to explain it.
Here’s Robert Sapolsky: Stanford professor (and 3-time Learning and the Brain speaker):
https://www.youtube.com/watch?v=OareDiaR0hg
As I said, this kind of analysis can be tricky to follow. But the core message is crucial:
Environment matters for the development of self-control.
Yes, of course, genes have an influence on our self-control. But, so does the environment in which those genes create proteins, which — after a staggeringly complex process — influence behavior.
All those self-control boosting techniques you’ve been hearing about at Learning and the Brain conferences: you can have confidence. They might not change everything overnight.
But, they can indeed help. And, studies about heritability don’t mean what we think they do, so they shouldn’t discourage us from trying.
By the way, Sapolsky’s book Behave goes into this topic with clarity, humor, and precision. If you want to understand the nuances of genetic and environmental interactions, it’s a splendid read.
Here‘s a quick summary of information about memory: sensory memory, working memory, long-term memory, and (crucially!) forgetting.
Author Steven Turner presents this brisk overview to combat “buzzword wasteland.” He fears the education-world habit of coming up with fancy new terms every six months or so. Rather than scamper after every new fad, he’d like us to focus on the enduring basics.
Like: memory.
I myself think of “sensory memory” as a part of our attentional systems. As long as teachers remember the key point — students have VERY little perceptual capacity for incoming sensory information — it doesn’t really matter what we call it.
The information on this page might all be review. However, as we know well, spaced repetition helps learning. A chance to rethink these topics right now will be beneficial to our understanding.
If we want our students to think creatively, should they listen to music? If yes, does the timing matter?
Intuition might lead us either to a “yes” or to a “no.”
Yes: music might get students’ creative juices flowing. Especially if it’s upbeat, energetic, and particularly creative in itself, music might spark parallel creativity in our students’ thought processes.
No: on the other hand, music just might be a serious distraction. Students might focus so keenly on the music — or on trying to ignore the music — that they can’t focus on the creative work before them.
Do You Smell a CRAT?
Researcher Emma Threadgold used a common creativity test – with the unlikely acronym of CRAT – to answer this question.
Here’s how a CRAT works:
I give you three words: “dress,” “dial,” and “flower.”
You have to think of another word that – when combined with each of those words – produces a real word or phrase.
To solve a CRAT, you have to rifle through your word bank and try all sorts of combinations before – AHA! – you pull the correct answer up from the depths of your brain.
In this case, the correct answer is “sun”: as in, sundress, sundial, and sunflower.
They played music with English lyrics, with foreign lyrics, and with no lyrics. They played upbeat, happy music.
They even played library noise – with the sound of a photocopier thrown in for good measure.
In every case, music made it harder to solve CRAT problems.
To put that in stark terms: music interfered with listeners’ creative thinking.
(For those of your interested in statistics, the Cohen’s d values here are astonishing. In one of the three studies, the difference between music and no music clocked in a d=2.86. That’s easily the highest d value I’ve seen in a psychology study. We’re typically impressed by a value above 0.67.)
Case Closed?
Having done such an admirably thorough study, has Threadgold’s team answered this question for good?
Nope.
As always, teachers should look not for one definitive study, but for several findings that point in the same direction.
And, we should also look for boundary conditions. This research might hold up for these particular circumstances. But: what other circumstances might apply?
For me, one obvious answer stands out: timing.
Other researchers have studied creativity by playing music before the creative task, not during it.
For instance, this study by Schellenberg found that upbeat music produces higher degrees of creativity in Canadian undergraduates AND in Japanese five-year-olds. (Unsurprisingly, the five-year-olds were especially creative after they sang songs themselves.)
In this study, crucially, they listened to the music before, not during, the task.
Threadgold’s study, in fact, cites other work where pre-test music enhanced creativity as well.
More Questions
Doubtless you can think of other related questions worth exploring.
Do people who learn to play music evince higher degrees of creativity in other tasks?
How about courses in music composition?
Music improvisation training?
Does this effect vary by age, by culture, by the kind of music being played?
For the time being, based on what I know about human attention systems, this study persuades me that playing music during the creative task is likely to be distracting.
Depending on what you want your students to do, you might investigate other essential variables.
__________________
On a related topic: for Dan Willingham’s thoughts on listening to music while studying, click here.
Should teachers ask students to work on projects in teams?
This question generates a great deal of heat.
Many education thinkers advocate for the benefits of teamwork. Others insist that learning happens one brain at a time, and so should not be cluttered with interference from other brains.
Working Memory: Blesses and Curses
Working memory allows humans to hold and reorganize facts and ideas in temporary mental storage.
When you do a word problem, you must decide which parts should be translated into an equation. (Those decisions take WM.) You have to recall the appropriate equation to use. (Ditto.) And, you must plug the correct data into the correct formula before you can arrive at an answer. (Re-ditto.)
Composing a new sentence in a foreign language? Lots of working memory demands.
Comparing Paul Lawrence Dunbar’s poetry with that of Countee Cullen? Yup.
Learning how to tell time? Once again – lots of working memory involved.
In other words, WM allows students to do practically everything that we want them to do in school.
And yet, this working memory blessing co-exists with a powerful curse: we just don’t have very much of it.
You probably can alphabetize five days of the work week. You probably can’t alphabetize 10 months of the year. The first task lies within WM limits; alas, the second goes way beyond them.
(These scholars, especially John Sweller, have elaborated “cognitive load theory” to explain the relationship between long-term memory, WM, and the external world of perception and experience. See here for a review.)
One important peril: the working memory demands created by collaboration. When students work together, they have to negotiate roles. They must create joint mental models. They have to schedule and prioritize and debate.
All these “musts” take up precious working memory space. The result might be that students get better at negotiating, modeling, and prioritizing. But, the WM devoted to those task might make it harder for them to learn the content at the heart of the project.
Of course: you might reasonably want your students to focus on the social-emotional skills. But, if you wanted them to focus on Shakespeare or Boyle’s law, then the project might not produce the results you hoped for.
Collaboration’s WM Benefits
At the same time, Kirschner & Co. also see working memory upsides to collaboration.
A particular cognitive task might include quite stiff WM demands. If the group includes members with the right kinds of background knowledge, then the WM chores can be divided up and managed more effectively.
Student A carries this part of the WM load.
Student B carries that part.
Student C takes care of the tricky last bit.
In this way, the WM whole can be greater than the sum of the parts.
In other words: if teachers can organize group projects so that a) the WM difficulties of collaboration remain low, and b) the benefits of sharing WM burdens remain high, then such collaboration truly help students learn.
Putting It Together
Kirschner’s article concludes with a list of key variables for teachers to track: task complexity, domain expertise, team size, and so forth.
Be aware that cognitive load theory gets a little jargony, and you’ll need some time to learn the lingo before the article makes sense.
However, if you can devote that time, I think you’ll benefit from its practical suggestions, and helpful frameworks for planning students’ collaborative learning.
This blog often critiques the hype around “brain training.” Whether Lumosity or Tom Brady‘s “brain speed” promises, we’ve seen time and again that they just don’t hold water.
Although I stand behind these critiques, I do want to pause and praise the determined researchers working in this field.
Although, as far as I can see, we just don’t have good research suggesting that brain training works*, it will be an AWESOME accomplishment if it someday comes to pass.
A Case In Point
I’ve just read a study that pursues this hypothesis: perhaps brain training doesn’t succeed because the training paradigms we’ve studied do only one thing.
So, a program to improve working memory might include cognitively demanding exercises, but nothing else. Or, brain stimulation, but nothing else. Or, physical exercise, but nothing else.
What would happen if you combined all three?
To test this question, Ward & Co. ran a remarkably complex study including 518 participants in 5 different research conditions. Some did cognitive exercises. Some also did physical exercises. And some also added neural stimulation.
The study even included TWO control groups.
And, each group participated in dozens of sessions of these trainings.
No matter the results, you have to be impressed with the determination (and organization) that goes into such a complex project.
Okay, but What Were The Results?
Sadly, not much. This study didn’t find that training results transferred to new tasks — which is the main reason we’d care about positive findings in the first place.
We might be inclined to think that the study “didn’t succeed.” That conclusion, however, misses the bigger point. The researchers pursued an entirely plausibly hypothesis…and found that their evidence didn’t support it.
That is: they learned something highly useful, that other researchers might draw on in their own work.
Someday — we fervently hope — researchers will find the right combination to succeed in this task. Those who do so will have relied heavily on all the seemingly unsuccessful attempts that preceded them.
__________
* To be clear: the phrase “brain training” means “training core cognitive capacities, like working memory.”
From a different perspective, teaching itself is a form of brain training. When we teach our students, brains that once could not do something now can do that something.
Brains change all the time. “Brain training” aims for something grander. And, we haven’t yet figured out how to do it.
