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Neuroscience and Neuromyths
Andrew Watson
Andrew Watson

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Does neuroscience education help reduce a teacher’s belief in neuromyths?

According to this recent study: not as much as we would like.

In some cases, neuroscience education does help teachers.

For instance, 59% of the general public falsely believe that listening to classical music increases reasoning ability. That number is 55% for teachers, but drops to 43% for teachers who have had neuroscience training.

Similarly, teachers with knowledge of neuroscience are less likely to embrace a “left-brained vs. right-brained” understanding of learning than teachers without. (See video here.)

However, neuromyths about learning styles and about dyslexia persist–even among teachers with neuroscience education.

Among the general population, 93% of people incorrectly believe that “individuals learn better when they receive information in their preferred learning style.” That number falls to 76% among teachers–but is almost identical (78%) for teachers who know from neuroscience.

And: teachers who have studied neuroscience believe that writing letters backwards is a sign of dyslexia at almost the same rate as those who haven’t.

The Big Question

Studies like these lead me to this question: why are some neuromyths so sticky? Why do so many of us teachers believe in, say, learning styles theory despite all the scientific evidence to the contrary?

Why does this belief persist even among those–like we who attend Learning and the Brain conferences–who have placed science at the center of our professional development?

I welcome all thoughts on this question…

Parents, High School Start Times, and Sleepy Teens
Andrew Watson
Andrew Watson

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Research findings that support later high-school start times have been more and more common in recent years. (See also here.) And teachers I know are increasingly vocal about letting teens sleep later.

And yet, when I talk with high school leaders, they ruefully cite sports schedules to explain the impossibility of making serious changes.

(I’ve also read that bus schedules get in the way.)

Here’s another–quite surprising–reason that this change might be hard to accomplish: parental uncertainty. According to this recent study, published in the Journal of Clinical Sleep Medicine, half of parents whose teens start school before 8:30 don’t support a later start time.

The study concludes that we need to do a better job educating parents about the biological changes in adolescent sleep patterns.

The more that parents understand how melatonin onset–and, hence, sleepiness–changes with adolescence, the more they might understand that their awake-at-midnight teens aren’t simply being willful. They are instead responding to powerful chemical signals.

Given all we know about adolescent sleep, and the effect of sleep on learning, teachers and parents should be champions of reasonable high school start times.

More Thoughts on Gender Differences
Andrew Watson
Andrew Watson

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Regular readers of this blog know that I’m a skeptic about gender differences in learning. Although they certainly do exist–I think particularly about differences in 3d mental rotation–I often think they’re overstated or overemphasized.

At the same time, my emphasis on this point might obscure the fact that at the population level, gender differences in learning do sometimes exist. Two articles are, I think, particularly helpful in understanding these ideas.

First, this weighty research review considers the number of women in STEM fields and reaches three broad conclusions:

  1. “Males are more variable [than females] on most measures of quantitative and visuospatial ability, which necessarily results in more males at both high- and low-ability extremes; the reasons why males are often more variable remain elusive.”
  2. “Females tend to excel in verbal abilities, with large differences between females and males found when assessments include writing samples. “
  3. “We conclude that early experience, biological factors, educational policy, and cultural context affect the number of women and men who pursue advanced study in science and math and that these effects add and interact in complex ways. There are no single or simple answers to the complex questions about sex differences in science and mathematics.”

The article stands out to me not only for its thoroughness, but for its all-star list of authors. Janet Shibley Hyde, for example, is well known for her skepticism about gender differences; in fact, she authored a widely-cited article called The Gender Similarities Hypothesis. If a known skeptic is on board with these conclusions, then I’m comfortable being there too.

(Another author, Diana Halpern, by the way, is a former president of the American Psychological Association.)

Second, Hyde has published an exploration of the first argument above: that men show greater variability in quantitative and visual abilities. This hypothesis suggests that–although large populations of men and women will have the same average math scores–we would expect to see more men who are very good at math (say, the top 5%) and also who are very bad at math (say, the bottom 5%).

Hyde’s article shows the complexity of this hypothesis. In particular, given that these variations differ from country to country, and can change over time, we have to recognize the social and historical context of any data set.

Decisions, Decisions: Helping Students with Complex Reasoning
Lindsay Clements
Lindsay Clements

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Most of us have heard the adage about the two ways that someone can get into a swimming pool: jump right in, or enter slowly to acclimate to the temperature a few inches at a time.

Most of us have probably also witnessed (or experienced) the varied ways that someone might approach an assignment: one could start and finish it right away; work on it in small chunks over an extended period of time; or wait until the last moment to start, likely rushing to finish.

And for those that are keeping an eye on back-to-school sales events, there are of course different ways to shop: one could impulse purchase an item, or do some research beforehand to get the best possible deal.

The common thread in all of those scenarios is that different methods, strategies, and thought processes can be employed to solve problems or complete tasks. And each has its own time and place. So how do we decide exactly which ones to use in a given situation?

Algorithms and heuristics

The science behind problem solving and decision-making comprises a robust portion of cognitive research and involves the study of both conscious and unconscious thought.

Overall, there are two primary ways that a problem can be tackled: with algorithms or with heuristics. [1] An algorithmic approach refers to a series of steps that are more or less guaranteed to yield the solution. While this approach is most easily thought of in the context of mathematics (e.g., following a mathematical formula), an algorithmic approach also refers to such procedures as following a recipe or backtracking your steps to find a lost object.

Heuristics, on the other hand, are associative strategies that don’t necessarily lead to a solution, but are generally pretty successful in getting you there. These include conscious strategies (such as solving a maze by making sure your path stays in the general direction of the end point) and unconscious strategies (such as emotional instincts). Because heuristics are more subjective and less systematic than an algorithmic approach, they tend to be more prone to error.

In the classroom, solving problems with an algorithmic approach is fairly straight-forward: students can learn the needed procedural steps for a task and identify any places where they might have gone wrong, such as a miscalculation or a typo.

Heuristics are more complicated, however, and much of the research on problem solving aims to understand how children and adults solve problems in complex, confusing, or murky situations. One question of particular interest involves transfer: how do children apply, or transfer, their knowledge and skills from one problem-solving scenario to another?

Six of one, half-dozen of the other

Research suggests that students tend to have trouble transferring knowledge between problems that share only the same deep structure. For example, two puzzles that can be solved with the same logic, but that have different numbers, settings, or characters, are tricky.

In contrast, problems that share both their deep structure and shallow structure can be solved with relative ease.

A seminal study that illustrates the challenges of transfer asked students to solve the Radiation Dilemma: a medical puzzle of how to destroy a tumor with laser beams. [2] Some of the students were first told to read The General: a puzzle (and its solution) based on the common military strategy of surrounding an enemy and attacking from all sides. The solution to the Radiation Dilemma was analogous to the solution for The General: radiation beams should target the tumor from all sides until destroyed.

The researchers found that the students who first read the solution to The General successfully solved the Radiation Dilemma more often than those who did not.

However, students who received a hint that the solution to The General problem would help them solve the Radiation Problem were actually more successful in solving it than those who read both problems but received no hint.

This finding suggests that analogies can certainly be a helpful guide when children (or adults) are trying to make sense of a problem or find similarities between different contexts. But, they can also be confusing. Presumably,  people become distracted by or hyper-focused on shallow structural features (e.g., reading the Radiation Dilemma and trying to remember what medical strategy was used on a TV drama) and thus overlook the deep structure similarities that are present.

So, when we ask students to make connections between two problems, scenarios, or stories that have surface-level differences, a little hint may just go a long way.

The less the merrier?

In addition to better understanding how to make decisions or think about problems, researchers also aim to understand how much we should think about them. And, contrary to popular thought, it appears that reasoned and evaluative thinking may not always be best.

In fact, there is evidence for the deliberation-without-attention effect: some problem-solving situations seem to benefit more from unconscious cognitive processing. To investigate this, scholars at the University of Amsterdam set out to determine whether better decisions result from unconscious or conscious thought. [3]

In their experiment:

  • participants (college students) read information about four hypothetical cars
  • the descriptions of the cars were either simple (four features of the car were listed) or complex (12 features were listed)
  • some of the features were positive and some were negative; the “best” car had the highest ratio of positive-to-negative features
  • four minutes passed between participants reading about the cars and being asked to choose the best one
  • some participants spent those four minutes thinking about the cars, while the others were given a puzzle to solve in order to distract them from such thinking

When asked to choose the “best” car, two groups stood out:

  • Group A: participants that (1) read the simple car description and (2) consciously thought about the cars were more likely to identify the best car than those who read the simple description and then worked on the puzzle
  • Group B: participants who: (1) read the most complex car descriptions and (2) were then distracted by the puzzle were more likely to identify the best car than those who read the complex description and consciously thought about the car options

The participants in Group B actually had a higher overall success rate than those in Group A.

Thus, it appeared that conscious thinkers made the best choices with simple conditions, but did not perform as well with complex circumstances. In contrast, the unconscious thinkers performed best with complex circumstances, but performed more poorly with simple ones.

Buyer’s Remorse

Of course, the cars that the participants evaluated were fictional. The researchers therefore wanted to see if their results would hold up in similar real-word circumstances. They traveled to two stores: IKEA (a complex store, because it sells furniture) and a department store (a simple store, because it sells a wide range of smaller items, such as kitchen accessories).

As shoppers were leaving the store with their purchases, the researchers asked them:

  • What did you buy?
  • How expensive was it?
  • Did you know about the product before you purchased it?
  • How much did you think about the product between seeing it and buying it?

The researchers then divided the shoppers into two groups: (1) conscious and (2) unconscious thinkers, based on amount of time they reportedly spent thinking about their purchased items.

After a few weeks, the researchers called the shoppers at home and asked them about their satisfaction with their purchases. In a similar vein to the first experiment, here the conscious thinkers reported more satisfaction for simple products (department store) and the unconscious thinkers reported more satisfaction for complex products (IKEA).

Thus, these experiments indicate that conscious thinking is linked to higher satisfaction with decisions when conditions are simple (less to evaluate), whereas unconscious thinking leads to higher satisfaction when conditions are complex (many factors to evaluate).

Why don’t you sleep on it

While these studies are only a snapshot of the problem-solving and decision-making research field, they offer some valuable thoughts for how we can support students in the classroom.

First, we know that students need to understand problems in order to solve them. It is likely a good habit to continually remind ourselves that our students do not all make sense of the same problems in the same way or at the same rate. Thus, as we saw in The General, when we offer students problem guides, strategies, or templates, a little nudge as to how to use them can be enormously beneficial.

Second, we often push our students to think deeply and critically about problems and context. And that is probably true now that, more than ever, thoughtful, evidence-based, and logical reasoning is critical for tackling both local and global issues.

But there is also much to be said about instinct, conscience, and whatever it is that goes on in our subconscious. So if we see our students dwelling on a problem, or sweating a decision, the best way that we can help them delve into a solution may just be to first have them step away for a little while.

References:

[1] Novick, L., & Bassok, M. (2006). Problem solving. In K. Holyoak & R. Morrison (Eds.), The Cambridge Handbook of Thinking and Reasoning (pp. 321-349). London: Cambridge University Press.

[2] Gick, M. & Holyoak, K. (1980). Analogical problem solving. Cognitive Psychology 12(3), 306-355.

[3] Dijksterhuis, A., Bos, M., Nordgren, L., & van Baaren, R. (2006). On making the right choice: The deliberation-without-attention effect. Science, 311, 1005-1007.

The Effect of Alcohol on Learning…
Andrew Watson
Andrew Watson

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…might not be what you’d expect.

My prediction would have been that if I have a glass of wine before I learn some new vocabulary words, I won’t learn those words as well as I would have fully sober.

That prediction, it turns out, is correct. New learning that takes place post-alcohol just doesn’t consolidate very well. It seems that alcohol inhibits long-term potentiation.

I also would have predicted that if I have a glass of wine just after I learn some new vocabulary words, that wine would muddle my memory of those new words as well.

That prediction, however, is just wrong. My post-study wine–surprise!–improves my recall of those words the next morning.

In fact, a recent study shows that this effect holds true not only in the psychology lab, but also at home. When participants (not just college students, by the way) went home after they learned new words and raised a pint or two, they remembered more of those words than their fully-sober counterparts.

Even more remarkable, they did better than their alcohol-free peers not because they forgot less, but because they remembered even more. That is, their recall score in the evening was in the mid 30% range; the next morning, it was in the low 40% range.

Theories, theories

The standard hypothesis to explain such a result goes like this: when we drink alcohol, the brain forms fewer new memories. The hippocampus takes advantage of this pause to consolidate previous memories.

In other words: since the brain has some alcohol-induced down time, it uses that time to firm up what it already knows.

The authors of this study suggest an alternate explanation: sleep. As they explain, alcohol increases the proportion of slow-wave sleep compared to rapid-eye-movement sleep. Because slow-wave sleep is good for the formation of factual memories, this SWS increase benefits factual learning.

(An implication of this hypothesis is that alcohol might be bad for other kinds of memory formation–such as procedural memory–which require more rapid-eye-movement sleep. That is: alcohol might help you learn more facts, but fewer skills.)

Some Caveats, and an Invitation

Needless to say, I’m not encouraging you to drink heavily to promote learning.

And, I wouldn’t share these results with my 2nd graders.

However, after a long evening of study, I just might feel a bit less guilty about relaxing with a cozy Cabernet.

And, when you come to this fall’s Learning and the Brain conference, you should definitely join us at the wine and cheese reception.

Innovating Minds: Rethinking Creativity to Inspire Change by Wilma Koutstaal and Jonathan Binks
Rebecca Gotlieb
Rebecca Gotlieb

How can creativity and innovation give rise to positive changes in ourselves and the world around us? Wilma Koutstaal, University of Minnesota Professor of Psychology, and Jonathan Binks, who runs the organization InnovatingMinds4Change, tackle this challenging question in their book Innovating Minds: Rethinking Creativity to Inspire Change. They offer a framework of five key questions to consider in undertaking endeavors that call for creativity. First, we should identify the ideas that capture our attention and consider how we shape those ideas. To see a problem differently, we should consider changing the level of abstraction with which we think about it. We should allow spontaneity and deliberateness to be part of the creative process. The authors encourage us to recognize the role of emotions, motivations, and perceptions in our creative endeavors. Finally, we should consider how our physical, symbolic, and social spaces and tools impact our ability to demonstrate creativity. Koutstaal and Binks conclude each chapter with stimulating questions to challenge their readers to think about how their habits impact their creativity. This book will provide help to the creative individual seeking to accelerate her work, as well as to the leader of an organization wishing to bring about change.

Our ideas come about from cyclical interactions among our minds, brains, and environments. Thinking occurs in our minds, supported by our brains. Our brains integrate signals from our bodies, and our bodies are continually exploring our environment. Depending on these interactions, different ideas can come to mind with differing levels of ease or challenge. To generate new and creative ideas it can be helpful to allow our thinking to oscillate between “zooming in” and “zooming out.” Changing levels of abstraction can help us reason by analogy, reduce our working memory load to create more space to think openly, and diminish our tendency to see objects in terms of only their intended use rather than in terms of all their possible uses.

Several distributed networks in the brain work together to orchestrate our creative thinking. The executive control network helps us plan, pay attention, and monitor progress towards a goal. The default mode network is important for imagining, thinking about the future, and taking others’ perspectives. The salience network helps us detect information in our environment, integrate information that is important to us, and switch between the utilization of other networks in the brain. Koutstaal and Binks explain that the brain’s prefrontal cortex is important for abstract thinking. They also explain the role of dopamine, a neurochemical, in producing cognitive stability and flexibility and in seeking new experiences, which can prompt creativity.

Either by our own violation or because of factors in our environment, our focus can shift from being pointed and deliberate to being expansive and free-flowing. The creative process necessitates both deliberate and spontaneous thoughts. Reducing our intense, pointed attention or allowing our minds to wander can foster creativity by making space for a greater variety of stimuli in the environment to enter our awareness. This, in turn, can shape the way we think about a challenge and impact our ability to notice opportunities to fill a need. On the other hand, intense focus and control allow us to persist through obstacles to achieve a creative goal.

The authors identify several factors that can boost creativity. A few of the examples the authors offer include: instructing people to think differently, having practiced and prepared for the demands of a creative task, explaining creative ideas to others to prompt shifting levels of abstraction, minimizing distractions to allow for a state of flow, adding and removing constraints within a creative problem, improvising, and thinking about the future without losing sight of the present.

Change begets change. More experience can foster more creativity. When teams or organizations seek to change or innovate, both the individual members of the group and the group as a whole impact the group’s adaptability. Teams that are more receptive to novelty, more emotionally stable, and more reflective about their practices are better able to change. Optimism is beneficial in promoting creativity, but it must be paired also with the ability to critique and be skeptical from time to time.

Ultimately, Koutstaal and Binks suggest identifying meaningful goals, finding synergy among one’s goals, being driven by one’s goals while remaining open to change in light of new information, modulating the extent to which our goals come to mind when we need them, and modifying our goals when needed. Because of the insights in this book into the innovation process and the examples of successful creative individuals and teams, Innovating Minds is likely to advance the way any reader thinks about the creative change process.

 

Koutstaal, W., & Binks, J. (2015). Innovating Minds: Rethinking Creativity to Inspire Change. New York: Oxford University Press.

 

Criticizing Critical Thinking
Andrew Watson
Andrew Watson

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Over at Newsweek, Alexander Nazaryan wants to vex you. Here’s a sample:

Only someone who has uncritically mastered the intricacies of Shakespeare’s verse, the social subtexts of Elizabethan society and the historical background of Hamlet is going to have any original or even interesting thoughts about the play. Everything else is just uninformed opinion lacking intellectual valence.

If you’d like a more nuanced version of this argument, check out Daniel Willingham’s Why Don’t Students Like School. 

In particular, you might read…

Chapter 2: “Factual knowledge must precede skill”

Chapter 4:  “We understand things in the context of what we already know, and most of what we know is concrete”

Chapter 5: “It is virtually impossible to become proficient at a mental task without extended practice”

and chapter 6: “Cognition early in training is different from cognition late in training”

From another vantage point: my own book Learning Begins discusses the dangers of working memory overload lurking in efforts to teach critical thinking.

Whether you prefer Nazaryan’s emphatic declamations, or Willingham’s and my more research-focused commentary, take some time to think critically about all the cognitive legwork that must precede real critical thought.

Lighten the Load
Andrew Watson
Andrew Watson

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You’d like an 8 page summary of Cognitive Load Theory, written in plain English for teachers? You’d like three pages of pertinent sources?

Click here for a handy report from the Centre for Education Statistics and Evaluation. (That’s not a typo; the Centre is in New South Wales, Australia.)

For example: you might check out the “expertise reversal effect” described on page 7; you’ll gain a whole new perspective on worked examples.

How Best to Count
Andrew Watson
Andrew Watson

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Should young children count on their fingers when learning math?

You can find strong opinions on both sides of this question. (This blog post uses 4 “No’s” and 5 exclamation points to discourage parents from allowing finger counting.)

Recent research from the University of Bristol, however, suggests that finger counting–when combined with other math exercises–improves quantitative skills more than either intervention by itself.

The study design is quite complex; check the link above if you’d like the details. But, the headline is clear: for 6- and 7-year-olds, a taboo against finger counting may well hinder the development of math skills.

Default Image
Andrew Watson
Andrew Watson

Here on the blog, we write a lot about desirable difficulties: that elusive middle ground where cognitive work is hard enough but not too hard.

Over at The Learning Scientists, they’ve got a handy list of resources to guide you through this idea more fully.

For an added benefit, the article begins with a brief criticism of the theory.

Enjoy!