Monthly Archives: November 2015

Humans are social beings, and we need others: Celebrating the good and coping with the bad is hard without friends and family. A loss of interest in social activities can be a sign of depression and mental illness. And social isolation is associated with abnormal behavior in rats¹ as well as in humans.²

But social ties are important beyond being a way to receive support. Research suggests that pro-social behavior—actions that help others, even at a sacrifice—is linked with better academic, social, and mental health outcomes in developing teens (and adults!). In other words, pro-sociality might be protective.

Eudaimonism and pro-social behavior may protect well-being

In my last post, I wrote about Dr. Eva Telzer’s research on family obligations as a potential buffer of the stressors of adolescence. In another study, Telzer and her colleagues explored this idea further. They presented teens (ages 15-17) with choices about giving money to themselves, or to their family, in an MRI scanner.³

Sometimes, the choices were no-brainers; adolescents were asked to choose between the scenario of gaining money for themselves, or not. At other times, the decision was a bit trickier. They asked participants: would you take a small personal loss if your family could gain even more cash?

The researchers described this self-sacrifice as a type of eudaimonic decision. Articulated by Aristotle, eudaimonia translates roughly to “flourishing,” and refers to a kind of happiness worth seeking and having.⁴ These kinds of behavior are often, but not exclusively, pro-social, meaning that they are voluntary social behaviors intended to help others. In contrast, the easy self-gain decision was hedonic—related to engaging in the immediate and easy pleasures of the moment.

Telzer and her colleagues noticed that changes in blood flow to the ventral striatum (suggesting that brain region’s neural activity) during certain decisions were correlated with long-term, real world outcomes for teens.

Adolescents with higher blood flow to the ventral striatum during self-sacrificing decisions were, on average, more likely to experience declines in depressive symptoms one year later. The ventral striatum is thought to be involved in processing the rewards, particularly the size of rewards. One possible explanation for this result is that the more adolescents experience self-sacrifice as rewarding, the more likely they might be to engage in protective eudaimonic activities. Over the course of a year, these activities might promote their well-being through building self-esteem and social relationships.

On the other hand, experiencing higher responses in the ventral striatum to the “easy reward” scenarios was associated with more extreme depressive symptoms one year later. It is possible that these teens were more likely to indulge in momentary pleasures than to invest in socially healthy exchanges.

The idea that pro-social and eudaimonic behaviors are related to happiness isn’t a new one. This self-protective link has been found in other studies, too:

• In middle school students, pro-social behaviors were associated with reduced feelings of loneliness one year later. This was true even when students had been the target of social bullying, like being left out of groups or being the target of gossip.⁵

• In adults, reporting engagement in eudaimonic activities, such as volunteering time, writing out future goals, and expressing gratitude, is associated with better well being and mood, particularly the next day.⁶

• Typically, low motivation and self worth are linked with emotional exhaustion in the workplace. Across two studies of different professions (professional fundraisers and sanitation workers), workers’ perceptions of their own pro-social impact buffered against these links. In other words, workers with low motivation or low self worth were less burnt-out at work if they felt like their work helped others—which has implications for teachers, too.⁷

Eudaimonism and pro-social behavior in schools

Celebrating acts of giving can be embedded in schools in ways big and small. Through extensive community service programming or classroom structures that reinforce helping behaviors, schools may transmit implicit messages about what it means to give.

At a recent conference for the Society for Research in Child Development, Dr. Ronald Dahl of the University of California, Berkeley suggested that one way to help teens and kids might be to figure out how to make giving a truly joyful experience.⁸

So, how can educators inspire the joy of giving?

While there’s no universal recipe, research suggests that certain elements of community service programming might best help teens:

1. Student choice: Meaningful choice can support middle school students’ developing sense of competence. In the Teen Outreach Program study, volunteer programs were more effective at reducing problem behaviors (like failing classes and school suspension rates) when middle school students chose the kinds of activities they participated in.⁹

2. Connecting with mentors: Social connection with adult mentors may enhance the experience of giving, potentially providing a model of giving for students to emulate. In the Teen Outreach Program, volunteer sites were more effective in reducing problem behaviors when middle school students reported a stronger sense of connection with the adult facilitators.⁹

3. It can’t come too easy: In Telzer’s study, there was another kind of “easy” decision teens could engage in: they could choose between giving money to their families, or not. Engagement of the ventral striatum during this decision was not linked with long-term changes in depression symptoms. At the recent Society for Research in Child Development conference, Telzer suggested that self-sacrifice might be a characteristic of the kinds of pro-social experiences that are self-protective.¹⁰ It is possible that adolescents may need to give up something meaningful, like their own time or personally valuable resources, in order to experience protective effects of pro-social behavior.

It’s important to note that the Teen Outreach Program study found no association between the first two elements and problem behaviors in high school students. These elements may have a greater impact in middle school, when student beliefs, like sense of competence, may be more flexible.

I’ve had the joy of seeing these elements play out in my 8th grade students’ yearlong Community Impact Projects. In these projects, students were mentored to develop a community program that spoke to their interests and passions. Carrying responsibility for a project with self-defined goals challenged students in many ways, including developing their meta-cognitive capacity for responding to challenges without spelled-out instructions about how to take next step. I hope that this psychosocial experience may have also been potent at buffering against some of the stressors of high school and beyond.

Currently, Americans are celebrating Thanksgiving weekend—the perfect merger of eudaimonic appreciation and hedonistic feasting. As we reflect on gratitude, let’s also consider the impact we have on others. This reflection, though particularly powerful for adolescents, may have protective value for all ages.

References & Further Reading

1. Kercmar, J., Büdefeld, T., Grgurevic, N., Tobet, S. A., & Majdic, G. (2011). Adolescent social isolation changes social recognition in adult mice. Behavioural Brain Research, 216(2), 647–651. [Paper]
2. Hall-Lande, J. A, Eisenberg, M. E., Christenson, S. L., & Neumark-Sztainer, D. (2007). Social isolation, psychological health, and protective factors in adolescence. Adolescence, 42, 265–286. [Paper]
3. Telzer, E. H., Fuligni, A. J., Lieberman, M. D., & Galvan, A. (2014). Neural sensitivity to eudaimonic and hedonic rewards differentially predict adolescent depressive symptoms over time. Proceedings of the National Academy of Sciences, 111(18), 6600–6605. [Paper]
4. Hursthouse, Rosalind,(2013), Virtue Ethics, The Stanford Encyclopedia of Philosophy, Fall Edition, Edward N. Zalta (ed.) [Article]
5. Griese, E. R., & Buhs, E. S. (2013). Prosocial Behavior as a Protective Factor for Children’s Peer Victimization. Journal of Youth and Adolescence, 43(7), 1052–1065. [Paper]
6. Steger, M. F., Kashdan, T. B., & Oishi, S. (2008). Being good by doing good: Daily eudaimonic activity and well-being. Journal of Research in Personality, 42(1), 22–42. [Paper]
7. Grant, A. M., & Sonnentag, S. (2010). Doing good buffers against feeling bad: Prosocial impact compensates for negative task and self-evaluations. Organizational Behavior and Human Decision Processes, 111(1), 13–22. [Paper]
8. Dahl, R. (September 16, 2015). Personal communication.
9. Allen, J. P., Philliber, S., & Herre, K. (1994). Programmatic Prevention of Adolescent Problem Behaviors: The Role of Autonomy, Relatedness, and Volunteer Service in the Teen Outreach Program. American Journal of Community Psychology. [Paper]
10. Telzer, E. (September 16, 2015). Personal communication.

• Caprara, G. V., Luengo Kanacri, B. P., Zuffianò, A., Gerbino, M., & Pastorelli, C. (2015). Why and How to Promote Adolescents’ Prosocial Behaviors: Direct, Mediated and Moderated Effects of the CEPIDEA School-Based Program. Journal of Youth and Adolescence, (November). [Paper]

Adolescence is the period between childhood and adulthood that largely coincides with the years of secondary schooling. This stage of life is characterized by many cognitive changes. One such change is in social signal sensitivity. Recent research has provided evidence for adolescence as a time of heightened receptivity and sensitivity to complex social signals in the environment, which are reflected in typical brain development patterns¹.

Developmental tasks

We are faced with certain developmental tasks at different points in our life. This means that we are expected to acquire certain skills or abilities at certain developmental stages. For instance, infants and young children are tasked to develop certain sensory and motor skills. And the human brain at this period of life reflects this, as it produces an excess number of connections between brain cells (called synapses) in sensory and motor cortices in early infancy, which are then pruned (or lost over time) to their adult levels across the first decade of life.

When it comes to the connections in the brain, more does not always mean better.

In fact, ‘synaptic pruning’ often allows the brain to communicate more efficiently.

The human brain also overproduces synapses in other regions of the cortex during infancy, such as the prefrontal cortex. However, unlike the sensory and motor cortices, the connections formed in this part of the brain continue to be pruned across the teenage years and into the twenties^2,3.

This prolonged development of the prefrontal cortex has intrigued developmental neuroscientists for decades. Given that synaptic pruning coincides with an increase in abilities associated with a given cortical area, perhaps the prolonged synaptic pruning of the prefrontal cortex coincides with the increased abilities associated with this part of the brain? This question underlies many developmental neuroscience studies.

In flux: The prefrontal cortex

The prefrontal cortex is often discussed as the hallmark of human cognition. Many complex cognitive abilities, such as inhibiting inappropriate behavior, planning for the future, and inferring the mental states of others, require the prefrontal cortex. It might be intuitive to many educators that an area of the brain involved in these complex behaviors and abilities is still developing throughout the teenage years.

However, the prefrontal cortex is not the neurological root of all behavioral changes between adolescence and adulthood.

The brain operates on a network level, which means that many different brain regions are constantly communicating with each other. While each region might have its own specific role, it is how the networks interact that ultimately matters. You can think of it as kind of like a team. Each member has its own role to play—and if a member gets weaker or stronger then it can change the way the team works—but the end result is a product of the whole team working together.

In flux: The nucleus accumbens

While the prefrontal cortex is often lauded as the seat of rational behavior, the nucleus accumbens is often demeaned as the cause of human hedonism or impulse. This subcortical brain region, hidden deep within the brain, is best known for its involvement in reward processing. Early research in rodents found evidence for dramatic remodeling of dopamine receptors in the nucleus accumbens during puberty⁴. This means that there was a change in how cells process dopamine, which is a neurotransmitter often connected to the experience of pleasure or rewards. Early fMRI studies then found increased recruitment of the nucleus accumbens in adolescence during reward processing⁵. This finding prompted developmental scientists to hypothesize that adolescent behaviors might be more influenced by nucleus accumbens signaling (or the sensitivity of this area to neurotransmitters like dopamine), which could explain why adolescents are drawn to risky or rewarding behaviors⁶. This heralded a change in thinking in developmental neuroscience. Rather than simply attributing adolescent changes to the developing prefrontal cortex, this new model posited that the changing interactions between the prefrontal cortex and nucleus accumbens underlie behavioral differences between adolescence and adulthood.

Not so simple

The model that I just described is more complex than can be described in a short blog post (see Further Reading). However, at its core is the interplay between two systems: one involved in socio-emotional processing and the other in cognitive control⁶. Subcortical regions such as the nucleus accumbens are considered part of the socio-emotional processing system because they are recruited during rewarding social interactions or emotional scenarios. However, we know that cortical regions are also involved in social cognitive processing (see previous blog post), and therefore these systems are starting to be taken into account when considering the neural correlates of adolescent behavior^7,8.

Social brain development

The network of brain regions involved in understanding or inferring the mental states of others (i.e. mentalizing) continues to develop across adolescence. Although they aren’t exclusively involved in mentalizing, these regions—the dorsomedial prefrontal cortex, temporal parietal junction, posterior superior temporal sulcus and anterior temporal cortex—are consistently recruited when individuals perform tasks that require understanding or inferring the mental states of others. Longitudinal studies of brain structure have found that these regions undergo substantial changes in structure throughout adolescence⁹.

And as described in my previous post, adolescents utilize the medial prefrontal cortex more than adults in tasks that require understanding the mental states of others¹⁰. Taken together, these changes in structure and function provide evidence for the continued development of a brain network involved in complex socio-cognitive processes that influence how we navigate the social world.

The developmental tasks of adolescence

Now, why would we expect adolescence to be a sensitive period for social brain development? The period of adolescence, which can be defined as beginning around puberty, is typically considered finished when one has reached a relatively stable role in society. Therefore, one of the major developmental tasks of adolescence is to learn how to navigate the complex social world of one’s society. Adolescents are more equipped to do this than children because they have the necessary cognitive abilities as well as the motivational drive to learn from their social environment. Educators can build on these capacities in learning settings if social motivation is used to bolster learning rather than seen as another behavior to inhibit in the classroom.

An aside on the nucleus accumbens and risk-taking

Earlier I described the nucleus accumbens being involved in reward processing. While this is true, it is also true that the nucleus accumbens is involved in learning. In a way, we can think of the nucleus accumbens as a sort of salience detector—it helps us know what to pay attention to in the environment. Therefore, the heightened sensitivity of the nucleus accumbens in adolescence presents a great opportunity for learning. Further, risk-taking is not inherently a bad behavior. In fact, we need to take many risks in order to succeed in the modern educational environment.

Encouraging these educational risks, which can be as minor as raising one’s hand to answer a question in front of one’s peers, or as substantial as spending the time to learn a new programming language, might be one way to take advantage of the natural inclinations of being young and flexible.

 

References

1. Blakemore, S.-J., & Mills, K. L. (2014). Is Adolescence a Sensitive Period for Sociocultural Processing? Annual Review of Psychology, 65(1), 187–207. [Paper]
2. Huttenlocher, P. R. (1979). Synaptic density in human frontal cortex — Developmental changes and effects of aging. Brain Research, 163(2), 195–205. [Paper]
3. Petanjek, Z., Judaš, M., Šimic, G., Rasin, M. R., Uylings, H. B. M., Rakic, P., & Kostovic, I. (2011). Extraordinary neoteny of synaptic spines in the human prefrontal cortex. Proceedings of the National Academy of Sciences of the United States of America, 108(32), 13281–13286. [Paper]
4. Andersen, S. L., Rutstein, M., Benzo, J. M., Hostetter, J. C., & Teicher, M. H. (1997). Sex differences in dopamine receptor overproduction and elimination. Neuroreport, 8(6), 1495–1498. [Paper].
5. Galvan, A., Hare, T. A., Parra, C. E., Penn, J., Voss, H., Glover, G., & Casey, B. J. (2006). Earlier Development of the Accumbens Relative to Orbitofrontal Cortex Might Underlie Risk-Taking Behavior in Adolescents. The Journal of Neuroscience, 26(25), 6885–6892. [Paper]
6. Steinberg, L. (2008). A Social Neuroscience Perspective on Adolescent Risk-Taking. Developmental Review: DR, 28(1), 78–106. [Paper]
7. Crone, E. A., & Dahl, R. E. (2012). Understanding adolescence as a period of social-affective engagement and goal flexibility. Nature Reviews. Neuroscience, 13(9), 636–650. [Paper]
8. Pfeifer, J. H., & Allen, N. B. (2012). Arrested development? Reconsidering dual-systems models of brain function in adolescence and disorders. Trends in Cognitive Sciences, 16(6), 322–329. [Paper]
9. Mills, K. L., Lalonde, F., Clasen, L. S., Giedd, J. N., & Blakemore, S. J. (2014). Developmental changes in the structure of the social brain in late childhood and adolescence. Social Cognitive and Affective Neuroscience, 9(1), 123–131. [Paper]
10. Blakemore, S.-J. (2008). The social brain in adolescence. Nature Reviews. Neuroscience, 9(4), 267–277. [Paper]

Further Reading

• Casey, B. J., Getz, S., & Galvan, A. (2008). The adolescent brain. Developmental Review: DR, 28(1), 62–77. http://doi.org/10.1016/j.dr.2007.08.003
• Gardner, M., & Steinberg, L. (2005). Peer influence on risk taking, risk preference, and risky decision making in adolescence and adulthood: an experimental study. Developmental Psychology, 41(4), 625–635. http://doi.org/10.1037/0012-1649.41.4.625
• Mills, K. L., Goddings, A.-L., Clasen, L. S., Giedd, J. N., & Blakemore, S.-J. (2014). The developmental mismatch in structural brain maturation during adolescence. Developmental Neuroscience. http://doi.org/10.1159/000362328
• Somerville, L. H., & Casey, B. J. (2010). Developmental neurobiology of cognitive control and motivational systems. Current Opinion in Neurobiology, 20(2), 236–241. http://doi.org/10.1016/j.conb.2010.01.006
• Somerville, L. H., van den Bulk, B. G., & Skwara, A. C. (2014). Response to: The triadic model perspective for the study of adolescent motivated behavior. Brain and Cognition. http://doi.org/10.1016/j.bandc.2014.01.003
• Steinberg, L. (2010). A dual systems model of adolescent risk-taking. Developmental Psychobiology, 52(3), 216–224. http://doi.org/10.1002/dev.20445

“It’s OK, some people just aren’t good at math”.

We’ve all heard this before. In fact, some of us have probably even thought it about ourselves (“I’m just not a math person”, “I’ve just never been great at spelling”).

But there’s a problem with this mindset: Not only is it not true, it’s hurting our children.

By believing the myth that talent is hardwired in our brains, and that some of us are naturally better at certain things than others, it keeps kids (and us, as parents and educators) from knowing that with a little hard work, dedication, and self-confidence they can improve.

The idea that math ability, or any ability for that matter, is an immalleable trait perpetuates the harmful myth that intelligence and creativity are mostly genetic. Research has pointed to two orientations of individual’s conceptions of ability: incremental orientation and entity orientation, sometimes also thought of as Fixed and Growth mindset¹. Students who lean towards a more incremental orientation believe that intelligence is malleable and can improve with effort. On the other hand, individuals whose ideas of intelligence align with an entity orientation believe that their abilities are fixed; you are born with a certain level of intelligence and no amount of effort can change this.

In other words, incremental orientation suggests that what you do affects what you know. Entity orientation suggests that who you are affects what you can do.

An entity orientation can lead to students giving up in subjects that they aren’t excelling in, likely because they believe that they are inherently incapable of excelling and any efforts to improve would be wasted energy². Another study found that women who believed their math abilities were fixed and unchangeable showed less interest in math related tasks and were therefore more likely to “fall prey to the gender gap that exists in mathematics fields”³. In this way, an entity orientation may make people more susceptible to “stereotype threat”, or the tendency to believe that you are more or less prone to something because of the innate abilities of the groups that you are a part of.

A recent nationwide, longitudinal study also supports these findings, suggesting that both male and female students who believed that their abilities were fixed genetic traits may keep them from later majoring in STEM (science, technology, engineering and mathematics) fields⁴. One author of the study suggests that “students may need to hear that encountering difficulty during classwork is expected and normal,” and that anyone can be good at math, or any other subjects they’re struggling with. This mentality, what scientists refer to as the “growth mindset”, seems to equally benefit both boys and girls⁵ and suggest that teaching this message in schools will help encourage more girls to pursue careers in STEM fields.

However, there are still a disparagingly low number of women in STEM fields, with men outnumbering women 3 to 1⁶. Recent research is pointing to one possibility: academics that believe in the concept of innate talent may lead to bias. Findings suggest that the more professors thought that innate talent was necessary to succeed within certain fields (namely philosophy, music, economics, and math), the less likely women and African Americans would dominate that field⁷. This mindset may be limiting people’s opportunities before they even get started. In other words, it may be just as important for teachers, professors, and leaders to believe that students have an incremental orientation as it is for the students themselves.

So how can we fix this? For starters, we can focus on teaching people of all ages the science behind a growth mindset. The first step towards incorporating these ideas in the classroom is making sure that teachers themselves believe them. Innate talent is a myth and our brains are constantly developing, even into adulthood⁸. This is evident in the dynamic memories of New York City taxi drivers⁹ or even playing games like Tetris (which research has found may thicken the cortex, or outer layer of the brain, in adolescence¹⁰). And this concept isn’t only relevant to students who are struggling; even students who advance in math can improve their cognitive abilities¹¹.

Teaching students these facts about the brain can actually help them learn. A new study has found that students who struggle in school actually improve once they’ve been taught that intelligence isn’t fixed and can advance with hard work¹². Researchers have called this concept “mindset interventions” – students spend around 45 minutes reading and writing about articles on the brain’s ability to grow and develop. While improvement in grades is only around one-tenth of a letter grade, this is still really impressive considering students spend less than an hour on these ‘interventions’. The key to these interventions is a supportive teacher who “encourages students to take advantage of such opportunities”¹².

Psychologist Carol Dweck and colleagues have shown that experiences as early as elementary school often reinforce mental habits that support the myth that intelligence is a fixed, genetic trait¹³. She has found that children come to an unconscious assumption that tasks given at school (such as quizzes, in-class assignments, or homework) are actually opportunities to measure how smart they are rather than innovative ways to challenge their intelligence. For these children, performing poorly on these assignments shows that they lack intelligence rather than being an indicator of how much more they have to learn¹⁴. Because they believe that the main reason behind these tasks is to measure their competence, these kids try to pick the easiest task to complete, which unfortunately means that they aren’t challenging their intelligence and often lose out on the full benefits of learning.

Dweck and colleagues have also shown ways to improve kids’ outlooks about their intellectual ability. They explained to a group of at-risk junior high school students that intelligence is highly malleable and can be developed with hard work. Most importantly, they explained to these students that they were in charge of their intelligence and with hard work could guide their brain’s improvement during the learning process. What they found was that convincing students that they could make themselves smarter made them work harder and achieve higher scores. This effect was seen even more so in students who initially believed that intelligence was an innate, genetic trait. Dweck reported some very emotional stories of junior high school boys who were “reduced to tears by the news that their intelligence was substantially under their control”¹⁵.

While these kids felt as though they were given a second chance, they actually had the right tools all along. Teachers face many challenges that are outside of their control and that may impede the learning process; but this is one thing every educator can offer their students that may have tremendous impact on their lives. By adopting a growth mindset themselves, educators can model, nurture, and share the value of an incremental orientation. It’s important to start explaining to children while their young that they have full control of their futures, and intellectual abilities.

Just because something doesn’t come easily or naturally doesn’t mean they aren’t smart or can never be good at math – all it really means is that they may have to keep trying.

References & Further Reading

1. Linehan, P. L. (1998). Conceptions of ability: Nature and impact across content areas. Purdue University: PhD Thesis. [Dissertation]
2. Burnette, J.L., O’Boyle, E.H., VanEpps, E.M., Pollack, J.M., Finkel, E.J. (2013). Mind-sets matter: A meta-analytic review of implicit theories and self-regulation. Psychological Bulletin, 139(3), p. 655-701. [Meta-Analysis]
3. Burkley, M., Parker, J., Stermer, S.P., & Burkley, E. (2010). Trait beliefs that make women vulnerable to math disengagement. Personality and Individual Differences, 48(2), p. 234-238. [Journal Article]
4. Nix, S., Perez-Felkner, L., & Thomas, K. (2015). Perceived Mathematical Ability under Challenge: A Longitudinal Perspective on Sex Segregation among STEM Degree Fields. Frontiers in Psychology, 6(530). [Journal Article]
5. Good, C., Rattan, A., & Dweck, C. (2012). Why do women opt out? Sense of belonging and women’s representation in mathematics. Journal of Personality and Social Psychology, 102(4), p. 700-717. [Journal Article]
6. Miller, D. & Wai, J. (2015). The bachelor’s to Ph.D. STEM pipeline no longer leaks more women than men: a 30 year analysis. Frontiers in Psychology, 6(37). [Journal Article]
7. Leslie, S., Cimpian, A., Meyer, M., & Freeland, E. (2015). Expectations of brilliance underlie gender distributions across academic disciplines. Science, 347 (6219), p. 262-265. [Journal Article]
8. May, A. (2011). Experience-dependent structural plasticity in the adult human brain. Trends in Cognitive Sciences, 15(10), p. 475-482. [Journal Article]
9. Maguire, E.A., Woollett, K., & Spiers, H. J. (2006). London Taxi Drivers and Bus Drivers: A Structural MRI and Neuropsychological Analysis. Hippocampus 16, p. 1091–1101. [Journal Article]
10. Haier, R., Karama, S., Leyba, L., & Jung, R. (2009). MRI Assessment Of Cortical Thickness And Functional Activity Changes In Adolescent Girls Following Three Months Of Practice On A Visual-spatial Task. BMC Research Notes, 174. [Report]
11. Miller, D. & Halpern, D.F. (2013). Can spatial training improve long-term outcomes for gifted STEM undergraduates? Learning and Individual Differences, 26, p.141-152. [Journal Article]
12. Yeager, D., & Walton, G. (2011). Social-Psychological Interventions in Education: They’re Not Magic. Review of Educational Research, 267-301. [Journal Article]
13. Dweck, C. (2007). Mindset: The New Psychology of Success. Ballantine Books: Random House, NY. [Book]
14. Edmondson, A. C. (2008). The Competitive Imperative of Learning. Harvard Business Review. [Web Article]
15. Nisbett, R. (2009). Intelligence and how to get it: Why schools and cultures count.W. Norton & Co: New York, NY. [Book]

 

At first glance, metaphor and science might seem to inhabit opposite ends of the things-we-learn-in-school continuum. We usually learn about metaphor through lessons on works like Langston Hughes’s Life ain’t been no crystal stair, and we associate science with topics like crystallization, the process of transferring a liquid to a solid. But metaphor is a mischief that doesn’t like to stay confined to the language arts classroom. It lurks in political discourse (the wealth gap), in music (you ain’t nothin’ but a hound dog), and – you guessed it – in education.

Analogies link two topics in order to bring attention to some of their commonalities, and metaphors are one way of using analogy in language. In most cases, metaphors describe a more novel target, an abstract concept that we can’t see, touch, or experience physically, by linking it to a familiar source concept, something more concrete that we do have experience with. For that reason, it might not be surprising that we often draw on real-world experiences to describe complex scientific concepts. The domain we’re drawing from is often called the source, while the domain we’re trying to explain or understand is the target. We describe molecules as excited when they have a lot of energy, and we learn that when they’re attracted to other molecules, they often form bonds. Whether these descriptions were intentionally metaphorical or not, our language to describe electron dynamics borrows heavily from the language we use to talk about human interactions, a context we’re much more familiar with than subatomic particle behavior. Once you start paying attention, metaphors seem to be everywhere: People who have diabetes are often told that insulin is the key that unlocks their cell doors. And the ozone layer is often described as a blanket that protects the earth. And DNA is often referred to as a blueprint or a recipe. Are these just convenient ways of talking? Or do the linguistic metaphors we use shape the way we think about the complex topics they describe?

Metaphor shapes thought
A growing body of research suggests that we don’t just use metaphors to talk; we use them to think as well. In a series of experiments by Paul Thibodeau and Lera Boroditsky¹, people read either that crime is a “wild beast preying on” or “virus infecting” the city of Addison (a fictional city). They then read some fake statistics, like “In 2004, there were 330 murders in the city, in 2007, there were over 500,” and they were asked what they thought Addison should do about the crime. People’s proposed solutions differed systematically depending on the metaphor they read earlier to describe the crime. Those who read that crime was a beast tended to make suggestions related to containing it and enforcing penalties, things people would probably suggest if an actual beast were loose in the town. The virus readers, on the other hand, were more likely than the beast readers to suggest that the city find the root causes of the crime problem and remedy those, in line with how they would likely eliminate a literal virus. People were still swayed by the metaphor even when they were given options to choose from instead of generating their own solutions. This work shows that the metaphor people encounter for a topic as complex as crime can influence the way they reason about it.

Metaphors in the classroom
How might metaphors affect students learning about complex topics? Since metaphors usually describe intangible ideas or processes by referring to things we actually have experience with, teachers often feel that they are an effective way to teach. In 1983, Dedre and Donald Gentner investigated this intuition more closely². They noticed that there are two common analogies for teaching electricity. The first is the water-flow analogy: just as water flows through pipes, electricity flows through the wires of an electrical system. The second is a moving-crowds analogy: the flow of electricity through the wires can be seen as similar to a crowd of mice running along an enclosed track.

Although both analogies demonstrate the gist of electricity flow, there are other features of electricity that they make less obvious. For example, what happens when multiple resistors are introduced in an electrical circuit? If it’s a series circuit (meaning that each component is connected in a series), the result will be different than if it’s a parallel circuit (meaning that the current divides in at least two paths before completing the circuit). The image below gives an example of each type of circuit.

If a student is thinking about the circuit as similar to water pipes, every blockage (created by a resistor) might seem to affect the circuit in the same way since all blockages slow flowing water down. However, this is not the case with electricity; in the case of a parallel circuit, more resistors actually create more current. Consistent with this idea, people who used the water-flow model to think about electricity were less likely to understand resistors than those who thought about electricity as moving crowds. The moving-crowds analogy was not a conceptual panacea, however: people using that mental metaphor had more trouble with questions about the effects of including multiple batteries in the circuit. This is likely because it’s not clear what the batteries in the circuit are analogous to in the moving mice model. In the water model, however, the battery’s analog is much clearer – it corresponds to a reservoir. This work shows that the metaphors used to teach complex concepts have consequences, both helpful and misleading, for how students understand the phenomena they describe.

Metaphor abounds in education about the brain as well. Because we can’t see or touch the brain and definitely can’t see or touch the many dynamic processes occurring within it, metaphors make neuroscience more tangible. The brain is frequently compared to a computer when we want to emphasize its ability to take in information from the world, “process” it, and behave accordingly. It’s a muscle when we want to emphasize our ability to change what we know and how we think. Metaphors are used to talk about the different parts of the brain, too. Neurons are often described and diagrammed as tree-like (which is the meaning of the Greek root in dendrite!), and neurons’ dynamics are almost inevitably talked about in terms of human communication. Neurons are seen as messengers that send and receive the messages underlying all cognition. And once those messages arrive at the frontal lobe – the area most known for its involvement in higher-level thinking like decision-making, inhibition, and rational thinking – we often say that they have reached the brain’s control center. In many cases, these metaphors shed light on the complexities of the brain that are far from our direct experience, but it’s important that we also keep in mind the hidden inferences each might contain about how the brain really works.

Effective metaphor use
Although metaphors can open doors to many useful insights, they can also encourage misunderstandings if students make unintended links between the source and target domains. The solution for avoiding these misleading inferences is not to abolish metaphor from the classroom completely. Not only would that be nearly impossible, but it would also bar us from the helpful insights that metaphors do foster. In addition, some research shows that metaphors can evoke more emotional responses in the brain (specifically, more amygdala and anterior hippocampus activation) than literal sentences containing the same content³. Since emotional stimuli tend to be remembered better than unemotional stimuli⁴, it’s an open question as to whether metaphor can help students learn by tapping into emotional cognitive resources.

Although it is difficult to provide advice for metaphors that will hold for all students, subjects, and topics, Benjamin Jee and colleagues have articulated some general guidelines that educators can follow to ensure that their analogies are as effective as possible⁵:

● Make sure that students can explicitly map the features of the analogy (a blueprint, for example) to the new concept (DNA). Instructors may first need to explicitly point out the mappings in order for the students to make the connections
● Acknowledge the incorrect inferences that students might make. Point out the ways in which DNA is not like a blueprint, in addition to the ways that it is.
● Keep the metaphorical source available. While explaining the ways that the analogy extends from one domain to another, keeping the source present helps students focus their mental energy on connecting the topics, instead of working to recall the example at hand.
● Introduce more similar source-target pairs before expanding to metaphors that have fewer surface similarities. The more similar the features are of the two concepts being compared, the easier it will be for students to extrapolate the conceptual similarities that the metaphor aims to highlight.

Instead, we might be better off adopting an everything in moderation mentality, a mentality that we strive to apply to many of the great things in our lives. When we indulge in a piece of chocolate cake, we savor it as something rich and satisfying. But we know that a diet consisting only, or even primarily, of chocolate cake would be harmful, so we try to balance our cake consumption with other foods. We can think of our metaphors in the same way: they’re worth savoring, but if consumed with reckless abandon, they may clog up our figurative arteries and prevent us from deep understandings.

References

1. Thibodeau PH, Boroditsky L (2011). Metaphors We Think With: The Role of Metaphor in Reasoning. PLoS ONE 6(2): e16782. doi:10.1371/journal.pone.0016782 [Paper]
2. Gentner, D. & Gentner, D. (1983). Flowing waters or teeming crowds: Mental models of electricity. In D. Gentner & A. L. Stevens (Eds.), Mental models (pp. 99-129). Hillsdale, NJ: Lawrence Erlbaum Associates. [Chapter]
3. Citron, F.M. & Goldberg, A.E. (2014). Metaphorical sentences are more emotionally engaging than their literal counterparts. J Cogn Neurosci, 26(11), 2585-95. [Paper]
4. Hamann, S. (2001). Cognitive and neural mechanisms of emotional memory. TRENDS in Cognitive Science, 5(9), 394-400. [Paper]
5. Jee, B. D., Uttal, D. H., Gentner, D., Manduca, C., Shipley, T., Sageman, B., Ormand, C. J., & Tikoff, B. (2010). Analogical thinking in geoscience education. Journal of Geoscience Education, 58 (1), 2-13. [Paper]

Further reading:

1. Richland, LE, Zur, O., & Holyoak, KJ. (2007). Cognitive supports for analogies in the mathematics classroom. Science, 316(5828), 1128-1129. DOI:10.1126/science.1142103. [Paper]
2. Hendricks, R. (2015) A metaphorical tour of the brain. [Article]

“The illiterate of the 21st century will not be those who cannot read and write, but those who cannot learn, unlearn and relearn”¹ 

The Issue

When we think about what we teach our students, the first thing that comes to mind is knowledge; the curriculum and standards are full of concepts students should learn and understand. As we think about it further, we realize it’s important that their knowledge does not remain inert: students should be able to apply what they know through skills like critical thinking, creativity, communication, and collaboration. We also realize that our students should embody certain character qualities in how they engage with the world: grit, perseverance, mindfulness, etc.

We may think that sounds like a complete, multi-dimensional education.

But there is one more dimension we are missing: the “meta” dimension. “Meta” is a term that means “referring to itself”. In other words, students must learn how to learn. They must be reflective about their growth. They must learn to set goals, select strategies, and evaluate their progress. They must internalize a growth mindset, believing effort matters and approaching challenges with excitement.

The Research

Metacognition (the process of thinking about thinking) has been shown to enhance learning,²  and to transfer across disciplines.³ To illustrate how this works on the level of student behavior, we can look to mathematics education research.

In one study, students were compared to seasoned mathematicians. The students consistently selected a seemingly useful strategy and continued to apply it without checking to see if it was actually working. They wasted a significant amount of time on fruitless pursuits. The more experienced mathematicians on the other hand, exercised metacognition, monitoring their approach all along the way to see if it was actually leading to a solution or a dead end. Rather than just using what they had learned, they thought about how they were using what they had learned – and that made a huge difference.

Of course, with such an abstract learning goal, it is important for us to be precise with how to teach it. Traditional methods of improving students’ learning strategies often focus on prescribed procedures such as note-taking, self-testing, and scheduling. These typically result in initial motivation and some short-term improvement, but ultimately a reversion to old habits.⁴ While these tactics may work in the short term (e.g. to cram for an exam), they don’t actually result in a deep, lasting change.

In The Classroom – Generally

There are four general aspects to teaching metacognition:
1. Promoting general awareness of the importance of metacognition
2. Improving awareness of cognition through modeling
3. Improving regulation and applications of cognition
4. Fostering environments that promote meta-learning.

First of all, it is important to explicitly talk about metacognition. Since the challenge is to teach students to consciously monitor and regulate their cognition, they should first consciously think about it, and choose to set it as a goal. We can remind students that learning isn’t something that just happens, and it doesn’t happen the same way for all of us all of the time. By watching how we’re learning, making note of our struggles, strengths, and patterns, we can actually become better learners. If a student fails at a math problem, for example, it may be valuable to talk about how thinking processes, attitudes, motivation, and context may have played a role in how they chose their method of solving the problem; not just the correct but mechanical application of a mathematical procedure.

Next, although metacognition is largely a student-centric practice, teachers play an important role in fostering it by modeling appropriate metacognitive practices explicitly as they teach, so that students can follow the thought process of an expert, and eventually internalize it for themselves. That means saying how you’re thinking about your own thinking, and reminding students why that’s important. As you’re teaching a class on grammar, for example, you might start a dialogue about how you put the lesson together: “Why do you think I decided to teach it this way?” Students can also model good metacognitive practices for each other. This can sometimes be even more effective, as students are often closer to peers’ levels of metacognitive development.

Third, it is important to move beyond simple “awareness,” to regulation and application. You can imagine being aware you are procrastinating, or not studying in the most efficient way, and yet not taking action in accordance with your awareness. This step seems like a given, and yet it is important to highlight it separately, because it is often the biggest roadblock to improvement. Mapping out a plan to make improvements based on self-awareness can be a challenging and cognitively demanding undertaking. By carving out classroom time dedicated to developing these skills, we send the message that it’s normal for these changes to not happen automatically. They take dedicated thought, practice, and reflection. Students can work alone or in groups to reflect on common obstacles like procrastination or test anxiety, and how they’ve been working to overcome them. This shows students that strategies are possible, they take time to find, and ultimately, they’re worth it.

Finally, as described above, it is important to foster a classroom climate that promotes a view of intelligence as malleable with hard work (a growth mindset) and the goal of learning as mastery, (rather than performance). This way, students can focus on internalizing skills and competencies rather than achieving a high but short-term, superficial and non-transferable level of performance. This means talking about these things. It might sound like a lot of talking, but if we can spend a semester teaching biology, we can interweave conversations about how to learn biology, too.

You might be thinking something along the lines of: “This may be hard to grasp for many students. Sure, I can introduce it to the students who are already excelling, but those who are struggling already have so much on their plates!” Metacognition can always be developed in students in the context of their current goals and can enhance their learning⁵ as well as transfer of learning,⁶  no matter their starting achievement level. In fact, it may be most useful for lower-achieving students, as the higher-achieving students are most likely already employing strategies that have proven successful for them.⁷ 

Research has shown that for learning disabled and low achieving students, metacognitive training can improve behavior more effectively than traditional attention control training.⁸  It has even been shown to increase academic self-confidence of non-Caucasian students in the STEM disciplines,⁹ counteracting the effects of stereotype threat.

Action Items

When students get back an exam, how often do they glance at the grade, and never look at it again? Exams can be very useful teaching tools. Many teachers offer students incentives for correcting their mistakes, hoping this will encourage them to fill in their gaps. Going one step further, Marsha C. Lovett at Carnegie Mellon has developed “exam wrappers” to scaffold students in digging deeply into their meta-cognitive process, reflect on their strengths and weaknesses, and adapt their strategies. These wrappers are basically tools for reflecting on and enhancing learning post-exam, reminding students that the grade is not the end goal. Below is an example wrapper from a physics test.

Exam wrappers help students to spend time thinking carefully about their strategies, and learn from understanding their performance on a test. Of course, this doesn’t have to apply only to exams. Wrappers can be developed for and activity, including homework assignments, in-class exercises, projects, and so on. For some more examples, check out the Eberly Center website.

Metacognitive scaffolding can enhance all parts of the learning experience, not just exams. Wrappers can be designed for homework assignments, in-class exercises, projects, etc. Discussing the learning goals and rationale behind assignments before students begin assignments has been shown to help students master the content.

So What?

When we teach our students, we hope they will apply what they learn to their lives. In teaching ethics, for example, we believe that we are helping them to become more ethical people. But the evidence suggests that ethicists “are no likelier to donate to charity, to choose a vegetarian diet, to reply to student emails, to pay conference registration fees they owe, to return their library books, to vote in public elections, to stay in regular contact with their mothers, to be blood or organ donors, or to behave politely at conferences.”¹⁰ 

It turns out that we have been skipping a step: meta-learning is crucial for the translation of understanding into action.

Meta-learning helps within subjects, and it helps to reach outside of them. It makes us more likely to transfer what we know from one sphere of life to another, to figure out a more optimal way of achieving our goals, and to live according to our principles. And it is not only achievable in our classrooms, it can enhance learning at every stage.

 

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To learn more, check out Maya Bialik’s new book Four-Dimensional Education. [Hint: Meta-Learning is the fourth dimension; the first three are knowledge, skills, and character].

References & Further Reading

1. Psychologist Herbert Gerjuoy as quoted by Alvin Toffler, Futurist, in “Future Shock” (1970) [Book]

2. Schmidt, A. M., & Ford, J. K. (2003). Learning Within a Learner Control Training Environment: the Interactive Effects of Goal Orientation and Metacognitive Instruction on Learning Outcomes. Personnel Psychology, 56(2), 405–429. [Paper]

3. Ford, J. K., Smith, E. M., Weissbein, D. a., Gully, S. M., & Salas, E. (1998). Relationships of goal orientation, metacognitive activity, and practice strategies with learning outcomes and transfer. Journal of Applied Psychology, 83(2), 218–233. [Paper]

4. E. Martin and P. Ramsden, “Learning Skills and Skill in Learning,” in J.T.E. Richardson, M. Eysenck, and D. Warren-Piper (Eds.), Student Learning: Research in Education and Cognitive Psychology (Guildford, Surrey: Society for Research into Higher Education and NFER-Nelson, 1986) as cited in J. Biggs, “The Role of Metacognition in Enhancing Learning,” Australian Journal of Education 32, no. 2, (1988): 127–138 [Paper]

5. Schmidt, A. M., & Ford, J. K. (2003). Learning Within a Learner Control Training Environment: the Interactive Effects of Goal Orientation and Metacognitive Instruction on Learning Outcomes. Personnel Psychology, 56(2), 405–429. [Paper]

6. Ford, J. K., Smith, E. M., Weissbein, D. a., Gully, S. M., & Salas, E. (1998). Relationships of goal orientation, metacognitive activity, and practice strategies with learning outcomes and transfer. Journal of Applied Psychology, 83(2), 218–233. [Paper]

7. McKeachie, W. J. (1988). The need for study strategy training. In C. E. Weinstein, E. T. Goetz, & P. A. Alexander (Eds.), Learning and study strategies: Issues in assessment, instruction, and evaluation (pp. 3-9). New York: Academic Press. [Chapter]

8. Larson, K. a., & Gerber, M. M. (1987). Effects of Social Metacognitive Training of Enhanced Overt Behavior in Learning Disabled and Low Achieving Delinquents. Exceptional Children. [Paper]

9. Winkelmes, M (2013), “Transparency in teaching: Faculty share data and improve students’ learning” Liberal Education 99/2 (Spring 2013), 48-55. [Article] See also Illinois Initiative on Transparency in Learning and Teaching, for http://go.illinois.edu/transparentmethods

10. Schwitzgebel, E. (2013). The Moral Behavior of Ethicists and the Role of the Philosopher. [Paper]