Misunderstandings about scientific findings can be the result of an honest desire to learn. Attempts at correcting misunderstandings can backfire, strengthening inaccurate beliefs.
Based on various scientific disciplines (see Chapter 2), there’s a lot we know about learning, and there’s also a great deal we don’t know. But who is the “we” in that statement? If a small, select group of scientists understand some process – say, the chemical reaction that occurs when neutrons collide – does that count as “known”? Or does it need to become part of everyday knowledge, such as the fact that the Earth is round? Scientists found this out, but now the average person also knows that the Earth is round – whereas in the neutron collision example, only a select few know the information. These two examples come from physics, but the same parallel can be drawn in learning: a small select group of scientists are trying to understand in detail how learning occurs in the brain, but all of us know that children are not innately equipped with knowledge about the world and need to be taught.
Scientists are trying to understand in detail how learning occurs in the brain.
This is ok. We don’t all need to know exactly how synapses operate in the brain; but what about a more general understanding of the mind? Isn’t it useful to know that as soon as we encounter a piece of information, we immediately start to forget it? Or what about the fact that our memories are not like libraries, but instead reconstruct everything we try to retrieve? (For more about memory, see Chapter 7.) We think that type of information is useful – and on the whole, so do teachers. A survey of teachers around the world revealed that, overall, educators are highly enthusiastic about what cognitive psychology and neuroscience have to offer to education (Pickering & Howard-Jones, 2007).
Overall, educators are highly enthusiastic about what cognitive psychology and neuroscience have to offer education.
The problem arises when information about learning – particularly about how learning occurs in the brain – is taken out of context and condensed into simplified overgeneralizations.
The problem arises when information about learning is taken out of context and condensed into overgeneralizations.
Once the message is passed down through various channels (from researchers, to journalists, to professional development workshops, to teachers), the science behind the “fact” often is lost, and the conclusion distorted.
Eventually, what started as a simplification or overgeneralization can turn into a slogan – and an inaccurate one at that. Indeed, a common term used to describe misunderstandings about the brain is “neuromyths.” However, myths about learning and the brain typically start from a grain of truth, large or small. For this reason, we would rather not call them “myths,” instead referring to them as “misunderstandings” or “misconceptions.”
Misconceptions are beliefs that contradict the current state of scientific evidence. (2017)
Annette Taylor
What are the most common misunderstandings? Two students in Yana’s lab, Marcus and Shannon, sifted through 12 empirical papers that surveyed a total of 14,737 participants in 15 different countries, to determine which misunderstandings were most commonly believed across the world.
In the table opposite, you will see the ten most common misunderstandings about learning and the brain, along with the average percentage of study participants who believed each one.
Now, let’s dig into three of these misunderstandings.
The data in this table have been aggregated from the following studies: Deligiannidi and Howard-Jones (2015); Dekker, Lee, Howard-Jones, and Jolles (2012); Dündar and Gündüz (2016); Ferrero, Garaiza, and Vadillo (2016); Gleichgerrcht, Luttges, Salvarezza, and Campos (2015); Herculano-Houzel (2002); Hermida, Segretin, Soni García, and Lipina (2016); Macdonald, Germine, Anderson, Christodoulou, and McGrath (2017); Karakus, Howard-Jones, and Jay (2015); Papadatou-Pastou, Haliou, and Vlachos, (2017); and Pei, Howard-Jones, Zhang, Liu, & Jin (2015). Note that not all of the studies mentioned included each statement.
Shannon Rowley & Marcus Lithander
This belief describes the idea that young children should be exposed to many interesting things to see and explore, and often manifests itself as gaudy, “visually noisy” classrooms (Erickson, 2017).
Some of our everyday understanding about enriching environments may come from a misapplication of studies performed in other species (e.g., rats). A study from the 1960s found that rats deprived of stimulation had sparser connections between their neurons, and by word-of-mouth this could have led people to believe that humans needed an “enriched” environment in order to thrive (Diamond, Krech, & Rosenzweig, 1964). It is also possible that this belief stems from an overcorrection for the real findings that sensory deprivation leads to decreased learning (Vernon & Hoffman, 1956). However, true sensory deprivation is very extreme, and would involve putting a child in a situation where they cannot see, hear, or feel anything. Take the classic case study of Genie as an example of extreme isolation (Fromkin, Krashen, Curtiss, Rigler, & Rigler, 1974). Genie was found in 1970, when she was 13 years old. She had been locked in a room by herself by her father, and was completely socially isolated. She spent much of her time tied to her crib or to a toilet chair. When child welfare found her, she could not talk. This is an extreme case of sensory deprivation, but demonstrates the type of deprivation that actually leads to a lack of development.
The reality is that in their everyday lives, even without decorated classrooms, children encounter sufficient information to enable their brains to develop normally. In fact, overly decorated classrooms can actually lead to a decrease in learning relative to more sparsely decorated classrooms, due to potential for distraction (Fisher, Godwin, & Seltman, 2014). Colorful decorations can lead children to shift or split their attention away from the teacher and the current learning tasks, and this can interfere with learning (see Chapter 6 on attention).
We may put children in visually noisy learning environments because we misunderstand their need for stimulation.
There is currently no solid evidence from controlled experiments to suggest that teaching in someone’s preferred modality (e.g., auditory) will help them learn. And yet, a lot of people hold on to the idea that learning styles are important and meaningful. Where does this misunderstanding come from?
A lot of people hold on to the idea that learning styles are important and meaningful.
It’s likely that the idea comes from an obvious truth: that individuals have preferences about the way they study. This is non-controversial; it would be strange to deny the existence of preferences, since we all have them. But where the overextension happens is where people immediately assume that these preferences should be honored in order to maximize learning. Think of the following nutritional analogy: let’s say one person likes apples, while the other person likes carrots.
Now let’s imagine we measure out 100 calories’ worth of apples and carrots, and have these two people eat either their preferred food, or their nonpreferred food, on top of what they normally eat, every day for a month. We then measure how much weight they gained (assuming they were maintaining their weight with their own caloric intake). Will they put on a different amount of weight depending on whether they ate their preferred or nonpreferred food? No. They are taking in the same number of calories regardless of whether they like or dislike the food. At the same time, carrots and apples contain different nutrients, so ideally, people would be eating a mix of both!
Learning styles seem impossible to get away from. Indeed, surveys conducted across the world typically find that over 90 percent of teachers believe in adapting teaching to each student’s preferred learning style. This statistic in and of itself might not be surprising, but the more surprising result is that greater interest in the neuroscience of education tends to be related to stronger – rather than weaker – beliefs in learning styles (Dekker et al., 2012)! Why is this the case? A review of the literature (Newton, 2015) suggests that one factor may be the proliferation of research that uses learning styles questionnaires and then concludes that learning styles are important and useful (without actually demonstrating this in a scientifically sound manner). Any well-meaning teacher who searches the literature is thus going to find many positive references to learning styles. Having said that, another survey did find that taking multiple classes about neuroscience reduced the belief in this idea, which is at least somewhat reassuring (Macdonald et al., 2017).
The thing is, the explanation for why we can’t conclude that learning styles are useful based on any of the published data is actually quite nuanced (Pashler, McDaniel, Rohrer, & Bjork, 2009). In order to understand why learning styles aren’t useful, teachers would need to invest quite a lot of time in understanding the research methods involved in the studies that claim to demonstrate their usefulness. So, what we need is more open-access, clear explanations of the research. These can include more traditional academic articles (Kirschner, 2017), but also popular science materials such as videos (https://ssec.si.edu/sending-learning-styles-out-style) and blog posts (www.learningscientists.org/blog/2017/5/25-1).
The most ironic thing about learning styles is that even if learning styles did matter for learning, a better idea would be to teach to students’ nonpreferred styles, in order to strengthen their weaknesses.
The other day, I (Yana) gave students in my First Year Experience Seminar a quiz that included true and false statements about learning and the brain. It wasn’t for points or anything – I was trying to gauge where the students were, and use the quiz as a jumping-off point for discussion. A lot of students said they believed this statement about the left and right brain. When I asked why they believed this, I received an alarming answer from one student: “My teacher told me.”
It is undeniably true that humans have two brain hemispheres. Also, there is scientific evidence (from brain-damaged patients as well as more modern neuroimaging techniques) to suggest that some types of tasks might use more resources from one hemisphere than the other. A good example of this is language, which tends to use more resources from the left hemisphere than the right (Springer & Deutsch, 1998). However, what is NOT true is that individuals can be “right-brained” or “left-brained,” or that the former is “creative” while the latter is “rational.” This is a misunderstanding of how the brain works: just because some tasks require more resources from one hemisphere, does not mean individuals differ in terms of their brains.
Just because some tasks require more resources from one hemisphere, does not mean individuals differ in terms of their brains.
Even if there were subtle differences between individuals at the level of brain hemispheres, there is no evidence that any of the “left/right brain questionnaires” that pop up frequently on social media would possibly pick up on these differences in any kind of meaningful way. Not to mention the complete lack of relevance of these potential subtle differences to education, contrary to what some for-profit training agencies will claim, e.g., http://kidgeniusapp.com/ – “an application for right brain training,” $199/year. Hence, many neuroscientists have come to call this the “left/right brain myth” (Goswami, 2006).
Another important point is that even if some tasks use more resources from one hemisphere than the other, there is no task that exclusively relies on only one hemisphere. As Dr. Melina Uncapher put it,
Every complex cognitive function is a result of the engagement of a network of multiple regions, distributed throughout both hemispheres, acting in coordinated ways. (2016)
Melina Uncapher
Why do people believe this idea? Actually, it’s not too different to the issue of learning styles. Since individuals tend to have preferences for certain types of tasks, some find it appealing to label people as “left-brain” or “right-brain” thinkers. For example, if someone likes math, they might be labeled a “left-brain” thinker, whereas if they are good at art they might be classified as a “right-brain” thinker. These categorizations do not serve us well, as they simply push people into boxes and can become self-fulfilling prophesies, preventing the development of novel interests.
You can read more about this misunderstanding in Melina Uncapher’s guest post on our blog (Uncapher, 2016).
It is important to emphasize that these misunderstandings do not arise simply because teachers are not paying attention to neuroscience or don’t want to learn. In fact, the opposite is true; teachers on the whole find neuroscience useful and important to understand, and find it interesting to explore and learn about (Pickering & Howard-Jones, 2007). However, there is a complex relationship between familiarity with neuroscience and the brain on a basic level, and accurate understanding of the nuances involved.
The relationship between interest in neuroscience and accurate understanding of learning is complex.
That is, an active interest in neuroscience unfortunately does not translate into the ability to distinguish between accurate and inaccurate statements about learning and the brain. On the contrary, multiple studies have found small but significant positive correlations between accurate general knowledge about the brain and belief in misunderstanding or “neuromyths” (Dekker et al., 2012; Gleichgerrcht et al., 2015).
In some cases, those most interested in neuroscience can be more susceptible to believing incorrect information.
That is, to some extent the more a non-expert is curious about neuroscience, the more likely they are to be led astray by what they read! Somewhat reassuringly, a recent study did show that actually being a neuroscientist drastically decreased the likelihood of believing in misunderstanding about the brain (Macdonald et al., 2017). That’s a relief!
Let’s say you’ve understood why it is not a good idea to put up too many decorations in a learning environment, but others believe that visual stimulation is important for learning, and don’t believe you. Unfortunately, simply providing people with accurate information is often not enough to combat misunderstandings, and can sometimes even create the opposite effect where people dig in to their inaccurate beliefs (Lewandowsky, Ecker, Seifert, Schwarz, & Cook, 2012; Pershan & Riley, 2017).
Shaming people for their beliefs is not an effective way to change minds.
Much research has gone into figuring out the most effective way to correct misunderstandings in an educational setting. One effective technique is called “refutational teaching,” and involves the following key stages: facts, refutation, and inoculation (Guzzetti, 2000; Lassonde, Kendeou, & O’Brien, 2016). That is, first of all, you need to start with the correct information (in this case, visually noisy environments lead to distraction and can decrease learning). After that, you would present the misunderstanding – for example, “some people believe that a visually stimulating environment can help children learn, and that this means that classrooms should include lots of bright decorations.” Now comes the refutational stage: explain why this is not true (see Chapter 9 for more about using “why” questions to increase understanding). Here you would bring in the evidence, referring back to the original factually correct statement. Finally, you can now “inoculate” your audience against the incorrect information, by reminding people of the types of incorrect arguments that tend to come up and how you can refute them. For instance, an argument for visual stimulation in the classroom might be “but children do not learn when they experience sensory deprivation.” In the inoculation phase, you would remind your audience that this claim only applies to extreme sensory deprivation, rather than lack of bright pictures in a classroom. You can read more about this method in Annette Taylor’s guest post on our blog (Taylor, 2017).
The most important thing is to focus as much as possible on the correct information, rather than repeating the misconception over and over again. That repetition could actually increase beliefs of the misunderstanding by causing it to feel more familiar (Lewandowsky et al., 2012; Skurnik, Yoon, Park, & Schwarz, 2005) and making it more memorable in the long run (Peter & Koch, 2016). That’s why we have made sure that as you continue to read this book, you will learn about the basic processes of perception, attention, and memory as they are currently understood by cognitive psychological scientists, along with learning strategies that have received decades of evidence to support their effectiveness.
Unfortunately, misconceptions about ways to improve learning are pervasive in education. For example, it is commonly believed that children in pre-schools need a highly stimulating environment in order to learn best, including many attractive visuals hung on the walls. The research actually shows that while children do need some stimulation, an overload can hinder learning. In this chapter, we discussed why this and other misconceptions have become so pervasive, and why we need to work hard to overcome them, and how we can best do that.
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