Looking Into the Biological Basis of Learning: Debunking Neuromyths and Understanding Key Concepts from Mind, Brain and Education
by Nataly Bringas and Rocio Mendoza Fox,
Colegio F. D. Roosevelt, Lima, Peru
Over the last 20 years, neuroscientific research has set the basis for many subject matters in the field such as the learning brain and its relationship with memory, attention and emotional systems. These topics directly impact the educational field, as they represent the neurological basis of learning. Educators are more aware of psychological findings that impact teaching and learning, though neuroscientific findings are still difficult to put into practice, as not everything that comes from Neuroscience can be used in the classroom.
Mind, Brain and Education Science, also called Neuroeducation (Tokuhama-Espinosa, 2010), is a transdisciplinary field that joins three important disciplines: Psychology, Pedagogy and Neuroscience (See Figure 1). This new field provides us with a holistic view of an individual, as “without the whole picture, there is no whole child” (Perkins, 2008).
Figure 1: Neuroeducation: The Mind, Brain and Education Science (Tokuhama-Espinosa, 2010)
Mind, Brain and Education Science works under three main goals: (1) Research, in order to establish dynamic relationship between how we learn, how we educate, how the brain constructs new learning, and how the brain organizes and process information; (2) practice, related to the way we connect what we observe in the classroom with the neurobiological processes of learning in the brain; and finally (3) a structured policy that keeps encouraging the pursuit of neuroscientifically sustained beliefs that impact the educational field. This leads to a particular way to categorize neuroscientific information:
Information that is well established in the field
Information that is probable
Intelligent speculations
Popular misconceptions or oversimplifications, also known as neuromyths.
This last category, neuromyths, can be created from distortions of scientific facts, offspring of scientific hypothesis, or misinterpretation of experimental results which can continue to persist depending on how the media communicates these findings. Most of the time media presents a tendency to offer irrelevant information, which produces the omission of relevant information, creating and depending on sensationalism to sell these misconceptions (OECD, 2010).
In order to explore how prevalent are certain neuromyths among AASSA educators, last semester we started a research in this field. The purpose of this investigation is to explore teachers’ perceptions regarding the biological basis of learning. Results should be able to identify any misconceptions and/or neuromyths held by educators at AASSA in regards to findings in the Mind, Brain, Education field. This research gathered educators’ perceptions via an online survey that included a research validated survey by Dr. Paul Howard-Jones. Our research team is comprised of Rocio Mendoza Fox, Special Educational Needs Coordinator and Nataly Bringas Special Educational Needs teacher at Colegio F. D. Roosevelt (Lima, Peru), Daniel Riquelme-Uribe, Director General Centro I+D APLICAE (Santiago, Chile) and Mauricio Valenzuela Harrington, Director Laboratorio Neurociencias Universidad de Playa Ancha (Valparaíso, Chile). Currently, our team is in the process of analyzing results. We thank our AASSA Executive Director, Paul Poore, for his constant support through this process. In addition, we wish to extend our thanks to all AASSA educators who have participated in this research and invite you to continue reading this piece to debunk some popular neuromyths among educators that were part of the aforementioned survey.
We mostly use 10% of our brains.
It is very interesting that this is a proven myth to continue to thrive despite all the research findings in neuroscience. One reason could be the default belief: if we use only 10% of our brain, just imagine what could be done if we could manage to use more!
Origins of this myth might be due to Karl Lashley’s experiments in the 1930’s. In his studies of learning and memory, Lashley found that after removing large parts of cerebral cortex in rats, they were still able to relearn tasks such as finding an exit in mazes (Howard-Jones, 2010, Hardiman, 2012). This may be one of the studies that might have been exaggerated or misinterpreted to derive in this myth that supports that we do not use large portions of our brain.
This neuromyth might have also become popular when it was claimed that Albert Einstein mentioned it in a radio interview when he was encouraging people to use their brains more (Howard-Jones, 2010). However, there is no record of Einstein stating that we only use “10% of our brain”.
We need to understand we use all of our brain! Studies with functional imaging generally highlight only differences in brain activity that can be seen while performing certain tasks. The areas that are not “highlighted” in these images are still active, but do not respond to the task which is the focus of the study. Functional brain images used in media where only certain regions are highlighted might also contribute to perpetuate this myth.
Differences in hemispheric dominance (left brain, right brain) can help explain individual differences amongst learners.
The idea of “left-brain vs. right-brain” arose from research on hemispheric specialization of “split-brain” patients. The fact is: many processes are associated with more brain activity in one hemisphere or than the other. For example: language is regarded to be more in the left hemisphere – although it is in the right hemisphere for about a third of left-handed people (Howard-Jones, 2010). Gazzaniga, Ivry, and Mangun note that while each hemisphere does have specialization, the two hemispheres are more similar in function than different (Hardiman, 2012). Moreover, unless the corpus callosum is severed, both sides of the brain are involved in performing most tasks, including learning. As Howard-Jones (2010) concludes “the idea that we use the left side of our brain for one task and the other side of our brain for another is very far from the mark” ( p. 25).
In addition, and as explained before, static functional brain images may have given the impression that there are specific areas for certain types of tasks. We now understand that no part of the brain is ever inactive- blood flow is always occurring all over the brain and brain activity is happening to different degrees throughout the brain.
Dividing students into left-brained or right-brained takes the myth even further. Details of such categories, right brain or left brain, vary depending on educational programs or models. For example an “intuitive” or “creative” learner is considered right-brained and a “sequential” or “logical” one could be considered left-brained. It should be noted that there is no evidence that supports identifying students more left-brained or right-brained and even more, that directing instruction towards these categories (Hardiman, 2012, Howard-Jones 2010) has implications for learning (Coffield et. al. 2004 in Howard-Jones, 2010, Dekker et. al, 2012, Hardiman 2012).
Individual learners show preferences for the mode in which they receive information (e.g. visual, auditory, kinaesthetic) and individuals learn better when they receive information in their preferred learning style (e.g. visual, auditory, kinaesthetic)
According to Pashler et. al. (2008), there was no evidence found in terms of the relationship between children’s preferred learning style and the level of performance being any better from others who were taught in non-preferred style. The way this neuromyth spread in the educational field showed how educators’ enthusiasm took this misconception to the next level, by trying to match students’ “learning style” with teachers’ “teaching style”. It is important to consider that most neuromyths may not be harmful to students, though “suggesting that a child and teacher has “styles” that don’t coincide causes harm” (Tokuhama-Espinosa, 2014). “Learning preferences” is a concept that has started to used to talk about these prime students’ factors in education. However, prior knowledge, background in content, level of mastery skill, motivation, or learning difference are better means to differentiate. In 2004 Coffield et al. failed to find convincing information about the effectiveness of matching instruction style with students’ learning styles.
These are just some neuromyths that have been found true among educators through various research studies. It is important for educators to learn about neuromyths, learn to be cautious about “research findings” in popular media articles, and learn more about research findings in the Mind, Brain, and Education field to not perpetuate common neuromyths or create new ones. It is very important to learn more about what neuroscience findings suggest to make informed decisions in our craft. In regards to our investigation among educators in the AASSA region, our research team will continue to analyze data and share results when concluded. In the meantime, stay tuned for an upcoming blog that will give more information to debunk other neuromyths held among educators like “Children are less attentive after sugary drinks and snacks” or “environments that are rich in stimulus improve the brains of preschool children”. Any questions or comments please feel free to contact us!
Nataly Bringas email: nbringas@amersol.edu.pe
Rocio Mendoza Fox: romendoz@amersol.edu.pe or
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@nataly_bringas
@rociomendozafox
Works Cited
Coffield, F., Moseley, D., Hall, E., & Ecclestone, K. (2004). Learning styles and pedagogy in post 16 learning: a systematic and critical review. The Learning and Skills Research Centre.
Dekker S, Lee NC, Howard-Jones P and Jolles J (2012) Neuromyths in education: Prevalence and predictors of misconceptions among teachers. Front. Psychology 3:429. doi: 10.3389/fpsyg.2012.00429
Hardiman, M. (2012). The brain-targeted teaching model for 21st century schools. Thousand Oaks, CA: Corwin.
Howard-Jones, P. (2010). Introducing neuroeducational research. New York: NY: Routledge.
Howard-Jones, P. (2014). Neuroscience and education: myths and messages. In Nature Reviews Neuroscience (15 pp. 817–824). doi:10.1038/nrn3817
Howard-Jones, P., Franey, L., Mashmoushi, R., & Liao, Y. -. C. (2009). The neuroscience literacy of trainee teachers. In Neuroscience Literacy (pp. 1-39). Recovered from http://70.33.241.170/~neuro647/wp-content/uploads/2012/03/Literacy.pdf
Organisation for Economic Co-operation and Development Staff. (2008).Education at a Glance: OECD Indicators, 2008. OECD.
Pashler, Harold, et al. “Learning styles concepts and evidence.”Psychological science in the public interest 9.3 (2008): 105-119
Ritchhart, R., & Perkins, D. (2008). Making Thinking Visible. Educational Leadership.
Tokuhama-Espinosa, T. (2010). Mind, brain, and education science: A comprehensive guide to the new brain-based teaching. WW Norton & Company.
Tokuhama-Espinosa, T. (2014). Making Classrooms Better: 50 Practical Applications of Mind, Brain, and Education Science. WW Norton & Company.
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