- Show more
The study of neuroscience to understand the development of dyslexia
Neurosciences gather classical disciplines and novel interdisciplinary fields, with objectives oriented to the search for responses on the structure and functioning of the brain with the ultimate goal of understanding in depth the cognitive processes and behavior of the human being (Mora and Sanguinetti, 1994).
Varma (2008) propose educational neuroscience as a common discipline so that both neurosciences and education are united in order to integrate procedures with learning methods related to learning, from which a multidisciplinary synergistic model can be configured. While the data found in neuroscientific experiments could lead to suggestive hypotheses to test in the classroom, so also some of the questions emanating from the classrooms could be designed and investigated by neuroscientific tools. In this sense, the integration of functional neuroimaging is going with behavioral methods to address educational and learning aspects.
In recent years, contributions and theoretical models of neuropsychology have emerged, which has led to the appearance of educational neuroscience. It is an interdisciplinary scientific field that studies the interaction between neuronal, psychological and educational processes with the aim of improving the teaching and learning process in the student.
At present, we know that dyslexia has a genetic origin, is associated with a double deficit in relation to the acquisition of phonological consciousness and also a visual deficit. In that sense, neuroscience provides new methods to understand the learning and cognitive development of children with dyslexia. From the point of view of educational neuroscience. Therefore, how can we predict that a child will have problems with reading? The present study argues that through neuroscience we can anticipate and solve dyslexia problems in children.
A priori the relationship between neuroscience and education does not seem evident, since traditionally these two disciplines have not shared theoretical or methodological approaches. On the one hand, neuroscience is an empirical discipline, based on evidence, while education is fundamentally related to practice and has only recently begun to move towards a more empirical perspective. On the other hand, if we think that education is mainly concerned with learning, it should not be strange then to assume that those who study or work in this area receive information about how the brain works; Well, it is the most important organ for learning. Interestingly, research in various countries indicates that current teacher training programs do not include neuroscience content (Coch, 2018: 312).
The absence of neuroscience in the initial teacher training programs may be due to the fact that this is a relatively new discipline, since only in recent decades methods that make the study of the brain in real time have been developed during its functioning in short, We obtain knowledge about how the brain learns, how different stimuli processes, what factors contribute to its development, among other aspects.
Neuroscience findings are not easy to interpret, especially for those who have little knowledge of discipline or are motivated only by the sensationalism that it causes. For this reason, it is very common to find in the media erroneous data, misunderstood or incomplete, inappropriate generalizations of scientific discoveries, which has been called neuromitos (Dekker, Lee, Howard-Jones et al., 2012: 1). Because society in general and, particularly teachers, are eager for knowledge about neuroscience, media and social networks are then transformed into the main sources of information, delivering partial or inappropriate responses to different topics applied to the classroom. This presents a fundamental problem, since by accessing neuroscience knowledge that is not correct, in the long run the teachers acquire erroneous beliefs about how the brain learns, which can negatively impact the teaching action and consequently of the student.
Today there is broad consensus in which neuroscience can provide relevant information for education, and that this path is marked by interaction with other learning sciences (Howard-Jones, Ioannou, Bailey et al., 2018: 1). This is because a direct relationship between neuroscience and education is complex, since most current neuroscientific findings do not have a direct application in the classroom. This is how, for example, knowing that certain areas of the brain increase in size when an individual specializes in a certain task does not inform us about what pedagogical activity we should use to optimize learning, but it does allow us to infer that the work done by the Daily students have palpable effects on their brain, which finally manifests itself in good performance in a subject. The then use of this type of knowledge by teachers allows improving expectations about their students and, at the same time, generating better learning instances (Ansari König, Leask et al., 2017: 196).
In that context, from a neuroscientific perspective, teachers are the main responsible for generating changes in students’ brain through the teaching they develop in the classroom. In other words, teachers are fundamental actors when deciding on how the neuronal plasticity of their students can give rise to learning experiences that contribute or not to the type of training that is sought. So, if teachers have greater knowledge about neuroscience, their work in the classroom will be significantly enriched.
Among the most important subjects during the first years of schooling, reading and mathematics seem to excel, given their importance in the development of future knowledge. A series of neuroscience findings have given lights on how our brain processes language during reading, and performs arithmetic operations (IM, VARM, VARMA, 2017: 13). In particular, it has been possible to verify what are the neuronal correlates of reading and mathematics, which is useful to establish how our brain processes the information, taking into account the brain areas involved and the time in which the different types of information (phonology, semantics).
It has been discovered, for example, that learning to read generates changes in the neuronal structures of auditory, visual, and language processing in general (Dehaene, 2009: 25), which allows more precision to demonstrate the result of a certain methodology of teaching, dedicated learning time, or the materials used. In addition, neuroscience has allowed clarifying the causes of learning difficulties such as dyslexia and have documented the effects of interventions aimed at these difficulties in development at structural and functional level in the brain (IM, VARMA, VARMA, 2017: 7).
The acquisition of reading ability is a milestone in the child’s development. Reading is not a natural act: the brain must learn to read (Dehaene, 2007). While oral language is biologically determined, there are no "instructions" preferred to read. To learn to read it is necessary. The brain specializes in decoding a new type of visual stimuli and putting them in relation to linguistic knowledge. Thus, to become a competent reader, two great skills are necessary, the ability to recognize written words and the ability to understand texts, which constitute the two great components of reading
In fact, an important part of the activities carried out by children at the beginning of the mandatory school are directed to the RCGF domain. With practice, words recognition becomes fluid and becomes an automatic process, which does not require excessive attention, so that, how much less attention resources are dedicated to this low -level operation, the greater the ability to execute the processes higher level that lead to understanding (Laberge and Samuels, 1975). Precisely, readers with difficulties fail in the phonological transformation of visual signals and, as we will see, phonological processes are considered key to reading, so they present a particular difficulty for children with dyslexia.
In the alphabetical stage, which consists in learning the correspondence rules, usually at school. Children would use a phonological or sub -elexic, partial or complete strategy, which through practice is consolidated, so that they are capable of distinguishing letters or groups of letters quickly, segmenting words in their sounds and combining them to read the words increasingly fast, automatic and less effort. At this stage, learning difficulties such as dyslexia and digction begin to demonstrate.
[Bookmark: BBIB0275] Therefore, the more linguistic knowledge the prelectors have, the better their reading learning will be. At the same time, when teaching to read, all this knowledge must continue to be developed, as well as take them into account when designing intervention programs to improve reading, which must be based on scientific evidence. In that sense, today the idea that children with reading difficulties can present other problems predominates, mainly have linguistic processing deficits that, above all, imply deficits in phonological processes; These, in turn, seem to do with deficits in speech signal processing (Goswami, 2011). Some authors suggest that linguistic game, poetry, nannies, children
In conclusion, neuroscience has allowed us. In this way, learning in all its forms is possible throughout life, if enough time is dedicated. The main problem in the lack of adult learning lies in the short time they dedicate to learning, unlike children whose main activity is to learn.
We show that there are various neuroscientific contents today that can be very useful for teaching, particularly reading and mathematics, fundamental pillars to build knowledge in other subjects. In addition to better understanding how the brain allows reading and carrying out arithmetic calculations, we integrate the concept of neuronal plasticity, which is at the base of children’s learning. In that context, the presence of neuroscience and cognitive psychology in the initial teacher training programs would allow a real approach of empirical evidence in the development of training and teaching action.
Finally, neuroscience becomes a possibility of solution to contribute to the improvement of educational processes and the solution of problems related to the learning of children with dyslexia, through relevant methods that test the educational pedagogical efficacy. Oral and written language.
- Barrios-Tao, h. (2016). Neurosciences, education and sociocultural environment 1. Education and educators, 19 (3), 395-415. DOI: http: // dx.doi.org.Ezproxybib.PUCP.Edu.PE: 2048/10.5294/EDU.2016.19.3.5
- Campos, r. F., & Álvarez, L. G. (2019). Why should neuroscience be part of the initial teacher training? Synergies Chili, (15), 45-56,124-125. Retrieved from https: // search-proQuest-com.Ezproxybib.PUCP.Edu.PE/DOCVIEW/2266377326?ACCOUNT = 28391
- Coch, d. 2018. Reflections on Neuroscience in Teacher Education?. Peabody Journal of Education, No. 93 (3), P. 309-319
- Dehaene, s. (2007) Les Neuronos de la Lecture: The Nouvelle Science of the Lecture ET de Son Apprentissage. Paris: Odile Jacob.
- Dehaene, s. 2009. Reading in the Brain: The New Science of How We Read. New York: Penguin.
- Defior, s. (2014). Processes involved in the recognition of written words/processes involved in the collection of written words. Classroom, 20, 25-44,257. Retrieved from https: // search-proQuest-com.Ezproxybib.PUCP.Edu.PE/Docvieww/1665180205?ACCOUNT = 28391
- Dekker, s., They read. C., Howard-Jones, p., Jolles, j. 2012. Neuromyths in Education: Predicorts of MisConceptions Among Teachers. Educational Psychology, No. 3 (429), P. 1-8.
- Goswami, u. (2011) to temporary sampling Framework for developmental dyslexia. Trends in Cognitive Sciences, 15 (1), 3-10.
- Howard-Jones, p., Ioannou, k., Bailey, r., Prior, j., Yau, s. H., Jay, t. 2018. Applying the Science of Learning in the Classroom. Impact: Journal of the Chartered College of Teaching, No. 2, P. 6.
- Im, s., Varma, k., Varma, s. 2017. EXTENDING THE SEDUCTIVE ALLURE OF NEUROSCIENCE EXPLANATIONS EFECT TO POPULAR ARTICLES ABOUT EDUCATIONAL TOPICS. British Journal of Educational Psychology, No. 87 (4), P. 518-534.
- Laberge and Samuels (1975) Toward A Theory of Automatic Information Processing In Reading. Cognitive Psychology, 6, 293-323.
- Martínez González, A. AND., Piqueras Rodríguez, J. A., Delgado, b., & Garcia-Fernández, J. M. (2018). Neuroeducation: contributions from neuroscience to curricular competences. Publications of the Faculty of Education and Humanities of Melilla Campus, 48 (2), 23-34. DOI: http: // dx.doi.org.Ezproxybib.PUCP.Edu.PE: 2048/10.30827/publications.V48I2
- Mora, f. and Sanguinetti, to. M. (1994). Neuroscience Dictionary. Madrid: Editorial Alliance.
- M. Styles, l. Joy, d. Whitleypoetry and Childhood Trentham Books (2010).
- Varma, s., McCandliss, b. D. and Schwartz, D. L. (2008). Scientific and pragmatic challenges for bridging education and neuroscience. Educational Researcher, 37 (3), 140-152.