Ronaldo Mota – Chancellor of Estácio Group, educational executive, lecturer, member of the board of the Brazilian Association of Owners of Private Institutions of Higher Education, he writes about new technologies in education and innovative educational methodologies.
Educational genomics is expanding quickly in the last few years because of the advances in genetics and digital technologies, allowing the use of detailed information about the human genome and, consequently, to identificafy its contribution to particular traits that are related to educational processes.
Learning analytics is an educational approach based on systematic analysis of data associated to the student’s behavior using models, algorithms, simulations and statistical patterns (http://reitoronline.ig.com.br/index.php/2016/09/26/analitica-da-aprendizagem-e-parte-da-solucao/). Educational genomics, together with learning analytics, are keys for a personalized education, avoiding penalizing learners who do not fit traditional methodologies applied to average students.
The theme Genetics and human behavior has been always filled with fascination and suspicion. Increasingly, in Medicine (Farmacogenomics), and in Psychology of Education, we are learning that we can improve the quality of life for all by knowing better and respecting individuals’ particularities, including genetics. The fears about eugenic feelings and inappropriate readings of the recent scientific advances will always be present and the better way to avoid them is to know more about the subject itself. This is the best strategy which keeps us alert to the distinction between the good use of the new knowledge and its improper uses and incorrect interpretations.
Throughout the year 2016, publications in prestigious journals of the Nature group presented surprising results about the influence of genetics on different educational characteristics. Last May, in the largest genomic association study of behavioral traits, researchers identified 74 regions of the genome associated with years of school completion (http://www.nature.com/nature/journal/v533/n7604/full/nature17671.html).
Based on the results mentioned above, another group of authors raised the possibility of predicting part of 7, 11 and 17-year-old students’ achievements from the analysis of their respective DNAs (http://www.nature.com/mp/journal/vaop/ncurrent/full/mp2016107a.html). They calculated the polygenic scores associated with years of schooling and compared them with the results of national exams in Math and English using a sample of students from England, Wales and Northern Ireland. Surprisingly, such genetic scores explained 9% of variability in educational achievement of 16-year-old students.
In addition, the researchers demonstrated that predictive power over school performance is most evident at the extremes of the distribution of genetic scores. Learners with higher polygenic scores obtained grades between A and B and those with lower scores the grades were between B and C (https://www.rt.com/news/352123-dna-test-school-study/). Thus, such an approach may be even more relevant for students with less satisfactory academic performance, since it allows for early intervention through appropriate actions and educational policies.
It is important to emphasize that the results described above reflect the responses of a specific educational system and of a particular set of tests. In addition, they do not mean that a student’s overall academic performance is determined solely by genetics. However, polygenic scores, according to the authors, can provide, in advance, relevant information about the greater or lesser genetic predisposition of the child/adolescent to achieve low (or high) performance in such standardized tests. Thus, through personalized approaches, depending on specific circumstances, it is possible to change, in a timely manner, the efficiency of the learning process.
One important educational novelty of the contemporary world is that every learner learns in a unique way, demanding that we offer multiple educational paths so that each one can find the approach that best fit him/her. Educational genomics, together with learning analytics and general environmental and socio-demographic factors, make it possible to inaugurate a new scenario of lifelong education where everyone learns, learns all the time, and, especially, where each one is able to fully exploit his/her own characteristics and talents.