ثورة التعليم الشخصي الدقيق: تحديد المتطلبات المستقبلية لدمج علم الجينوم في الممارسات التعليمية
الملخص
لقد حقق الباحثون في مجال علم الجينوم اكتشافًا بالغ الأهمية، يتعلق بتحديد العلاقة بين جينوم معين وجوانب مختلفة من السلوك الإنساني، والقدرة المعرفية، واكتساب المهارات، والتحصيل الدراسي. تهدف هذه الدراسة، استنادًا إلى إسهامات الباحثين في التعليم الشخصي الدقيق وعلم الجينوم، إلى الكشف عن الإمكانات الواعدة للاستفادة من علم الجينوم في تطبيق التعليم الشخصي الدقيق، وتحديد أولويات المتطلبات المستقبلية التي تجب مراعاتها لتحقيق الدمج الناجح بين علم الجينوم والتعليم الشخصي الدقيق من منظور تربوي. وهذه المتطلبات لم تسبق مناقشتها إلا من المنظور الطبي في إطار الطب الدقيق، وغيره من التخصصات العلمية الأخرى، ولا توجد دراسة استهدفت تحديد المتطلبات المستقبلية التي تجب مراعاتها لتحقيق الدمج الناجح بين علم الجينوم والتعليم الشخصي الدقيق من منظور تربوي، وهذا ما يؤد على أهمية هذه الدراسة. وقد أبرزت الدراسة الأهمية البالغة لدمج علم الجينوم في النظم التعليمية، وتوصلت إلى أن التعليم الشخصي الدقيق المستند إلى علم الجينوم، يمثل المرحلة المستقبلية في تقديم الخدمات التعليمية، كما حددت أربع فئات من المتطلبات المستقبلية، تتضمن 22 متطلبًا، مع تحديد أولوية كل متطلب عند تطبيق التعليم الشخصي الدقيق المستند إلى علم الجينوم في الواقع العملى.
المقاييس
##plugins.themes.bootstrap3.article.details##
علم الجينومعلم الجينوم التربويالتعليم الشخصي الدقيقمستقبل التعليم
Asbury, K., & Plomin, R. (2013). G is for genes: The impact of genetics on education and achievement. http://doi.org/10.1002/9781118482766
Baron-Cohen, S., Murphy, L., Chakrabarti, B., Craig, I., Mallya, U., Lakatošová, S., ... & Warrier, V. (2014). A genome-wide association study of mathematical ability reveals an association at chromosome 3q29, a locus associated with autism and learning difficulties: A preliminary study. PloS One. 5(5), e96374. https//doi.org/10.1371/journal.pone.0096374
Cesarini, D., & Visscher, P. M. (2017). Genetics and educational attainment. npj Science of Learning. 2(4), 4. https//doi.org/10.1038/s41539-017-0005-6
Collins, F. S. (2010). Has the revolution arrived? Nature. 464(7289), 674–675. https//doi.org/10.1038/464674a
Conley, D. C., & Fletcher, J. M. (2017). The Genome Factor: What the Social Genomics Revolution Reveals about Ourselves, Our History, and the Future. Princeton University Press.
Cook, C. R., Kilgus, S. P., & Burns, M. K. (2018). Advancing the science and practice of precision education to enhance student outcomes. Journal of School Psychology. 66, 4–10. https//doi.org/10.1016/j.jsp.2017.11.004
Docherty, S. J., Kovas, Y., Petrill, S. A., & Plomin, R. (2010). Generalist genes analysis of DNA markers associated with mathematical ability and disability reveals shared influence across ages and abilities. BMC Genetics. 11(1), 61. https//doi.org/10.1186/1471-2156-11-61
Grigorenko, E. L. (2007). How Can Genomics Inform Education? Mind, Brain, and Education. 1(1), 20–27. https//doi.org/10.1111/j.1751-228X.2007.00001.x
Kovas, Y., & Malykh, S. (2016). Conclusion: Behavioural genomics and education. In Y. Kovas, S. Malykh, & D. Gaysina (Eds.). Behavioural genetics for education. (pp. 269–276). Palgrave Macmillan.
Kovas, Y., Haworth, C. M. A., Dale, P. S., & Plomin, R. (2007). The genetic and environmental origins of learning abilities and disabilities in the early school years. Monographs of the Society for Research in Child Development. 72(1), i–144. https//doi.org/10.1111/j.1540-5834.2007.00439.x
Kovas, Y., Tikhomirova, T., Selita, F., Tosto, M. G., & Malykh, S. (2016). How genetics can help education. In Y. Kovas, S. Malykh, & D. Gaysina (Eds.). Behavioural genetics for education. (pp. 1–23). Palgrave Macmillan. https//doi.org/10.1057/9781137437327_1
Kovas, Y., Voronin, I., Kaydalov, A., Malykh, S. B., Dale, P. S., & Plomin, R. (2013). Literacy and numeracy are more heritable than intelligence in primary school. Psychological Science 24(10), 2048–2056. https//doi.org/10.1177/0956797613486982
Krapohl, E., Rimfeld, K., Shakeshaft, N. G., Trzaskowski, M., McMillan, A., Pingault, J.-B., Asbury, K., Harlaar, N., Kovas, Y., Dale, P. S., & Plomin, R. (2014). The high heritability of educational achievement reflects many genetically influenced traits, not just intelligence. Proceedings of the National Academy of Sciences of the United States of America. 111(45), 16013–16018. https//doi.org/10.1073/pnas.1408777111
Krasa, N., & Shunkwiler, S. (2009). Number sense and number nonsense: Understanding the challenges of learning math. Brookes Publishing Company.
Kuch, D., Kearnes, M., & Gulson, K. (2020). The promise of precision: Datafication in medicine, agriculture, and education. Policy Studies. 59(1), 1–20. https//doi.org/10.1080/01442872.2020.1724384
Kung, J. T., & Gelbart, M. E. (2012). Getting a head start: The importance of personal genetics education in high schools. The Yale Journal of Biology and Medicine. 85(1), 87–92.
Lee, J. J. (2018). Gene discovery and polygenic prediction from a genome-wide association study of educational attainment in 1.1 million individuals. Nature Genetics. 49(8), 1195–1201. https//doi.org/10.1038/s41588-018-0147-3
Lian, A.-P., & Sangarun, P. (2017). Precision language education: A glimpse into a possible future. Journal of Language Studies. 17(4), 1–15. https//doi.org/10.17576/gema-2017-1704-01
Lu, O. H. T., Huang, A. Y. Q., Lin, A. J. Q., Ogata, H., & Yang, S. J. H. (2018). Applying learning analytics for the early prediction of students’ academic performance in blended learning. Educational Technology & Society. 21(2), 220–232.
Mazoue, J. G. (2013). The MOOC model: Challenging traditional education. EDUCAUSE Review Online. http://www.educause.edu/ero/article/mooc-model-challenging-traditional-education
McCarthy, M. I., & Mahajan, A. (2018). The value of genetic risk scores in precision medicine for diabetes. Expert Review of Precision Medicine and Drug Development, 3(3), 279–281. https://doi.org/10.1080/23808993.2018.1510732
Meaburn, E. L., Harlaar, N., Craig, I. W., Schalkwyk, L. C., & Plomin, R. (2008). Quantitative trait locus association scan of early reading disability and ability using pooled DNA and 100k SNP microarrays in a sample of 5760 children. Molecular Psychiatry, 13(7), 729–740. doi:10.1038/sj.mp.4002063
Nisselle, A., King, E., Terrill, B., et al. (2023). Investigating genomic medicine practice and perceptions amongst Australian non-genetics physicians to inform education and implementation. npj Genom. Med. 8(13). https://doi.org/10.1038/s41525-023-00360-1
Panofsky, A. (2015). What does behavioral genetics offer for improving education? Hastings Center Report. 45(S1), S43–S49. https//doi.org/10.1002/hast.498
Plomin, R. (2018). Blueprint: How DNA makes us who we are. The MIT Press.
Plomin, R., DeFries, J. C., Knopik, V. S., & Neiderhiser, J. M. (2013). Behavioral genetics (6th ed.). Worth Publishers.
Rahimzadeh, V., Knoppers, B. M.& Bartlett. G. (2020). Ethical, Legal, and Social Issues (ELSI) of Responsible Data Sharing Involving Children in Genomics: A Systematic Literature Review of Reasons. AJOB Empirical Bioethics. 11(4), 233-245. https//doi.org/10.1080/23294515.2020.1818875
Rietveld, C. A., et al. (2013). GWAS of 126,559 individuals identifies genetic variants associated with educational attainment. Science. 340(6139), 1467–1471. https//doi.org/10.1126/science.1235488
Sabatello, M. (2018). A genomically informed education system? Challenges for behavioral genetics. Journal of Law, Medicine & Ethics. 46(1), 130–144. https//doi.org/10.1177/1073110518766027
Söderqvist, S., Matsson, H., Peyrard-Janvid, M., Kere, J. & Klingberg, T. (2013). Polymorphisms in the dopamine receptor 2 gene region influence improvements during working memory training in children and adolescents. Journal of Cognitive Neuroscience. 26(1), 54-62. https//doi.org/10.1162/jocn_a_00478
Strianese, O., Rizzo, F., Ciccarelli, M., Galasso, G., D’Agostino, Y., Salvati, A., Del Giudice, C., Tesorio, P., & Rusciano, M. R. (2020). Precision and personalized medicine: How genomic approach improves the management of cardiovascular and neurodegenerative disease. Genes (Basel). 11(7), 747.
Thomas, M. S. C. (2013). Educational neuroscience in the near and far future: Predictions from the analogy with the history of medicine. Trends in Neuroscience and Education. 2, 23-26.
Thomas, M. S. C., et al. (2015). What Can the Study of Genetics Offer to Educators? Mind, Brain, and Education. 9(2),72-80. https//doi.org/I: 10.1111/mbe.12077
Whitley, K. V., Tueller, J. A., & Weber, K. S. (2020). Genomics education in the era of personal genomics: Academic, professional, and public considerations. International Journal of Molecular Sciences. 21(3), 768. https://doi.org/10.3390/ijms21030768
Williamson, B. (2019a). Digital policy sociology: software and science in data-intensive precision education. Critical Studies in Education. https//doi.org/10.1080/17508487.2019.1691030.
–––. (2019b). Personalized precision education and intimate data analytics: Code Acts in Education. https://codeactsineducation.wordpress.com/2018/04/16/personalized-precisioneducation/
Yang, S. J. H. (2019, June). Precision education: New challenges for AI in education [Keynote address]. The 27th International Conference on Computers in Education (ICCE 2019). http://index.j-ets.net/Published/24_1/ETS_24_1_08.pdf

https://orcid.org/0000-0002-1227-6624