Educating the adult brain: How the neuroscience of learning can inform educational policy

International Review of Education volume 60, pages99–122(2014)Cite this article

Abstract

The acquisition of new skills in adulthood can positively affect an individual’s quality of life, including their earning potential. In some cases, such as the learning of literacy in developing countries, it can provide an avenue to escape from poverty. In developed countries, job retraining in adulthood contributes to the flexibility of labour markets. For all adults, learning opportunities increase participation in society and family life. However, the popular view is that adults are less able to learn for an intrinsic reason: their brains are less plastic than in childhood. This article reviews what is currently known from neuroscientific research about how brain plasticity changes with age, with a particular focus on the ability to acquire new skills in adulthood. Anchoring their review in the examples of the adult acquisition of literacy and new motor skills, the authors address five specific questions: (1) Are sensitive periods in brain development relevant to learning complex educational skills like literacy? (2) Can adults become proficient in a new skill? (3) Can everyone learn equally effectively in adulthood? (4) What is the role of the learning environment? (5) Does adult education cost too much? They identify areas where further research is needed and conclude with a summary of principles for enhancing adult learning now established on a neuroscience foundation.

Résumé

Former le cerveau adulte : comment les neurosciences de l’apprentissage peuvent éclairer les politiques éducatives – L’acquisition de nouvelles compétences à l’âge adulte peut avoir une influence positive sur la qualité de la vie d’un individu, y compris son potentiel de revenus. Dans certaines situations, tels que l’alphabétisation dans les pays en développement, elle peut permettre de sortir de la pauvreté. Dans les pays industrialisés, la reconversion professionnelle à l’âge adulte contribue à la flexibilité des marchés du travail. Chez tous les adultes, l’apprentissage augmente leur participation à la société et à la vie familiale. Néanmoins, l’opinion générale veut que les adultes soient moins aptes à apprendre, et ce pour une raison intrinsèque : leur cerveau serait moins malléable que dans l’enfance. Les auteurs recensent les connaissances actuelles de la recherche neuroscientifique sur l’évolution de la flexibilité du cerveau avec l’âge, en particulier sur la capacité d’acquérir de nouvelles compétences à l’âge adulte. Appuyant leur examen sur des exemples de l’acquisition des compétences de base et fondamentales chez les adultes, les auteurs traitent cinq questions spécifiques : (1) Les périodes sensibles au cours du développement cérébral affectent-elles l’apprentissage de compétences éducatives complexes telles que l’alphabétisation ? (2) Les adultes peuvent-ils devenir chevronnés dans une nouvelle compétence ? (3) Tous les adultes apprennent-ils avec la même efficacité ? (4) Quel est le rôle de l’environnement éducatif ? (5) Les coûts de l’éducation des adultes sont-ils trop élevés ? Les auteurs identifient les domaines appelant des études plus poussées et concluent par une synthèse des principes valorisant l’apprentissage des adultes désormais fondé sur une base neuroscientifique.

This is a preview of subscription content, access via your institution.

Access options

Buy single article

Instant access to the full article PDF.

US$ 39.95

Tax calculation will be finalised during checkout.

References

  1. Abadzi, H. (2003). Improving adult literacy outcomes: Lessons from cognitive research for developing countries. Washington, D.C.: The World Bank.

    Book  Google Scholar 

  2. Abadzi, H. (2012). Can adults become fluent readers in newly learned scripts? Education Research International, 2012. Article ID 710785, doi: 10.1155/2012/710785.

  3. Abe, M., Schambra, H., Wassermann, E. M., Luckenbaugh, D., Schweighofer, N., & Cohen, L. G. (2011). Reward improves long-term retention of a motor memory through induction of offline memory gains. Current Biology, 21(7), 557–562.

    Article  Google Scholar 

  4. Aberg, M. A., Pedersen, N. L., Toren, K., Svartengren, M., Backstrand, B., Johnsson, T., et al. (2009). Cardiovascular fitness is associated with cognition in young adulthood. Proceedings of the National Academy of Sciences of the United States of America (PNAS), 106(49), 20906–20911.

    Article  Google Scholar 

  5. Adeladza, A. T. (2009). The influence of socio-economic and nutritional characteristics on child growth in Kwale district of Kenya. African Journal of Food, Agriculture, Nutrition and Development, 9(7), 1570–1590.

    Google Scholar 

  6. Andrews-Hanna, J. R., Snyder, A. Z., Vincent, J. L., Lustig, C., Head, D., Raichle, M. E., et al. (2007). Disruption of large-scale brain systems in advanced aging. Neuron, 56(5), 924–935.

    Article  Google Scholar 

  7. Avery, T., Sanchez, L. & Froud, K. (2013). Word reading automaticity in Spanish-speaking adult neoliterates: An ERP Study. Poster presented at Cognitive Neuroscience Society Annual Meeting, 13–16 April. San Francisco, USA.

  8. Barth, M., Hirsch, H. V. B., Meinertzhagen, I. A., & Heisenberg, M. (1997). Experience dependent developmental plasticity in the optic lobe of Drosophila melanogaster. Journal of Neuroscience, 17, 1493–1504.

    Google Scholar 

  9. Bavelier, D., Levi, D. M., Li, R. W., Dan, Y., & Hensch, T. K. (2010). Removing brakes on adult brain plasticity: From molecular to behavioral interventions. Journal of Neuroscience, 30(45), 14964–14971.

    Article  Google Scholar 

  10. Beilock, S. L., Carr, T. H., MacMahon, C., & Starkes, J. L. (2002). When paying attention becomes counterproductive: Impact of divided versus skill-focused attention on novice and experienced performance of sensorimotor skills. Journal of Experimental Psychology: Applied, 8(1), 6–16.

    Google Scholar 

  11. Bengtsson, S. L., Nagym, Z., Skare, S., Forsman, L., Forssberg, H., & Ullen, F. (2005). Extensive piano practicing has regionally specific effects on white matter development. Nature Neuroscience, 8(9), 1148–1150.

    Article  Google Scholar 

  12. Bhargava, A. (2001). Nutrition, health, and economic development: Some policy priorities. Food & Nutrition Bulletin, 22(2), 173–177.

    Google Scholar 

  13. Bherer, L., Kramer, A. F., Peterson, M. S., Colcombe, S., Erickson, K., & Becic, E. (2006). Testing the limits of cognitive plasticity in older adults: Application to attentional control. Acta Pyschologica, 123(3), 261–278.

    Article  Google Scholar 

  14. Birch, E. E., & Stager, D. R. (1996). The critical period for surgical treatment of dense congenital unilateral cataract. Investigative Ophthalmology & Visual Science, 37(8), 1532–1538.

    Google Scholar 

  15. BIS (Department for Business Innovation and Skills). (2009). Skills for life: Changing lives. London, UK: BIS.

    Google Scholar 

  16. Boyke, J., Driemeyer, J., Gaser, C., Buchel, C., & May, A. (2008). Training-induced brain structure changes in the elderly. The Journal of Neuroscience, 28(28), 7031–7035.

    Article  Google Scholar 

  17. Brans, R. G. H., Kahn, S., Schnack, H. G., van Baal, G. C., Posthuma, D., van Haren, Lepage, C., N. E. M., Lerch, J. P., Collins, L., Evans, A. C., Boomsma, D. I. & Hulshoff Pol, H. E. (2010). Brian plasticity and intellectual ability are influenced by shared genes. The Journal of Neuroscience, 30(16), 5519–1124.

  18. Brenowitz, E. A., & Beecher, M. D. (2005). Song learning in birds: Diversity and plasticity, opportunities and challenges. Trends in Neurosciences, 28(3), 127–132.

    Article  Google Scholar 

  19. Bus, A. G., & van Ijzendoorn, M. H. (1999). Phonological awareness and early reading: A meta-analysis of experimental training studies. Journal of Educational Psychology, 91(3), 403–414.

    Article  Google Scholar 

  20. Cabeza, R. (2002). Hemispheric asymmetry reduction in older adults: The HAROLD model. Psychology of Aging, 17(1), 85–100.

    Article  Google Scholar 

  21. Cannonieria, G. C., Bonilhab, L., Fernandesa, P. T., Cendesa, F., & Lia, L. M. (2007). Practice and perfect: length of training and structural brain changes in experienced typists. NeuroReport, 18(10), 1063–1066.

    Article  Google Scholar 

  22. Cantlon, J. F., Brannon, E. M., Carter, E. J., & Pelphrey, K. A. (2006). Functional imaging of numerical processing in adults and 4-y-old children. PLoS Biology, 4(5), e125.

    Article  Google Scholar 

  23. Chang, E. F., & Merzenich, M. M. (2003). Environmental noise retards auditory cortical development. Science, 300(5618), 498–502.

    Article  Google Scholar 

  24. Chen, E., Cohen, S., & Miller, G. E. (2010). How low socioeconomic status affects 2-year hormonal trajectories in children. Psychological Science, 21(1), 31–37.

    Article  Google Scholar 

  25. Constantino, R. (2005). Print environments between high and low socioeconomic status communities. Teacher Librarian, 32(3), 22–25.

    Google Scholar 

  26. Cotman, C. W., & Berctold, N. C. (2002). Exercise: A behavioural intervention to enhance brain health and plasticity. Trends in Neurosciences, 25(6), 295–301.

    Article  Google Scholar 

  27. Craik, F. I. M., & Bialystock, E. (2006). Cognition through the lifespan: Mechanisms of change. Trends in Cognitive Sciences, 10(3), 131–138.

    Article  Google Scholar 

  28. Cunha, F., Heckman, J. J., & Schennach, S. M. (2010). Estimating the technology of cognitive and non-cognitive skill formation. Econometrica, 78(3), 883–931.

    Article  Google Scholar 

  29. Dani, J., Burrill, C., & Demmig-Adams, B. (2005). The remarkable role of nutrition in learning and behavior. Nutrition & Food Science, 35(4), 258–263.

    Article  Google Scholar 

  30. Darmon, N., & Drewnowski, A. (2008). Does social class predict diet quality? American Journal of Clinical Nutrition, 87(5), 1107–1117.

    Google Scholar 

  31. Debas, K., Carriera, J., Orbana, P., Barakat, M., Lungua, O., Vandewallea, G., et al. (2010). Brain plasticity related to the consolidation of motor sequence learning and motor adaptation. Proceedings of the National Academy of Sciences of the United States of America (PNAS), 107(41), 17839–17844.

    Article  Google Scholar 

  32. Dehaene, S., & Cohen, L. (2007). Cultural recycling of cortical maps. Neuron, 56(2), 384–398.

    Article  Google Scholar 

  33. Dehaene, S., Pegado, F., Braga, L. W., Ventura, P., Nunes Filho, G., Jobert, A., et al. (2010a). How learning to read changes the cortical networks for vision and language. Science, 330(6009), 1359–1364.

    Article  Google Scholar 

  34. Dehaene, S., Pegado, F., Braga, L. W., Ventura, P., Nunes Filho, G., Jobert, A., et al. (2010b). How learning to read changes the cortical networks for vision and language. Science, 330(6009), 1359–1364.

    Article  Google Scholar 

  35. Dockrell, J., & Shield, B. (2012). The impact of sound field systems on learning and attention in elementary school classrooms. Journal of Speech, Language, and Hearing Research, 55, 1163–1176.

    Article  Google Scholar 

  36. Doyon, J., Korman, M., Morin, A., Dostie, V., Hadj Tahar, A., Benali, H., et al. (2009). Contribution of night and day sleep vs. simple passage of time to the consolidation of motor sequence and visuomotor adaptation learning. Experimental Brain Research, 195(1), 15–26.

    Article  Google Scholar 

  37. Draganski, B., Gaser, C., Busch, V., Schuierer, G., Bogdahn, U., & May, A. (2004). Neuroplasticity: Changes in grey matter induced by training. Nature, 427(6972), 311–312.

    Article  Google Scholar 

  38. Duflo, E., Dupas, P. & Kremer, M. (2008). Peer effects and the impact of tracking: Evidence from a randomized evaluation in Kenya. CEPR Discussion Paper No. DP7043. Available at the Social Sciences Research Network (SSRN): http://ssrn.com/abstract=1311167.

  39. Erickson, K. I., Prakash, R. S., Voss, M. W., Chaddock, L., Hu, L., Morris, K. S., et al. (2009). Aerobic fitness is associated with hip-pocampal volume in elderly humans. Hippocampus, 19(10), 1030–1039.

    Article  Google Scholar 

  40. Fischer, S., Hallschmid, M., Elsner, A. L., & Born, J. (2002). Sleep forms memory for finger skills. Proceedings of the National Academy of Sciences of the United States of America (PNAS), 99(18), 11987–11991.

    Article  Google Scholar 

  41. Floyer-Lea, A., & Matthews, P. M. (2005). Distinguishable brain activation networks for short- and long-term motor skill learning. Journal of Neurophysiology, 94(1), 512–518.

    Article  Google Scholar 

  42. Gervain, J., Vines, B. W., Chen, L. M., Seo, R. J., Hensch, T. K., Werker, J. F. & Young, A. H. (2013). Valporate reopens critical period learning of absolute pitch. Frontiers in Systems Neuroscience, 7(102). doi: 10.3389/fnsys.2013.00102.

  43. Greenberg, D., Ehri, L. C., & Perin, D. (1997). Are word-reading processes the same or different in adult literacy students and third-fifth graders matched for reading? Journal of Educational Psychology, 89(2), 262–275.

    Article  Google Scholar 

  44. Greenberg, D., Ehri, L. C., & Perin, D. (2002). Do adult literacy students make the same word-reading and spelling errors as children matched for word-reading age? Scientific Studies of Reading, 6(3), 221–243.

    Article  Google Scholar 

  45. Guo, G., & Harris, K. M. (2000). The mechanisms mediating the effects of poverty on children’s intellectual development. Demography, 37(4), 431–447.

    Article  Google Scholar 

  46. Hackman, D. A., & Farah, M. J. (2008). Socioeconomic status and the developing brain. Trends in Cognitive Sciences, 13(2), 65–73.

    Article  Google Scholar 

  47. Hanulíková, A., Dediu, D., Fang, Z., Bašnaková, J., & Huettig, F. (2012). Individual differences in the acquisition of a complex L2 phonology: A training study. Language Learning, 62(s2), 79–109.

    Article  Google Scholar 

  48. Heckman, J. J. (2006). Skill formation and the economics of investing in disadvantaged children. Science, 312(5782), 1900–1902.

    Article  Google Scholar 

  49. Heckman, J. J. (2007). The economics, technology and neuroscience of human capability formation. Proceedings of the National Academy of Sciences of the United States of America (PNAS), 104(33), 13250–13255.

    Article  Google Scholar 

  50. Ho, C., Lin, J., Wu, A. D., Udompholkul, P., & Knowlton, B. J. (2010). Contextual interference effects in sequence learning for young and older adults. American Psychological Association, 25(4), 929–939.

    Google Scholar 

  51. Howard-Jones, P. A., Washbrook, E. V., & Meadows, S. (2012). Neuroscience and the timing of educational investment. Developmental Cognitive Neuroscience, 2(s1), S18–S29.

    Article  Google Scholar 

  52. Hubel, D. H., & Weisel, T. N. (1970). The period of susceptibility to the physiological effects of unilateral eye closure in kittens. Journal of Physiology, 206(2), 419–436.

    Google Scholar 

  53. Huttenlocher, P. R. (2002). Neural plasticity: The effects of the environment on the development of the cerebral cortex. Cambridge, MA: Harvard University Press.

    Google Scholar 

  54. James, K.-H. (2010). Sensori-motor experience leads to changes in visual processing in the developing brain. Developmental Science, 13(2), 279–288.

    Article  Google Scholar 

  55. Jones, A. E., Ten Cate, C., & Slater, P. J. B. (1996). Early experience and plasticity of song in adult male zebra finches (Taeniopygia guttata). Journal of Comparative Psychology, 110, 354–369.

    Article  Google Scholar 

  56. Kannangara, T. S., Lucero, M. J., Gil-Mohapel, J., Drapala, R. J., Simpson, J. M., Christie, B. R., et al. (2010). Running reduces stress and enhances cell genesis in aged mice. Neurobiology of Aging, 32(12), 2279–2286.

    Article  Google Scholar 

  57. Kantak, S. S., Sullivan, K. J., Fisher, B. E., Knowlton, B. J., & Winstein, C. J. (2010). Neural substrates of motor memory consolidation depend on practice structure. Nature Neuroscience, 13(8), 923–925.

    Article  Google Scholar 

  58. Katzir, T., Kim, Y., Wolf, M., O’Brien, B., Kennedy, B., Lovett, M., et al. (2006). Reading fluency: The whole is more than the parts. Annals of Dyslexia, 56(1), 51–82.

    Article  Google Scholar 

  59. Kempermann, G., Fabel, K., Ehninger, D., Babu, H., Leal-Galicia, P., Garthe, A. & Wolf, S. A. (2010). Why and how physical activity promotes experience-induced brain plasticity. Frontiers in Neuroscience, 4, Article 189.

  60. Kempermann, G., Gast, D., & Gage, F. H. (2002). Neuroplasticity in old age: Sustained fivefold induction of hippocampal neurogenesis by long-term environmental enrichment. Annals of Neurology, 52(2), 135–143.

    Article  Google Scholar 

  61. Keuroghlian, A. S., & Knudsen, E. I. (2007). Adaptive auditory plasticity in developing and adult animals. Progress in Neurobiology, 82(3), 109–121.

    Article  Google Scholar 

  62. Knudsen, E. I. (2004). Sensitive periods in the development of the brain and behavior. Journal of Cognitive Neuroscience, 16(8), 1412–1425.

    Article  Google Scholar 

  63. Kuhl, P. K., Conboy, B. T., Coffey-Corina, S., Padden, D., Rivera-Gaxiola, M., & Nelson, T. (2008). Phonetic learning as a pathway to language: new data and native language magnet theory expanded (NLM-e). Proceedings of the Royal Society of London Series B—Biological Sciences, 363(1493), 979–1000.

    Google Scholar 

  64. Kuhl, P. K., Tsao, F.-M., & Liu, H.-M. (2003). Foreign-language experience in infancy: effects of short-term exposure and social interaction on phonetic learning. Proceedings of the National Academy of Sciences of the United States of America (PNAS), 100(15), 9096–9101.

    Article  Google Scholar 

  65. Lee, T. D., & Simon, D. (2004). Contextual interference. In A. M. Williams & N. Hodges (Eds.), Skill acquisition in sport: Research, theory and practice (pp. 29–44). London, UK: Routledge.

    Google Scholar 

  66. Mahncke, H. W., Bronstone, A., & Merzenich, M. M. (2006). Brain plasticity and functional losses in the aged: scientific bases for a novel intervention. Progress in Brain Research, 157, 81–109.

    Article  Google Scholar 

  67. Mareschal, D., Tolmie, A., & Butterworth, B. (2013). Educational neuroscience. Oxford: Wiley-Blackwell.

    Google Scholar 

  68. Martijn Jansma, J., Ramsey, N. F., Slagter, H. A., & Kahn, R. S. (2001). Functional anatomical correlates of controlled and automatic processing. Journal of Cognitive Neuroscience, 13(6), 730–743.

    Article  Google Scholar 

  69. McCandliss, B. D., Cohen, L., & Dehaene, S. (2003). The visual word form area: Expertise for reading in the fusiform gyrus. Trends in Cognitive Sciences, 7(7), 293–299.

    Article  Google Scholar 

  70. McCandliss, B. D., Fiez, J. A., Protopapas, A., Conway, M., & McClelland, J. L. (2002). Success and failure in teaching the [r]-[l] contrast to Japanese adults: Tests of a Hebbian model of plasticity and stabilization in spoken language perception. Cognitive, Affective and Behavioural Neuroscience, 2(2), 89–108.

    Article  Google Scholar 

  71. Mohsena, M., Mascie-Taylor, C. G. N., & Goto, R. (2010). Association between socio-economic status and childhood under-nutrition in Bangladesh: A comparison of possession score and poverty index. Public Health Nutrition, 13(10), 1498–1504.

    Article  Google Scholar 

  72. Moors, A., & De Houwer, J. (2006). Automaticity: A theoretical and conceptual analysis. Psychological Bulletin, 132(2), 297–326.

    Article  Google Scholar 

  73. Morin, A., Doyon, J., Dostie, V., Barakat, M., Hadj Tahar, A., Kormam, M., et al. (2008). Motor sequence learning increases sleep spindles and fast frequencies in post-training sleep. Sleep, 31(8), 1149–1156.

    Google Scholar 

  74. NCES (National Center for Education Statistics) (2004). International outcomes of learning in mathematics literacy and problem solving. PISA 2003 Results from the U.S. perspective. Washington, DC: NCES, Institute of Education Sciences.

  75. NCES (National Center for Education Statistics) (2006). The health literacy of America’s adults. Results from the 2003 National Assessment of Adult Literacy(NAAL). Washington, DC: NCES, Institute of Education Sciences.

  76. Neville, H. J., Mills, D. L., & Lawson, D. S. (1992). Fractionating language: Different neural subsystems with different sensitive periods. Cerebral Cortex, 2(3), 244–258.

    Article  Google Scholar 

  77. Nitsche, M. A., Cohen, L. G., Wassermann, E. M., Priori, A., Lang, N., Antal, A., et al. (2008). Transcranial direct current stimulation: State of the art 2008. Brain Stimulation, 1(3), 206–223.

    Article  Google Scholar 

  78. Park, D. C., & Reuter-Lorenz, P. (2009). The adaptive brain: Aging and neurocognitive scaffolding. Annual Review of Psychology, 60, 173–196.

    Article  Google Scholar 

  79. Pena, J. L., & DeBello, W. M. (2010). Auditory processing, plasticity, and learning in the barn owl. ILAR Journal, 51(4), 338–352.

    Article  Google Scholar 

  80. Rayner, K. (1998). Eye movements and information processing: 20 years of research. Psychological Bulletin, 124(3), 372–422.

    Article  Google Scholar 

  81. Russo, F. A., Windell, D. L., & Cuddy, L. L. (2003). Learning the “special note”: Evidence for a critical period for absolute pitch acquisition. Music Perception, 21, 119–127.

    Article  Google Scholar 

  82. Sabatini, J. P. (2002). Efficiency in word reading of adults: Ability group comparisons. Scientific Studies of Reading, 6(3), 267–298.

    Article  Google Scholar 

  83. Schneider, W., & Shiffrin, R. M. (1977). Controlled and automatic human information processing: I. Detection, search, and attention. Psychological Review, 84(1), 1–66.

    Article  Google Scholar 

  84. Scholz, J., Klein, M. C., Behrens, T. E. J., & Johansen-Berg, H. (2009). Training induces changes in white matter architecture. Nature Neuroscience, 12(11), 1370–1371.

    Article  Google Scholar 

  85. Sebastián, C., & Moretti, R. (2012). Profiles of cognitive precursors to reading acquisition. Contributions to a developmental perspective of adult literacy. Learning and Individual Differences, 22(5), 585–596.

    Article  Google Scholar 

  86. Shea, C. H., & Kohl, R. M. (1991). Composition of practice: Influence on the retention of motor skills. Research Quarterly for Exercise and Sport, 62, 187–195.

    Article  Google Scholar 

  87. Shield, B., & Dockrell, J. E. (2008). The effects of environmental and classroom noise on the academic attainments of primary school children. Journal of the Acoustical Society of America (JASA), 123(1), 133–144.

    Article  Google Scholar 

  88. Snowball, A., Tachtsidis, I., Popescu, T., Thompson, J., Delazer, M., Zamarian, L., et al. (2013). Long-term enhancement of brain function and cognition using cognitive training and brain stimulation. Current Biology, 23(11), 987–992.

    Article  Google Scholar 

  89. Stefan, K., Wycislo, M., & Classen, J. (2004). Modulation of associative human motor cortical plasticity by attention. Journal of Neurophysiology, 92(1), 66–72.

    Article  Google Scholar 

  90. Stevens, C., Lauinger, B., & Neville, H. (2009). Differences in the neural mechanisms of selective attention in children from different socioeconomic backgrounds: an event-related brain potential study. Developmental Science, 12(4), 634–646.

    Article  Google Scholar 

  91. Tanner, E. M., & Finn-Stevenson, M. (2002). Nutrition and brain development: Social policy implications. American Journal of Orthopsychiatry, 72(2), 182–193.

    Article  Google Scholar 

  92. Thomas, M. S. C. (2012). Brain plasticity and education. British Journal of Educational Psychology—Monograph Series II: Educational Neuroscience, 8, 142–156.

    Google Scholar 

  93. Thomas, M. S. C., Forrester, N. A., & Ronald, A. (2013). Modeling socio-economic status effects on language development. Developmental Psychology, 49(12), 2325–2343.

    Article  Google Scholar 

  94. Thomas, M. S. C., & Johnson, M. H. (2008). New advances in understanding sensitive periods in brain development. Current Directions in Psychological Science, 17(1), 1–5.

    Article  Google Scholar 

  95. Thomas, M. S. C., & Knowland, V. (2009). Sensitive periods in brain development: Implications for education policy. European Psychiatric Review, 2(1), 17–20.

    Google Scholar 

  96. Tomassini, V., Jbabdi, S., Kincses, Z. T., Bosnell, R., Douaud, G., Pozzilli, C., et al. (2011). Structural and functional bases for individual differences in motor learning. Human Brain Mapping, 32(3), 494–508.

    Article  Google Scholar 

  97. Torgesen, J. K., Rashotte, C. A., & Alexander, A. W. (2001). Principles of fluency instruction in reading: Relationships with established empirical outcomes. In M. Wolf (Ed.), Dyslexia, fluency and the brain. Timonium, MD: York Press.

    Google Scholar 

  98. Tricomi, E., Delgado, M. R., McCandliss, B. D., McClelland, J. L., & Feiz, J. A. (2006). Performance feedback drives caudate activation in a phonological learning task. Journal of Cognitive Neuroscience, 18(6), 1029–1043.

    Article  Google Scholar 

  99. UNESCO (United Nations Educational, Scientific and Cultural Organisation). (2004). The plurality of literacy and its implications for policies and programmes. Paris: UNESCO Education Sector.

    Google Scholar 

  100. Unsworth, N., & Engle, R. W. (2005). Individual differences in working memory capacity and learning: Evidence from the serial reaction time task. Memory and Cognition, 33(2), 213–220.

    Article  Google Scholar 

  101. Valenzuela, M., & Sachdev, P. (2009). Can cognitive exercise prevent the onset of dementia? Systematic review of randomized clinical trials with longitudinal follow-up. American Journal of Geriatric Psychiatry, 17(3), 179–187.

    Article  Google Scholar 

  102. Walker, M. P., Brakefield, T., Morgan, A., Hobson, J. A., & Stickgold, R. (2002). Practice with sleep makes perfect: Sleep-dependent motor skill learning. Neuron, 35, 205–211.

    Article  Google Scholar 

  103. Wang, L. C. (2011). Shrinking classroom age variance raises student achievement: Evidence from developing countries. Washington, DC: World Bank, Development Research Group, Human Development and Public Services Team.

    Book  Google Scholar 

  104. Wishart, L. R., Lee, T. D., Cunningham, S. J., & Murdoch, J. E. (2002). Age-related differences and the role of augmented visual feedback in learning a bimanual coordination pattern. Acta Psychologia, 110(2–3), 247–263.

    Article  Google Scholar 

  105. Zelazo, P. D. (2004). The development of conscious control in childhood. Trends in Cognitive Sciences, 8(1), 12–17.

    Article  Google Scholar 

  106. Zhou, X., Panizzutti, R., de Villers-Sidani, E., Madeira, C., & Merzenich, M. M. (2011). Natural restoration of critical period plasticity in the juvenile and adult primary auditory cortex. The Journal of Neuroscience, 31(15), 5625–5634.

    Article  Google Scholar 

Download references

Acknowledgments

This research was sponsored by the BBK-UCL-IOE Centre for Educational Neuroscience (http://www.educationalneuroscience.org.uk/). The work was supported by UK Economic and Social Research Grant RES-062-23-2721 and a postdoctoral fellowship from City University London. The authors would like to thank Helen Abadzi for her advice and encouragement in the writing of this article.

Author information

Affiliations

  1. City University London, Northampton Square, London, EC1V 0HB, UK

    Victoria C. P. Knowland

  2. Centre for Educational Neuroscience and Birkbeck College, University of London, Malet Street, London, WC1E 7HX, UK

    Michael S. C. Thomas

Authors
  1. Victoria C. P. Knowland
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Michael S. C. Thomas
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Michael S. C. Thomas.

Rights and permissions

Reprints and Permissions

About this article

Verify currency and authenticity via CrossMark

Cite this article

Knowland, V.C.P., Thomas, M.S.C. Educating the adult brain: How the neuroscience of learning can inform educational policy. Int Rev Educ 60, 99–122 (2014). https://doi.org/10.1007/s11159-014-9412-6

Download citation

Keywords

  • Lifelong learning
  • Adult education
  • Adult leaning
  • Adult literacy
  • Brain plasticity
  • Sensitive periods
  • Educational neuroscience