Advertisement

International Review of Education

, Volume 62, Issue 3, pp 253–278 | Cite as

Training 21st-century workers: Facts, fiction and memory illusions

  • Helen Abadzi
Original Paper

Abstract

Technological achievements require complex skills for the workplace, along with creativity, communication, and critical thinking. To compete effectively in the global economy, governments must provide their citizens with relevant education and training. To help close the skills gap, international agencies often advise governments of developing countries to de-emphasise basic knowledge and focus instead on complex cognition and systemic improvements. However, the donors’ advice may be due to memory biases of highly educated people. Such training strategies would fail most students, because complex skills are built by combining and automatising shorter chains of thoughts or behaviours. An effective training process requires much practice, feedback and rearrangement of subcomponents over time. Execution of various tasks must become automatic and effortless to avoid using up too much of the very limited capacity of what is termed the “working memory”. Marketable skills are those skills which are fluently performed without excessive cognitive load. To provide complex skills for all, including non-cognitive skills, curricula should therefore first ensure detailed instruction and practice of basic components which can then be strung together and applied to new tasks. Policy advisers seem unaware of these scientific insights, so they are not taken into account. The article reviews the essential neurocognitive functions involved in the acquisition and execution of skills chains. The author concludes that to improve the skills of economically disadvantaged populations, donors and governments must acquire expertise and offer advice on the basis of cognitive science.

Keywords

skills “21st century” learning curves automaticity low-income countries vocational training “cognitive science” 

Résumé

Former la main-d’oeuvre du 21e siècle : faits, fiction et illusions de la mémoire – Les prouesses technologiques exigent des compétences complexes adaptées au poste de travail, parallèlement à la créativité, la communication et la pensée critique. En vue d’une concurrence efficace dans l’économie mondiale, les gouvernements doivent dispenser à leurs citoyens des programmes d’éducation et de formation pertinents. Désireuses de contribuer à combler le fossé des compétences, les agences internationales conseillent fréquemment aux gouvernements des pays en développement de désacraliser les savoirs de base pour valoriser la cognition complexe et les améliorations systémiques. Cependant, ce conseil des organismes de financement pourrait reposer sur une mémoire défaillante de personnes hautement instruites. De telles stratégies de formation feraient échouer la plupart des élèves, car les compétences complexes se construisent en associant et en automatisant de courtes chaînes de pensées ou de comportements. Un processus efficace de formation exige beaucoup de pratique, de retours d’information et la réorganisation d’éléments secondaires sur le long terme. L’exécution de diverses tâches doit devenir automatique et dénuée d’effort pour éviter de trop exploiter la capacité très limitée de ce qui est appelé la « mémoire de travail ». Les compétences commercialisables sont celles qui sont pratiquées couramment sans fatigue cognitive excessive. En vue de doter tous les individus de compétences complexes, y compris de compétences non cognitives, les programmes de formation devraient par conséquent dispenser en premier lieu une instruction et une pratique détaillées des composantes de base, qui peuvent ensuite être reliées ensemble et appliquées à de nouvelles tâches. Les conseillers en matière de politiques ne semblent pas être conscients de ces découvertes scientifiques, de sorte qu’ils ne les prennent pas en compte. L’auteure recense les principales fonctions neurocognitives impliquées dans l’acquisition et l’exécution des chaînes de compétences. Elle conclut que, s’ils entendent améliorer les compétences des groupes économiquement défavorisés, les organismes de financement et les gouvernements doivent acquérir une expertise et prodiguer des conseils fondés sur la science cognitive.

References

  1. Abadzi, H. (2012). Developing cross-language metrics for reading fluency measurement: Some issues and options. Global Partnership for Education working paper series on learning no. 6. Washington, DC: The World Bank.Google Scholar
  2. Abadzi, H. (2015). Training the 21st-century worker: Policy advice from the dark network of implicit memory. IBE working papers on curriculum issues, no 16. Geneva: UNESCO International Bureau of Education (IBE).Google Scholar
  3. Abadzi, H., Martelli, M., & Primativo, S. (2014). Explorations of creativity: A review for educators and policy making. Wise matters, 02. Doha (Qatar): World Innovation Summit for Education (WISE).Google Scholar
  4. Acedo, C., & Hughes, C. (2014). Principles for learning and competences in the 21st-century curriculum. Prospects, 44(4), 503–525.CrossRefGoogle Scholar
  5. Adams, A. V. (2008). Skills development in the informal sector of sub-Saharan Africa. Washington, DC: The World Bank.Google Scholar
  6. Agam, Y., & Sekuler, R. (2008). Geometric structure and chunking in reproduction of motion sequences. Journal of Vision, 8(1), 111–112.CrossRefGoogle Scholar
  7. Akyeampong, K. (2014). Reconceptualised life skills in secondary education in the African context. Lessons learnt from reforms in Ghana. International Review of Education, 60(2), 217–234.CrossRefGoogle Scholar
  8. Anderson, A., & Burggren, A. (2014). Cognitive and neurodevelopmental benefits of extended formula-feeding in infants: Re: Deoni et al. 2013. Neuroimage, 100, 706–709.CrossRefGoogle Scholar
  9. Bachman, H. J., Vortruba-Drzal, E., El Nokali, N., & Heatly, M. C. (2015). Opportunities for learning math in elementary school: Opportunities for SES disparities in procedural and conceptual math. American Educational Research Journal, 52(5), 894–923.CrossRefGoogle Scholar
  10. Bahrick, H. P., & Hall, L. K. (2005). The importance of retrieval failures to long-term retention: A metacognitive explanation of the spacing effect. Journal of Memory and Language, 52(4), 566–577.CrossRefGoogle Scholar
  11. Baldé, I. (2016). Sénégal : Projet dappui au renouveau des curricula – Un reméde contre les faibles performances des élèves [Senegal: Project in support of curricular reforms—A remedy against students’ weak performance]. All Africa, 27 January. http://fr.allafrica.com/stories/201601271331.html. Accessed 8 Feb 2016.
  12. Banerji, A., Cunningham, W., Fiszbein, A., King, E., Patrinos, H., Robalino, D., et al. (2010). Stepping up skills for more jobs and higher productivity. Report 55666. Washington, DC: The World Bank.Google Scholar
  13. Blom, A., & Saeki, H. (2011). Employability and skill set of newly graduated engineers in India. Policy research working paper 5640. Washington, DC: The World Bank.Google Scholar
  14. Calder Stegemann, K. J. (2014). Confessions of an educational psychologist. Frontiers in Psychology, 5, article 892. doi: 10.3389/fpsyg.2014.00892.
  15. Cook, L. G., Chapman, S. B., Elliott, A. C., Evenson, N. N., & Vinton, K. (2014). Cognitive gains from gist reasoning training in adolescents with chronic-stage traumatic brain injury. Frontiers in Neurology, 5, article 87. doi: 10.3389/fneur.2014.00087.
  16. Cooper, G., & Sweller, J. (1987). The effects of schema acquisition and rule automation on mathematical problem-solving transfer. Journal of Educational Psychology, 79(4), 347–362.CrossRefGoogle Scholar
  17. Crossman, E. R. (1959). A theory of the acquisition of speed-skill. Ergonomics, 2, 153–166.CrossRefGoogle Scholar
  18. DeYoung, C. G. (2011). Intelligence and personality. In R. J. Sternberg & S. B. Kaufman (Eds.), The Cambridge handbook of intelligence (pp. 711–737). New York: Cambridge University Press.CrossRefGoogle Scholar
  19. Fuchs, L. S., Fuchs, D., Hamlett, C. L., & Karns, K. (1998). High-achieving students’ interactions and performance on complex mathematical tasks as a function of homogeneous and heterogeneous pairings. American Educational Research Journal, 35(2), 227–268.CrossRefGoogle Scholar
  20. Gamino, J. F., Motes, M. M., Riddle, R., Reid Lyon, G., Spence, J. S., & Chapman, S. B. (2014). Enhancing inferential abilities in adolescence: New hope for students in poverty. Frontiers in Human Neuroscience, 8, article 924. doi: 10.3389/fnhum.2014.00924.
  21. Garron-Carrier, G., Boivin, M., Guay, F., Kovas, Y., Dionne, G., Lemelin, J.-P., et al. (2016). Intrinsic motivation and achievement in mathematics in elementary school: A longitudinal investigation of their association. Child Development, 87(1), 165–175.CrossRefGoogle Scholar
  22. Gaschler, R., Progscha, J., Smallbone, K., Ram, N., & Bilalić, M. (2014). Playing off the curve – Testing quantitative predictions of skill acquisition theories in development of chess performance. Frontiers in Psychology, 5, article 923. doi: 10.3389/fpsyg.2014.00923.
  23. Glennie, A. (2014). Out of the equation! Fired Apprentice girls who couldn’t do basic maths say: “We just do the glamour”. Daily Mail, 22 October. http://www.dailymail.co.uk/news/article-2803994/Apprentice-girls-couldn-t-basic-maths-just-glamour-say-fired-pair.html#ixzz3qOrjuMH4. Accessed 22 Oct 2014.
  24. Groener, Z. (2013). Skills development and structural change: Possibilities for and limitations of redressing structural racial inequalities in Africa. International Review of Education, 59(6), 723–749.CrossRefGoogle Scholar
  25. Guastello, S. J. (2001). Nonlinear dynamics in psychology. Discrete Dynamics in Nature and Society, 6(1), 11–29.CrossRefGoogle Scholar
  26. Guerra, N., Modecki, K., & Cunningham, W. (2014). Developing socialemotional skills for the labor market: The PRACTICE model. Policy research working paper 7123. Washington, DC: The World Bank.Google Scholar
  27. Hair, N. L., Hanson, J. L., Wolfe, B. L., & Pollak, S. D. (2015). Association of child poverty, brain development, and academic achievement. Journal of the American Medical Association (JAMA) Pediatrics, 169(9), 822–829.Google Scholar
  28. Hannon, V. (2012). New skills and capabilities are needed to thrive in this new world of work. http://www.wise-qatar.org/valerie-hannon-life-skills-education. Accessed 26 April 2016.
  29. Hayes, N., & Broadbent, D. (1988). Two modes of learning for interactive tasks. Cognition, 28(3), 249–276.CrossRefGoogle Scholar
  30. Huitt, W. (2003). The information processing approach to cognition. Educational psychology interactive. Valdosta, GA: Valdosta State University.Google Scholar
  31. Johnston, J., Loyalka, P., Chu, J., Song, Y., Yi, H., & Huang, X. (2016). The impact of vocational teachers on student learning in developing countries: Does enterprise experience matter? Comparative Education Review, 60(1), 131–150.CrossRefGoogle Scholar
  32. Kahneman, D. (2011). Thinking fast and slow. New York: Farrar, Strauss and Giroux.Google Scholar
  33. Kar, B. R., Rao, S. L., & Chandramouli, B. A. (2008). Cognitive development in children with chronic protein energy malnutrition. Behavioral and Brain Functions, 4(31), 31–36.CrossRefGoogle Scholar
  34. Kautz, T., Heckman, J. J., Diris, R., Ter Weel, B., & Borghans, L. (2015). Fostering and measuring skills: Improving cognitive and non-cognitive skills to promote lifetime success. Paris: OECD.Google Scholar
  35. Kirschner, P. A., Sweller, J., & Clark, R. E. (2006). Why minimal guidance during instruction does not work: An analysis of the failure of constructivist, discovery, problem-based, experiential, and inquiry-based teaching. Educational Psychologist, 41(2), 75–86.CrossRefGoogle Scholar
  36. Koopmans, G. M., & Pincus, D. (2009). Chaos and complexity in psychology: The theory of nonlinear dynamical systems. New York: Cambridge University Press.Google Scholar
  37. Lee, M. C. Y., Chow, J. Y., Komar, J., Tan, C. W. K., & Button, C. (2014). Nonlinear pedagogy: An effective approach to cater for individual differences in learning a sports skill. PLoS ONE, 9(8), e104744. doi: 10.1371/journal.pone.0104744.CrossRefGoogle Scholar
  38. Lumina and Gallup. (2013). What America needs to know about higher education redesign. https://www.luminafoundation.org/files/resources/2013-gallup-lumina-foundation-report.pdf. Accessed 24 Feb 2014.
  39. Mansel, W. (2014). (Not) picking a sideSkills v. knowledge. Waterloo Global Science Initiative. Waterloo, ON: Waterloo Global Science Initiative (WGSI). http://www.wgsi.org/blog/not-picking-side-skills-v-knowledge. Accessed 14 Feb 2016.
  40. Mayombe, C., & Lombard, A. (2015). How useful are skills acquired at adult non-formal education and training centres for finding employment in South Africa? International Review of Education, 61(5), 611–630.CrossRefGoogle Scholar
  41. Mehta, R. K., & Parasuraman, R. (2013). Effects of mental fatigue on the development of physical fatigue: A neuroergonomic approach. The Journal of the Human Factors and Ergonomics Society, 56(4), 645–656.CrossRefGoogle Scholar
  42. Mizuno, K., Tanaka, M., Yamaguti, K., Kajimoto, O., Kuratsune, H., & Watanabe, Y. (2011). Mental fatigue caused by prolonged cognitive load associated with sympathetic hyperactivity. Behavioral and Brain Functions. doi: 10.1186/1744-9081-7-17.Google Scholar
  43. Mosha, N., & Robertson, E. M. (2016). Unstable memories create a high-level representation that enables learning transfer. Current Biology, 26(1), 100–105.CrossRefGoogle Scholar
  44. Nyaradi, A., Li, J. H., Hickling, S., Foster, J., & Oddy, W. H. (2013). The role of nutrition in children’s neurocognitive development, from pregnancy through childhood. Frontiers of Human Neuroscience. doi: 10.3389/fnhum.2013.00097.Google Scholar
  45. Oates, T. (2014). Why textbooks count: A policy paper. Cambridge: University of Cambridge Local Examinations Syndicate.Google Scholar
  46. OECD (Organisation for Economic Cooperation and Development) (2013a). OECD Skills Outlook 2013: First results from the survey of adult skills. Paris: OECD.Google Scholar
  47. OECD (2013b). Skilled for life: Key findings from the survey of adult skills. Paris: OECD. https://www.oecd.org/site/piaac/SkillsOutlook_2013_ebook.pdf. Accessed 14 April 2016.
  48. OECD (2014). PISA 2012 results: Creative problem solving: Studentsskills in tackling real-life problems (Vol. V). Paris: OECD. http://www.oecd.org/pisa/keyfindings/pisa-2012-results-volume-v.htm. Accessed 14 April 2016.
  49. OECD (2015). Students, computers and learning: Making the connection. Paris: OECD Directorate for Education and Skills, OECD. http://www.keepeek.com/Digital-Asset-Management/oecd/education/students-computers-and-learning_9789264239555-en#page1. Accessed 14 April 2016.
  50. OECD (2016). Who are the low-performing students? In PISA in focus, no. 60. Paris: OECD. doi: 10.1787/5jm3xh670q7g-en.
  51. Pekrun, R., Goetz, T., Daniels, L. M., Stupnisky, R. H., & Perry, R. P. (2010). Boredom in achievement settings: Exploring control-value antecedents and performance outcomes of a neglected emotion. Journal of Educational Psychology, 102(3), 531–549.CrossRefGoogle Scholar
  52. Rahwan, I., Krasnoshtan, D., Shariff, A., & Bonnefon, J. F. (2014). Analytical reasoning task reveals limits of social learning in networks. Journal of the Royal Society – Interface,. doi: 10.1098/rsif.2013.1211.Google Scholar
  53. Reisberg, D. (2013). Cognition: Exploring the science of the mind (5th ed.). New York: Norton.Google Scholar
  54. Rennik-Egglestone, S. (2015). This is why traditional lectures are better than watching a video. Times Higher Education, 24 September. www.timeshighereducation.com/blog/why-traditional-lectures-are-better-watching-video. Accessed 14 April 2016.
  55. Reynolds, M. (2011). Critical thinking and systems thinking: Towards a critical literacy for systems thinking in practice. In C. P. Horvath & J. M. Forte (Eds.), Critical thinking (pp. 37–68). New York: Nova Science Publishers.Google Scholar
  56. Reynolds, N. P. (2014). Learning and knowledge: University and community perspectives in an international service-learning partnership. In Paper presented at the American Educational Research Association (AERA) conference, Philadelphia, PA, 3–11 April.Google Scholar
  57. Roegiers, X. (2006). LAPC, quest-ce que cest ? Approche par les compétences et pédagogie de lintégration expliquées aux enseignants [What is the APC? Competence approach and pedagogy of integration explained to teachers]. Paris: Editions Classiques d’Expression Française (EDICEF).Google Scholar
  58. Roegiers, X. (2008). LApproche par compétences en Afrique francophone : Quelques tendances [Competence approach in Francophone Africa? A few trends]. Geneva: UNESCO-IBE working papers on curriculum issues no. 7.Google Scholar
  59. Sané, M. V. (2015). L’approche par compétence au Sénégal : De la bonne intention aux défis de realisation [Competence approach in Senegal: From good intentions to the challenges of realisation]. LeralNet, 16 January. http://www.leral.net/L-approche-par-competence-au-Senegal-De-la-bonne-intention-aux-defis-de-realisation_a135346.html. Accessed 8 Feb 2016.
  60. Schupak, A. (2015). Award-winning teen explains Einstein’s special theory of relativity (in a way you can actually understand). CBS News, 9 November. http://www.cbsnews.com/news/breathrough-prize-2016-winning-teen-explains-einstein-special-theory-of-relativity/. Accessed 12 Feb 2016.
  61. Simons, D. J., & Chabris, C. F. (2011). What people believe about how memory works: A representative survey of the U.S. population. PLoS One, 6(8), e22757. doi: 10.1371/journal.pone.0022757.CrossRefGoogle Scholar
  62. Soler-Hampejsek, E., Kelly, C. A., Mensch, B. S., Heswett, P. C., & Grant, M. J. (2013). Retention of literacy and numeracy in rural Malawi: A longitudinal analysis. In Paper presented at the 57th annual conference of the Comparative and International Education Society (CIES), New Orleans, LA, 11 March.Google Scholar
  63. Spaull, N., & Taylor, S. (2015). Access to what? Creating a composite measure of educational quantity and educational quality for 11 African countries. Comparative Education Review, 59(1), 133–165.CrossRefGoogle Scholar
  64. Speelman, C. (2014). The acquisition of expertise in the classroom: Are current models of education appropriate? Frontiers in Psychology, 5(580), 1–3.Google Scholar
  65. Speelman, C., & Kirsner, K. (2005). Beyond the learning curve: The construction of mind. New York: Oxford University Press.CrossRefGoogle Scholar
  66. Squire, L. R. (2004). Memory systems of the brain: A brief history and current perspective. Neurobiology of Learning and Memory, 82(3), 171–177.CrossRefGoogle Scholar
  67. Steel, P. (2007). The nature of procrastination: A meta-analytic and theoretical review of quintessential self-regulatory failure. Psychological Bulletin, 133(1), 65–94.CrossRefGoogle Scholar
  68. Sun, R. (Ed.). (2008). The Cambridge handbook of computational psychology. New York: Cambridge University Press.Google Scholar
  69. Sun, R., Mathews, R. C., & Lane, S. M. (2007). Implicit and explicit processes in the development of mental skills: A theoretical interpretation with some practical implications for science instruction. In E. Vargios (Ed.), Educational psychology research focus (pp. 1–26). Hauppauge, NY: Nova Science Publishers.Google Scholar
  70. Sun, R., Slusarz, P., & Terry, C. (2005). The interaction of the explicit and the implicit in skill learning: A dual-process approach. Psychological Review, 112(1), 159–192.CrossRefGoogle Scholar
  71. Tenison, C., Fincham, J. M., & Anderson, J. R. (2016). Phases of learning: How skill acquisition impacts cognitive processing. Cognitive Psychology, 87, 1–28.CrossRefGoogle Scholar
  72. 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
  73. Tulving, E., & Thomson, D. M. (1973). Encoding specificity and retrieval processes in episodic memory. Psychological Review, 80(5), 352–373.CrossRefGoogle Scholar
  74. United Kingdom Forum for International Education and Training, UKFIET. (2015). Can stronger skills markets contribute to sustainable and decent work for all? In Symposium booklet; 13th UKFIET international conference on education and development. Cambridge: Cambridge Education. http://www.camb-ed.com/Portals/0/Documents/SYMPOSIUM%20Can%20stronger%20skills%20markets%20contribute%20UKFIET%202015.pdf. Accessed 14 April 2016.
  75. Van Vechten, D. (2013). Impact of home literacy environments on students from low socioeconomic status backgrounds. In Education Masters. Paper 248. Rochester, NY: St. John Fischer University, Fisher Digital Publications. http://fisherpub.sjfc.edu/education_ETD_masters/248. Accessed 14 April 2016.
  76. Wang, Y. (2012). Education in a changing world: Flexibility, skills, and employability. Washington, DC: The World Bank.Google Scholar
  77. Warrington, E., & Weiskrantz, L. (1982). Amnesia: A disconnection syndrome? Neuropsychologia, 20(3), 233–248.CrossRefGoogle Scholar
  78. Weis, L., Eisenhart, M., Cipollone, K., Stich, A. E., Nikischer, A. B., Hanson, J., et al. (2015). In the guise of STEM education reform: Opportunity structures and outcomes in inclusive STEM-focused high schools. American Educational Research Journal. doi: 10.3102/0002831215604045.Google Scholar
  79. World Bank (2010). Stepping up skills for more jobs and higher productivity. Publication no. 55566. Washington, DC: The World Bank.Google Scholar
  80. World Bank (2011). Strengthening skills and employability in Peru. Report 61699. Washington, DC: The World Bank.Google Scholar
  81. World Bank (2013). Framing the global landscape of entrepreneurship education and training programs. Education Department Human Development Network, Report 78983. Washington, DC: The World Bank.Google Scholar
  82. World Bank (2015). World development report. Washington, DC: The World Bank.Google Scholar
  83. Wulf, G., & Shea, C. H. (2002). Principles derived from the study of simple skills do not generalize to complex skill learning. Psychonomic Bulletin Review, 9(2), 185–211.CrossRefGoogle Scholar
  84. Wymbs, N. F., Bastian, A. J., & Celnik, A. J. (2016). Motor skills are strengthened through reconsolidation. Current Biology, 26(3), 338–343.CrossRefGoogle Scholar
  85. Yuksel, B. F., Oleson, K. B., Harrison, L., Peck, E. M., Afergan, D. A. Chang, R., et al. (2016). Learn piano with BACh: An adaptive learning interface that adjusts task difficulty based on brain state. In SIGCHI conference proceedings. www.eecs.tufts.edu/~byukse01/yukselCHI2016.pdf. Accessed 14 April 2016.

Copyright information

© Springer Science+Business Media Dordrecht and UNESCO Institute for Lifelong Learning 2016

Authors and Affiliations

  1. 1.University of Texas at ArlingtonArlingtonUSA

Personalised recommendations