Advertisement

Understanding Learning for the Professions: How Theories of Learning Explain Coping with Rapid Change

  • Erno LehtinenEmail author
  • Kai Hakkarainen
  • Tuire Palonen
Chapter
Part of the Springer International Handbooks of Education book series (SIHE)

Abstract

Working life is increasingly in turbulence. Whole traditional professional fields disappear as new ones emerge. Within traditional professions technological and organisational development often means rapid changes in knowledge, skills, and working attitudes required from workers. All of this results in a challenge to develop vocational and professional education, and models of workplace learning that respond to these changes. The central questions are how new generations should be prepared for a future, at least partly unknown, working lives and how old workers should be supported in the necessary updating of their knowledge and skills during their work careers are added challenges. The aim of this chapter is to analyse how adequate the contemporary theories of learning are for dealing with these challenges.

Keywords

Change Learning theories Soft skills Transfer Expertise Knowledge acquisition Participation Sociocultural learning Conceptual change Knowledge transformation Activity theory Deliberate practice Cognitive theory 

References

  1. Achtenhagen, F. (1995). Fusing experience and theory—Sociopolitical and cognitive issues. Learning and Instruction, 5, 409–417.CrossRefGoogle Scholar
  2. Alexander, P. A., Schallert, D. L., & Reynolds, R. E. (2009). What is learning anyway? A topographical perspective considered. Educational Psychologist, 44, 176–192.CrossRefGoogle Scholar
  3. Anderson, R. A., Reder, L. M., & Simon, H. A. (1996). Situated learning and education. Educational Researcher, 25, 5–11.CrossRefGoogle Scholar
  4. Beach, K. (1999). Consequential transitions: A sociocultural expedition beyond transfer in education. Review of Research in Education, 24, 101–139.Google Scholar
  5. Bereiter, C. (2002). Education and mind in the knowledge age. Hillsdale: Erlbaum.Google Scholar
  6. Bereiter, C., & Scardamalia, M. (1993). Surpassing ourselves. An inquiry into the nature and implications of expertise. Chicago: Open Court.Google Scholar
  7. Billett, S. (2001). Knowing in practice: Re-conceptualising vocational expertise. Learning and Instruction, 11(6), 431–452.CrossRefGoogle Scholar
  8. Billett, S. (2003). Vocational curriculum and pedagogy: An activity theory perspective. European Educational Research Journal, 2(1), 6–21.CrossRefGoogle Scholar
  9. Bransford, J. D., & Schwartz, D. L. (1999). Rethinking transfer: A simple proposal with multiple implications. Review of Research in Education, 24, 61–100.Google Scholar
  10. Chi, M. T. H. (2008). Three types of conceptual change: Belief revision, mental model transformation, and categorical shift. In S. Vosniadou (Ed.), Handbook of research on conceptual change (pp. 61–82). Hillsdale: Erlbaum.Google Scholar
  11. Chi, M. T. H., Glaser, R., & Farr, M. F. (1988). The nature of expertise. Hillsdale: Erlbaum.Google Scholar
  12. Chi, M. T. H., Slotta, J. D., & de Leeuw, N. (1994). From things to processes: A theory of conceptual change for learning science concepts. Learning and Instruction, 4, 27–43.CrossRefGoogle Scholar
  13. Csikszentmihalyi, M., & Sawyer, K. (1995). Creative insight: The social dimension of a solitary moment. In R. Sternberg & J. E. Davidson (Eds.), The nature of insight (pp. 329–361). Cambridge, MA: The MIT Press.Google Scholar
  14. Davies, A., Fidler, D., & Gorbis, M. (2011). Future work skills 2020. Phoenix: Institute for the Future for University of Phoenix Research Institute.Google Scholar
  15. De Corte, E. (1999). On the road to transfer: An introduction. International Journal of Educational Research, 31, 555–559.CrossRefGoogle Scholar
  16. De Corte, E. (2003). Transfer as the productive use of acquired knowledge, skills, and motivations. Current Directions in Psychological Science, 12, 142–146.CrossRefGoogle Scholar
  17. Detterman, D. K. (1993). The case for prosecution: Transfer as an epiphenomenon. In D. K. Detterman & R. J. Sternberg (Eds.), Transfer on trial: Intelligence, cognition, and instruction (pp. 1–24). Norwood: Ablex Publishing Corporation.Google Scholar
  18. Detterman, D. K., & Sternberg, R. J. (Eds.). (1993). Transfer on trial: Intelligence, cognition, and instruction. Norwood: Ablex Publishing Corporation.Google Scholar
  19. Donald, M. (2000). The central role of culture in cognitive evolution: A reflection on the myth of the isolated mind. In L. P. Nucci, G. B. Saxe, & E. Turiel (Eds.), Culture, thought, and development (pp. 19–37). Mahwah: Erlbaum.Google Scholar
  20. Dreyfus, H., & Dreyfus, S. (1986). Mind over machine: The power of human intuition and expertise in the era of the computer. Oxford: Basil Blackwell.Google Scholar
  21. Duit, R. (1999). Conceptual change approaches in science education. In W. Schnotz, S. Vosniadou, & M. Carretero (Eds.), New perspectives on conceptual change (pp. 263–282). Killington: Elsevier Science.Google Scholar
  22. Efklides, A., Akilina, S., & Petropoulou, M. (1999). Feeling of difficulty: An aspect of monitoring that influences control. European Journal of Psychology of Education, 15, 461–476.CrossRefGoogle Scholar
  23. Engeström, Y. (1987). Learning by expanding. Helsinki: Orienta-Konsultit.Google Scholar
  24. Engeström, Y. (1999). Innovative learning in work teams: Analyzing cycles of knowledge creation in practice. In Y. Engeström, R. Miettinen, & R.-L. Punamäki (Eds.), Perspectives on activity theory (pp. 377–404). Cambridge: Cambridge University Press.CrossRefGoogle Scholar
  25. Ericsson, K. A. (1999). Creative expertise as superior reproducible performance: Innovative and flexible aspects of expert performance. Psychological Inquiry, 10, 329–333.CrossRefGoogle Scholar
  26. Ericsson, K. A. (2006). The influence of experience and deliberate practice on the development of superior expert performance. In K. A. Ericsson, N. Charness, P. Feltovich, & R. Hoffman (Eds.), The Cambridge handbook of expertise and expert performance (pp. 683–704). Cambridge, MA: Cambridge University Press.CrossRefGoogle Scholar
  27. Ericsson, K. A., & Lehmann, A. C. (1996). Experts and exceptional performance. Evidence on maximal adaptation on task constraints. Annual Review of Psychology, 47, 273–305.CrossRefGoogle Scholar
  28. Ericsson, K. A., Krampe, R. T., & Tesch-Römer, C. (1993). The role of deliberate practice in the acquisition of expert performance. Psychological Review, 100, 363–406.CrossRefGoogle Scholar
  29. Fallows, S., & Steven, C. (2000). Building employability skills into the higher education curriculum: A university-wide initiative. Education + Training, 42(2), 75–83.CrossRefGoogle Scholar
  30. Feltovich, P. J., Spiro, R. R., & Coulson, R. L. (1997). Issues of expert flexibility in contexts characterized by complexity and change. In P. J. Feltovich, K. M. Ford, & R. R. Hoffman (Eds.), Expertise in context (pp. 125–146). Menlo Park: AAAI/MIT Press.Google Scholar
  31. Flavell, J. H. (1979). Metacognition and cognitive monitoring. A new area of cognitive-developmental inquiry. American Psychologist, 34, 906–911.CrossRefGoogle Scholar
  32. Fodor, J. A. (1976). The language of thought. Hassocks: Harvester Press.Google Scholar
  33. Frenkel-Brunswik, E. (1948). Intolerance of ambiguity as an emotional perceptual personality variable. Journal of Personality, 18, 108–143.CrossRefGoogle Scholar
  34. Göbel, K. (1962/1992). On formally undecidable propositions of Principia Mathematica and related systems. New York: Dover.Google Scholar
  35. Greeno, J. G., Smith, D. R., & Moore, J. L. (1993). Transfer of situated learning. In D. K. Detterman & R. J. Sternberg (Eds.), Transfer on trial: Intelligence, cognition, and instruction (pp. 99–167). Norwood: Ablex Publishing Corporation.Google Scholar
  36. Gruber, H. (1981). Darwin on man: A psychological study of scientific creativity (2nd ed.). Chicago: The Chicago University Press.Google Scholar
  37. Gruber, H. (1995). Insight and affect in the history of science. In R. Sternberg & J. E. Davidson (Eds.), The nature of insight (pp. 397–431). Cambridge, MA: MIT.Google Scholar
  38. Gruber, H., Lehtinen, E., Palonen, T., & Degner, S. (2008). Persons in shadow: Assessing the social context of high ability. Psychology Science Quarterly, 50, 237–258.Google Scholar
  39. Hakkarainen, K., Paavola, S., & Lipponen, L. (2004a). From communities of practice to innovative knowledge communities. LLine – Lifelong Learning in Europe, 9, 2/2004, pp. 74–83.Google Scholar
  40. Hakkarainen, K., Palonen, T., Paavola, S., & Lehtinen, E. (2004b). Communities of networked expertise: Professional and educational perspectives. Amsterdam: Elsevier Science.Google Scholar
  41. Hakkarainen, K., Lallimo, J., Toikka, S., & White, H. (2011). Cultivating collective expertise within innovative knowledge-practice networks. In S. Ludvigsen, A. Lund, I. Rasmussen, & R. Säljö (Eds.), Learning across sites: New tools, infrastructures and practices (pp. 69–86). Earli series: New perspectives on learning and instruction. New York: Routledge.Google Scholar
  42. Harkin, J. (2004). How do professionals learn and develop? In D. Baume & P. Kahn (Eds.), Enhancing staff and educational development (pp. 132–153). London: RoutledgeFalmer.Google Scholar
  43. Hatano, G., & Inagaki, K. (1986). Two courses of expertise. In H. A. H. Stevenson & K. Hakuta (Eds.), Child development and education in Japan. New York: Freeman.Google Scholar
  44. Howe, M. (1999). Genius explained. Cambridge, MA: Cambridge University Press.Google Scholar
  45. Howells, J. (1999). Management and hybridization of expertise in network design. In R. Williams, W. Faulkner, & J. Fleck (Eds.), Exploring expertise: Issues and perspectives (pp. 265–285). London: Macmillan.Google Scholar
  46. Jerneck, A., Olsson, L., Barry, N., Anderberg, S., Baier, M., Clark, E., Hickler, T., Hornborg, A., Kronsell, A., Övbrand, E., & Persson, J. (2011). Structuring sustainability science. Sustainability Science, 6, 69–82.CrossRefGoogle Scholar
  47. Klein, J. T. (2010). A taxonomy of interdisciplinarity. In R. Frodeman, J. T. Klein, C. Mitcham, & J. B. Holbrook (Eds.), The Oxford handbook of interdisciplinarity (pp. 15–30). Oxford: Oxford University Press.Google Scholar
  48. Knorr-Cetina, K. (1999). Epistemic cultures: How the sciences make knowledge. Cambridge, MA: Harvard University Press.Google Scholar
  49. Knorr-Cetina, K. (2001). Objectual practices. In T. Schatzki, K. Knorr-Cetina, & E. Von Savigny (Eds.), The practice turn in contemporary theory (pp. 175–188). London: Routledge.Google Scholar
  50. Langley, P., & Jones, R. (1988). A computational model of scientific insight. In R. Sternberg (Ed.), The nature of creativity: Contemporary psychological perspectives (pp. 177–201). Cambridge: Cambridge University Press.Google Scholar
  51. Lave, J. (1988). Cognition in practice: Mind, mathematics, and culture in everyday life. New York: Cambridge University Press.CrossRefGoogle Scholar
  52. Lave, J., & Wenger, E. (1991). Situated learning: Legitimate peripheral participation. Cambridge, MA: Cambridge University Press.CrossRefGoogle Scholar
  53. Lehtinen, E. (2012). Learning of complex competences: On the need to coordinate multiple theoretical perspectives. In A. Koskensalo, J. Smeds, A. Huguet, & R. de Cillia (Eds.), Language: Competencies – Contact – Change (pp. 13–27). Berlin: LIT Verlag.Google Scholar
  54. Lehtinen, E., & Hannula, M. M. (2006). Attentional processes, abstraction and transfer in early mathematical development. In L. Verschaffel, F. Dochy, M. Boekaerts, & S. Vosniadou (Eds.), Instructional psychology: Past, present and future trends. Fifteen essays in honour of Erik De Corte (Advances in learning and instruction series, pp. 39–54). Oxford: Elsevier.Google Scholar
  55. Lenat, D. B., & Feigenbaum, E. A. (1991). On the thresholds of knowledge. Artificial Intelligence, 47, 185–250.CrossRefGoogle Scholar
  56. Limon, M. (2001). On the cognitive conflict as an instructional strategy for conceptual change: A critical appraisal. Learning and Instruction, 11, 357–380.CrossRefGoogle Scholar
  57. Linnenbrink, E. A., & Pintrich, P. R. (2003). Achievement goals and intentional conceptual change. In G. M. Sinatra & P. R. Pintrich (Eds.), Intentional conceptual change (pp. 347–374). Mahwah: Erlbaum.Google Scholar
  58. Lobato, J. (2012). The actor-oriented transfer perspective and its contributions to educational research and practice. Educational Psychologist, 47(3), 232–247.CrossRefGoogle Scholar
  59. Lobato, J., & Siebert, D. (2002). Quantitative reasoning in a reconceived view of transfer. Journal of Mathematical Behavior, 21, 87–116.CrossRefGoogle Scholar
  60. Markes, I. (2006). A review of literature on employability skills in engineering. European Journal of Engineering Education, 31(6), 637–650.CrossRefGoogle Scholar
  61. Mason, L. (2001). Introducing talk and writing for conceptual change: A classroom study. Learning and Instruction, 11, 305–329.CrossRefGoogle Scholar
  62. Merenluoto, K., & Lehtinen, E. (2004). Number concept and conceptual change: Towards a systemic model of the processes of change. Learning and Instruction, 14, 519–534.CrossRefGoogle Scholar
  63. Mikkilä-Erdmann, M. (2001). Improving conceptual change concerning photosynthesis through text design. Learning and Instruction, 11, 241–257.CrossRefGoogle Scholar
  64. Nonaka, I., & Takeuchi, H. (1995). The knowledge-creating company: How Japanese companies create the dynamics of innovation. New York: Oxford University Press.Google Scholar
  65. Ohlsson, S. (2009). Resubsumption: A possible mechanism for conceptual change and belief revision. Educational Psychologist, 44, 20–40.CrossRefGoogle Scholar
  66. Ohlsson, S. (2011). Deep learning: How the mind overrides experience. New York: Cambridge University Press.CrossRefGoogle Scholar
  67. Ohlsson, S., & Lehtinen, E. (1997). Abstraction and the acquisition of complex ideas. International Journal of Educational Research, 27, 37–48.CrossRefGoogle Scholar
  68. Paavola, S., & Hakkarainen, K. (2005). Three abductive solutions to the learning paradox – Instinct, inference, and distributed cognition. Studies in Philosophy and Education, 24, 235–253.CrossRefGoogle Scholar
  69. Paavola, S., Lipponen, L., & Hakkarainen, K. (2004). Modeling innovative knowledge communities: A knowledge-creation approach to learning. Review of Educational Research, 74, 557–576.CrossRefGoogle Scholar
  70. Palonen, T., Boshuizen, E., & Lehtinen, E. (2014). Promoting, assessing, recognizing and certifying lifelong learning: International perspectives and practices. In S. Billett, T. Halttunen, & M. Koivisto (Eds.), How expertise is created in emerging professional fields (pp. 131–149). Springer.Google Scholar
  71. Piaget, J. (1976). The grasp of consciousness. Cambridge, MA: Harvard University Press.Google Scholar
  72. Piaget, J. (1978). Success and understanding. London: Routledge & Kegan Paul.Google Scholar
  73. Posner, G., Strike, K., Hewson, P., & Gertzog, W. (1982). Accommodation of a scientific conception: Toward a theory of conceptual change. Science Education, 66, 211–227.CrossRefGoogle Scholar
  74. Powell, J. J. W., & Solga, H. (2008). Internationalization of vocational and higher education systems: A comparative-institutional approach. Discussion paper//Wissenschaftszentrum Berlin für Sozialforschung (WZB), Forschungsschwerpunkt Bildung, Arbeit und Lebenschancen, Abteilung Ausbildung und Arbeitsmarkt, No. SP I 2008–501.Google Scholar
  75. Pring, R. (2004). Philosophy of education. London: Continuum.Google Scholar
  76. Redecker, C., Leis, M., Leendertse, M., Punie, Y., Gijsbers, G., Kirschner, P., Stoyanov, S., & Hoogveld, B. (2010). The future of learning: New ways to learn. New skills for future jobs. Results from an online expert consultation. Luxembourg: Publications Office of the European Union. European Communities.Google Scholar
  77. Säljö, R. (2009). Learning, theories of learning, and units of analysis in research. Educational Psychologist, 44(3), 202–208.CrossRefGoogle Scholar
  78. Salomon, G., & Perkins, D. N. (1989). Rocky roads to transfer: Rethinking mechanisms of a neglected phenomenon. Educational Psychologist, 24, 113–142.CrossRefGoogle Scholar
  79. Sameroff, A. J., & Mackenzie, M. (2003). Research strategies for capturing transactional models of development: The limit of the possible. Development and Psychopathology, 15, 613–640.CrossRefGoogle Scholar
  80. Sfard, A. (1998). On two metaphors for learning and the dangers of choosing just one. Educational Researcher, 27(2), 4–13.CrossRefGoogle Scholar
  81. Sharpe, R. (2004). How do professionals learn and develop? In D. Baume & P. Kahn (Eds.), Enhancing staff and educational development (pp. 132–153). London: RoutledgeFalmer.CrossRefGoogle Scholar
  82. Simon, H. (1977). Models of discovery. Dordrecht: Reidel.CrossRefGoogle Scholar
  83. Simon, H. (2002). Achieving excellence in institutions. In M. Ferrari (Ed.), The pursuit of excellence through education (pp. 181–194). Mahwah: Erlbaum.Google Scholar
  84. Simonton, D. K. (2000). Creativity, cognitive, personal, developmental, and social aspects. American Psychologist, 55(1), 151–158.CrossRefGoogle Scholar
  85. Singley, M. K., & Anderson, J. R. (1989). The transfer of cognitive skill. Cambridge, MA: Harvard University Press.Google Scholar
  86. Skagestad, P. (1993). Thinking with machines: Intelligence augmentation, evolutionary epistemology, and semiotic. The Journal of Social and Evolutionary System, 16, 157–180.CrossRefGoogle Scholar
  87. Star, S. L. (1989). The structure of ill-structured solutions: Boundary objects and heterogeneous distributed problem solving. In L. Glasser & M. N. Huhns (Eds.), Distributed artificial intelligence (Vol. II). London: Pitman.Google Scholar
  88. Stark, R., Mandl, H., Gruber, H., & Renkl, A. (2002). Conditions and effects on example elaboration. Learning and Instruction, 12, 39–60.CrossRefGoogle Scholar
  89. Starker, J. L., & Ericsson, K. A. (Eds.). (2003). Expert performance in sports: Advances in research on sport expertise. Champaign: Human Kinetics.Google Scholar
  90. Stasz, C., & Brewer, D. J. (1999). Academic skills at work: Two perspectives (MDS-1193). Berkeley: National Center for Research in Vocational Education, University of California.Google Scholar
  91. Talwar, R., & Hancock, T. (2010, January). The shape of jobs to come: Possible new careers emerging from advances in science and technology (2010–2030). Final Report. Fast Future Research.Google Scholar
  92. Tillema, H., & Orland-Barak, L. (2006). Constructing knowledge in professional conversations: The role of beliefs on knowledge and knowing. Learning and Instruction, 16, 592–608.CrossRefGoogle Scholar
  93. Tynjälä, P., Nuutinen, A., Eteläpelto, A., Kirjonen, J., & Remes, P. (1997). The acquisition of professional expertise – A challenge for educational research. Scandinavian Journal of Educational Research, 41(3–4), 475–494.CrossRefGoogle Scholar
  94. Vosniadou, S. (1994). Capturing and modelling the process of conceptual change. Learning and Instruction, 4, 45–69.CrossRefGoogle Scholar
  95. Vosniadou, S. (1999). Conceptual change research: State of the art and future directions. In W. Schnotz, S. Vosniadou, & M. Carretero (Eds.), New perspectives on conceptual change (pp. 1–14). Amsterdam: Pergamon.Google Scholar
  96. Vosniadou, S. (Ed.). (2008). International handbook of research on conceptual change. New York: Routledge.Google Scholar
  97. Vygotsky, L. S. (1978). Mind in society: The development of higher psychological processes. Cambridge, MA: Harvard University Press.Google Scholar
  98. Weisberg, R. W. (2006). Models of expertise in creative thinking: Evidence from case studies. In K. A. Ericsson, N. Charness, P. J. Feltovich, & R. R. Hoffman (Eds.), The Cambridge handbook of expertise and expert performance (pp. 761–787). New York: Cambridge University Press.CrossRefGoogle Scholar
  99. Wertheimer, M. (1959/1968). Productive thinking. Northampton: Tavistock Publications.Google Scholar

Copyright information

© Springer Science+Business Media Dordrecht 2014

Authors and Affiliations

  1. 1.Centre for Learning Research and Department of Teacher EducationUniversity of TurkuTurkuFinland
  2. 2.Department of EducationUniversity of TurkuTurkuFinland

Personalised recommendations