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Understanding the Mind

  • Lina Markauskaite
  • Peter Goodyear
Chapter
Part of the Professional and Practice-based Learning book series (PPBL, volume 14)

Abstract

In this chapter we contend that research in and for education has suffered from a tendency to emphasise one aspect of human capability at the expense of others. For example, some research traditions give a central place to human cognition and marginalise the social; other bodies of research focus on the brain, while marginalising human experience. This chapter uses some recent ideas on grounded cognition to show how it is possible, and necessary, to connect mind, brain, body, culture and environment in providing satisfactory explanations of how people get things done. This also gives us a better way of talking about relations between the kinds of codified knowledge encountered in formal instruction and the experiential knowledge people develop in the rest of life. We argue that a better understanding of relations between codified and experiential knowledge helps resolve some problems involved in conceptual change and in understanding the status of threshold concepts.

Keywords

Mind Grounded cognition Actionable knowledge Conceptual change Threshold concepts 

References

  1. Anderson, J. R. (1983). The architecture of cognition. Cambridge, MA: Harvard University Press.Google Scholar
  2. Anderson, M. L. (2003). Embodied cognition: A field guide. Artificial Intelligence, 149(1), 91–130. doi: 10.1016/s0004-3702(03)00054-7.CrossRefGoogle Scholar
  3. Anderson, J. R., Reder, L. M., & Simon, H. A. (1996). Situated learning and education. Educational Researcher, 25(4), 5–11. doi: 10.3102/0013189x025004005.CrossRefGoogle Scholar
  4. Atkinson, R. C., & Shiffrin, R. M. (1968). Human memory: A proposed system and its control processes. In K. W. Spence & J. T. Spence (Eds.), The psychology of learning and motivation (Vol. 2, pp. 89–195). New York, NY: Academic Press.Google Scholar
  5. Barnett, R. (2004). Learning for an unknown future. Higher Education Research & Development, 23(3), 247–260.CrossRefGoogle Scholar
  6. Barrows, H. S., & Tamblyn, R. M. (1980). Problem-based learning: An approach to medical education. New York, NY: Springer.Google Scholar
  7. Barsalou, L. W. (1999). Perceptual symbol systems. Behavioral and Brain Sciences, 22, 577–609.Google Scholar
  8. Barsalou, L. W. (2003). Situated simulation in the human conceptual system. Language and Cognitive Processes, 18(5–6), 513–562. doi: 10.1080/01690960344000026.CrossRefGoogle Scholar
  9. Barsalou, L. W. (2008). Grounded cognition. Annual Review of Psychology, 59, 617–645. doi: 10.1146/annurev.psych.59.103006.093639.CrossRefGoogle Scholar
  10. Barsalou, L. W. (2009). Situating concepts. In P. Robbins & M. Aydede (Eds.), The Cambridge handbook of situated cognition (pp. 236–263). Cambridge, MA: Cambridge University Press.Google Scholar
  11. Barsalou, L. W. (2010). Grounded cognition: Past, present, and future. Topics in Cognitive Science, 2(4), 716–724. doi: 10.1111/j.1756-8765.2010.01115.x.CrossRefGoogle Scholar
  12. Barsalou, L. W., Breazeal, C., & Smith, L. (2007). Cognition as coordinated non-cognition. Cognitive Processing, 8(2), 79–91. doi: 10.1007/s10339-007-0163-1.CrossRefGoogle Scholar
  13. Barsalou, L. W., Kyle Simmons, W., Barbey, A. K., & Wilson, C. D. (2003). Grounding conceptual knowledge in modality-specific systems. Trends in Cognitive Sciences, 7(2), 84–91. doi: 10.1016/s1364-6613(02)00029-3.CrossRefGoogle Scholar
  14. Barsalou, L. W., & Prinz, J. J. (1997). Mundane creativity in perceptual symbol systems. In T. B. Ward, S. M. Smith, & J. Vaid (Eds.), Creative thought: An investigation of conceptual structures and processes (pp. 267–307). Washington, DC: American Psychological Association.CrossRefGoogle Scholar
  15. Bereiter, C. (1991). Implications of connectionism for thinking about rules. Educational Researcher, 20(3), 10–16.CrossRefGoogle Scholar
  16. Bereiter, C. (2002). Education and mind in the knowledge age. Mahwah, NJ: Lawrence Erlbaum Associates.Google Scholar
  17. Billett, S. (1996). Situated learning: Bridging sociocultural and cognitive theorising. Learning and Instruction, 6(3), 263–280.CrossRefGoogle Scholar
  18. Boivin, N. (2008). Material cultures, material minds: The impact of things on human thought, society and evolution. Cambridge, UK: Cambridge University Press.Google Scholar
  19. Boud, D., & Feletti, G. (Eds.). (1997). The challenge of problem based learning (2nd ed.). London, UK: Kogan Page.Google Scholar
  20. Bransford, J. D., Brown, A. L., & Cocking, R. R. (Eds.). (1999). How people learn: Brain, mind, experience, and school. Washington, DC: National Academy Press.Google Scholar
  21. Brookfield, S. (1986). Understanding and facilitating adult learning. Milton Keynes, UK: Open University Press.Google Scholar
  22. Brooks, R. A. (1991). Intelligence without representation. Artificial Intelligence, 47, 139–159.CrossRefGoogle Scholar
  23. Brooks, R. A., & Stein, L. A. (1994). Building brains for bodies. Autonomous Robots, 1, 7–25.CrossRefGoogle Scholar
  24. Carmichael, P. (2012). Tribes, territories and threshold concepts: Educational materialisms at work in higher education. Educational Philosophy and Theory, 44(sup1), 31–42. doi: 10.1111/j.1469-5812.2010.00743.x.CrossRefGoogle Scholar
  25. Chi, M. T. H. (2005). Commonsense conceptions of emergent processes: Why some misconceptions are robust. Journal of the Learning Sciences, 14(2), 161–199.CrossRefGoogle Scholar
  26. Chi, M. T. H., De Leeuw, N., Chiu, M.-H., & Lavancher, C. (1994). Eliciting self-explanations improves understanding. Cognitive Science, 18(3), 439–477. doi: http://dx.doi.org/  10.1016/0364-0213(94)90016-7
  27. Chi, M. T. H., & Ohlsson, S. (2005). Complex declarative learning. In K. J. Holyoak & R. G. Morrison (Eds.), The Cambridge handbook of thinking and reasoning (pp. 371–400). Cambridge, MA: Cambridge University Press.Google Scholar
  28. Chi, M. T. H., & Roscoe, R. (2002). The processes and challenges of conceptual change. In M. Limon & L. Mason (Eds.), Reconsidering conceptual change: Issues in theory and practice (pp. 3–27). Dordrecht, The Netherlands: Kluwer.CrossRefGoogle Scholar
  29. Clark, A. (1999). Embodied, situated and distributed cognition. In W. Bechtel & G. Graham (Eds.), A companion to cognitive science (pp. 506–517). Oxford, UK: Basil Blackwell.Google Scholar
  30. Clark, R. C. (2008). Building expertise: Cognitive methods for training and performance improvement (3rd ed.). San Francisco, CA: John Wiley & Sons.Google Scholar
  31. Clark, A. (2011). Supersizing the mind: Embodiment, action and cognitive extension. Oxford, UK: Oxford University Press.Google Scholar
  32. Clark, A. (2012). Embodied, embedded, and extended cognition. In K. Frankish & W. M. Ramsey (Eds.), The Cambridge handbook of cognitive science (pp. 275–291). New York, NY: Cambridge University Press.CrossRefGoogle Scholar
  33. Cole, M. (1996). Cultural psychology. Cambridge, MA: Harvard University Press.Google Scholar
  34. Cole, M., Engeström, Y., & Vasquez, O. A. (Eds.). (1997). Mind, culture, and activity: Seminal papers from the laboratory of comparative human cognition. Cambridge, UK: Cambridge University Press.Google Scholar
  35. Colley, A., & Beech, J. (Eds.). (1989). Acquisition and performance of cognitive skills. Chichester, UK: John Wiley & Sons.Google Scholar
  36. Dall’Alba, G. (2009). Learning to be professionals. Dordrecht, The Netherlands: Springer.CrossRefGoogle Scholar
  37. Dall’Alba, G., & Barnacle, R. (2007). An ontological turn for higher education. Studies in Higher Education, 32(6), 679–691. doi: 10.1080/03075070701685130.CrossRefGoogle Scholar
  38. Damasio, A. R. (1994). Descartes’ error: Emotion, reason, and the human brain. New York, NY: G.P. Putnam.Google Scholar
  39. Damasio, A. R. (2012). Self comes to mind: Constructing the conscious brain. New York, NY: Vintage Books.Google Scholar
  40. de Jong, T., van Gog, T., Jenks, K., Manlove, S., van Hell, J., Jolles, J., … Boschloo, A. (2009). Explorations in learning and the brain: On the potential of cognitive neuroscience for educational science. New York, NY: SpringerGoogle Scholar
  41. diSessa, A. A. (1988). Knowledge in pieces. In G. Forman & P. Pufall (Eds.), Constructivism in the computer age (pp. 49–70). Hillsdale, NJ: Lawrence Erlbaum Associates.Google Scholar
  42. diSessa, A. A. (1993). Toward an epistemology of physics. Cognition and Instruction, 10(2/3), 105–225.CrossRefGoogle Scholar
  43. diSessa, A. A. (2000). Does the mind know the difference between the physical and social worlds? In L. Nucci, G. B. Saxe, & E. Turiel (Eds.), Culture, thought, and development (pp. 141–166). Mahwah, NJ: Lawrence Erlbaum Associates.Google Scholar
  44. diSessa, A. A. (2006). A history of conceptual change research: Threads and fault lines. In K. Sawyer (Ed.), The Cambridge handbook of the learning sciences (pp. 265–293). Cambridge, UK: Cambridge University Press.Google Scholar
  45. diSessa, A. A. (2008). A bird’s-eye view of the “pieces” vs. “coherence” controversy (from the “pieces” side of the fence). In S. Vosniadou (Ed.), International handbook of research on conceptual change (pp. 35–60). New York, NY: Routledge.Google Scholar
  46. diSessa, A. A., & Sherin, B. L. (1998). What changes in conceptual change? International Journal of Science Education, 20(10), 1155–1191.CrossRefGoogle Scholar
  47. diSessa, A. A., & Wagner, J. F. (2005). What coordination has to say about transfer. In J. P. Mestre (Ed.), Transfer of learning from a modern multidisciplinary perspective (pp. 121–154). Greenwich, CT: Information Age.Google Scholar
  48. Dreyfus, H. L. (1992). What computers still can’t do: A critique of artificial reason. Cambridge, MA: MIT Press.Google Scholar
  49. Dreyfus, H. L. (2014). Skilful coping: Essays on the phenomenology of everyday perception and action. New York, NY: Oxford University Press.CrossRefGoogle Scholar
  50. Engeström, Y. (2008). From teams to knots: Activity-theoretical studies of collaboration and learning at work. Cambridge, NY: Cambridge University Press.CrossRefGoogle Scholar
  51. Fuchs, L. S., Fuchs, D., Prentice, K., Burch, M., Hamlett, C. L., Owen, R., … Jancek, D. (2003). Explicitly teaching for transfer: Effects on third-grade students’ mathematical problem solving. Journal of Educational Psychology, 95(2), 293–305.Google Scholar
  52. Geake, J. (2009). The brain at school: Educational neuroscience in the classroom. Buckingham, UK: Open University Press.Google Scholar
  53. Gibson, J. J. (1979). The ecological approach to visual perception. Boston, MA: Houghton Mifflin.Google Scholar
  54. Gibson, E. J., & Pick, A. D. (2000). An ecological approach to perceptual learning and development. Oxford, UK: Oxford University Press.Google Scholar
  55. Goleman, D. (2006). Emotional intelligence. New York, NY: Bantam Books.Google Scholar
  56. Goodson-Espy, T. (2005). Why reflective abstraction remains relevant in mathematics education research. Paper presented at the annual meeting of the North American Chapter of the International Group for the Psychology of Mathematics Education.Google Scholar
  57. Goodwin, C. (1994). Professional vision. American Anthropologist, 96(3), 606–633.CrossRefGoogle Scholar
  58. Greeno, J. G. (2012). Concepts in activities and discourses. Mind, Culture, and Activity, 19(3), 310–313. doi: 10.1080/10749039.2012.691934.CrossRefGoogle Scholar
  59. Gupta, A., Hammer, D., & Redish, E. F. (2010). The case for dynamic models of learners’ ontologies in physics. Journal of the Learning Sciences, 19(3), 285–321.CrossRefGoogle Scholar
  60. Hallden, O., Scheja, M., & Haglund, L. (2008). The contextuality of knowledge: An intentional approach to meaning making and conceptual change. In S. Vosniadou (Ed.), International handbook of research on conceptual change (pp. 509–532). New York, NY: Routledge.Google Scholar
  61. Holland, D., & Quinn, N. (Eds.). (1987). Cultural models in language and thought. Cambridge, UK: Cambridge University Press.Google Scholar
  62. Hoyles, C., Noss, R., & Pozzi, S. (2001). Proportional reasoning in nursing practice. Journal for Research in Mathematics Education, 32(1), 4–27.CrossRefGoogle Scholar
  63. Hutchins, E. (1995). Cognition in the wild. Cambridge, MA: MIT Press.Google Scholar
  64. Hutchins, E. (2010). Cognitive ecology. Topics in Cognitive Science, 2(4), 705–715. doi: 10.1111/j.1756-8765.2010.01089.x.CrossRefGoogle Scholar
  65. Ingold, T. (2011). Being alive: Essays on movement, knowledge and description. Abingdon, UK: Routledge.Google Scholar
  66. Jarvis, P. (2012). Adult learning in the social context (Vol. 78). New York, NY: Routledge.Google Scholar
  67. Jonassen, D. H. (2011). Learning to solve problems: A handbook for designing problem-solving learning environments. New York, NY: Routledge.Google Scholar
  68. Kapur, M. (2008). Productive failure. Cognition and Instruction, 26(3), 379–424. doi: 10.1080/07370000802212669.CrossRefGoogle Scholar
  69. Kaufman, D. R., Keselman, A., & Patel, V. L. (2008). Changing conceptions in medicine and health. In S. Vosniadou (Ed.), International handbook of research on conceptual change (pp. 295–327). New York, NY: Routledge.Google Scholar
  70. Keil, F. C., & Silberstein, C. S. (1998). Schooling and the acquisition of theoretical knowledge. In D. R. Olson & N. Torrance (Eds.), The handbook of education and human development (pp. 621–645). Malden, MA: Blackwell.Google Scholar
  71. Keller, P. E., Knoblich, G., & Repp, B. H. (2007). Pianists duet better when they play with themselves: On the possible role of action simulation in synchronization. Consciousness and Cognition, 16(1), 102–111. doi: 10.1016/j.concog.2005.12.004.CrossRefGoogle Scholar
  72. Keselman, A., Kaufman, D. R., & Patel, V. L. (2004). “You can exercise your way out of HIV” and other stories: The role of biological knowledge in adolescents’ evaluation of myths. Science Education, 88(4), 548–573. doi: 10.1002/sce.10135.CrossRefGoogle Scholar
  73. 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. doi: 10.1207/s15326985ep4102_1.CrossRefGoogle Scholar
  74. Kirsh, D. (2009). Problem solving and situated cognition. In P. Robbins & M. Aydede (Eds.), The Cambridge handbook of situated cognition (pp. 264–306). Cambridge, MA: Cambridge University Press.Google Scholar
  75. Knorr-Cetina, K. (1999). Epistemic cultures: How the sciences make knowledge. Cambridge, MA: Harvard University Press.Google Scholar
  76. Knowland, V. P., & Thomas, M. C. (2014). Educating the adult brain: How the neuroscience of learning can inform educational policy. International Review of Education, 60(1), 99–122.CrossRefGoogle Scholar
  77. Kuhn, D. (2007). Is direct instruction an answer to the right question? Educational Psychologist, 42(2), 109–113.CrossRefGoogle Scholar
  78. Land, R., & Meyer, J. H. F. (2010). Threshold concepts and troublesome knowledge (5): Dynamics of assessment. In J. H. F. Meyer, R. Land, & C. Baillie (Eds.), Threshold concepts and transformational learning (pp. 61–80). Rotterdam, The Netherlands: Sense.Google Scholar
  79. Land, R., Meyer, J. H. F., & Baillie, C. (2010). Editors’ preface: Threshold concepts and transformational learning. In J. H. F. Meyer, R. Land, & C. Baillie (Eds.), Threshold concepts and transformational learning (pp. IX–XLII). Rotterdam, The Netherlands: Sense.Google Scholar
  80. Land, R., Meyer, J., & Smith, J. B. (Eds.). (2008). Threshold concepts within the disciplines. Rotterdam, The Netherlands: Sense.Google Scholar
  81. Lave, J. (1988). Cognition in practice. Cambridge, MA: Cambridge University Press.CrossRefGoogle Scholar
  82. Lave, J. (2012). Changing practice. Mind, Culture, and Activity, 19(2), 156–171. doi: 10.1080/10749039.2012.666317.CrossRefGoogle Scholar
  83. Lave, J., & Wenger, E. (1991). Situated learning: Legitimate peripheral participation. Cambridge, MA: Cambridge University Press.CrossRefGoogle Scholar
  84. Lobato, J. (2012). The actor-oriented transfer perspective and its contributions to educational research and practice. Educational Psychologist, 47(3), 232–247. doi: 10.1080/00461520.2012.693353.CrossRefGoogle Scholar
  85. Malafouris, L. (2013). How things shape the mind: A theory of material engagement. Cambridge, MA: MIT Press.Google Scholar
  86. Marton, F., & Pang, M. F. (2008). The idea of phenomenography and the pedagogy of conceptual change. In S. Vosniadou (Ed.), International handbook of research on conceptual change (pp. 533–559). New York, NY: Routledge.Google Scholar
  87. McGann, M., De Jaegher, H., & Di Paolo, E. (2013). Enaction and psychology. Review of General Psychology, 17(2), 203–209.CrossRefGoogle Scholar
  88. Meyer, J. H. F., & Land, R. (2005). Threshold concepts and troublesome knowledge (2): Epistemological considerations and a conceptual framework for teaching and learning. Higher Education, 49(3), 373–388.CrossRefGoogle Scholar
  89. Meyer, J. H. F., & Land, R. (Eds.). (2006). Overcoming barriers to student understanding: Threshold concepts and troublesome knowledge. London, UK: Routledge.Google Scholar
  90. Meyer, J. H. F., Land, R., & Baillie, C. (Eds.). (2010). Threshold concepts and transformational learning. Rotterdam, The Netherlands: Sense.Google Scholar
  91. Nemirovsky, R. (2011). Episodic feelings and transfer of learning. Journal of the Learning Sciences, 20(2), 308–337.CrossRefGoogle Scholar
  92. Nersessian, N. J. (2005). Interpreting scientific and engineering practices: Integrating the cognitive, social, and cultural dimensions. In M. E. Gorman, R. D. Tweney, D. C. Gooding, & A. P. Kincannon (Eds.), Scientific and technological thinking (pp. 17–56). Mahwah, NJ: Lawrence Erlbaum Associates.Google Scholar
  93. Newell, A., & Simon, H. A. (1972). Human problem solving. Englewood Cliffs, NJ: Prentice-Hall.Google Scholar
  94. Noë, A. (2004). Action in perception. Cambridge, MA: MIT Press.Google Scholar
  95. Nokes, T. J. (2009). Mechanisms of knowledge transfer. Thinking & Reasoning, 15(1), 1–36.CrossRefGoogle Scholar
  96. OECD. (2007). Understanding the brain: The birth of a learning science. Paris, France: Centre for Educational Research and Innovation.Google Scholar
  97. Ohlsson, S. (1995). Learning to do and learning to understand: A lesson and a challenge for cognitive modelling. In P. Reimann & H. Spada (Eds.), Learning in humans and machines: Towards an interdisciplinary learning science (pp. 37–62). London, UK: Pergamon Press.Google Scholar
  98. Ohlsson, S. (2009). Resubsumption: A possible mechanism for conceptual change and belief revision. Educational Psychologist, 44(1), 20–40. doi: 10.1080/00461520802616267.CrossRefGoogle Scholar
  99. Ohlsson, S. (2011). Deep learning: How the mind overrides experience. Cambridge, MA: Cambridge University Press.CrossRefGoogle Scholar
  100. Özdemir, G., & Clark, D. B. (2007). An overview of conceptual change theories. Eurasia Journal of Mathematics, Science & Technology Education, 3(4), 351–361.Google Scholar
  101. Papert, S. (1980). Mindstorms: Children, computers, and powerful ideas. New York, NY: Basic Books.Google Scholar
  102. Patel, V. L., Arocha, J. F., & Zhang, J. (2005). Thinking and reasoning in medicine. In K. J. Holyoak & R. G. Morrison (Eds.), The Cambridge handbook of thinking and reasoning (pp. 727–750). Cambridge, MA: Cambridge University Press.Google Scholar
  103. Pecher, D., & Zwaan, R. A. (Eds.). (2010). Grounding cognition: The role of perception and action in memory, language, and thinking. New York, NY: Cambridge University Press.Google Scholar
  104. Perkins, D. (2006). Constructivism and troublesome knowledge. In J. H. F. Meyer & R. Land (Eds.), Overcoming barriers to student understanding: Threshold concepts and troublesome knowledge (pp. 33–47). London, UK: Routledge.Google Scholar
  105. Perkins, D. (2007). Theories of difficulty. BJEP Monograph Series II, Number 4 – Student Learning and University Teaching, 1(1), 31–48.Google Scholar
  106. Perkins, D. N., & Salomon, G. (1989). Are cognitive skills context-bound? Educational Researcher, 18(1), 16–25. doi: 10.3102/0013189x018001016.CrossRefGoogle Scholar
  107. Perry, L. R. (1965). Commonsense thought, knowledge and judgement and their importance for education. British Journal of Educational Studies, 13(2), 125–138.CrossRefGoogle Scholar
  108. Philip, T. M. (2011). An “ideology in pieces” approach to studying change in teachers’ sensemaking about race, racism, and racial justice. Cognition and Instruction, 29(3), 297–329. doi: 10.1080/07370008.2011.583369.CrossRefGoogle Scholar
  109. Redish, E. F. (2004). A theoretical framework for physics education research: Modeling student thinking. Proceedings of the International School of Physics, “Enrico Fermi” Course CLVI, Amsterdam.Google Scholar
  110. Rogoff, B., & Lave, J. (Eds.). (1984). Everyday cognition. Cambridge, MA: Harvard University Press.Google Scholar
  111. Rommetveit, R. (1978). On negative rationalism in scholarly studies of verbal communication and dynamic residuals in the construction of human subjectivity. In M. M. P. Brenner & M. Brenner (Eds.), The social contexts of method (pp. 16–32). London, UK: Croom Helm.Google Scholar
  112. Säljö, R. (1991). Piagetian controversies, cognitive competence, and assumptions about human communication. Educational Psychology Review, 3(2), 117–126. doi: 10.1007/bf01417923.CrossRefGoogle Scholar
  113. Savin-Baden, M. (2000). Problem-based learning in higher education. Buckingham, UK: SRHE/Open University Press.Google Scholar
  114. Schank, R. C., & Abelson, R. P. (1977). Scripts, plans, goals, and understanding: An inquiry into human knowledge structures. Hillsdale, NJ: Lawrence Erlbaum Associates.Google Scholar
  115. Schatzki, T. R., Knorr-Cetina, K., & von Savigny, E. (2001). The practice turn in contemporary theory. London, UK: Routledge.Google Scholar
  116. Schraw, G. (2006). Knowledge structures and processes. In P. A. Alexander & P. Winne (Eds.), Handbook of educational psychology (pp. 245–263). Mahwah, NJ: Lawrence Erlbaum Associates.Google Scholar
  117. Schwartz, D. L., & Bransford, J. D. (1998). A time for telling. Cognition and Instruction, 16(4), 475–522. doi: 10.2307/3233709.CrossRefGoogle Scholar
  118. Schwartz, D. L., Varma, S., & Martin, L. (2008). Dynamic transfer and innovation. In S. Vosniadou (Ed.), International handbook of research on conceptual change (pp. 479–508). New York, NY: Routledge.Google Scholar
  119. Scribner, S. (1985). Knowledge at work. Anthropology and Education Quarterly, 16, 199–206.CrossRefGoogle Scholar
  120. Scribner, S. (1997). Mind and social practice: Selected writings of Sylvia Scribner. Cambridge, NY: Cambridge University Press.Google Scholar
  121. Siegel, D. J. (2012). The developing mind: How relationships and the brain interact to shape who we are (2nd ed.). New York, NY: The Guilford Press.Google Scholar
  122. Sinatra, G. M., & Pintrich, P. R. (Eds.). (2003). Intentional conceptual change. Mahwah, NJ: Lawrence Erlbaum Associates.Google Scholar
  123. Skinner, B. F. (1938). The behavior of organisms: An experimental analysis. New York, NY: D.Appelton-Century.Google Scholar
  124. Smith, L. B. (2005). Cognition as a dynamic system: Principles from embodiment. Developmental Review, 25(3–4), 278–298. doi: 10.1016/j.dr.2005.11.001.CrossRefGoogle Scholar
  125. Smith, L. B., & Gasser, M. (2005). The development of embodied cognition: Six lessons from babies. Artificial Life, 11(1–2), 13–29. doi: 10.1162/1064546053278973.CrossRefGoogle Scholar
  126. Sousa, D. A. (2011). How the brain learns (4th ed.). Thousand Oaks, CA: Corwin.Google Scholar
  127. Sterelny, K. (2003). Thought in a hostile world: The evolution of human cognition. Oxford, UK: Blackwell.Google Scholar
  128. Sterelny, K. (2012). The evolved apprentice: How evolution made humans unique. Cambridge, MA: MIT Press.CrossRefGoogle Scholar
  129. Sternberg, R. J. (1985). Beyond IQ: A triadic theory of human intelligence. Cambridge, UK: Cambridge University Press.Google Scholar
  130. Sternberg, R. J. (2004). Wisdom, intelligence, and creativity synthesized. Cambridge, NY: Cambridge University Press.Google Scholar
  131. Stewart, J., Gapenne, O., & Paolo, E. A. D. (Eds.). (2010). Enaction: Toward a new paradigm for cognitive science. Cambridge, MA: MIT Press.Google Scholar
  132. Sweller, J., van Merrienboer, J. G., & Paas, F. W. C. (1998). Cognitive architecture and instructional design. Educational Psychology Review, 10(3), 251–296.CrossRefGoogle Scholar
  133. Szymanski, M. H., & Whalen, J. (Eds.). (2011). Making work visible: Ethnographically grounded case studies of work practice. Cambridge, MA: Cambridge University Press.Google Scholar
  134. Turnbull, D. (2000). Masons, tricksters and cartographers: Comparative studies in the sociology of scientific and indigenous knowledge. Abingdon, OX: Routledge.CrossRefGoogle Scholar
  135. Varela, F., Thompson, E., & Rosch, E. (1991). The embodied mind: Cognitive science and human experience (6th ed.). Cambridge, MA: MIT Press.Google Scholar
  136. Vera, A. H., & Simon, H. A. (1993). Situated action: A symbolic interpretation. Cognitive Science, 17(1), 7–48.CrossRefGoogle Scholar
  137. Vosniadou, S. (Ed.). (2008/2013). International handbook of research on conceptual change (1st and 2nd eds.). New York, NY: Routledge.Google Scholar
  138. Vosniadou, S., & Brewer, W. F. (1994). Mental models of the day/night cycle. Cognitive Science, 18(1), 123–183. doi: 10.1207/s15516709cog1801_4.CrossRefGoogle Scholar
  139. Vosniadou, S., & Ioannides, C. (1998). From conceptual development to science education: A psychological point of view. International Journal of Science Education, 20(10), 1213–1230. doi: 10.1080/0950069980201004.CrossRefGoogle Scholar
  140. Wagner, J. F. (2006). Transfer in pieces. Cognition and Instruction, 24(1), 1–71.CrossRefGoogle Scholar
  141. Wagner, J. F. (2010). A transfer-in-pieces consideration of the perception of structure in the transfer of learning. Journal of the Learning Sciences, 19(4), 443–479.CrossRefGoogle Scholar

Copyright information

© Springer Science+Business Media Dordrecht 2017

Authors and Affiliations

  • Lina Markauskaite
    • 1
  • Peter Goodyear
    • 1
  1. 1.Centre for Research on Learning and Innovation (CRLI), Faculty of Education & Social WorkThe University of SydneySydneyAustralia

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