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Merging Cognitive and Sociocultural Approaches: Toward Better Understandings of the Processes of Developing Thinking and Reasoning

  • Paul WebbEmail author
  • J. W. (Bill) Whitlow
Chapter
First Online:
Part of the Contemporary Trends and Issues in Science Education book series (CTISE, volume 49)

Abstract

Educational psychology research in general, as well as in terms of science education in the twentieth century, has generally followed one of three distinct and exclusionary approaches: laboratory-based studies of cognitive processes presumed important for education; observational field studies of classrooms and educational practices viewed from a sociocultural perspective; and psychometric-based analyses of student aptitudes and achievements as measured on standardized tests. However, recent advances in knowledge and theory have led researchers from all of these approaches to adopt more global views of their research, with the result that there is considerable potential for developing meaningful linkages among these different approaches. One such linkage has been an increased concern with understanding how to produce “far transfer” effects as a common goal of most educational interventions, i.e., to prepare students to perform well in new situations by adapting what they have been explicitly taught to solve problems and produce outcomes that are new or different from their specific training. In this chapter we consider some of the promising new directions and important research questions raised by this more integrated view of the nature of educational practices.

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References

  1. Ackerman, P. L., Beier, M. E., & Boyle, M. O. (2005). Working memory and intelligence: The same or different constructs? Psychological Bulletin, 131, 30–60.CrossRefGoogle Scholar
  2. Anderson, J. R. (2007). How can the human mind occur in the physical universe. New York: Oxford University Press.CrossRefGoogle Scholar
  3. Backman, L., Nyberg, L., Soveri, A., Johansson, J., Andersson, M., Dahlin, E., et al. (2011). Effects of working-memory training on striatal dopamine release. Science, 333, 718.CrossRefGoogle Scholar
  4. Barnett, S., & Ceci, S. (2002). When and where do we apply what we learn? A taxonomy for far transfer. Psychological Bulletin, 128, 612–637.  https://doi.org/10.1037//0033-2909.128.4.612CrossRefGoogle Scholar
  5. Benton, D. (2008). The influence of children’s diet on their cognition and behavior. European Journal of Nutrition, 47(3), 25–37.  https://doi.org/10.1007/s00394-008-3003-xCrossRefGoogle Scholar
  6. Carey, S. (1985). Conceptual change in childhood. Cambridge, MA: MIT Press.Google Scholar
  7. Carraher, T. N., Carraher, D. W., & Schliemann, A. D. (1985). Mathematics in the streets and in schools. British Journal of Developmental Psychology, 3(1), 21–29.CrossRefGoogle Scholar
  8. Clark, R., & Mayer, R. E. (2016). E-learning and the science of instruction (4th ed.). San Francisco: Pfeiffer.CrossRefGoogle Scholar
  9. Cole, M., Gay, J., & Glick, J. (1968). A cross-cultural investigation of information processing. International Journal of Psychology, 3, 93–102.CrossRefGoogle Scholar
  10. Cole, M., Gay, J., Glick, J. A., & Sharp, D. W. (Eds.). (1971). The cultural context of learning and thinking. New York: Basic Books.Google Scholar
  11. Deijen, J. B., & Orlebeke, J. F. (1994). Effect of tyrosine on cognitive function and blood pressure under stress. Brain Research Bulletin, 33(3), 319–323.CrossRefGoogle Scholar
  12. diSessa, A. A. (1983). Phenomenology and the evolution of intuition. In D. Gentner & A. Stevens (Eds.), Mental Models (pp. 15–33). Mahwah, NJ: Lawrence Erlbaum Associates, Inc.Google Scholar
  13. Dole, J. A., & Sinatra, G. M. (1998). Reconceptualizing change in the cognitive construction of knowledge. Educational Psychologist, 33(2/3), 109–128.CrossRefGoogle Scholar
  14. Driver, R., Asoko, I., Leach, J., Mortimer, E., & Scott, P. (1994). Constructing scientific knowledge in the classroom. Educational Researcher, 23, 5–12.CrossRefGoogle Scholar
  15. Duit, R. (1999). Conceptual changes approaches in science education. In W. Schnotz, S. Vosniadou, & M. Carretero (Eds.), New perspectives on conceptual change (pp. 263–282). Oxford, UK: Elsevier-Pergamon.Google Scholar
  16. Dunlosky, J., Rawson, K. A., Marsh, E. J., Nathan, M. J., & Willingham, D. T. (2013). Improving students’ learning with effective learning techniques: Promising directions from cognitive and educational psychology. Psychological Science in the Public Interest, 14, 4–58.  https://doi.org/10.1177/1529100612453266CrossRefGoogle Scholar
  17. Fiorella, L., & Mayer, R. (2015). Learning as a generative activity: Eight learning strategies that promote understanding. New York: Cambridge University Press.CrossRefGoogle Scholar
  18. Gailliot, M. T., Baumeister, R. F., DeWall, N. C., Maner, J. K., Plant, A. E., Tice, D. M., et al. (2007). Self-control relies on glucose as a limited energy source: Willpower is more than a metaphor. Journal of Personality and Social Psychology, 92(2), 325–336.  https://doi.org/10.1037/0022-3514.92.2.325CrossRefGoogle Scholar
  19. Gomez-Pinilla, F. (2008). Brain foods: The effects of nutrients on brain function. Nature Reviews/Neuroscience, 9, 568–578.Google Scholar
  20. Greeno, J. G. (2006). Authoritative, accountable positioning and connected, general knowing: Progressive themes in understanding transfer. The Journal of the Learning Sciences, 15(4), 537–547.CrossRefGoogle Scholar
  21. Greeno, J. G., Collins, A. M., & Resnick, L. B. (1996). Cognition and learning. In D. C. Berliner & R. C. Calfee (Eds.), Handbook of educational psychology. New York: McMillan.Google Scholar
  22. Hall, G. S. (1909). Youth: Its education, regimen and hygiene. New York: Appleton & Co.Google Scholar
  23. Harrison, T. L., Shipstead, Z., Hicks, K. L., Hambrick, D. Z., Redick, T. S., & Engle, R. W. (2013). Working memory training may increase working memory capacity but not fluid intelligence. Psychological Science.  https://doi.org/10.1177/0956797613492984CrossRefGoogle Scholar
  24. Jaeggi, S., Buschkuehl, M., Jonides, J., & Perrig, W. (2008). Improving fluid intelligence with training on working memory. Proceedings of the National Academy of Science of the United States of America, 105(15), 6829–6833.CrossRefGoogle Scholar
  25. Kane, M. J., Hambrick, D. Z., & Conway, A. R. A. (2005). Working memory and fluid intelligence are strongly related constructs: Comment on Ackermain, Beier & Boyle (2005). Psychological Bulletin, 131, 66–71.CrossRefGoogle Scholar
  26. Kuhn, D., & Crowell, A. (2011). Dialogic argumentation as a vehicle for developing young adolescents’ thinking. Psychological Science, 22, 545–552.CrossRefGoogle Scholar
  27. Lave, J. (1988). Cognition in practice: Mind, mathematics and culture in everyday life. Cambridge, UK: Cambridge University Press.CrossRefGoogle Scholar
  28. Lehman, D. R., Lempert, R. O., & Nisbett, R. E. (1988). The effects of graduate training on reasoning: Formal discipline and every-day life events. American Psychologist, 43, 431–442.CrossRefGoogle Scholar
  29. Maguire, E., Woollett, K., & Speirs, H. (2006). London taxi drivers and bus drivers: A structural MRI and neuropsychological analysis. Hippocampus, 16, 1091–1101.CrossRefGoogle Scholar
  30. Mason, L. (2007). Introduction: Bridging the cognitive and sociocultural approaches in research on conceptual change: Is it feasible? Educational Psychologist, 42(1), 1–7.CrossRefGoogle Scholar
  31. Mayer, R. E. (2009). Multimedia learning. Cambridge, UK: Cambridge University Press.CrossRefGoogle Scholar
  32. Mayer, R. E. (2011). Applying the science of learning. Boston: Pearson/Allyn & Bacon.Google Scholar
  33. Mayer, R. E., & Alexander, P. A. (2017). Handbook of research on learning and instruction (2nd ed.). New York: Routledge.Google Scholar
  34. Miller, G. A. (1956). The magical number seven, plus or minus two: Some limits on our capacity for processing information. Psychological Review, 63(2), 81–97.Google Scholar
  35. Miyake, A., Friedman, N. P., Emerson, M. J., Witzki, A. H., Howerter, A., & Wager, T. D. (2000). The unity and diversity of executive functions and their contributions to complex “frontal lobe” tasks: A latent variable analysis. Cognitive Psychology, 41, 49–100.CrossRefGoogle Scholar
  36. Morehouse, R., & Williams, M. (1998). Report on student use of argument skills. Critical and Creative Thinking, 6(1), 14–20.Google Scholar
  37. Moulton, S. T. (2014). Applying psychological science to higher education: Key findings and open questions. Retrieved from http://hilt.harvard.edu/hilt-publications on June 18,
  38. Mrazek, M. D., Franklin, M. S., Phillips, D. T., Baird, B., & Schooler, J. W. (2013). Mindfulness training improves memory capacity and GRE performance while reducing mind wandering. Psychological Science, 24, 776–781.  https://doi.org/10.1177/0956797612459659CrossRefGoogle Scholar
  39. Mrazek, M. D., Smallwood, J., Franklin, M. S., Chin, J. M., Baird, B., & Schooler, J. W. (2012). The role of mind-wandering in measurements of general aptitude. Journal of Experimental Psychology: General, 141, 788–798.  https://doi.org/10.1037/a0027968CrossRefGoogle Scholar
  40. Oberauer, K., Schulze, R., Wilhelm, O., & Suss, H.-M. (2005). Working memory and intelligence – Their correlation and relation: Comment on Ackerman, Beier, & Boyle (2005). Psychological Bulletin, 131, 61–65. Orquin & Kurzban, 2016.CrossRefGoogle Scholar
  41. Owasoyo, J., Neri, D., & Lamberth, J. (1992). Tyrosine and its potential use as a countermeasure to performance decrement in military sustained operations. Aviation, Space, and Environmental Medicine, 63(5), 364–369.Google Scholar
  42. Packer, M. J., & Goicoechea, J. (2000). Sociocultural and constructivist theories of learning: Ontology, not just epistemology. Educational Psychologist, 35, 227–241.CrossRefGoogle Scholar
  43. Pintrich, P. R., Marx, R. W., & Boyle, R. B. (1993). Beyond cold conceptual change: The role of motivational beliefs and classroom contextual factors in the process of conceptual change. Review of Educational Research, 63, 167–199.CrossRefGoogle Scholar
  44. Posner, G. J., Strike, K. A., Hewson, P. W., & Gertzog, W. A. (1982). Accommodation of a scientific conception: Towards a theory of conceptual change. Science Education, 67(4), 489–508.Google Scholar
  45. Pozo, J. I., Gomez, M. A., & Sanz, A. (1999). When change does not mean replacement: Different representations for different contexts. In W. Schnotz, S. Vosniadou, & M. Carretero (Eds.), New perspectives on conceptual change (pp. 161–174). Oxford, UK: Elsevier-Pergamon.Google Scholar
  46. Raven, J., & Raven, J. (2003). Raven progressive matrices. In R. S. McCallum (Ed.), Handbook of nonverbal assessment (pp. 223–237). Boston: Springer.Google Scholar
  47. Redick, T. S., Shipstead, Z., Harrison, T. L., Hicks, K. L., Fried, D. E., Hambrick, D. Z., et al. (2013). No evidence of intelligence improvement after working memory training: A randomized, placebo controlled study. Journal of Experimental Psychology: General, 142(2), 359–379.CrossRefGoogle Scholar
  48. Resnick, L. B. C., Asterhan, C. S. C., & Clarke, S. N. (2015). Introduction: Talk, learning, and teaching. In L. B. Resnick, C. S. C. Asterhan, & S. N. Clarke (Eds.), Socializing intelligence through academic talk and dialogue (pp. 1–12). Washington, DC: AERA.CrossRefGoogle Scholar
  49. Resnick, L. B. C., Asterhan, C. S. C., & Clarke, S. N. (2016). Introduction: Talk, learning, and teaching. In L. B. Resnick, C. S. C. Asterhan, & S. N. Clarke (Eds.), Socializing intelligence through academic talk and dialogue (pp. 1–12). Washington, DC: AERA.Google Scholar
  50. Reznitskaya, A., Glina, M., Carolan, B., Michaud, O., Rogers, J., & Sequeira, L. (2012). Examining transfer effects from dialogic discussions to new tasks and contexts. Contemporary Educational Psychology, 37, 288–306.CrossRefGoogle Scholar
  51. Reznitskaya, A., & Wilkinson, I. A. G. (2015a). Positively transforming classroom practice through dialogic teaching. In S. Joseph (Ed.), Positive psychology in practice (pp. 279–296). New York: Wiley and Sons.Google Scholar
  52. Reznitskaya, A., & Wilkinson, I. A. G. (2015b). Professional development in dialogic teaching: Helping teachers promote argument literacy in their classrooms. In D. Scott & E. Hargreaves (Eds.), Sage handbook of learning (pp. 219–232). London: Sage.CrossRefGoogle Scholar
  53. Rezntiskaya, A., Wilkinson, A. I. G., Oyler, J., Bourdage-Reninger, K., & Sykes, A. (2016, April). Using the argumentation rating tool to support teacher facilitation of inquiry dialogue in elementary language arts classrooms. Paper presented at the Annual Meeting of the American Educational Research Association, Washington, DC.Google Scholar
  54. Roediger, H. L. (2013). Applying cognitive psychology to education: Translational educational science. Psychological Science in the Public Interest, 14(1), 1–3.CrossRefGoogle Scholar
  55. Rogoff, B. (1990). Apprenticeship in thinking: Cognitive development in social context. Oxford, UK: Oxford University Press.Google Scholar
  56. Rudy, J. R. (2013). The neurobiology of learning and memory (2nd ed.). New York: Sinauer Associates.Google Scholar
  57. Säljö, R. (1999). Concepts, cognition and discourse: From mental structures to discursive tools. In W. Schnotz, S. Vosniadou, & M. Carretero (Eds.), New perspectives on conceptual change (pp. 81–90). Oxford, UK: Elsevier-Pergamon.Google Scholar
  58. Sfard, A. (1998). On two metaphors for learning and the danger of choosing just one. Educational Researcher, 27(2), 4–13.CrossRefGoogle Scholar
  59. Shayer, M., & Adey, P. (2002). Learning intelligence: Cognitive acceleration across the curriculum from 5 to 15 years. Maidenhead, UK: Open University Press.Google Scholar
  60. Smith, M., & Farah, M. (2011). Are prescription stimulants “smart pills”? The epidemiology and cognitive neuroscience of prescription stimulant use by normal healthy individuals. Psychological Bulletin, 137(5), 717–741.CrossRefGoogle Scholar
  61. Spada, H. (1994). Conceptual change or multiple representations? [special issue]. Learning and Instruction, 4, 113–116.CrossRefGoogle Scholar
  62. Szpunar, K. K., Khan, N. Y., & Schacter, D. L. (2013). Interpolated memory tests reduce mind wandering and improve learning of online lectures. Proceedings of the National Academy of Sciences, 110, 6313–6317.CrossRefGoogle Scholar
  63. Szpunar, K. K., Moulton, S. T., & Schacter, D. L. (2013). Mind wandering and education: From the classroom to online learning. Frontiers in Psychology, 4, 1–7.CrossRefGoogle Scholar
  64. Szymanski, C., Pesquita, A., Brennan, A. A., Perdikis, D., Enns, J. T., Brick, T. R., et al. (2017). Teams on the same wavelength perform better: Inter-brain phase synchronization constitutes a neural substrate for social facilitation. NeuroImage, 152, 425–436.  https://doi.org/10.1016/j.neuroimage.2017.03.013CrossRefGoogle Scholar
  65. The NEMO Study group. (2007). Effect of a 12-mo micronutrient intervention on learning and memory in well-nourished and marginally nourished school-aged children: 2 parallel, randomized, placebo-controlled studies in Australia and Indonesia. The American Journal of Clinical Nutrition, 86, 1082–1093.CrossRefGoogle Scholar
  66. Thorndike, E. L. (1906). Principles of teaching. New York: A.G. Seiler.Google Scholar
  67. Thorndike, E. L. (1931). Human learning. New York: The Century Co.CrossRefGoogle Scholar
  68. Thorndike, E. L., & Woodworth, R. S. (1901). The influence of improvement in one mental function on the efficiency of other functions. Psychological Review, 8, 247–261.CrossRefGoogle Scholar
  69. Toulmin, S. (2003). The uses of argument. New York: Cambridge University Press.CrossRefGoogle Scholar
  70. Trickey, S., & Topping, K. (2004). Philosophy for children: A systematic review. Research Papers in Education, 19(3), 365–380.CrossRefGoogle Scholar
  71. Van Niekerk, J., & Webb, P. (2016). The effectiveness of brain-compatible blended learning material in the teaching of programming logic. Computers & Education, 103, 16–27.CrossRefGoogle Scholar
  72. van Praag, H. (2009). Exercise and the brain: Something to chew on. Trends in Neurosciences, 32(5), 283–290.CrossRefGoogle Scholar
  73. Villanueva, M. G.. (2010).grated teaching strategies model for improved scientific literacy in second-language learners. Unpublished PhD. Nelson Mandela Metropolitan University, Port Elizabeth, South Africa.Google Scholar
  74. Vosniadou, S., & Brewer, W. F. (1987). Theories of knowledge restructuring in development. Review of Educational Research, 57, 51–67.CrossRefGoogle Scholar
  75. Vygotsky, L. S. (1978). Mind in society. Cambridge, MA: Harvard University Press.Google Scholar
  76. Webb, P. (2010). Science education and literacy: Imperatives for the developed and developing world. Science, 328(5977), 448–450.CrossRefGoogle Scholar
  77. Webb, P., & Treagust, D. (2003). Using exploratory talk to enhance problem-solving and reasoning skills in grade-7 science classrooms. Research in Science Education, 36(4), 381–401.CrossRefGoogle Scholar
  78. Webb, P., Whitlow Jr., J. W., & Venter, D. (2016). From exploratory talk to abstract reasoning: A case for far transfer? Educational Psychology Review, 1–17.  https://doi.org/10.1007/s10648-016-9369-zCrossRefGoogle Scholar
  79. Wegerif, R., Mercer, N., & Dawes, L. (1999). From social interaction to individual reasoning: An empirical investigation of a possible socio-cultural model of cognitive development. Learning and Instruction, 9, 493–516.CrossRefGoogle Scholar
  80. Wertsch, J. V. (1998). Mind as actions. New York: Cambridge University Press.Google Scholar
  81. Whitlow, J. W., Jr., Rowe, S., & Wigley, S. (2017, March). Effects of tyrosine on discrimination learning. Poster presented at the annual meeting of the Eastern Psychological Association, Boston, MA.Google Scholar
  82. Wilkinson, I. A. G., Murphy, P. K., & Binici, S. (2015). Dialogue-intensive pedagogies for promoting Reading comprehension: What we know, what we need to know. In L. B. Resnick, C. S. C. Asterhan, & S. N. Clarke (Eds.), Socializing intelligence through academic talk and dialogue (pp. 1–12). Washington, DC: AERA. (35–48). Washington, DC: AERA.Google Scholar
  83. Wilkinson, I., Reznitskaya, A., Bourdage, K., Oyler, J., Glina, M., Drewry, R., et al. (2016). Toward a more dialogic pedagogy: Changing teachers’ beliefs and practices through professional development in language arts classrooms. Language and Education.  https://doi.org/10.1080/09500782.2016.1230129CrossRefGoogle Scholar

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Authors and Affiliations

  1. 1.Nelson Mandela Metropolitan UniversityPort ElizabethSouth Africa
  2. 2.Rutgers University – CamdenCamdenUSA

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