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General Versus Specific Intellectual Competencies

The Question of Learning Transfer

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Fostering Human Development Through Engineering and Technology Education

Part of the book series: International Technology Education Studies ((ITES,volume 6))

Abstract

One major goal of education is to provide students with the knowledge and skills that will prepare them to be productive citizens and enable them to make informed decisions about work, family and societal issues. It is commonly believed that what we learn in school will be applied at appropriate times later in life. Unfortunately, research on transfer of learning raises doubts about the effectiveness of education to create transferable knowledge and skills.

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REFERENCES

  • Anolli, L., Antonietti, A., Crisafulli, L., & Cantoia, M. (2001). Accessing source information in analogical problem-solving. Quarterly Journal of Experimental Psychology, 54A(1), 237–261.

    Google Scholar 

  • Ball, L. J., Ormerod, T. C., & Morely, N. J. (2004). Spontaneous analogising in engineering design: A comparative analysis of experts and novices. Design Studies, 25, 495–508.

    Article  Google Scholar 

  • Bayles, E. E. (1936). A factor unemphasized in current theories regarding the transfer of training. Journal of Educational Psychology, 27(6), 425–430.

    Article  Google Scholar 

  • Beach, K. D. (1999). Consequential transitions: A sociocultural expedition beyond transfer in education. In A. Iran-Nejad & P. D. Pearson (Eds.), Review of research in education (Vol. 24, pp. 101–140). Washington, DC: American Educational Research Association.

    Google Scholar 

  • Bransford, J. D., & Schwartz, D. L. (1999). Rethinking transfer: A simple proposal with multiple implications. In A. Iran-Nejad & P. D. Pearson (Eds.), Review of research in education (Vol. 24, pp. 61–101). Washington, DC: American Educational Research Association.

    Google Scholar 

  • Bransford, J. D., Brown, A. L., & Cocking, R. R. (1999). How people learn: Brain, mind, experience and school. Washington, DC: National Academy Press.

    Google Scholar 

  • Brewer, W. (2001). Models in science and mental models in scientists and nonscientist. Mind and Society, 2, 33–48.

    Article  Google Scholar 

  • Brewer, W. (2003). Mental models. In L. Nadle (Ed.), Encyclopedia of cognitive science (Vol. 3, pp. 1–5). London: Nature Publishing Group.

    Google Scholar 

  • Brown, A. L. (1978). Knowing when, where and how to remember: A problem of metacognition. In R. Glaser (Ed.), Advances in instructional psychology (Vol. 1, pp. 225–253). Hillsdale, NJ: Erlbaum.

    Google Scholar 

  • Brown, D. E., & Clement, J. (1989). Overcoming misconceptions via analogical reasoning: Abstract transfer versus explanatory model construction. Instructional Science, 18, 237–261.

    Article  Google Scholar 

  • Case, J., Gunstone, R., & Lewis, A. (2001). Students’ metacognitive development in an innovative second year chemical engineering course. Research in Science Education, 31(3), 313–335.

    Article  Google Scholar 

  • Chambres, P., Bonin, D., Izaute, M., & Marescaux, P. J. (2002). Metacognition triggered by social aspect of expertise. In P. Chambres, M. Izaute, & P. J. Marescaux (Eds.), Metacognition process, function and use (pp. 153–168). Norwell, MA: Kluwer.

    Google Scholar 

  • Chan, L. K. S., & Moore, P. J. (2006). Development of attributional beliefs and strategic knowledge in Years 5 to 9: A longitudinal analysis. Educational Psychology, 26(2), 161–185.

    Article  Google Scholar 

  • Chi, M. T. H., de Leeuw, N., Chiu, M. H., & LaVancher, C. (1994). Eliciting self-explanations improves understanding. Cognitive Science, 18, 439–477.

    Google Scholar 

  • Chi, M. T. H. (2000). Self-explaining expository texts: The dual processes of generating inferences and repairing mental models. In R. Glaser (Ed.), Advances in instructional psychology (pp. 161–238), Hillsdale, NJ: Erlbaum.

    Google Scholar 

  • Clark, R. E., & Voogel, A. (1985). Transfer of training principles for instructional design. Educational Communication and Technology Journal, 33(2), 113–123.

    Google Scholar 

  • Clark, R. V., & Mayer, R. E. (2003). E-learning and the science of instruction. San Francisco: Pfeiffer.

    Google Scholar 

  • Clement, C. A. (1994). Effect of structural embedding on analogical transfer: Manifest versus latent analogs. American Journal of Psychology, 107(1), 1–38.

    Article  Google Scholar 

  • Collins, A. (1985). Component models of physical systems. In Proceedings of the seventh annual conference of Cognitive Science Society (pp. 80–89). Irvine, CA: Cognitive Science.

    Google Scholar 

  • Cuasay, P. (1992). Cognitive factors in academic achievement. Higher Education Extension Service, 3(3), 1–8.

    Google Scholar 

  • Daugherty, J., & Mentzer, N. (2008). Analogical reasoning in the engineering design process and technology education applications. Journal of Technology Education, 19(2), 7–21.

    Google Scholar 

  • Dym, C. L., & Little, P. (2004). Engineering design: A project based approach (2nd ed.). Hoboken: Wiley.

    Google Scholar 

  • Flavell, J. H. (1976). Metacognitive aspects of problem solving. In L. B. Resnick (Ed.), The nature of intelligence (pp. 231–236). Hillsdale, NJ: Erlbaum.

    Google Scholar 

  • Flavell, J. H. (1979). Metacognition and cognitive monitoring: A new area of cognitive developmental inquiry. American Psychologist, 34, 906–911.

    Article  Google Scholar 

  • Garner, R., & Alexander, P. A. (1989). Metacognition: Answered and unanswered questions. Educational Psychologist, 24, 143–158.

    Article  Google Scholar 

  • Gelman, S. A. (1996). Concept and theories. In R. Gelman & T. Kit-Fong Au (Eds.), Perceptual and cognitive development: Handbook of perception and cognition (2nd ed., pp. 117–150). San Diego, CA: Academic Press.

    Google Scholar 

  • Gentner, D. (1983). Structure-mapping: A theoretical framework for analogy. Cognitive Science, 7, 155–170.

    Article  Google Scholar 

  • Gentner, D. (1989). The mechanisms of analogical learning. In S. Vosniadou & A. Ortony (Eds.), Similarity and analogical reasoning (pp. 199–241). Cambridge, MA: Cambridge University Press.

    Google Scholar 

  • Gentner, D., Loewenstein, J., & Thompson, L. (2003). Learning and transfer: A general role for analogical encoding. Journal of Educational Psychology, 95(3), 393–408.

    Article  Google Scholar 

  • Gentner, D., & Markman, A. B. (1997). Structure mapping in analogy and similarity. American Psychologist, 52(1), 45–56.

    Article  Google Scholar 

  • Gibson, K. (2008). Analogy in scientific argumentation. Technical Communication Quarterly, 17(2), 202–219.

    Article  Google Scholar 

  • Glynn, S. M. (1989). The teaching with analogies model. In S. Vosniadou & A. Ortony (Eds.), Similarity and analogical reasoning (pp. 199–241). Cambridge, MA: University Press.

    Google Scholar 

  • Gourgey, A. (1998). Metacognition in basic skills instruction. Instructional Science, 26(1–2), 81–96.

    Article  Google Scholar 

  • Greeno, J., 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, NJ: Ablex.

    Google Scholar 

  • Hamilton, R., & Ghatala, E. (1994). Learning and instruction. New York: McGraw-Hill.

    Google Scholar 

  • Hayes, J. R. (1989). The complete problem solver (2nd ed.). Hillsdale, NJ: Erlbaum.

    Google Scholar 

  • Holyoak, K. J., & Thagard, P. (1997). The analogical mind. American Psychologist, 52(1), 35–44.

    Article  Google Scholar 

  • Johnson, S. D. (1995). Transfer of learning. The Technology Teacher, 54(7), 33–35.

    Google Scholar 

  • Johnson, S. D., & Satchwell, R. E. (1993). The effect of functional flow diagram on apprentice aircraft mechanics’ technical system understanding. Performance Improvement Quarterly, 6(4), 73–91.

    Article  Google Scholar 

  • Judd, C. H. (1936). Education as cultivation of higher mental processes. New York: Macmillan.

    Google Scholar 

  • Kempton, W. (1986). Two theories of home heat control. Cognitive Science, 10, 75–90.

    Article  Google Scholar 

  • Kieras, D. E., & Bovair, S. (1984). The role of a mental model in learning to operate a device. Cognitive Science, 8, 363–385.

    Article  Google Scholar 

  • Kluwe, R. H. (1982). Cognitive knowledge and executive control: Metacognition. In D. R. Griffin (Ed.), Animal mind-human mind (pp. 201–224). New York: Springer-Verlag.

    Google Scholar 

  • Kolodner, J. L. (1997). Educational implications of analogy: A view from case-based reasoning. American Psychologist, 52(1), 57–66.

    Article  Google Scholar 

  • Lai, S. L., & Repman, J. L. (1996). The effects of analogies and mathematics ability on students’ programming learning using computer-based learning. International Journal of Instructional Media, 23(4), 355–364.

    Google Scholar 

  • Leberman, S., McDonald, L., & Doyle, S. (2006). The transfer of learning. Burlington, VT: Gower.

    Google Scholar 

  • Lee, Y., & Nelson D. W. (2005). Viewing or visualizing-which concept map strategy works best on problem-solving performance? British Journal of Educational Technology, 36(2), 193–203.

    Article  Google Scholar 

  • Magee, G. B. (2005). Fostering understanding by structural alignment as a route to analogical learning. Journal of Economic Behavior & Organization, 57, 29–48.

    Article  Google Scholar 

  • Mandrin, P., & Preckel, D. (2009). Effect of similarity-based guided discovery learning on conceptual performance. School Science and Mathematics, 109(3), 133–145.

    Article  Google Scholar 

  • Marchant, G. (1989). Analogical reasoning and hypothesis generation in auditing. The Accounting Review, 64(3), 500–513.

    Google Scholar 

  • Markman, A. B., & Gentner, D. (2001). Thinking. Annual Review of Psychology, 52, 223–247.

    Article  Google Scholar 

  • Mason, L. (2004). Fostering understanding by structural alignment as a route to analogical learning. Instructional Science, 32, 293–318.

    Article  Google Scholar 

  • McCombs, B. L., & Marzano, R. J. (1990). Putting the self-regulated learning: The self as agent in integrating will and skill. Educational Psychologist, 25(1), 51–69.

    Article  Google Scholar 

  • Mokhtari, K., & Reichard, C. A. (2002). Assessing students’ metacognitive awareness of reading skills. Journal of Educational Psychology, 94(2), 249–259.

    Article  Google Scholar 

  • Paivio, A. (1990). Mental representations. New York: Oxford University Press.

    Google Scholar 

  • Paris, S. G. (1986). Teaching children to guide reading and learning. In T. Raphael (Ed.), Contexts of school-based literacy (pp. 115–130). NY: Random House.

    Google Scholar 

  • Paris, S. G., & Winograd, P. (1990). Metacognition in academic learning and instruction. In B. F. Jones (Ed.), Dimension of thinking and cognitive instruction (pp. 15–44). Hillsdale, NJ: Erlbaum.

    Google Scholar 

  • Perkins, D. N., & Salomon, G. (1988). Teaching for transfer. Educational Leadership, 46(1), 22–32.

    Google Scholar 

  • Perkins, D. N., & Salomon, G. (1992). Transfer of learning. In International encyclopedia of education. Oxford: Pergamon Press.

    Google Scholar 

  • Perkins, D. N., & Salomon, G. (1996). Learning transfer. In A. C. Tuijnman (Ed.), International encyclopedia of adult education and training (2nd ed., pp. 422–427). Tarrytown, NY: Pergamon.

    Google Scholar 

  • Phelps, R., Ellis, A., & Hase, S. (2002). The role of metacognitive and reflective learning processes in developing capable computer users. Paper presented at the 18th annual conference of the Australasian Society for Computers in Learning in Tertiary Education (ASCILITE) (pp. 481–490), Melbourne.

    Google Scholar 

  • Pintrich, P. R. (2002). The role of metacognitive knowledge in learning, teaching and assessing. Theor into Practice, 41(4), 219–225

    Article  Google Scholar 

  • Reeves, L. M., & Weisberg, R. W. (1993). On the concrete nature of human thinking: Content and context in analogical transfer. Educational Psychology, 13(3/4), 245–258.

    Article  Google Scholar 

  • Reitman, W. R. (1965). Cognition and thought. New York: Wiley.

    Google Scholar 

  • Resnick, L. B. (1987, December). Learning in school and out. Educational Researcher, 16, 13–20.

    Google Scholar 

  • Royer, J. M. (1986). Designing instruction to produce understanding: An approach based on cognitive theory. In G. D. Phye & T. Andre (Eds.), Cognitive classroom learning: Understanding, thinking and problem solving (pp. 83–117). New York: Academic Press.

    Google Scholar 

  • Royer, J. M., Mestre, J. P., & Dufresne, R. J. (2005). Introduction: Framing the transfer problem. In J. P. Mestre (Ed.), Transfer of learning: From a modern multidisciplinary perspective. Greenwich, CT: Information Age Publishing.

    Google Scholar 

  • Satchwell, R. E. (1997). Functional flow diagrams to enhance technical system understanding. Journal of Industrial Teacher Education, 34(2), 50–81.

    Google Scholar 

  • Schoenfeld, A. H. (1987). What’s all the fuss about metacognition? In A. H. Schoenfeld (Ed.), Cognitive science and mathematics education (pp. 189–215). Hillsdale, NJ: Erlbaum.

    Google Scholar 

  • Schoenfeld, A. H. (1999). Looking toward the 21st century: Challenges of educational theory and practice. Educational Researcher, 28(7), 4–14.

    Google Scholar 

  • Simon, H. A. (1973). The structure of ill-structured problems. Artificial Intelligence, 4, 145–180.

    Article  Google Scholar 

  • Spector, J. M. (2000). System dynamics and interactive learning environments: Lessons learned and implications for the future. Simulation & Gaming, 31(4), 509–512.

    Article  Google Scholar 

  • Spiro, R. J., Feltovich, P. J., Coulson, R. L., & Anderson, D. K. (1989). Multiple analogies for complex concepts: Antidotes for analogy-induced misconception in advanced knowledge acquisition. In S. Vosniadou & A. Ortony (Eds.). Similarity and analogical reasoning (pp. 498–531). Cambridge, MA: Cambridge University Press.

    Google Scholar 

  • Steif, P. S., Lobue, J. M., Kara, L. B., & Fay, A. L. (2010). Improving problem solving performance by inducing talk about salient problem features. Journal of Engineering Education, 99(2), 135–142.

    Google Scholar 

  • Sutton, M. J. (2003). Problem representation, understanding and learning transfer: Implications for technology education research. Journal of Industrial Teacher Education, 40(4), 47–61.

    Google Scholar 

  • Takahashi, Y., & Murata, A. (2001). Role of metacognition to promote strategy transfer in problem solving. Proceedings of IEEE International Conference on Systems, Man and Cybernetics, 5, 2787–2792. doi:10.1109/ICSMC.2001.971931

    Google Scholar 

  • Thorndike, E. L. (1924). Mental discipline in high school studies. Journal of Educational Psychology, 15, 1–22.

    Article  Google Scholar 

  • Thorndike, E. L., & Woodworth, R. S. (1901). The influence of improvement in one mental function upon the efficiency of other functions. Psychological Review, 8, 247–261.

    Article  Google Scholar 

  • Velcro Industries N. V. (2010). Who is Velco USA Inc.? Retrieved May 17, 2010, fromhttp://www.velcro.com/index.php?page=company

  • Vokey, J. R., & Higham, P. A. (2005). Abstract analogies and positive transfer in artificial grammar learning. Canadian Journal of Experimental Psychology, 59(4), 54–61.

    Google Scholar 

  • White, B. Y., & Frederiksen, J. R. (1986). Intelligent tutoring systems based upon qualitative model evaluations. Available at http://www.aaai.org/Papers/AAAI/1986/AAAI86-052.pdf

  • Wong, E. D. (1993). Self-generated analogies as a tool for construction and evaluating explanations of scientific phenomena. Journal of Research in Science Teaching, 30, 367–380.

    Article  Google Scholar 

  • Zhang, J. (1997). The nature of external representations in problem solving. Cognitive Science, 21, 179–217.

    Article  Google Scholar 

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Johnson, S.D., Dixon, R., Daugherty, J., Lawanto, O. (2011). General Versus Specific Intellectual Competencies. In: Barak, M., Hacker, M. (eds) Fostering Human Development Through Engineering and Technology Education. International Technology Education Studies, vol 6. SensePublishers. https://doi.org/10.1007/978-94-6091-549-9_4

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