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The role of epistemology in instructional design

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Abstract

The Generic Tutoring Environment (GTE) is an authoring environment for the development of courseware. Claims with regard to GTE's epistemological foundations are analyzed and explored. GTE's assumptions are thereby shown to reveal a somewhat reductionist bias, which is to say that GTE has placed emphasis on computational approaches to instructional modeling. Nevertheless, pragmatic concerns with regard to GTE's utility and effectiveness are of interest to the developers and to other researchers in the fields of courseware design and instructional modeling. In general, GTE is seen to be both ambitious and powerful. While GTE does not truly provide an epistemology of instructional design, it does provide a powerful framework within which effective tutors can be efficiently generated.

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References

  • Ericsson, K.A. & Smith, J., eds. (1991). Toward a General Theory of Expertise: Prospects and Limits. New York: Cambridge University Press.

    Google Scholar 

  • Gagné, R.M. (1985). Conditions of Learning (4th Ed.).New York: Holt, Rinehart, and Winston.

    Google Scholar 

  • Gagné, R.M. (1995). Learning processes and instruction. Training Research Journal 1: 17–28.

    Google Scholar 

  • Grimstad Group (1995). Applying system dynamics to courseware development. Computers in Human Behavior 11(2): 325–339. [The Grimstad Group consists of P.I. Davidsen, J.J. Gonzalez, D.J. Muraida, J.M. Spector & R.D. Tennyson.]

    Google Scholar 

  • Hannafin, M.J., Hall, C., Land, S. & Hill, J. (1994). Larning in open-ended environments: Assumptions, methods, and implications. Educational Technology 34(8): 48–55.

    Google Scholar 

  • Harward, V.J. & Lerman, S.R. (1994). The Athena Muse???Multimedia Environment. Internal Technical Paper. Cambridge, MA: MIT Center for Educational Computing Intitiatives.

    Google Scholar 

  • Kozma, R.B. (1994). Will media influence learning? Reframing the debate. Instructional Science 42(2): 7–19.

    Google Scholar 

  • Krammer, H.P.M., Bosch, J. & Dijkstra, S. (1995). Scalability in instructional method specification: An experiment-directed approach, in R.D. Tennyson & A. Barron, eds., Automating Instructional Design: Computer-Based Development and Delivery Tools. Berlin: Springer-Verlag.

    Google Scholar 

  • Merrill, M.D. (1993). An integrated model for automating instructional design and delivery, in J.M. Spector, M.C. Polson & D.J. Muraida, eds., Automating Instructional Design: Concepts and Issues. Englewood Cliffs, NJ: Educational Technology.

    Google Scholar 

  • Muraida, D.J., Spector, J.M., O'Neil, H.F. & Marlino, M.R. (1993). Evaluation, in J.M. Spector, M.C. Polson, & D.J. Muraida, eds., Automating Instructional Design: Concepts and Issues. Englewood Cliffs, NJ: Educational Technology.

    Google Scholar 

  • Paquette, G., Aubin, C. & Crevier, F. (1994). An intelligent support system for course design. Educational Technology 34(9): 50–57.

    Google Scholar 

  • Perez, R.S. & Neiderman, E.C. (1992). Modeling the expert training developer, in R.J. Seidel & P. Chatelier, eds., Advanced Training Technologies Applied to Training Design. New York: Plenum Press.

    Google Scholar 

  • Reigeluth, C.M., ed. (1983). Instructional-Design Theories and Models: An Overview of Their Current Status. Hillsdale, NJ: Erlbaum.

  • Resnick, L.B., ed. (1989). Knowing, Learning, and Instruction. Hillsdale, NJ: Lawrence Erlbaum.

  • Rowland, G. (1992). What do instructional designers actually do? An initial investigation of expert practice. Performance Improvement Quarterly 5(2): 65–86.

    Google Scholar 

  • Simon, H.A. (1969). The Sciences of the Artificial. Cambridge, MA: MIT Press.

    Google Scholar 

  • Spector, J.M. (1994). Integrating instructional science, learning theory and technology, in R.D. Tennyson, ed., Automating Instructional Design, Development, and Delivery. Berlin: Springer-Verlag.

    Google Scholar 

  • Spector, J.M., Arnold, E.M. & Wilson A.S. (1996). A Turing test for automatically generated instruction. Journal of Structural Learning 12(4): 301–313.

    Google Scholar 

  • Tennyson, R.D. (1994). Knowledge base for automated instructional system development, in R.D. Tennyson, ed., Automating Instructional Design, Development, and Delivery. Berlin: SpringerVerlag.

    Google Scholar 

  • Van Marcke, K. (1992). A generic task model for instruction, in S. Dijkstra, ed., Instructional Models in Computer-Based Learning Environments (NATO ASI Series, Vol. F104.) Berlin: Spinger-Verlag.

    Google Scholar 

  • Van Marcke, K. (1996). GTE: An epistemological approach to instructional modelling. Instructional Science.

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Spector, J.M. The role of epistemology in instructional design. Instructional Science 26, 193–203 (1998). https://doi.org/10.1023/A:1003023701635

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