A model of instruction described by Wenger (1987) identifies three elements that are active during instruction: the mental model the instructor wishes to share with the learner, the external experience used to communicate the mental model, and the evolving mental model of the learner. Gibbons (2003a), writing in response to Seel (2003), noted this three-part description as a bridge concept relating learning and instruction. This view has important practical implications for designers of instruction. For example, Gibbons and Rogers (in press) propose that there exists a natural layered architecture within instructional designs that corresponds with instructional functions. Among these layers is the content layer, which determines the structural form in which learnable subject-matter is stored and supplied to the learner. This may include the expression of the content in terms of tasks, semantic networks, rules, or other structures. The designer’s com- mitment at the content layer strongly constrains all other parts of the design, making some future decisions imperative, some irrelevant, and defining the range of possibilities for still others. One possible content layer commitment is to select the model structure as the basic unit of analysis. Having made the model the primary content structure commitment influences designer choices within other layers. This chapter describes the implications for designers of a model content commit ment. It describes the constraints automatically placed on other layers of the design.
Access provided by Autonomous University of Puebla. Download to read the full chapter text
Chapter PDF
Similar content being viewed by others
References
Baldwin, C. Y., & Clark, K. B. (2000). Design rules, vol. 1: The power of modularity. Cambridge, MA: MIT Press.
Bransford, J. D., Brown, A. L., & Cocking, R. R. (Eds.). (2000). How people learn: Brain, mind, experience, and school. Washington, D. C.: National Academy Press.
Brown, A. L., & Palincsar, A. S. (1989). Guided, cooperative learning and individual knowledge acquisition. In L. Resnick (Ed.), Knowing, learning, and instruction: Essays in honor of Robert Glaser. Hillsdale, NJ: Lawrence Erlbaum Associates.
Carbonell, J. (1970). AI in CAI: An artificial intelligence approach to computer-assisted instruction. IEEE transactions on man-machine systems, 11, 190-202.
Clancey, W. J. (1984a). Extensions to rules for explanation and tutoring. In B. G. Buchanan & E. H. Shortliffe (Eds.), Rule-based expert systems: The MYCIN experiments of the Stanford heuristic programming project. Reading, MA: Addison-Wesley.
Clancey, W. J. (1984b). Use of MYCIN’s rules for tutoring. In B. G. Buchanan & E. H. Shortliffe (Eds.), Rule-based expert systems: The MYCIN experiments of the Stanford heuristic programming project. Reading, MA: Addison-Wesley.
Collins, A., Warnock, E., & Passafiume, J (1975). Analysis and synthesis of tutorial dialogues. In G. Bower (Ed.), The psychology of learning and motivation (Vol. IX). New York: Academic Press.
Crawford, C. (2003). The art of interactive design. San Francisco, CA: No Starch Press.
Drake, L., Mills, R., Lawless, K., Curry, J., & Merrill, M. D. (1998). The role of explanations in learning environments. Paper presented at the annual meeting of the American Educational Research Association, San Diego, CA.
Fox, B. A. (1993). The human tutorial dialogue project: Issues in the design of instructional systems. Hillsdale, NJ: Lawrence Erlbaum Associates.
Gibbons, A. (2001). Model-centered instruction. Journal of structural learning and intelligent systems, 14(4), 511-540.
Gibbons, A. S. (2003a). Model-centered learning and instruction: Comments on Seel (2003). Technology, instruction, cognition, and learning, 1(3), 291-9.
Gibbons, A. S. (2003b). What and how do designers design?: A theory of design structure. Tech trends, 47(5), 22-27.
Gibbons, A. S., & Fairweather, P. G. (2000). Computer-based instruction. In S. Tobias & J. D. Fletcher (Eds.), Training and retraining: A handbook for business, industry, government, and the military. New York: Macmillan Reference USA.
Gibbons, A. S., Fairweather, P. G., Anderson, T., & Merrill, M. D. (1997). Simulation and computer-based instruction: A future view. In C. R. Dills & A. J. Romiszowski (Eds.), Instructional development paradigms (pp. 769-805). Englewood Cliffs, NJ: Educational Technology Publications.
Gibbons, A. S., Lawless, K. A., Anderson, T. A., & Duffin, J. R. (2001). The web and modelcentered instruction. In B. R. Khan (Ed.), Web-based training. Englewood Cliffs, NJ: Educational Technology Publications.
Gibbons, A. S., McConkie, M., Seo, K. K., & Wiley, D. (in press). Theory for the design of instructional simulations and microworlds. In C. M. Reigeluth & A. Carr-Chellman (Eds.), instructional-design theories and models, Volume III. Mahwah, NJ: Erlbaum.
Gibbons, A. S., & Rogers, P. C. (in press). The architecture of instructional theory. In C. M. Reigeluth & A. Carr-Chellman (Eds.), Instructional-design theories and models, Volume III. Mahwah, NJ: Erlbaum.
Horn, R. E. (1997). Structured writing as a paradigm. In C. R. Dills & A. J. Romiszowski (Eds.), Instructional development paradigms. Englewood Cliffs, NJ: Educational Technology Publications.
Merrill, M. D. (1994). The descriptive component display theory. In M. D. Merrill & D. G. Twitchell (Eds.), Instructional design theory. Englewood Cliffs, NJ: Educational Technology Publications.
Munro, A., Surmon, D., & Pizzini, Q. (2006) . Teaching procedural knowledge in distance learning environments. In R. Perez & H. O Neal (Eds.), Web-based learning: theory, research, and practice. Mahwah, NJ: Lawrence Erlbaum Associates.
Sawyer, R. K. (2006). Analyzing collaborative discourse. In R. K. Sawyer (Ed.), The Cambridge handbook of the learning sciences. Cambridge, UK: Cambridge University Press.
Seel. (2003). Model-centered learning and instruction. Technology, instruction, cognition, and learning, 1(1), 59-85.
Simon, A., & Boyer, E. G. (1974). Mirrors for behavior III: An anthology of observation instruments. Wyncote, PA: Communication Materials Center in Cooperation with Humanizing Learning Program, Research For Better Schools, Inc.
Stokes, P. (2005). Creativity from constraints: The psychology of breakthrough. New York: Springer.
Wenger, E. (1987). Artificial intelligence and tutoring systems. Los Altos, CA: Morgan Kauffmann Publishers.
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2008 Springer Science+Business Media, LLC
About this chapter
Cite this chapter
Gibbons, A.S. (2008). Model-Centered Instruction, the Design and the Designer. In: Ifenthaler, D., Pirnay-Dummer, P., Spector, J.M. (eds) Understanding Models for Learning and Instruction. Springer, Boston, MA. https://doi.org/10.1007/978-0-387-76898-4_8
Download citation
DOI: https://doi.org/10.1007/978-0-387-76898-4_8
Publisher Name: Springer, Boston, MA
Print ISBN: 978-0-387-76897-7
Online ISBN: 978-0-387-76898-4
eBook Packages: Humanities, Social Sciences and LawEducation (R0)