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1994 Book DidacticsOfMathematicsAsAScien
view (2nd ed.). New York: Holt, Rinehart & Winston.
Cabri Géomètre (1987). [Computer program]. Université de Grenoble, France (IMAG, BP 53X). Goldenberg, P. (1988). Mathematics, metaphors and human factors: Mathematical, techni- cal and pedagogical challenges in the educational use of graphical representations of functions. Journal of Mathematical Behaviour, 7(2), 135-173. Linn, M. C., & Nachmias, R. (1987). Evaluations of science laboratory data: The role of computer-presented information. Journal of Research in Science Teaching, 24(5), 491- 506. Papert, S. (1980). Mindstorms. Brighton, Sussex: Harvester Press. Pratt, D. (1988). Taking a dive with Newton. Micromath, 4(1), 33–35. Skemp, R. R. (1979). Intelligence. Learning and action. Chichester, Sussex: Wiley. Tall, D. O. (1989). Concept images, generic organizers, computers and curriculum change. For the Learning of Mathematics, 9(3), 37–42. Tall, D. O., & Winkelmann, B., (988). Hidden algorithms in the drawing of discontinuous functions. Bulletin of the I.M.A., 24, 111-115. DAVID TALL Tall, D. O., Blokland, P., & Kok, D. (1990). A graphic approach to the calculus. Pleasantville, NY: Sunburst. [also published in German as Graphix by CoMet Verlag, Duisburg, and in French as Graphe, by Nathan, Paris] The Geometer’s Sketchpad. (1992). [Computer program]. Visual Geometry Project. Berkeley, CA: Key Curriculum Press. Thompson, P. (1992). Blocks microworld. [Computer program]. University of California, San Diego, CA. 199 THE ROLE OF COGNITIVE TOOLS IN MATHEMATICS EDUCATION Tommy Dreyfus Holon 1. INTRODUCTION Imagine a group of junior high school teachers or students; suppose you are asked to teach them something relevant and interesting and you decide to introduce them to some elementary notions about chaotic dynamical sys- tems. One possible way to do this would be to roughly follow the approach taken by Devaney (1990); this approach starts by letting students explore what can happen when a function such as is repeatedly ap- plied to an initial value among the observed phenomena are attractive and repulsive fixpoints and periodic cycles as well as chaotic behavior. A typical activity in investigating the behavior of iterated applications of a function might include, as a first stage, the computation of long sequences of numbers for various values of Because the structure of such a number sequence is grasped more easily in a holistic representation, it would be ad- vantageous, in a second stage, to graph the sequence as a function of the number of iterations. Moreover, in a third stage, the parameter c needs to be varied, and the effects of this, variation investigated. One might want to do this dynamically by looking at the effect of continuously changing the pa- rameter c on the global shape of the graph of the sequence. Finally, in a fourth stage, one might want to show that fixpoints, cycles, attraction, and repulsion can be explained by using a completely different graphical repre- sentation of the process, namely spiderweb diagrams; these are diagrams obtained by finding and connecting the sequence of points in a Cartesian coordinate system in which the graphs of y = f(x) and y = x have been drawn. Let us now look at the support provided by a computer tool in each of the four stages. The first two stages – computing the sequences and graphing them – are so time-consuming as to make them virtually impossible without the computational power of a computer. But computer use in these stages is trivial, in the sense that the computational power only helps one to carry out many more explorations much more quickly than would otherwise be pos- sible. The computer acts as an amplifier. In the third and fourth stages, how- R. Biehler, R. W. Scholz, R. Sträßer, B. Winkelmann (Eds.), Download 5.72 Mb. Do'stlaringiz bilan baham: |
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