SIMCALC: Accelerating students’ engagement with the mathematics of change

Innovations in Science and Mathematics Education: Advanced Designs for Technologies of Learning

Volumn , Issue , 2012, Pages 47-76

  Roschelle, Jeremy ^a   Kaput, James J ^b   Stroup, Walter ^c  

^a SRI INTERNATIONAL   (United States)

^b UNIVERSITY OF MASSACHUSETTS DARTMOUTH   (United States)

^c UNIVERSITY OF TEXAS AT AUSTIN   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

EID: 85070943500     PISSN: None     EISSN: None     Source Type: Book    
DOI: 10.4324/9781410602671-9     Document Type: Chapter

References (51)

1. Bochner, S. (1966). The role of mathematics in the rise of science. Princeton, NJ: Princeton University Press.
2. Carpenter, T.P., Ansell, E., Franke, M.L., Fennema, E., & Weisbeck, L. (1993). Models of problem solving: A study of kindergarten children’s problem-solving processes. Journal for Research in Mathematics Education, 24(5), 427-440.
3. Carpenter, T.P., Fennema, E., Peterson, P.L., & Carey, D.A. (1988). Teachers’ pedagogical content knowledge of students’ problems solving in elementary arithmetic. Journal for Research in Mathematics Education, 19(5), 385-401.
4. Carpenter, T., Fennema, E., & Franke, M. (1996). Cognitively guided instruction: A knowledge base for reform in primary mathematics instruction. Elementary School Journal, 97(1), 3-20.
5. Confrey, J. (1991). Function Probe [Computer software], Ithaca, NY: Department of Education, Cornell University.
6. Csikszentmihalyi, M. (1990). Flow: The psychology of optimal experience. New York: ElarperCollins.
7. diSessa, A. A. (1986). Artificial worlds and real experience. Instructional Science, 14, 201-221.
8. Duckworth, E. (1991). Twenty-four, forty-two, and I love you: Keeping it complex. Harvard Educational Review, 61(1), 1-24.
9. Elardin, J. & Ziebarth, J. (1996). Digital technology and its impact on education [Online], Washington, DC: Department of Education. Available: http://www.ed.gov/Technology/Futures/hardin.html
10. Goldenberg, P. (1995). Multiple representations: A vehicle for understanding understandings. In D.N. Perkins, J.L. Schwartz, M.M. West, & M.S. Wiske (Eds.), Software goes to school (pp. 155-171). New York: Oxford University Press.
11. Gordin, D. N., & Pea, R. D. (1995). Prospects for scientific visualization as an educational technology. Journal of the Learning Sciences, 4(3), 249.
12. Elickman, L.A. (1990). John Dewey’s pragmatic technology. Indianapolis: Indiana University Press.
13. Elorwitz, P., & Barowy, W. (1994). Designing and using open-ended software to promote conceptual change. Journal of Science Education and Technology, 3, 161-185.
14. Kaput, J. (1992). Technology and mathematics education. In D. Grouws (Ed.), Uhandbook of research on mathematics teaching and learning (pp. 515-556). New York: Macmillan.
15. Kaput, J. (1994). Democratizing access to calculus: New routes using old roots. In A. Schoenfeld, (Ed.), Mathematical thinking and problem solving (pp. 77-155). Elillsdale, NJ: Lawrence Erlbaum Associates.
16. Kaput, J., & Roschelle, J. (1996). Connecting the connectivity and the component revolutions to deep curriculum reform [Online], Washington, DC: Department of Education. Available: http://www.ed.gOv/Technology/Futures/kaput.html
17. Larkin, J. H., & Simon, El. A. (1987). Why a diagram is (sometimes) worth 10,000 words. Cognitive Science, 11, 65-100.
18. Latour, B. (1986). Visualization and cognition: Thinking with eyes and hands. Knowledge and Society: Studies in the Sociology of Culture, 6, 1-40.
19. Laurillad, D. (1992). Learning through collaborative computer simulations. British Journal of Educational Technology, 23(3), 164-171.
20. Levin, H., & Hopfenberg, W. (1991). Don’t remediate: Accelerate! Principal, 70(3), 11-13.
21. Lynch, M. (1985). Discipline and the material form of images. An analysis of scientific visibility. Social Studies of Science, 15, 37-66.
22. McDermott, J. J. (1981). The philosophy of John Dewey. Chicago: University of Chicago Press.
23. Meira, L. (1991). Exploration of mathematical sense-making: An activity oriented account of children’s use and design of material displays. Unpublished doctoral dissertation, Berkeley: University of California.
24. Miller, A. I. (1986). Imagery and scientific thought. Cambridge, MA: MIT Press.
25. Mokris, J. R., & Tinker, R. F. (1987). The impact of microcomputer-based labs on children’s ability to interpret graphs. Journal of Research in Science Teaching, 24(4), 369-383.
26. Monk, S., & Nemirovsky, R. (1994). The case of Dan: Student construction of a functional situation through visual attributes. Research in Collegiate Mathematics Education, 4, 139-168.
27. Moschovich, J. N. (1996). Moving up and getting steeper: Negotiating shared descriptions of linear graphs. Journal of the Learning Sciences, 5(3), 239-277.
28. Nemirovsky, R. (1994). On ways of symbolizing: The case of Laura and velocity sign. The Journal of Mathematical Behavior, 13, 389-422.
29. Nemirovsky, R. (1996). Mathematical narratives. In N. Bednarz, C. Kieran, & L. Lee (Eds.), Approaches to algebra: Perspectives for research and teaching (pp. 197-223). Dordrecht, The Netherlands: Kluwer Academic Publishers.
30. Nemirovsky, R., Kaput, J., & Roschelle, J. (1998). Enlarging mathematical activity from modeling phenomena to generating phenomena. Proceedings of the 22nd annual meeting of the International Group for the Psychology of Mathematics Education, A. Oliver & K. Newstead (Eds). South Africa: University of Stellenbosch.
31. Nemirovsky, R., & Noble, T. (in press). Mathematical visualization and the place where we live. Educational Studies of Mathematics.
32. Nemirovsky, R., Tierney, C., & Wright, T. (in press). Body motion and graphing. Cognition and Instruction.
33. Noble, T., Nemirovsky, R., Solomon, J., & Cook, J. (1995, October). Impossible graphs. Paper presented at the Annual Meeting of the North American Chapter of the International Group for the Psychology of Mathematics Education, Columbus, OE1.
34. Norman, D. A. (1993). Things that make us smart. New York: Addison-Wesley.
35. Reddy, M. (1979). The conduit metaphor: A case of frame conflict in our language about language. In A. Ortony (Ed.), Metaphor and thought (pp. 284-310). Cambridge, England: Cambridge University Press.
36. Rieber, L.P. (1995). A historical review of visualization in human cognition. Educational Technology Research and Development, 43(1), 45-56.
37. Roschelle, J. (1991). Students’ construction of qualitative physics knowledge: Learning about velocity and acceleration in a computer microworld. Unpublished doctoral dissertation, University of California, Berkeley.
38. Roschelle, J. (1992). Learning by collaborating: Convergent conceptual change. Journal of the Learning Sciences, 2(3), 235-276.
39. Roschelle, J. (1996). Designing forcognitive communication: Epistemic fidelity ormediating collaborating inquiry. In D.L. Day & D.K. Kovacs (Eds.), Computers, communication & mental models (pp. 13-25). London: Taylor & Francis.
40. Roschelle, J., & Kaput, J. (1996). Educational software architecture and systemic impact: The promise of component software. Journal of Educational Computing Research, 14(3), 217-228.
41. Roschelle, J., Kaput, J., & DeLaura, R. (1996). Scriptable applications: Implementing open architectures in learning technology. In P. Carlson & F. Makedon (Eds.), Proceedings of ED-MEDIA 96-World conference on educational multimedia and hypermedia (pp. 599-604), American Association of Computers. Charlottesville, VA: AACE.
42. Roschelle, J., & Jackiw, N. (in press). Technology design as educational research: Interweaving imagination, inquiry & impact. In A. Kelly & R. Lesh (Eds.), Research design in mathematics & science education. Amsterdam: Kluwer.
43. Roth, W.M. (1997, March 28). Computers and cognition: Towards a phenomenology of learning in the presence of computers. Paper presented at the Annual Meeting of the American Educational Research Association, Chicago, IL.
44. Snir, J., Smith, C., & Grosslight, L. (1993). Conceptually-enhanced simulations: A computer tool for science teaching. Journal of Science Education and Technology, 2(2), 373-388.
45. Stroup, W. (1996). Embodying a nominalist constructivism: Making graphical sense of learning the calculus of how much and how fast. Unpublished doctoral dissertation, Elarvard University, Cambridge, MA.
46. Thompson, A.G., & Thompson, P.W. (1995). Talking about rates conceptually: A teacher’s struggle. Journal for Research in Mathematical Education, 27(1), 2-24.
47. Thornton, R. (1987). Tools for scientific thinking: Microcomputer based laboratory for physics teaching. Physics Education, 22,230-238.
48. Thornton, R. (1992). Enhancing and evaluating students’ learning of motion concepts. In A. Tiberghien, & H. Mandl (Eds.), Physics and learning environments (NATO Science Series). New York: Springer-Verlag.
49. Tucker, T. (1990). Priming the calculus pump: Innovations and resources. Washington, DC: MAA.
50. U.S. Department of Education. (1996). The Condition of Education (Supplemental Table 29-6). National Center For Education Statistics, Washington, DC [Producer and Distributor. Online], Available: http://www.ed.gov/NCES/pubs/ce/c9629d06.html
51. White, B. (1993). Thinkertools: Casual models, conceptual change, and science education. Cognition and Instruction, 10, 1-100.