No data available.
Please log in to see this content.
You have no subscription access to this content.
No metrics data to plot.
The attempt to load metrics for this article has failed.
The attempt to plot a graph for these metrics has failed.
Using visualizations to teach electrostatics
1.M. C. Linn, “The knowledge integration perspective on learning and instruction,” in The Cambridge Handbook of the Learning Sciences, edited by R. K. Sawyer (Cambridge University Press, New York, in press).
3.D. B. Clark and M. C. Linn, “Scaffolding knowledge integration through curricular depth,” J. Learn. Sci.1050-8406 12, 451–494 (2003).
4.E. A. Davis, “Creating critique projects,” in Internet Environments for Science Education, edited by M. Linn, E. Davis, and P. Bell (Lawrence Erlbaum Associates, Mahwah, NJ, 2004).
5.E. A. Davis and J. Krajcik, “Designing educative curriculum materials to promote teacher learning,” Educ. Res. 34, 3–14 (2005).
6.M. C. Linn and B.-S. Eylon, “Knowledge integration and displaced volume,” J. Sci. Educ. Technol.1059-0145 9, 287–310 (2000).
7.M. C. Linn and S. Hsi, Computers, Teachers, Peers: Science Learning Partners (Lawrence Erlbaum Associates, Mahwah, NJ, 2000).
8.M. R. Abraham, V. M. Williamson, and S. L. Westbrook, “A cross-age study of the understanding of five chemistry concepts,” J. Res. Sci. Teach.0022-4308 31, 147–165 (1994).
9.A. H. Haidar and M. R. Abraham, “A comparison of applied and theoretical knowledge of concepts based on the particulate nature of matter,” J. Res. Sci. Teach.0022-4308 28, 919–938 (1991).
10.R. Ben-Zvi, B.-S. Eylon, and J. Silbestein, “Is an atom of copper malleable?,” J. Chem. Educ.0021-9584 63, 64–66 (1986).
11.C. S. Miller, J. F. Lehman, and K. R. Koedinger, “Goals and learning in microworlds,” Cogn. Sci.0364-0213 23, 305–336 (1999).
13.J. R. Frederiksen and B. Y. White, “Mental models and understanding: A problem for science education,” in New Directions in Educational Technology, edited by E. Scanlon and T. O’Shea (Springer-Verlag, New York, 1992), Vols. 211–226.
15.J. D. Slotta and M. T. H. Chi, “Understanding constraint-based processes: A precursor to conceptual change in physics,” in Proceedings of the Eighteenth Annual Conference of the Cognitive Science Society, edited by G. W. Cottrell (Lawrence Erlbaum Associates, Mahwah, NJ, 1996).
16.A. A. diSessa, Changing Minds: Computers, Learning and Literacy (MIT Press, Cambridge, MA, 2000).
17.M. C. Linn and B.-S. Eylon, “Science education: Integrating views of learning and instruction,” in Handbook of Educational Psychology 2nd ed. edited by P. A. Alexander and P. H. Winne (Lawrence Erlbaum Associates, Mahwah, NJ, in press).
19.A. Pallant and R. Tinker, “Reasoning with atomic-scale molecular dynamic models,” J. Sci. Educ. Technol.1059-0145 13, 51–66 (2004).
21.M. C. Linn, D. Clark, and J. D. Slotta, “WISE design for knowledge integration,” Sci. Educ.0036-8326 87, 517–538 (2003).
22.M. C. Linn, “WISE design for lifelong learning—Pivotal cases,” in Cognition, Education and Communication Technology, edited by P. Gärdenfors and P. Johannsson (Lawrence Erlbaum Associates, Mahwah, NJ, 2005), pp. 223–256.
23.How People Learn: Brain, Mind, Experience, and School, edited by J. D. Bransford, A. L. Brown, and R. R. Cocking (National Research Council, Washington, DC, 1999).
24.R. White and R. Gunstone, Probing Understanding (The Falmer Press, New York, 1992).
25.D. C. McClelland, “The knowledge-testing educational complex strikes back,” Am. Psychol.0003-066X 49, 66–69 (1994).
26.N. B. Songer, “Exploring learning opportunities in coordinated network-enhanced classrooms: A case of kids as global scientists,” J. Learn. Sci.1050-8406 5, 297–327 (1996).
27.A. Steinberg, “Girls talk; Boys talk more,” Harvard Educ. Lett. 7, 6–8 (1991).
28.K. Cummings, J. Marx, R. Thornton, and D. Kuhl, “Evaluating innovation in studio physics,” Am. J. Phys.0002-9505 67, S38–S44 (1999).
29.M. L. Gick and K. J. Holyoak, “Analogical problem solving,” Cognit Psychol.0010-0285 12, 306–355 (1980).
30.S. Ainsworth and N. Van Labeke, “Multiple forms of dynamic representation,” Learn. Instr.0959-4752 14, 241–255 (2004).
31.B. Y. White and J. R. Frederiksen, “Technological tools and instructional approaches for making scientific inquiry accessible to all,” in Innovations in Science and Mathematics Education, edited by M. J. Jacobson and R. B. Kozma (Lawrence Erlbaum Associates, Mahwah, NJ, 2000).
32.M. Hegarty, J. Quilici, N. H. Narayanan, S. Holmquist, and R. Moreno, “Multimedia instruction: Lessons from evaluation of a theory-based design,” J. Educ. Multimed. Hypermedia1055-8896 8, 119–150 (1999).
33.R. B. Kozma, “The use of multiple representations and the social construction of understanding in chemistry,” in Innovations in Science and Mathematics Education: Advanced Designs for Technologies of Learning, edited by M. Jacobson and R. Kozma (Lawrence Erlbaum Associates, Mahwah, NJ, 2000).
34.N. B. Songer and M. C. Linn, “How do students’ views of science influence knowledge integration?,” J. Res. Sci. Teach.0022-4308 28, 761–784 (1991).
35.K. Varma, “Supporting teachers enacting inquiry based technology: An emergent professional development model: Technology enhanced learning in science,” paper presented at the TELS meeting prior to the annual meeting of the American Educational Research Association, Montreal, 2005 (unpublished).
37.M. C. Linn and J. Holmes, “TELS design of science curriculum materials design process: Technology enhanced learning in science,” paper presented at the TESL meeting prior to the annual meeting of the American Educational Research Association, Montreal 2005 (unpublished).
38.D. E. Penner, N. D. Giles, R. Lehrer, and L. Schauble, “Building functional models: Designing an elbow,” J. Res. Sci. Teach.0022-4308 34, 125–143 (1997).
39.P. F. Mottelay, Bibliographical History of Electricity and Magnetism (Charles Griffin & Co., London, 1922).
40.In this experiment, Stephen Gray suspended a -old boy from the ceiling, placed a stand holding flakes of brass leaf beneath his head and held a charged glass tube near his feet. Gray described the result as follows: “Upon the tube’s being rubbed, and held near his feet without touching them, the leaf-brass was attracted by the boy’s face with much vigor, so as to rise to the height of eight, and sometimes ten inches,” For a full description of this experiment, see S. Gray, “A letter to Cromwell Mortimer M. D. Secr. R. S. containing several experiments concerning electricity,” Philosophical Transactions (1683–1775), 37, 18–44 (1731).
42.For those unfamiliar with this statistical technique see D. Nolan and T. P. Speed, Mathematical Statistics Through Applications (Springer-Verlag, Berlin, 2000).
43.In our notation indicates the mean, indicates the standard deviation, indicates the ratio, df indicates the degrees of freedom, and indicates the probability. See Ref. 42 for an explanation of these quantities. The low value indicates that there is a very low probability that the observed increase from pretest to post-test can be explained by chance. Such a low value indicates that the observed increase is a significant result.
44.See Fig. 5 for the text and context of these embedded assessment prompts.
45.These models showed an isolated material with equivalent numbers of electrons and positive ions and another with a significant excess of negative charge. When run, the electrons are attracted to the positive ions. In the model of the negative material the excess electrons spread to the outside edge of the model container.
46.See Fig. 5 for the text of the assessment given on the pretest and post-test to reflect students’ understanding of induction.
47.B.-S. Eylon and U. G. Ganiel, “Macro-micro relationships: The missing link between electrostatics and electrodynamics in students’ reasoning,” Int. J. Sci. Educ.0950-0693 12, 79–94 (1990).
48.B. Sherwood and R. Chabay, “Electrical interactions and the atomic structure of matter: Adding qualitative reasoning to a calculus-based electricity and magnetism course,” in Proceedings of the NATO Advanced Research Workshop on Learning Electricity or Electronics with Advanced Educational Technology, edited by M. Caillot (Springer-Verlag, Berlin, 1991), Vols. 23–35.
50.M. Clancy, N. Titterton, C. Ryan, J. Slotta, and M. Linn, “New roles for students, instructors and computers in a lab-based introductory programming course,” ACM SIGCSE Bulletin 35, 132–136 (2003).
51.C. H. Crouch, A. P. Fagen, J. P. Callan, and E. Mazur, “Classroom demonstrations: Learning tools or entertainment?,” Am. J. Phys.0002-9505 72, 835–838 (2004).
Article metrics loading...
Full text loading...
Most read this month