Spatial learning and computer simulations in science

International Journal of Science Education

Volumn 31, Issue 3, 2009, Pages 419-438

  Lindgren, Robb ^a   Schwartz, Daniel L ^a  

^a STANFORD UNIVERSITY   (United States)

Author keywords

Computer simulations; K 12; Perceptual learning; Spatial learning; Undergraduate

Indexed keywords

EID: 61349162393     PISSN: 09500693     EISSN: 14645289     Source Type: Journal    
DOI: 10.1080/09500690802595813     Document Type: Review

References (80)

1. Adcock, O. (2005) LiveChem [Software]
2. Akpan, J. P. and Andre, T. (1999) The effect of a prior dissection simulation on middle school students' dissection performance and understanding of the anatomy and morphology of the frog. Journal of Science Education and Technology, 8:2, pp. 107-121.
3. Anderson, J. R. and Bower, G. H. (1973) Human associative memory, Winston, Washington, DC
4. Apogee Components (2008) RockSim [Software]
5. Barnett, M., Yamagata-Lynch, L., Keating, T., Barab, S. A. and Hay, K. E. (2005) Using virtual reality computer models to support student understanding of astronomical concepts. Journal of Computers in Mathematics and Science Teaching, 24:4, pp. 333-356.
6. Barsalou, L. W. (1999) Perceptual symbol systems. Behavioral and Brain Sciences, 22, pp. 577-660.
7. Baudrillard, J. (1983) Simulations, Semiotext(e)/Columbia University Press, New York
8. Biederman, I. and Shiffrar, M. M. (1987) Sexing day-old chicks: A case study and expert systems analysis of a difficult perceptual-learning task. Journal of Experimental Psychology: Learning, Memory, and Cognition, 13:4, pp. 640-645.
9. Biological Sciences Curriculum Study (1999) Disease Transmission Simulation [Software]
10. Bradley, M. M., Greenwald, M. K., Petry, M. C. and Lang, P. J. (1992) Remembering pictures: Pleasure and arousal in memory. Journal of Experimental Psychology: Learning, Memory, and Cognition, 18:2, pp. 279-390.
11. Bransford, J. D., Franks, J. J., Vye, N. J. and Sherwood, R. D. (1989) New approaches to instruction: Because wisdom can't be told. Similarity and analogical reasoning, pp. 470-497. Cambridge University Press, New York
12. Bransford, J. D. and Schwartz, D. L. (1999) Rethinking transfer: A simple proposal with multiple implications. Review of research in education, 24, pp. 61-100. American Educational Research Association, Washington, DC
13. Bruner, J. S. (1957) Going beyond the information given. Contemporary approaches to cognition, pp. 258-290. Harvard University Press, Cambridge, MA
14. Clark, D. and Jorde, D. (2004) Helping students revise disruptive experientially supported ideas about thermodynamics: Computer visualizations and tactile models. Journal of Research in Science Teaching, 41:1, pp. 1-23.
15. Clement, J. (1994) Use of physical intuition and imagistic simulation in expert problem solving. Implicit and explicit knowledge, pp. 204-244. Ablex, Norwood, NJ
16. Collyer, S. C., Jonides, J. and Bevan, W. (1972) Images as memory aids: Is bizarreness helpful?. American Journal of Psychology, 85, pp. 31-38.
17. Concord Consortium (2008) Molecular Rover [Software]
18. Craighero, L., Fadiga, L., Rizzolatti, G. and Umilta, C. (1999) Action for perception: A motor-visual attentional effect. Journal of Experimental Psychology: Human Perception and Performance, 25:6, pp. 1673-1692.
19. Crocodile Clips (2008) Crocodile Physics [Software]
20. de Jong, T. and van Joolingen, W. R. (1998) Scientific discovery learning with computer simulations of conceptual domains. Review of Educational Research, 68, pp. 179-201.
21. Doltar, B. (2002) BioLab Frog [Software]
22. Dubson, M. (2008) PhET Projectile Motion Simulation [Software]
23. Echevarria, M. (2003) Anomalies as a catalyst for middle school students' knowledge construction and scientific reasoning during science inquiry. Journal of Educational Psychology, 95:2, pp. 357-374.
24. Edelson, D. C., Gordin, D. N. and Pea, R. D. (1999) Addressing the challenges of inquiry_based learning through technology and curriculum design. Journal of the Learning Sciences, 8:34, pp. 391-450.
25. Erdogan, I. (2006) Real science, real scientistis: Students' experiments with natural and artificial wastewater treatment in the classroom. Science Activities: Classroom Projects and Curriculum Ideas, 43:1, pp. 3-7.
26. Fajen, B. R. (2005) The scaling of information to action in visually guided braking. Journal of Experimental Psychology: Human Perception and Performance, 31:5, pp. 1107-1123.
27. Fendt, W. (2008) Java Applets on Physics [Software]
28. Finke, R. (1990) Creative imagery: Discoveries and inventions in visualization, Lawrence Erlbaum, Hillsdale, NJ
29. Fund, Z. (2007) The effects of scaffolded computerized science problem-solving on achievement outcomes: A comparative study of support programs. Journal of Computer Assisted Learning, 23:5, pp. 410-424.
30. Gibson, J. J. and Gibson, E. J. (1955) Perceptual learning: Differentiation or enrichment. Psychological Review, 62, pp. 32-41.
31. Glenberg, A. M., Gutierrez, T., Levin, J. R., Japuntich, S. and Kaschak, M. P. (2004) Activity and imagined activity can enhance young children's reading comprehension. Journal of Educational Psychology, 96, pp. 424-436.
32. Goldstone, R. L. and Barsalou, L. W. (1998) Reuniting perception and conception. Cognition, 65, pp. 231-262.
33. Goodwin, C. (1994) Professional vision. American Anthropologist, 96, pp. 606-633.
34. Gredler, M. (1994) Designing and evaluating games and simulations: A process approach, Gulf, Houston, TX
35. Hennessy, S., Wishart, J., Whitelock, D., Deaney, R., Brawn, R. la Velle, L. et al. (2007) Pedagogical approaches for technology-integrated science teaching. Computers & Education, 48:1, pp. 137-152.
36. Hickey, D., Kindfield, A., Horowitz, P. and Christie, M. (2003) Integrating curriculum, instruction, assessment, and evaluation in a technology-supported genetics learning environment. American Educational Research Journal, 40:2, pp. 495-538.
37. Hulshof, C. D. and de Jong, T. (2006) Using just-in-time information to support scientific discovery learning in a computer-based simulation. Interactive Learning Environments, 14:1, pp. 79-94.
38. Huppert, J., Yaakobi, J. and Lazarowitz, R. (1998) Learning microbiology with computer simulations: Students' academic achievement by method and gender. Research in Science and Technological Education, 16:2, pp. 231-245.
39. Kohler, I. (1964) The formation and transformation of the perceptual world. Psychological Issues, 3, pp. 1-173.
40. Kuhn, D. (1989) Children and adults as intuitive scientists. Psychological Review, 96:4, pp. 674-689.
41. Larkin, J. H. and Simon, H. A. (1987) Why a diagram is (sometimes) worth ten thousand words. Cognitive Science, 11:1, pp. 65-100.
42. Marton, F. and Booth, S. (1997) Learning and awareness, Lawrence Erlbaum, Mahwah, NJ
43. McDaniel, M. A. and Einstein, G. O. (1986) Bizarre imagery as an effective memory aid: The importance of distinctiveness. Journal of Experimental Psychology: Human Learning and Memory, 12, pp. 54-65.
44. McKagan, S. B., Perkins, K. K., Dubson, M., Malley, C., Reid, S. LeMaster, R. et al. (2008) Developing and researching PhET simulations for teaching quantum mechanics. American Journal of Physics, 76, pp. 406-417.
45. MIT Scheller Teacher Education Program (2006) StarLogo TNG [Software]
46. Monaghan, J. M. and Clement, J. (1999) Use of a computer simulation to develop mental simulations for understanding relative motion concepts. International Journal of Science Education, 21:9, pp. 921-944.
47. Myles-Worsley, M., Johnston, W. A. and Simons, M. A. (1988) The influence of expertise on X-ray image processing. Journal of Experimental Psychology: Learning, Memory, and Cognition, 14:3, pp. 553-557.
48. Newell, A. and Simon, H. A. (1972) Human problem solving, Prentice Hall, Englewood Cliffs, NJ
49. Paivio, A. (1971) Imagery and verbal processes, Holt, Rinehart and Winston, Hillsdale, NJ
50. Pennock, R. T. (2007) Avida-Ed [Software]
51. Posner, M. I. and Keele, S. W. (1968) On the genesis of abstract ideas. Journal of Experimental Psychology, 77:3, pp. 353-363.
52. Redding, G. M. and Wallace, B. (2006) Generalization of prism adaptation. Journal of Experimental Psychology: Human Perception and Performance, 32:4, pp. 1006-1022.
53. Reeves, B. and Nass, C. (1998) The media equation: How people treat computers, television, and new media like real people and places, Cambridge University Press, New York
54. Reid, D. (1990) The role of pictures in learning biology: Part 1. Perception and observation. Journal of Biological Education, 24:3, pp. 161-172.
55. Richards, J., Barowy, W. and Levin, D. (1992) Computer simulations in the science classroom. Journal of Science Education and Technology, 1:1, pp. 67-79.
56. Richardson, A. D. and Waller, D. (2007) Interaction with an immersive virtual environment corrects users' distance estimates. Human Factors, 49:3, pp. 507-517.
57. Rocke, A. J. (1985) Hypothesis and experiment in the early development of Kekule's benzene theory. Annals of Science, 42:4, pp. 355-381.
58. Schwartz, D. L. and Black, J. B. (1996) Shuttling between depictive models and abstract rules: Induction and fallback. Cognitive Science, 20, pp. 457-497.
59. Schwartz, D. L. and Bransford, J. D. (1998) A time for telling. Cognition and Instruction, 16, pp. 475-522.
60. Schwartz, D. L. and Heiser, J. (2006) Spatial representations and imagery in learning. Cambridge handbook of the learning sciences, pp. 283-298. Cambridge University Press, New York
61. Schwartz, D. L., Blair, K. P., Biswas, G., Leelawong, K. and Davis, J. (2007) Animation of thought: Interactivity in the teachable agent paradigm. Learning with animation: Research and implications for design, pp. 114-140. Cambridge University Press, Cambridge
62. Shannon, C. E. (1948) A mathematical theory of communication. Bell System Technical Journal, 27, pp. 379-423.
63. Shavelson, R. J., Baxter, G. P. and Pine, J. (1992) Performance assessments: Political rhetoric and measurement reality. Educational Researcher, 21:4, pp. 22-27.
64. Shepard, R. (1967) Recognition memory for words, sentences, and pictures. Journal of Verbal Learning and Verbal Behavior, 6, pp. 156-163.
65. Singer, J., Marx, R. W., Krajcik, J. and Chambers, J. C. (2000) Constructing extended inquiry projects: Curriculum materials for science education reform. Educational Psychologist, 35:3, pp. 165-178.
66. Soderberg, P. and Price, F. (2003) An examination of problem based teaching and learning in population biology and genetics using EVOLVE, a computer simulation. International Journal of Science Education, 25:1, pp. 35-55.
67. Standing, L. (1973) Learning 10,000 pictures. Quarterly Journal of Experimental Psychology, 25:2, pp. 207-222.
68. Stieff, M. and Wilensky, U. (2003) Connected Chemistry-Incorporating interactive simulations into the chemistry classroom. Journal of Science Education and Technology, 12:3, pp. 285-302.
69. Swaak, J. and de Jong, T. (2001) Discovery simulations and the assessment of intuitive knowledge. Journal of Computer Assisted Learning, 17, pp. 284-294.
70. Teachable Agents Group at Vanderbilt University (2005) Betty's Brain [Software]
71. University of Twente (2008) SimQuest [Software]
72. van der Meij, J. and de Jong, T. (2006) Learning with multiple representations: Supporting students' learning with multiple representations in a dynamic simulation-based learning environment. Learning & Instruction, 16, pp. 199-212.
73. Wertheimer, M. (1938) Laws of organization in perceptual forms. A sourcebook of Gestalt psychology, pp. 71-88. Routledge, London
74. Wexler, M. and Klam, F. (2001) Movement prediction and movement production. Journal of Experimental Psychology: Human Perception and Performance, 27:1, pp. 48-64.
75. Wieman, C. E. and Perkins, K. K. (2006) A powerful tool for teaching science. Nature Physics, 2, pp. 290-292.
76. Wilder, A. and Brinkerhoff, J. (2007) Supporting representational competence in high school biology with computer-based biomolecular visualizations. Journal of Computers in Mathematics and Science Teaching, 26:1, pp. 5-26.
77. Wilensky, U. (2005) NetLogo Connected Chemistry 5 Temperature and Pressure [Software]
78. Windschitl, M. (2000) Supporting the development of science inquiry skills with special classes of software. Educational Technology Research and Development, 48:2, pp. 81-95.
79. Windschitl, M. and Andre, T. (1998) Using computer simulations to enhance conceptual change: The roles of constructivist instruction and student epistemological beliefs. Journal of Research in Science Teaching, 35, pp. 145-160.
80. Winn, W., Stahr, F., Sarason, C., Fruland, R., Oppenheimer, P. and Lee, Y. -L. (2006) Learning oceanography from a computer simulation compared with direct experience at sea. Journal of Research in Science Teaching, 43:1, pp. 25-42.