Interactive elements for dynamically linked multiple representations in computer simulations

Applied Cognitive Psychology

Volumn 25, Issue 1, 2011, Pages 12-19

  Rey, Günter Daniel ^a  

^a UNIVERSITY OF WÜRZBURG   (Germany)

Author keywords

[No Author keywords available]

Indexed keywords

ARTICLE; COMPUTER; COMPUTER SIMULATION; HUMAN; INFORMATION PROCESSING; LEARNING; MULTIVARIATE ANALYSIS OF VARIANCE; NORMAL HUMAN; PRIORITY JOURNAL; SCORING SYSTEM; SIGNAL DETECTION; STUDENT;

EID: 78651433761     PISSN: 08884080     EISSN: 10990720     Source Type: Journal    
DOI: 10.1002/acp.1633     Document Type: Article

References (41)

1. Ainsworth, S. (1999). The functions of multiple representations. Computers and Education, 33, 131-152.
2. Ainsworth, S. (2006). DeFT: A conceptual framework for considering learning with multiple representations. Learning and Instruction, 16, 183-198.
3. Ayres, P., & Sweller, J. (2005). The split-attention principle in multimedia learning. In R. E. Mayer (Ed.), The Cambridge handbook of multimedia learning (pp. 135-146). Cambridge, MA: Cambridge University Press.
4. Berthold, K., Eysink, T. H. S., & Renkl, A. (2009). Assisting self-explanation prompts are more effective than open prompts when learning with multiple representations. Instructional Science, 37, 345-363.
5. Bloom, B. S., & Krathwohl, D. R. (1956). Taxonomy of educational objectives. The classification of educational goals, Handbook I: Cognitive domain. New York: Longmans Green.
6. Bloom, B. S., Madaus, G. F., & Hastings, J. T. (1981). Evaluation to improve learning. New York, NY: McGraw-Hill.
7. Carney, R. N., & Levin, J. R. (2002). Picturial illustrations still improve students' learning from text. Educational Psychology Review, 14, 5-26.
8. de Jong, T. (2006). Computer simulations - technological advances in inquiry learning. Science, 312, 532-533.
9. de Jong, T., & van Joolingen, W. R. (1998). Scientific discovery learning with computer simulations of conceptual domains. Review of Educational Research, 68, 179-201.
10. Eilam, B., & Poyas, Y. (2008). Learning with multiple representations: Extending multimedia learning beyond the lab. Learning and Instruction, 18, 368-378.
11. Fletcher, J. D., & Tobias, S. (2005). The multimedia principle. In R. E. Mayer (Ed.), The Cambridge handbook of multimedia learning (pp. 117-133). Cambridge, MA: Cambridge University Press.
12. Goldman, S. R. (2003). Learning in complex domains: When and why do multiple representations help? Learning and Instruction, 13, 239-244.
13. Kaput, J. J. (1989). Linking representations in the symbol systems of algebra. In S. Wagner, & C. Kieran (Eds.), Research issues in the learning and teaching of algebra (pp. 167-194). Hillsdale, NJ: LEA.
14. Kennedy, G. E. (2004). Promoting cognition in multimedia interactivity research. Journal of Interactive Learning Research, 15, 43-61.
15. Kirschner, F., Paas, F., & Kirschner, P. A. (2009). Individual and group-based learning from complex cognitive tasks: Effects on retention and transfer efficiency. Computers in Human Behavior, 25, 306-314.
16. Kozma, R. B. (2003). The material features of multiple representations and their cognitive and social affordances for science understanding. Learning and Instruction, 13, 205-226.
17. Kozma, R. B., Russell, J., Jones, T., Marx, N., & Davis, J. (1996). The use of multiple, linked representations to facilitate science understanding. In S. Vosniadou, R. Glaser, E. DeCorte, & H. Mandl (Eds.), International perspectives on the psychological foundations of technology-based learning environments (pp. 41-60). Hillsdale, NJ: Erlbaum.
18. Levie, H. W., & Lentz, R. (1982). Effects of text illustrations: A review of research. Educational Communication and Technology Journal, 30, 195-232.
19. Levin, J. R., Anglin, G. J., & Carney, R. N. (1987). On empirically validating functions of pictures in prose. In D. M. Willows, & H. A. Houghton (Eds.), The psychology of illustration (Vol. 1, pp. 51-86). New York: Springer.
20. Lowe, R. K. (1999). Extracting information from an animation during complex visual learning. European Journal of Psychology of Education, 14, 225-244.
21. Mayer, R. E. (1997). Multimedia learning: Are we asking the right questions? Educational Psychologist, 32, 1-19.
22. Mayer, R. E. (2004). Should there be a three strike rule against pure discovery learning? The case for guided methods of instruction. American Psychologist, 59, 14-19.
23. Mayer, R. E. (2005a). Cognitive theory of multimedia learning. In R. E. Mayer (Ed.), The Cambridge handbook of multimedia learning (pp. 31-48). Cambridge, MA: Cambridge University Press.
24. Mayer, R. E. (2005b). Introduction to multimedia learning. In R. E. Mayer (Ed.), The Cambridge handbook of multimedia learning (pp. 1-16). Cambridge, MA: Cambridge University Press.
25. Mayer, R. E. (2005c). Principles for reducing extraneous processing in multimedia learning: Coherence, signaling, redundancy, spatial contiguity, and temporal contiguity principles. In R. E. Mayer (Ed.), The Cambridge handbook of multimedia learning (pp. 183-200). Cambridge, MA: Cambridge University Press.
26. Mayer, R. E. (2009). Multimedia learning (2nd ed.). Cambridge: Cambridge University Press.
27. Rieber, L. P. (2005). Multimedia learning in games, simulations, and microworlds. In R. E. Mayer (Ed.), The Cambridge handbook of multimedia learning (pp. 549-567). Cambridge, MA: Cambridge University Press.
28. Rogers, Y. (1999). Commentary: What is different about interactive graphical representations? Learning and Instruction, 9, 419-425.
29. Salomon, G. (1979). Interaction of media, cognition and learning. San Francisco, CA: Jossey-Bass.
30. Scaife, M., & Rogers, Y. (1996). External cognition: How do graphical representation work? International Journal of Human Computer Studies, 45, 185-213.
31. Schnotz, W. (2005). An integrated model of text and picture comprehension. In R. E. Mayer (Ed.), The Cambridge handbook of multimedia learning (pp. 49-69). Cambridge, MA: Cambridge University Press.
32. Shneiderman, B. (1983). Direct manipulation. A step beyond programming languages. IEEE Transactions on Computers, 16, 57-69.
33. Sims, R. (1997). Interactivity: A forgotten art? Computers in Human Behavior, 13, 157-180.
34. Sweller, J. (2005). Implications of cognitive load theory for multimedia learning. In R. E. Mayer (Ed.), The Cambridge handbook of multimedia learning (pp. 19-30). Cambridge, MA: Cambridge University Press.
35. Sweller, J., & Chandler, P. (1994). Why some material is difficult to learn. Cognition and Instruction, 12, 185-233.
36. Tabachneck, H. J. M., Leonardo, A. M., & Simon, H. A. (1994). How does an expert use a graph? A model of visual and verbal inferencing in economics. In A. Ram, & K. Eiselt (Eds.), 16th Annual conference of the cognitive science society (pp. 842-847). Hillsdale, NJ: Erlbaum.
37. van der Meij, J. (2007). Support for learning with multiple representations: Designing simulation-based learning environments. The Netherlands: University of Twente, Enschede.
38. van der Meij, J., & de Jong, T. (2006). Supporting students' learning with multiple representations in a dynamic simulation-based learning environment. Learning and Instruction, 16, 199-212.
39. Van Merriënboer, J. J. G., & Sweller, J. (2005). Cognitive load theory and complex learning: Recent developments and future directions. Educational Psychology Review, 17, 147-177.
40. Wouters, P., Tabbers, H. K., & Paas, F. (2007). Interactivity in video-based models. Educational Psychology Review, 19, 327-342.
41. Yerushalmy, M. (1991). Student perceptions of aspects of algebraic function using multiple representation software. Journal of Computer Assisted Learning, 7, 42-57.