The effects of an animation-based on-line learning environment on transfer of knowledge and on motivation for science and technology learning

Journal of Educational Computing Research

Volumn 40, Issue 4, 2009, Pages 451-467

  Rosen, Yigal ^a  

^a UNIVERSITY OF HAIFA   (Israel)

Author keywords

[No Author keywords available]

Indexed keywords

EID: 70349622504     PISSN: 07356331     EISSN: None     Source Type: Journal    
DOI: 10.2190/EC.40.4.d     Document Type: Article

References (50)

1. Ben-Bassat Levy, R., Ben-Ari, M., & Uronen, P. A. (2003). The Jeliot 2000 program animation system. Computers & Education, 40, 1-15.
2. Betrancourt, M. (2005). The animation and interactivity principles in multimedia learning. In R. E. Mayer (ed.), The Cambridge handbook of multimedia learning (pp. 287-296). Cambridge: Cambridge University Press.
3. Boucheix, J-M. (2007). Young learners' control of technical animations. In R. Lowe, & W. Schnotz (Eds.) Learning with animation: Research and design implications (pp. 208-234). New York: Cambridge University Press.Bransford, J. D., Brown, A. L., & Cocking, R. R. (Eds.). (1999). How people learn: brain, mind, experience, and school. National Research Council.
4. Bransford, J. D., & Schwartz, D. L. (1999). Rethinking transfer: A simple proposal with multiple implications. Review of Research in Education, 24, 61-100.
5. Brown, A., & Campione, J. (1994). Guided discovery in a community of learners. In K. McGilly (Ed.), Classroom lessons: Integrating cognitive theory and classroom practice (pp. (229-272). Cambridge, MA: MIT Press.
6. Chandler, P., & Sweller, J. (1991). Cognitive load theory and the format of instruction. Cognition and Instruction, 8, 293-332.
7. Cormier, S. M., & Hagman, J. D. (Eds.). (1987). Transfer of learning; Contemporary research and applications. New York: Academic Press.
8. Csikszentmihalyi, M. (1988). The flow experience and its significance for human psychology. In M. Csikszentmihalyi & I. S. Csikszentmihalyi (Eds.), Optimal experience: Psychological studies of flow in consciousness (pp. 15-35). Cambridge, UK: Cambridge University Press.
9. Eshet, Y. (2004). Digital literacy: A conceptual framework for survival in the digital era. Journal of Educational Multimedia and Hypermedia, 13(1), 93-106.
10. Esponda-Arguero, M. (2008). Algorithmic animation in educationâ €"Review of academic experience. Journal of Educational Computing Research, 39(1), 1-15.
11. Fleming, S. A., Hart, G. R., & Savage, P. B. (2000). Molecular orbital animations for organic chemistry. Journal of Chemical Education, 77(6), 790-793.
12. Ford, M. J., Poe, V., & Cox, J. (1993). Attending behaviors of children with ADHD in math and reading using various types of software. Journal of Computing in Childhood Education, 4, 183-196.
13. Glynn, S. M., & Koballa, T. R., Jr. (2005). The contextual teaching and learning instructional approach. In R. E. Yager (Ed.), Exemplary science: Best practices in professional development (pp. 75-84). Arlington, VA: National Science Teachers Association Press.
14. Glynn, S. M., & Koballa, T. R., Jr. (2006). Motivation to learn college science. In J. J. Mintzes & H. Leonard (Eds.), Handbook of college science teaching (pp. 25-32). Arlington, VA: National Science Teachers Association Press.
15. Good, D. J. (2004). The use of flash animations within a WebCT environment: Enhancing comprehension of experimental procedures in a biotechnology laboratory. International Journal of Instructional Media, 31(4), 355-370.
16. Halpern, D. F. (1998). Teaching critical thinking for transfer across domains: Disposition, skills, structure training, and metacognitive monitoring. American Psychologist, 53, 449-455.
17. Haskell, E. M. (2001). Transfer of learning: Cognition, instruction, and reasoning. New York: Academic Press.
18. Hickey, D., Moore, A., & Pellegrino, J. (2001). The motivational and academic consequences of elementary mathematics environments: Do constructivist innovations and reforms make a difference? American Educational Research Journal, 38, 611-652.
19. Hoeffler, T. N., & Leutner, D. (2007). Instructional animation versus static pictures: A meta-analysis. Learning and Instruction, 17(6), 722-738.
20. Hopson, M., Simms, R., & Knezek, G. (2001-2002). Using a technology-enriched environment to improve higher-order thinking skills. Journal of Research on Technology in Education, 34(2), 109-119.
21. Kelly, R. M., & Jones, L. L. (2007). Exploring how different features of animations of sodium chloride dissolution affect students' explanations. Journal of Science Education and Technology, 16(4), 413-429.
22. Lowe, R. K. (2004). Interrogation of a dynamic visualisation during learning. Learning and Instruction, 14, 257-274.
23. Marini, A., & Genereux, R. (1995) The challenge of teaching for transfer. In A. McKeough, J. Lupart, & A. Marini (Eds.), Teaching for transfer: Fostering generalization in learning (pp. 1-19). Mahwah, NJ: Erlbaum.
24. Mayer, R. E., & Anderson, R. B. (1991). Animations need narrations: An experimental test of a dual-coding hypothesis. Journal of Educational Psychology, 83, 484-490.
25. Mayer, E. R., & Chandler, P. (2001). When learning is just a click away: does simple interaction foster deeper understanding of multimedia messages? Journal of Educational Psychology, 93(2), 390-397.
26. Mayer, R. E., & Sims, V. K. (1994). For whom is a picture worth a thousand words? Extensions of a dual-coding theory of multimedia learning. Journal of Educational Psychology, 86, 389-401.
27. Mayer, R. E., Steinhoff, K., Bower, G., & Mars, R. (1995). A generative theory of textbook design: Using annotated illustrations to foster meaningful learning of science text. Educational Technology Research and Development, 43, 31-44.
28. Misko, J. (1995). Transfer: Using learning in new contexts. Leabrook: NCVER.
29. Misko, J. (1999). The transfer of knowledge and skill to different contexts: An empirical perspective. Leabrook: NCVER.
30. Nakamura, J., & Csikszentmihalyi, M. (2002). The concept of flow. In C. R. Snyder & Lopez, S. J. (Eds.), Handbook of positive psychology (pp. 87-92). Oxford University Press.
31. Ota, K. R., & DuPaul, G. J. (2002). Task engagement and mathematics performance in children with attention-deficit hyperactivity disorder: Effects of supplemental computer instruction. School Psychology Quarterly, 17(3), 242-257.
32. Park, O. (1994). Dynamic visual displays in media-based instruction. Educational Technology, 21-25.
33. Park, O. C., & Gittelman, S. S. (1992). Selective use of animation and feedback in computer-based instruction. Educational Technology, Research, and Development, 40(4), 27-38.
34. Presseau, A., & Frenay, M. (2004) Le transfert des apprentissages. Comprendre pour mieux intervenir. Presses de l'universite de Laval.
35. Reed, S. K. (2005). From research to practice and back: The animation tutor project. Educational Psychology Review, 17(1), 55-82.
36. Rieber, L. P. (1989). The effects of computer animated elaboration strategies and practice on factual and application learning in an elementary science lesson. Journal of Educational Computing Research, 5(4), 431-444.
37. Rieber, L. P. (1991). Computer-based microworlds: a bridge between constructivism and direct instruction. Paper presented at the meeting of the Annual Convention of the Association for Educational Communications and Technology (pp. 692-707).
38. Rosen, Y., & Salomon, G. (2007). The differential learning achievements of constructivist technology-intensive learning environments as compared with traditional ones: A meta-analysis. Journal of Educational Computing Research, 36(1), 1-14.
39. Rotbain, Y., Marbach-Ad, G., & Stavy, R. (2008). Using a computer animation to teach high school molecular biology. Journal of Science Education and Technology, 17(1), 49-58.
40. Rubio Garcia, R., Suarez Quiros, J., Gallego Santos, R., Gonzalez, S. M., & Morán Fernanz, S. (2007). Interactive multimedia animation with Macromedia Flash in descriptive geometry teaching. Computers & Education, 49(3), 615-639.
41. Salomon, G. (2002). Technology and pedagogy: Why don't we see the promised revolution? Educational Technology, 42(2), 71-75.
42. Salomon, G., & Perkins, D. (1989). Rocky roads to transfer: Rethinking mechanism of a neglected phenomenon. Educational Psychologist, 24, 113-142.
43. Schnotz, W., & Lowe, R. (2003). Introduction. Learning and Instruction, 13(2), 117-124.
44. Scardamalia, M., Bereiter, C., & Lamon, M. (1994). The CSILE project: Trying to bring the classroom lessons. Integrating cognitive theory into classroom practice. Cambridge, MA: MIT Press.
45. Schwan, S., & Riempp, R. (2004). The cognitive benefits of interactive videos: Learning to tie nautical knots. Learning and Instruction, 14(3), 293-305.
46. Tversky, B., Bauer-Morrison, J., & Betrancourt, M. (2002). Animation: can it facilitate? International Journal of Human-Computer Studies, 57, 247-262.
47. Williamson, V. M., & Abraham, M. R. (1995). The effects of computer animation on the particulate mental models of college chemistry students. The Journal of Research in Science Teaching, 32(5), 521-534.
48. Yarden, A., & Yarden, H. (2006). Supporting learning of biotechnological methods using interactive and task included animations. European Association of Research on Learning and Instruction, SIG Biennial Meeting on Comprehension of Text and Graphics, Nottingham, UK.
49. Zohar, A. (2004). Higher order thinking in science classroom: Students' learning and teachers' professional development. Science & Technology Educational Library (Vol. 22). Dordrecht, Netherlands: Kluwer.
50. Zohar, A., & Dori, Y. J. (2003). Higher order thinking skills and low achieving students: Are they mutually exclusive? The Journal of the Learning Sciences, 12, 145-182.