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Educational Technology Research and Development

, Volume 61, Issue 1, pp 91–105 | Cite as

Guided self-management of transient information in animations through pacing and sequencing strategies

  • George Hatsidimitris
  • Slava Kalyuga
Research Article

Abstract

Learning with instructional animations may overstretch limited working memory resources due to intense processing demands associated with transient information. The authors investigated whether explicit instructional advice coupled with a task-specific learner control mechanism (such as a timeline scrollbar) could facilitate the successful self-management of transient information. The effectiveness of a timeline scrollbar that allowed self-pacing and self-sequencing of animations was compared with computer-controlled animations. Experiment 1 demonstrated that a timeline scrollbar (with instructional advice on its strategic use) enhanced the retention of stroke sequences in writing Chinese characters. In Experiment 2, a timeline scrollbar was used in an integrated set of narrated animations dealing with complex scientific information. Retention and comprehension post-tests indicated that although a scrollbar accompanied by instructional advice in its use assisted novice learners, no such effect was found with participants who possessed higher levels of prior knowledge. The findings have implications for the formulation of criteria for the effective incorporation of learner control into the design of instructional animations.

Keywords

Cognitive load Animations Learner control Expertise reversal effect Transient information 

Notes

Acknowledgments

We would like to thank Professor Joe Wolfe for contributing the test materials for Experiment 2.

References

  1. Ainsworth, S., & VanLabeke, N. (2004). Multiple forms of dynamic representation. Learning and Instruction, 14, 241–255. doi: 10.1016/j.learninstruc.2004.06.002.CrossRefGoogle Scholar
  2. Arguel, A., & Jamet, E. (2009). Using video and static pictures to improve learning of procedural contents. Computers in Human Behavior, 25(2), 354–359. doi: 10.1016/j.chb.2008.12.014.CrossRefGoogle Scholar
  3. Ayres, P. (2006). Impact of reducing intrinsic cognitive load on learning in a mathematical domain. Applied Cognitive Psychology, 20(3), 287–298. doi: 10.1002/acp.1245.CrossRefGoogle Scholar
  4. Ayres, P., & Paas, F. (2007). Can the cognitive load approach make instructional animations more effective? Applied Cognitive Psychology, 21, 811–820. doi: 10.1002/acp.1351.CrossRefGoogle Scholar
  5. Höffler, T. N., & Leutner, D. (2007). Instructional animation versus static pictures: A meta-analysis. Learning and Instruction, 17(6), 722–738. doi: 10.1016/j.learninstruc.2007.09.013.CrossRefGoogle Scholar
  6. Kalyuga, S. (2007). Enhancing instructional efficiency of interactive e-learning environments: A cognitive load perspective. Educational Psychology Review, 19(3), 387–399. doi: 10.1007/s10648-007-9051-6.CrossRefGoogle Scholar
  7. Kalyuga, S. (2008). Relative effectiveness of animated and static diagrams: An effect of learner prior knowledge. Computers in Human Behavior, 24(3), 852–861. doi: 10.1016/j.chb.2007.02.018.CrossRefGoogle Scholar
  8. Leahy, W., & Sweller, J. (2011). Cognitive load theory, modality of presentation and the transient information effect. Applied Cognitive Psychology, 25, 943–951. doi: 10.1002/acp.1787.CrossRefGoogle Scholar
  9. Low, R., & Sweller, J. (2005). The modality principle in multimedia learning. In R. Mayer (Ed.), Cambridge handbook of multimedia learning (pp. 147–158). New York: Cambridge University Press. doi: 10.1017/CBO9780511816819.010.CrossRefGoogle Scholar
  10. Lowe, R. (2003). Animation and learning: Selective processing of information in dynamic graphics. Learning and Instruction, 13(2), 157–176. doi: 10.1016/S0959-4752(02)00018-X.CrossRefGoogle Scholar
  11. Mayer, R. E. (2005a). Principles for managing extraneous processing in multimedia learning: Coherence, signalling, redundancy, spatial contiguity and temporal contiguity principles. In R. E. Mayer (Ed.), Cambridge handbook of multimedia learning (pp. 183–200). New York: Cambridge University Press. doi: 10.1017/CBO9780511816819.010.CrossRefGoogle Scholar
  12. Mayer, R. E. (2005b). Principles for managing essential processing in multimedia learning: Segmenting, pretraining and modality principles. In R. E. Mayer (Ed.), Cambridge handbook of multimedia learning (pp. 169–182). New York: Cambridge University Press. doi: 10.1017/CBO9780511816819.010.CrossRefGoogle Scholar
  13. Mayer, R. E. (2009). Multimedia learning (2nd ed.). New York: Cambridge University Press. doi: 10.1017/CBO9780511811678.CrossRefGoogle Scholar
  14. Mayer, R. E., Hegarty, M., Mayer, S., & Campbell, J. (2005). When static media promote active learning: Annotated illustrations versus narrated animations in multimedia instruction. Journal of Experimental Psychology Applied, 11, 256–265. doi: 10.1037/1076-898X.11.4.256.CrossRefGoogle Scholar
  15. Miller, G. A. (1956). The magical number seven, plus or minus two: Some limits on our capacity for processing information. Psychological Review, 63, 81–97. doi: 10.1037//0033-295X.101.2.343.CrossRefGoogle Scholar
  16. Pollock, E., Chandler, P., & Sweller, J. (2002). Assimilating complex information. Learning and Instruction, 12(1), 61–86. doi: 10.1016/S0959-4752(01)00016-0.CrossRefGoogle Scholar
  17. Schnotz, W., & Kürschner, C. (2007). A reconsideration of cognitive load theory. Educational Psychology Review, 19(4), 469–508. doi: 10.1007/s10648-007-9053-4.CrossRefGoogle Scholar
  18. Spanjers, I. A. E., Wouters, P., van Gog, T., & van Merriënboer, J. J. G. (2011). An expertise reversal effect of segmentation in learning from animated worked-out examples. Computers in Human Behavior, 27(1), 46–52. doi: 10.1016/j.chb.2010.05.011.CrossRefGoogle Scholar
  19. Sweller, J. (1989). Cognitive technology: Some procedures for facilitating learning and problem solving in mathematics and science. Journal of Educational Psychology, 81(4), 457–466. doi: 10.1037/0022-0663.81.4.457.CrossRefGoogle Scholar
  20. Sweller, J., Ayres, P., & Kalyuga, S. (2011). Cognitive load theory. New York: Springer. doi: 10.1007/978-1-4419-8126-4_17.CrossRefGoogle Scholar
  21. Tversky, B., Morrison, J., & Betrancourt, M. (2002). Animation: Can it facilitate? International Journal of Human–Computer Studies, 57(4), 247–262. doi: 10.1006/ijhc.2002.1017.CrossRefGoogle Scholar
  22. Young, J. (1996). The effect of self-regulated learning strategies on performance in learner controlled computer-based instruction. Educational Technology Research and Development, 44(2), 17–27. doi: 10.1007/bf02300538.CrossRefGoogle Scholar

Copyright information

© Association for Educational Communications and Technology 2012

Authors and Affiliations

  1. 1.School of PhysicsThe University of New South WalesSydneyAustralia
  2. 2.School of EducationThe University of New South WalesSydneyAustralia

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