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Multimedia Presentations of Mitosis: An Examination of Split-Attention, Modality, Redundancy, and Cueing
ARTICLE

, , Clemson University, United States

Journal of Educational Multimedia and Hypermedia Volume 23, Number 2, ISSN 1055-8896 Publisher: Association for the Advancement of Computing in Education (AACE), Waynesville, NC USA

Abstract

Multimedia presentations that combine visual and verbal information are widely used for instructional purposes. While the design of the text-graphic relationship is difficult, several design strategies with the potential to reduce cognitive load have been identified in the literature. The purpose of this study is to examine how split-attention, modality, redundancy, and cueing influence how both high and low prior knowledge participants view and learn from four different multimedia presentations on mitosis. The findings indicate that low prior knowledge learners were more prone to cognitive overload with split-attention and redundant designs. While there were no differences in learning gains among the presentations compared for high prior knowledge students, these learners did not prefer the narrated presentation. More research is necessary on how to best design multimedia presentations for diverse learners.

Citation

Cook, M. & Visser, R. (2014). Multimedia Presentations of Mitosis: An Examination of Split-Attention, Modality, Redundancy, and Cueing. Journal of Educational Multimedia and Hypermedia, 23(2), 145-162. Waynesville, NC USA: Association for the Advancement of Computing in Education (AACE). Retrieved March 23, 2019 from .

View References & Citations Map

References

  1. Chandler, P., & Sweller, J. (1991). Cognitive load theory and the format of instruction. Cognition and Instruction, 8, 293-332.
  2. Chi, M.T.H., Feltovich, P.J., & Glaser, R. (1981). Categorization and representation of physics problems by experts and novices. Cognitive Science, 5, 121-152.
  3. Chi, M.T.H., Glaser, R., & Rees, E. (1982). Expertise in problem solving. In R. Sternberg (Ed.), Advances in the Psychology of Human Intelligence (pp. 7-75). Hillsdale,
  4. Cohen, J. (1988). Statistical power analysis for the behavioural sciences. Hillsdale: Erlbaum.
  5. De Koning, B.B., Tabbers, H.K., Rikers, R.M.J.P, & Pass, F. (2009) Towards a framework for attention cueing in instructional animations: Guidelines for research and design. Educational Psychology Review, 21, 113-140.
  6. DiSessa, A.A. (2004). Metarepresenatations: Native competence and targets for instruction. Cognition and Instruction, 22(3), 293-331.
  7. Duchowski, A.T. (2003). Eye tracking methodology: Theory and practice. Berlin: Springer Verlag.
  8. Kirschner, P. (2002). Cognitive load theory: Implications of cognitive load theory on the Multimedia Presentations of Mitosis: An Examination of Split-Attention 161
  9. Kalyuga, S., Chandler, P., & Sweller, J. (1998). Levels of expertise and instructional design. Human Factors, 40(1), 1-17.
  10. Larkin, J.H. (1983). The role of problem representation in physics. In D. Gentner & A.L. Stevens (Eds.), Mental Models (pp. 75-98). Hillsdale, NJ: Erlbaum.
  11. Lewalter, D. (2003). Cognitive strategies for learning from static and dynamic visuals. Learning and Instruction, 13(2), 177-189.
  12. Mathewson, J.H. (1999). Visual-spatial thinking: An aspect of science overlooked by educators. Science Education, 83(1), 33-54.
  13. Mayer, R.E., & Massa, L.J. (2003). Three facets of visual and verbal learners: Cognitive ability, cognitive style, and learning preference. Journal of Educational Psychology, 95(4), 833-846.
  14. Mayer, R.E., & Moreno, R. (2003). Nine ways to reduce cognitive load in multimedia learning. Educational Psychologist, 38(1), 43-52.
  15. Morrison, G., & Anglin, G. (2005). Research on cognitive load theory: Application toelearning. Educational Technology, Research, & Development, 53(3), 94.
  16. Paas, F., & Kester, L. (2006). Learning and information characteristics in the design of powerful learning environments. Applied Cognitive Psychology, 20, 281-285.
  17. Paas, F., Tuovinen, J.E., Tabbers, H., & Van Gerven, P.W. (2003). Cognitive load measurement as a means to advance cognitive load theory. Educational Psychologist, 38(1), 63-71.
  18. Paas, F., Tuovinen, J., van Merriënboer, J., & Darabi, A. (2005). A motivational perspective on the relation between mental effort and performance: Optimizing learner involvement in instruction. Educational Technology, Research, & Development, 53(3), 25-34.
  19. Patrick, M.D., Carter, G., & Wiebe, E.N. (2005). Visual representations of DNA replication: Middle grades students’ perceptions and interpretations. Journal of Science Education and Technology, 14(3), 353-365.
  20. Schnotz, W., Picard, E., & Hron, A. (1993). How do successful and unsuccessful learners use texts and graphics? Learning and Instruction, 3, 181-199.
  21. Schnotz, W., & Rasch, T. (2005). Enabling, facilitating, and inhibiting effects of animations in multimedia learning: Why reduction of cognitive load can have negative results on learning. Educational Technology, Research, & Development, 53(3), 47-58.
  22. Sweller, J., van Merrienboer, J.J.G., & Paas, F.G.W.C. (1998). Cognitive architecture and instructional design. Educational Psychology Review, 10, 251-296.
  23. Van Someren, M., Reimann, P., Boshuizen, H., & De Jong, T. (1998). Learning with multiple representations. Amsterdam: Pergamon.
  24. Zywno, M.S., & Stewart, M.F. (2005). Learning styles of engineering students, online learning objects and achievement. Proceedings of the Americal Society for Engineering Education Annual Conference& Exposition. Portland, OR.

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