Exposing Gaps in Students’ Mental Model of the Neuron : Comparing traditional neuroscience instruction of the Action Potential to Layered, Iterative Visual External Representations
PROCEEDINGS
Satyugjit Virk, John Black, Teachers College Columbia University, United States
E-Learn: World Conference on E-Learning in Corporate, Government, Healthcare, and Higher Education, in Honolulu, Hawaii, USA ISBN 978-1-880094-90-7 Publisher: Association for the Advancement of Computing in Education (AACE), San Diego, CA
Abstract
Students were run in two groups, one consisting of a series of animations depicting neural signal transmission at the cellular and molecular levels using iterative visualizations, where a visualization for every concept appears, or “iterates” at each and every instance where it should occur throughout the visualization, which had the cellular and molecular levels layered on top of each other. The second group also had cellular and molecular animations of neural signal transmission, but these were not iterative, instead the visualizations only appeared where they are normally depicted in traditional instruction and were not layered. The experimental, iterative and layered visualization condition performed significantly better on cellular-level free response essay and individual questions than the control, and there was a trend for significance in favor of the iterative, layered condition on the molecular free response questions. These findings advocate for the use of iterative visualizations in science teaching e-learning modules.
Citation
Virk, S. & Black, J. (2011). Exposing Gaps in Students’ Mental Model of the Neuron : Comparing traditional neuroscience instruction of the Action Potential to Layered, Iterative Visual External Representations. In C. Ho & M. Lin (Eds.), Proceedings of E-Learn 2011--World Conference on E-Learning in Corporate, Government, Healthcare, and Higher Education (pp. 467-473). Honolulu, Hawaii, USA: Association for the Advancement of Computing in Education (AACE). Retrieved March 19, 2024 from https://www.learntechlib.org/primary/p/38752/.
© 2011 Association for the Advancement of Computing in Education (AACE)
References
View References & Citations Map- 1. Baddeley, A. (1992). Working memory. Science, 255, 556-559. 2. Gentner, D., & Steven, A. (Eds.). (1983). Mental models. Hillsdale, NJ: Lawrence Erlbaum.
- 3. Hashner, L. (1971). Retention of Free Recall Learning: The Whole-Part Problem. Journal of Experimental Psychology, 90(1), 8-17.
- 4. Kozhevnikov, M., Motes, M.A. & Hegarty, M. (2007). Spatial Visualization in Physics Problem Solving. Cognitive Science, 2007, 549-579.
- 5. Mayer, R.E. (1997). Multimedia learning: Are we asking the right questions? Educational Psychologist, 32, 1-19.
- 6. Mayer, R.E. & Chandler, P. (2001). When learning is just a click away: Does simple user interaction foster deeper understanding of multimedia messages? Journal of EducationalPsychology, 93 (2), 390-397.
- 7. Carroll, W.M. (1994). Using worked examples as an instructional support in the algebra classroom. Journal of Educational Psychology, 86, 360-367.
- 8. Kirschner, P., Sweller, J., & Clark, R. (2006). Why minimal guidance during instruction does not work: An analysis of the failure of constructivist, discovery, problem-based, experiential and inquiry-based teaching. Educational Psychologist, 41, 75-86.
- 9. Kozma, R. (2003). The material features of multiple representations and their cognitive and social affordances for science understanding. Learning and Instruction, 13, 205-226.
- 10. Sweller, J., & Chandler, P. (1994). Why some material is difficult to learn. Cognition and Instruction, 12, 185233.
- 11. Wilder, A., & 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), 5-26.
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