Improving the design and impact of interactive, dynamic visualizations for science learning
Authors: 
Marcia C. Linn, Chris Quintana, Hsin-Yi Chang, Ji Shen, Jennifer L. Chiu, Douglas Clark, Muhsin Menekse, Cynthia D'Angelo, Sharon Schleigh, Stephanie Touchman, Kevin W. McElhaney, Keisha Varma, Aaron Price, Hee-Sun LeeAuthors Info & Claims
Marcia C. Linn, Chris Quintana, Hsin-Yi Chang, Ji Shen, Jennifer L. Chiu, Douglas Clark, Muhsin Menekse, Cynthia D'Angelo, Sharon Schleigh, Stephanie Touchman, Kevin W. McElhaney, Keisha Varma, Aaron Price, Hee-Sun LeeAuthors Info & ClaimsPages 221 - 228
Abstract
This interactive poster session features seven research groups exploring how interactive, dynamic visualizations impact student learning. Six empirical studies report on promising designs for visualizations. These studies use logs of student interactions and embedded assessments to document the quality and trajectory of learning and to capture the cognitive and social processes mediated by the visualization. The review synthesizes previous and current empirical work. It offers design guidelines, principles, patterns, and examples to inform those designing interactive, dynamic visualization and aligned learning support. These posters show why dynamic visualizations are both difficult to design and valuable for science instruction.
References
[1]
Andriessen, J., Baker, M., & Suthers, D. (2003). Argumentation, computer support, and the educational contexts of confronting cognitions. In J. Andriessen, M. Baker & D. Suthers (Eds.), Arguing to learn: Confronting cognitions in computer-supported collaborative learning environments (pp. 1-25). Dordrecht: Kluwer Academic Publishers.
[2]
Ben-Zvi, R., Eylon, B.-S., & Silberstein, J. (1987). Students' visualization of a chemical reaction. Education in Chemistry, 24(4), 117-120.
[3]
Betrancourt, M. (2005). The animation and interactivity principles in multimedia learning. In R. E. Mayer (Ed.), Cambridge handbook of multimedia learning (pp. 287-296). New York, NY: Cambridge University Press.
[4]
Bodner, G. M., & Guay, R. B. (1997). The Purdue visualization of rotations test. The Chemical Educator, 2, 1-17.
[5]
Brewer, W., & Nakamura, G. (1984). The nature and functions of schemas. In R. S. Wyer & T. K. Skull (Eds.), Handbook of social cognition (Vol. 1). Hillsdale, NJ: Lawrence Erlbaum.
[6]
Chi, M. T. H., De Leeuw, N., Chiu, M.-H., & Lavancher, C. (1994). Eliciting self-explanations improves understanding. Cognitive Science, 18, 439-477.
[7]
Driver, R., Newton, P. & Osborne, J. (2000). Establishing the norms of scientific argumentation in classrooms. Science Education, 84, 287-312.
[8]
Duschl, R. (2000). Making the nature of science explicit. In R. Millar, J. Leach & J. Osborne (Eds.), Improving science education: The contribution of research. Philadelphia, PA: Open University Press.
[9]
Ekstrom, R. B., French, J. W., Harman, H. H., & Derman, D. (1976). Kit of factor-referenced cognitive tests. Princeton, NJ: Educational Testing Service. Executive functions in clinical settings: Problems and recommendations. Seminars in Speech and Language, 21, 169-183.
[10]
Hegarty, M., Kriz, S., & Cate, C. (2003). The roles of mental animations and external animations in understanding mechanical systems. Cognition and Instruction, 21(4), 325-360.
[11]
Klahr, D. & Nigam, M. (2004). The equivalence of learning paths in early science instruction: Effects of direct instruction and discovery learning. Psychological Science, 15(10), 661-667.
[12]
Koschmann, T. (2002). Dewey's contribution to the foundations of CSCL research. In G. Stahl (Ed.), Computer support for collaborative learning, proceedings of CSCL 2002 (pp. 17-22). Boulder Colorado.
[13]
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.
[14]
Kuhn, D. & Dean, D. (2005). Is developing scientific thinking all about learning to control variables? Psychological Science, 16, 866-870.
[15]
Large, A. (1996). Computer animation in an instructional environment. LISR, 18(3-23).
[16]
Linn, M. C. & Eylon, B.-S. (2006). Science education: Integrating views of learning and instruction. In P. A. Alexander & P. H. Winne (Eds.), Handbook of educational psychology, 2nd edition (pp. 511-544). Mahwah, NJ: Lawrence Erlbaum Associates.
[17]
Linn, M. C. and Hsi, S. (2000). Computers, teachers, peers: Science learning partners. Mahwah, NJ: Erlbaum.
[18]
Linn, M. C., Lee, H.-S., Tinker, R., Husic, F., & Chiu, J. L. (2006). Teaching and assessing knowledge integration. Science, 313, 1049-1050.
[19]
Lowe, R. (2004) Interrogation of a dynamic visualization during learning. Learning and Instruction, 14, 257-274.
[20]
Mayer, R. E. (2005). Principles for reducing extraneous processing in multimedia learning: coherence, signaling, redundancy, spatial contiguity, and temporal contiguity principles. In R. E. Mayer (Ed.), Cambridge handbook of multimedia learning (pp. 183-200). New York, NY: Cambridge University Press.
[21]
Mayer, R. E., & Moreno, R. (2002). Animation as an aid to multimedia learning. Educational Psychology Review, 14(1), 87-99.
[22]
Miller, C. S., Lehman, J. F., and Koedinger, K. R. (1999). Goals and learning in microworlds. Cognitive Science, 23 (3), 305-336.
[23]
Morin, P. (2004). State of the geowall. Retrieved November 10, 2007, from http://geowall.geo.lsa.umich.edu/talks/StateoftheGeoWall.ppt
[24]
Nakhleh, M.B., Samarapungavan, A., & Saglam, Y. (2005). Middle school students' belief about matter. Journal of Research in Science Teaching, 42, 581-612.
[25]
Pallant, A. and Tinker, R. F. (2004). Reasoning with atomic-scale molecular dynamic models. Journal of Science Education and Technology, 13(1), 51-66.
[26]
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, 431-444.
[27]
Schank, R., & Abelson, R. (1977). Scripts, plans, goals, and understanding. Hillsdale, NJ: Lawrence Erlbaum.
[28]
Schauble, L. (1996). The development of scientific reasoning in knowledge-rich contexts. Developmental Psychology. 32(1), 102-119.
[29]
Shah, P., & Miyake, A. (1996). The separability of working memory resources for spatial thinking and language processing: An individual differences approach. Journal of Experimental Psychology: General, 125, 4-27.
[30]
Sweller, J. (2005). Implications for cognitive load theory for multimedia learning. In R. E. Mayer (Ed.), Cambridge handbook of multimedia learning (pp. 19-30). New York, NY: Cambridge University Press.
[31]
Treagust, D. F., Chittleborough, G., & Mamiala, T. L. (2002). Students' understanding of the role of scientific models in learning science. International Journal of Science Education, 24(4), 357-368.
[32]
Tretter, T. R., Jones, G. M., & Minogue, J. (2006). Accuracy of scale conceptions in science: mental maneuverings across many orders of spatial magnitude. Journal of Research in Science Teaching, 43, 1061-2085.
[33]
Trindade, J., Fiolhais, C., & Almeida, L. (2002). Science learning in virtual environments: a descriptive study. British Journal of Educational Technology, 33, 471-488.
[34]
Tversky, B., Bauer Morrison, J., & Betrancourt, M. (2002). Animation: Can it facilitate? International Journal of Human-Computer Studies, 57, 247-262.
[35]
White, B. Y., & Frederiksen, J. R. (1998). Inquiry, modeling, and metacognition: Making science accessible to all students. Cognition and Instruction, 16(1), 3-118.
[36]
Wilensky, U. (1999). NetLogo {Computer software}. Evanston, IL: Center for Connected Learning and Computer Based Modeling, Northwestern University. http://ccl.northwestern.edu/netlogo.
[37]
Windschitl, M. (1996). Instructional animations: The in-house production of biology software. Journal of Computing in Higher Education 7(2), 78-94.
[38]
Wu, H., Krajcik, J. S., & Soloway, E. (2001). Promoting understanding of chemical representations: Students' use of a visualization tool in the classroom. Journal of Research in Science Teaching, 38, 821-842.
[39]
Xie, Q. & Tinker, R. (2006). Molecular Dynamics Simulations of Chemical Reactions for Use in Education, Journal of Chemical Education, 83, 77-83.
Index Terms
- Improving the design and impact of interactive, dynamic visualizations for science learning
Recommendations
Constructing Interactive Visualizations with iVoLVER
CHI EA '16: Proceedings of the 2016 CHI Conference Extended Abstracts on Human Factors in Computing SystemsiVoLVER, the Interactive Visual Language for Visualization Extraction and Reconstruction, is a web-based pen and touch system that graphically supports the construction of interactive visualizations and allows the extraction of data from different types ...
Hierarchical Temporal Patterns and Interactive Aggregated Views for Pixel-Based Visualizations
IV '09: Proceedings of the 2009 13th International Conference Information VisualisationMany real-world problems involve time-oriented data. Time data is different from other kinds of data--explicitly harnessing the structures of time in visualizations can guide and support users’ visual analysis processes. State-of-the-art visualizations ...
Design choices when architecting visualizations
Special issue of selected and extended InfoVis 03 papersIn this paper, we focus on some of the key design decisions we faced during the process of architecting a visualization system and present some possible choices, with their associated advantages and disadvantages. We frame this discussion within the ...
Comments
Information & Contributors
Information
Published In
June 2008
421 pages
Publisher
International Society of the Learning Sciences
Publication History
Published: 24 June 2008
Qualifiers
- Article
Acceptance Rates
Overall Acceptance Rate 307 of 307 submissions, 100%
Contributors
Other Metrics
Bibliometrics & Citations
Bibliometrics
Article Metrics
- 0Total Citations
- 188Total Downloads
- Downloads (Last 12 months)0
- Downloads (Last 6 weeks)0
Reflects downloads up to 26 Jan 2025
Other Metrics
Citations
View Options
Login options
Check if you have access through your login credentials or your institution to get full access on this article.
Sign in