Animation and grammar in science education: Learners’ construal of animated educational software

Article

Abstract

This case study reports on how students, working collaboratively, interpret and construct a written report of the events described in animated educational software. The analysis is based on video recordings of two upper-secondary-school students while they are endeavouring to construe an animated sequence of the mouldering process. How the students grammatically construct their written account by means of available semiotic resources (i.e., animation and educational text) provided by the software is investigated. The results show that attentionally detected features of the animation take the role of active subjects in the students’ description of the animated phenomena. When framing their sentences, the students derive noun phrases from animated active subjects and from the educational text. In the students’ efforts to express themselves in their own words, they use verbs that differ from the educational text. These two actions together contribute to giving the students’ description of the process a character of a non-scientific explanation. Lacking relevant subject matter knowledge, the students cannot judge whether they have given an adequate account or not. The only way that the students have to appraise their written report is to check if it is grammatically correct. It is concluded that it is essential to consider both cultural and semiotic processes when designing technology-supported educational approaches to the teaching of scientific concepts.

Keywords

Computer animation Educational software Interaction analysis Science education 

Notes

Acknowledgment

The work reported here has been supported by the Linnaeus Centre for Research on Learning, Interaction, and Mediated Communication in Contemporary Society (LinCS). I thank the teachers and students at the Upper Secondary School where the study was carried out for their willing cooperation. I am indebted to Jonas Ivarsson for his invaluable comments on earlier versions of this article.

References

  1. Arnseth, H. C., & Ludvigsen, S. (2006). Approaching institutional contexts: Systemic versus dialogic research in CSCL. International Journal of Computer-Supported Learning, 1(2), 167–185.CrossRefGoogle Scholar
  2. Bakhtin, M. M. (1986). Speech genres and other late essays. Austin: University of Texas Press.Google Scholar
  3. Brown, A. L. (1992). Design experiments: Theoretical and methodological challenges in creating complex interventions in classroom settings. The Journal of the Learning Sciences, 2(2), 141–178.CrossRefGoogle Scholar
  4. Cañal, P. (1999). Photosynthesis and “inverse respiration” in plants: An inevitable misconception? International Journal of Science Education, 21(4), 363–371.CrossRefGoogle Scholar
  5. Chittleborough, G. D., Treagust, D. F., Mamiala, T. L., & Mocerino, M. (2005). Students’ perceptions of the role of models in the process of science and in the process of learning. Research in Science & Technological Education, 23(2), 195–212.CrossRefGoogle Scholar
  6. Duranti, A. (2004). A companion to linguistic anthropology. Malden: Blackwell.Google Scholar
  7. Eisner, W. (1985). Comics and sequential art. Tamarac: Poorhouse.Google Scholar
  8. Fillmore, C. J. (1968). The case for case. In E. Bach & R. T. Harms (Eds.), Universals in linguistic theory. New York: Holt, Rinehart and Winston, Inc.Google Scholar
  9. Goodwin, C. (1994). Professional vision. American Anthropologist, 96(3), 606–633.CrossRefGoogle Scholar
  10. Greiffenhagen, C., and Watson, R. (2007). Visual repairables: Analyzing the work of repair in human-computer interaction. Visual Communication, 8(1), 65–90.Google Scholar
  11. Grosslight, L., Unger, J., Jay, E., & Smith, C. (1991). Understanding models and their use in science: Conceptions of middle and high school students and experts. Journal of Research in Science Teaching, 28(9), 799–822.CrossRefGoogle Scholar
  12. Halliday, M. A. K. (2004). The language of science. London: MPG Books Ltd.Google Scholar
  13. Ivarsson, J. (2010). Developing the construction sight: Architectural education and technological change. Visual Communication, 9(2), 1–21.Google Scholar
  14. Jordan, B., & Henderson, A. (1995). Interaction analysis: Foundations and practice. The Journal of the Learning Science, 4(1), 39–103.CrossRefGoogle Scholar
  15. Karlsson, G., & Ivarsson, J. (2008). Animations in science education. In T. Hansson (Ed.), Handbook of research on digital information technologies: Innovations, methods, and ethical issues (pp. 68–82). Hershey: IGI Global.Google Scholar
  16. Kozma, R. B., & Russell, J. (1997). Multimedia and understanding: Expert and novice responses to different representations of chemical phenomena. Journal of Research in Science Teaching, 34(9), 949–968.CrossRefGoogle Scholar
  17. Krange, I., & Ludvigsen, S. (2008). What does it mean? Students’ procedural and conceptual problem solving in a CSCL environment designed within the field of science education. International Journal of Computer-Supported Collaborative Learning, 3, 25–51.CrossRefGoogle Scholar
  18. Kuech, R., Zogg, G., Zeeman, S., & Johnson, M. (2003). Technology rich biology labs: Effects of misconceptions. Paper presented at the Annual Meeting of the National Association for Research in Science Teaching, Philadelphia, PA, USA. Available online.Google Scholar
  19. Lemke, J. L. (1990). Talking science—language, leaning, and values. London: Ablex.Google Scholar
  20. Lemke, J. L. (1998). Analysing verbal data: Principles, methods, and problems. In K. Tobin & B. Fraser (Eds.), International handbook of science education (pp. 1175–1189). Boston: Kluwer.Google Scholar
  21. Lemke, J. L. (2006). Towards critical multimedia literacy: Technology, research, and politics. In M. McKenna, L. Labbo, R. Keiffer, & D. Reinking (Eds.), Handbook of literacy and technology (Vol. 2, pp. 3–14). New York: Erlbaum (LEA Publishing).Google Scholar
  22. Lindwall, O. (2008). Lab work in science education. Linköping: Linköping University.Google Scholar
  23. Lowe, R. K. (1999). Extracting information from an animation during complex visual learning. European Journal of Psychology of Education, 14(2), 225–244.CrossRefGoogle Scholar
  24. Lowe, R. K. (2003). Animation and learning: Selective processing of information in dynamic graphics. Learning and Instruction, 13, 157–176.CrossRefGoogle Scholar
  25. Lund, A., & Rasmussen, I. (2008). The right tool for the wrong task? Match and mismatch between first and second stimulus in double stimulation. International Journal of Computer-Supported Collaborative Learning, 3(4), 387–412.CrossRefGoogle Scholar
  26. McCloud, S. (1994). Understanding comics. The invisible art. New York: HarperPerennial.Google Scholar
  27. Morton, J. P., Doran, D. A., & MacLaren, D. P. M. (2008). Common student misconceptions in exercise physiology and biochemistry. Advances in Physiology Education, 32(2), 142–146.CrossRefGoogle Scholar
  28. Sanders, M. (1993). Erroneous ideas about respiration: The teacher factor. Journal of Research in Science Teaching, 30(8), 919–934.CrossRefGoogle Scholar
  29. Smith, C., Maclin, D., Grosslight, L., & Davis, H. (1997). Teaching for understanding: A study of students’ pre-instruction theories of matter and a comparison of the effectiveness of two approaches to teaching about matter and density. Cognition and Instruction, 15(3), 317–394.CrossRefGoogle Scholar
  30. Stahl, G. (2006). Group cognition: Computer support for collaborative knowledge building. Cambridge: MIT.Google Scholar
  31. Säljö, R. (1998). Thinking with and through artifacts: The role of psychological tools and physical artifacts in human learning and cognition. In D. Faulkner, K. Littleton, & M. Woodhead (Eds.), Learning relationships in the classroom. London: Routledge.Google Scholar
  32. Teasley, S. D., & Roschelle, J. (1998). Constructing a joint problem space: The computer as a tool for sharing knowledge. Retrieved from http://ctl.sri.com/publications/downloads/JointProblemSpace.pdf.
  33. Tomlin, R. S. (1997). Mapping conceptual representations into linguistic representations: The role of attention in grammar. In J. Nuyts & E. Pedersen (Eds.), Language and conceptualization (pp. 162–189). Cambridge: Cambridge University Press.Google Scholar
  34. Wegerif, R. (2007). Dialogic education and technology. New York: Springer Verlag.CrossRefGoogle Scholar
  35. Wertsch, J. V. (1991). Voices of the mind. A sociocultural approach to mediated action. Cambridge: Harvard University Press.Google Scholar
  36. Vygotsky, L. (1934/1986). Thought and language. Cambridge: MIT.Google Scholar

Copyright information

© International Society of the Learning Sciences, Inc.; Springer Science + Business Media, LLC 2010

Authors and Affiliations

  1. 1.Department of Applied Information TechnologyIT University of GothenburgGöteborgSweden

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