Research in Science Education

, Volume 40, Issue 5, pp 639–673 | Cite as

Comparison of Earth Science Achievement Between Animation-Based and Graphic-Based Testing Designs

  • Huang-Ching Wu
  • Chun-Yen Chang
  • Chia-Li D. Chen
  • Ting-Kuang Yeh
  • Cheng-Chueh Liu


This study developed two testing devices, namely the animation-based test (ABT) and the graphic-based test (GBT) in the area of earth sciences covering four domains that ranged from astronomy, meteorology, oceanography to geology. Both the students’ achievements of and their attitudes toward ABT compared to GBT were investigated. The purposes of this study were fourfold as follows: (1) to examine the validity and the reliability of ABT, (2) to compare the difference of ABT and GBT in student achievements, (3) to investigate the impact of ABT versus GBT on student achievements with different levels of prior knowledge and (4) to explore the ABT participants’ attitudes toward ABT in comparison with GBT. A total of 314 students, divided into two groups, participated in the study. Upon completion of the test, the students who took the ABT were given the survey, Attitude toward Animated Assessment Scale (AAAS). The results of the study indicated that ABT was a valid and reliable way of testing. While no significant difference was found between the test formats in student achievements in general, practical significance existed when the study further compared the impact of ABT versus GBT in student achievements with various levels of prior knowledge. It was found that low prior knowledge students performed better in ABT while high prior knowledge students performed better in GBT. Finally, more than 60% of the participants who took ABT were satisfied and held positive attitudes toward ABT.


Animation Computerized assessment Achievement Attitude 



The work in this study was supported by the National Science Council of Taiwan under contracts NSC 97-2631-S-003 -003 and NSC 98-2631-S-003 -002. The authors especially thank Nan-hu senior high school’searth science teacher Dong jia-ju and 10th grade students for their kindly help to this project.


  1. American Association for the Advancement of Science. (1993). Benchmarks for science literacy. New York: Oxford University Press.Google Scholar
  2. Ainsworth, S., & VanLabeke, N. (2004). Multiple forms of dynamic representation. Learning and Instruction, 14(3), 241–255. doi: 10.1016/j.learninstruc.2004.06.002.CrossRefGoogle Scholar
  3. Alessi, S. M., & Trollip, S. R. (2001). Multimedia for learning: methods and development (3rd ed.). Boston, MA: Allyn & Bacon.Google Scholar
  4. Bakx, A. W. E. A., & Sijtsma, K. (2002). Development and evaluation of a students-centered multimedia self-assessment instrument for social-communicative competence. Instructional Science, 30, 335–359. doi: 10.1023/A:1019820629644.CrossRefGoogle Scholar
  5. Bodemer, D., Ploetzner, R., Feuerlein, I., & Spada, H. (2004). The active integration of information during learning with dynamic and interactive visualizations. Learning and Instruction, 14, 325–341. doi: 10.1016/j.learninstruc.2004.06.006.CrossRefGoogle Scholar
  6. Chang, C. Y., Barufaldi, J. P., Lin, M. C., & Chen, Y. C. (2007). Assessing tenth-grade students’ problem solving ability online in the area of earth sciences. Computers in Human Behavior, 23, 1971–1981. doi: 10.1016/j.chb.2006.02.014.CrossRefGoogle Scholar
  7. Clark, R., Ngyuyen, F., & Sweller, J. (2006). Efficiency in learning: evidence-based guidelines to manage cognitive load. San Francisco, CA: Wiley.Google Scholar
  8. Cohen, J. (1988). Statistical power analysis for the behavioral sciences (2nd ed.). Hillsdale, NJ: Lawrence Erlbaum.Google Scholar
  9. Cook, M. P. (2006). Visual representation in science education: the influence of prior knowledge and cognitive load theory on instructional design principles. Science Education, 90, 1073–1091. doi: 10.1002/sce.20164.CrossRefGoogle Scholar
  10. Dancy, M. H., & Beichner, R. (2006). Impact of animation on assessment of conceptual understanding in physics. Physics Education Research, 2, 010104. doi: 10.1103/PhysRevSTPER.2.010104.CrossRefGoogle Scholar
  11. Daniel, L. G. (1998). Statistical significance testing: a historical overview of misuse and misinterpretation with implication for the editorial policies of educational journals. Research in the Schools, 5(2), 23–32.Google Scholar
  12. Dexter, S. (2006). Educational theory into practice software. In D. Gibson, C. Aldrich & M. Prensky (Eds.), Games and simulations in online learning: research & development frameworks (pp. 223–234). Hershey, PA: Idea Group.Google Scholar
  13. Fraenkel, J. R., & Wallen, N. E. (1993). How to design and evaluate research in education (2nd ed.). New York: McGraw-Hill.Google Scholar
  14. Kalyuga, S., Ayres, P., Chandler, P., & Sweller, J. (2003). The expertise reversal effect. Educational Psychologist, 38(1), 23–21. doi: 10.1207/S15326985EP3801_4.CrossRefGoogle Scholar
  15. Kirschner, P. A., Sweller, J., & Clark, R. E. (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(2), 75–86. doi: 10.1207/s15326985ep4102_1.CrossRefGoogle Scholar
  16. Lepper, M. R., Keavney, M., & Drake, M. (1996). Intrinsic motivation and extrinsic rewards: a commentary on Cameron and Pierce’s meta-analysis. Review of Educational Research, 66, 5–32.Google Scholar
  17. Lowe, R. K. (2003). Animation and learning: selective processing of information in dynamic graphics. Learning and Instruction, 13, 157–176. doi: 10.1016/S0959-4752(02)00018-X.CrossRefGoogle Scholar
  18. Lowe, R. (2004). Interrogation of a dynamic visualization during learning. Learning and Instruction, 14, 257–274. doi: 10.1016/j.learninstruc.2004.06.003.CrossRefGoogle Scholar
  19. Malone, T. W., & Lepper, M. R. (1987). Making learning fun: A taxonomy of intrinsic motivations for learning. In R. E. Snow & M. J. Farr (Eds.), Aptitude, learning and instruction: III. Cognitive and affective process analyses (pp. 223–253). Hillsdale, NJ: Erlbaum.Google Scholar
  20. Mayer, R. E. (2001). Multimedia learning. Cambridge, UK: Cambridge University Press.Google Scholar
  21. McLean, J. E., & Ernest, J. M. (1998). The role of statistical significance testing in educational research. Research in the Schools, 5(2), 15–22.Google Scholar
  22. Rieber, L. P. (1990). Using computer animated graphics in science instruction with children. Journal of Educational Psychology, 82, 135–140. doi: 10.1037/0022-0663.82.1.135.CrossRefGoogle Scholar
  23. Schnotz, W., & Grzondziel, H. (1996). Knowledge acquisition with static and animated pictures in computer-based learning. Paper presented at the Annual Meeting of the American Educational Research Association, New York.Google Scholar
  24. Smith, B., & Caputi, P. (2004). The development of the attitude towards the computerized assessment scale. Journal of Educational Computing Research, 31, 407–422. doi: 10.2190/R6RV-PAQY-5RG8-2XGP.CrossRefGoogle Scholar
  25. Sweller, J. (1988). Cognitive load during problem solving: effects on learning. Cognitive Science, 12, 257–285.CrossRefGoogle Scholar
  26. Tversky, B., Morrison, J. B., & Betrancourt, M. (2002). Animation: can it facilitate? International Journal of Human-Computer Studies, 57, 247–262. doi: 10.1006/ijhc.2002.1017.CrossRefGoogle Scholar
  27. van Merrienboer, J. J. G., & Sweller, J. (2005). Cognitive load theory and complex learning: recent developments and future directions. Educational Psychology Review, 17(2), 147–177. doi: 10.1007/s10648-005-3951-0.CrossRefGoogle Scholar
  28. Wouters, P., Paas, F., & van Merrienboer, J. J. G. (2008). How to optimize learning from animated models: a review of guidelines based on cognitive load. Review of Educational Research, 78(3), 645–675. doi: 10.3102/0034654308320320.CrossRefGoogle Scholar

Copyright information

© Springer Science+Business Media B.V. 2009

Authors and Affiliations

  • Huang-Ching Wu
    • 1
  • Chun-Yen Chang
    • 1
    • 2
    • 3
    • 4
  • Chia-Li D. Chen
    • 3
  • Ting-Kuang Yeh
    • 1
    • 3
  • Cheng-Chueh Liu
    • 3
  1. 1.Department of Earth SciencesNational Taiwan Normal UniversityTaipeiTaiwan
  2. 2.Graduate Institute of Science EducationTaipeiTaiwan
  3. 3.Science Education CenterNational Taiwan Normal UniversityTaipeiTaiwan
  4. 4.TaipeiTaiwan

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