Journal of Science Education and Technology

, Volume 21, Issue 3, pp 370–383 | Cite as

The Role of Computer Simulation in an Inquiry-Based Learning Environment: Reconstructing Geological Events as Geologists



Several researchers have investigated the effects of computer simulations on students’ learning. However, few have focused on how simulations with authentic contexts influences students’ inquiry skills. Therefore, for the purposes of this study, we developed a computer simulation (FossilSim) embedded in an authentic inquiry lesson. FossilSim integrated data from real field investigations with geological laws for identifying the sequence of geological events. Data were collected from two experiments to examine ninth graders’ abilities for reconstructing a sequence of geological events with the aid of FossilSim. The sample groups in Experiments 1 and 2 were 58 and 11 ninth graders, respectively. The results indicated that the authentic inquiry lesson promoted the development of students’ inquiry skills. In addition, FossilSim played a key role in engaging students to apply geological laws, make multi-scale observations, and clarify their ideas about geological time.


Inquiry-based learning Inquiry skills Computer simulation Geological time 


  1. Ault CR (1998) Criteria of excellence for geological inquiry: the necessity of ambiguity. J Res Sci Teach 35(2):189–212CrossRefGoogle Scholar
  2. Bell RL, Trundle KC (2008) The use of a computer simulation to promote scientific conceptions of moon phases. J Res Sci Teach 45(3):346–372CrossRefGoogle Scholar
  3. Chinn CA, Malhotra BA (2002) Epistemologically authentic inquiry in schools: a theoretical framework for evaluating inquiry tasks. Sci Educ 86(2):175–218CrossRefGoogle Scholar
  4. de Jong T, Van Joolingen W (1998) Scientific discovery learning with computer simulations of conceptual domains. Rev Edu Res 68(2):179–201Google Scholar
  5. Dodick J, Orion N (2003a) Cognitive factors affecting students understanding of geological time. J Res Sci Teach 40(4):415–442CrossRefGoogle Scholar
  6. Dodick J, Orion N (2003b) Measuring student understanding of geological time. Sci Educ 87(5):708–731CrossRefGoogle Scholar
  7. Fretz EB, Wu HK, Zhang B, Davis EA, Krajcik JS, Soloway E (2002) An investigation of software scaffolds supporting modeling practices. Res Sci Edu 32:567–589CrossRefGoogle Scholar
  8. Frodeman RL (1995) Geological reasoning: geology as an interpretive and historical science. Geol Soc Am Bull 107(8):960–968CrossRefGoogle Scholar
  9. Gilbert JK (2005) Visualization: a metacognitive skill in science and science education. In: Gilbert JK (ed) Visualization in science education. Springer, Dodrecht, pp 9–27CrossRefGoogle Scholar
  10. Hidalgo AJ, Fernando SIES, Otero JICE (2004) An analysis of the understanding of geological time by students at secondary and post-secondary levels. Int J Sci Edu 26(7):845–857CrossRefGoogle Scholar
  11. Hsu YS, Thomas RA (2002) The impacts of a web-aided instructional simulation on science learning. Int J Sci Edu 24(9):955–979CrossRefGoogle Scholar
  12. Kali Y, Orion N, Mazor E (1997) Software for assisting high-school students in the spatial perception of geological structures. J Geosci Edu 45:10–21Google Scholar
  13. Kastens KA, Agrawal S, Liben LS (2009) How students and field geologists reason in integrating spatial observations from outcrops to visualize a 3-D geological structure. Int J Sci Edu 31:365–393CrossRefGoogle Scholar
  14. Kozma RB (1982) The design of instruction in a chemistry laboratory course. J Res Sci Teach 19:261–270CrossRefGoogle Scholar
  15. Lehrer R, Schauble L (2006) Cultivating model-based reasoning in science education. In: Sawyer RK (ed) The Cambridge handbook of the learning sciences. Cambridge University Press, Cambridge, pp 371–388Google Scholar
  16. Libarkin JC, Brick C (2002) Research methodologies in science education: visualization and the geosciences. J Geosci Edu 50(4):449–455Google Scholar
  17. Luo W, Konen M (2007) New results from using a web-based interactive landform simulation model (WILSIM) in a general education physical geography course. J Geosci Edu 55(5):423–425Google Scholar
  18. Luo W, Stravers J, Duffin K (2005) Lessons learned from using a web-based interactive landform simulation model (WILSIM) in a general education physical geography course. J Geosci Edu 53(5):489–493Google Scholar
  19. National Research Council (2000) Inquiry and the national science education standards: a guide for teaching and learning. National Academies Press, WAGoogle Scholar
  20. Orion N, Kali Y (2005) The effect of an earth-science learning program on students’ scientific thinking skills. J Geosci Edu 53(4):387–393Google Scholar
  21. Orion N, Ben-Chaim D, Kali Y (1997) Relationship between earth-science education and spatial visualization. J Geosci Edu 45:129–132Google Scholar
  22. Pena CM, Alessi SM (1999) Promoting a qualitative understanding of physics. J Comput Math Sci Teach 18:439–448Google Scholar
  23. Piburn MD, Reynolds SJ, Leedy DE, McAuliffe CM, Birk JP, Johnson JK (2002) The hidden earth: visualization of geologic features and their subsurface geometry. In: Proceedings of the paper presented at the annual conference of the national association for research in science teaching, New Orleans, LAGoogle Scholar
  24. Roth WM (1995) Authentic school science: knowing and learning in open-inquiry science laboratories. Kluwer, DordrechtGoogle Scholar
  25. Roth WM, Roychoudhury A (1993) The development of science process skills in authentic contexts. J Res Sci Teach 30(2):127–152CrossRefGoogle Scholar
  26. Taylor JC (1994) Novex analysis: a cognitive science approach to instructional design. Edu Technol 34:5–13Google Scholar
  27. Trend R (2000) Conceptions of geological time among primary teacher trainees, with reference to their engagement with geoscience, history, and science. Int J Sci Edu 22(5):539–555CrossRefGoogle Scholar
  28. White BY (1984) Designing computer games to help physics students understand Newton’s laws of motion. Cogn Instr 1(1):69–108CrossRefGoogle Scholar
  29. White BY, Frederiksen JR (1998) Inquiry, modeling, metacognition: making science accessible to all students. Cogn Instr 16(1):3–118CrossRefGoogle Scholar
  30. Winn W, Stahr F, Sarason C, Fruland R, Oppenheimer P, Lee YL (2006) Learning oceanography from a computer simulation compared with direct experience at sea. J Res Sci Teach 43:25–42CrossRefGoogle Scholar
  31. Wu H-K, Hsu Y-S, Hwang F-K (2010) Designing a technology-enhanced learning environment to support scientific modeling. Turk Online J Edu Technol 9(4):58–65Google Scholar

Copyright information

© Springer Science+Business Media, LLC 2011

Authors and Affiliations

  1. 1.National Taiwan Normal UniversityTaipeiTaiwan

Personalised recommendations