Journal of Science Education and Technology

, Volume 21, Issue 1, pp 133–147 | Cite as

Virtual and Physical Experimentation in Inquiry-Based Science Labs: Attitudes, Performance and Access

Article

Abstract

This study investigated the learning dimensions that occur in physical and virtual inquiry-based lab investigations, in first-year secondary chemistry classes. This study took place over a 2 year period and utilized an experimental crossover design which consisted of two separate trials of laboratory investigation. Assessment data and attitudinal data were gathered and analyzed to measure the instructional value of physical and virtual lab experiences in terms of student performance and attitudes. Test statistics were conducted for differences of means for assessment data. Student attitudes towards virtual experiences in comparison to physical lab experiences were measured using a newly created Virtual and Physical Experimentation Questionnaire (VPEQ). VPEQ was specifically developed for this study, and included new scales of Usefulness of Lab, and Equipment Usability which measured attitudinal dimensions in virtual and physical lab experiences. A factor analysis was conducted for questionnaire data, and reliability of the scales and internal consistency of items within scales were calculated. The new scales were statistically valid and reliable. The instructional value of physical and virtual lab experiences was comparable in terms of student performance. Students showed preference towards the virtual medium in their lab experiences. Students showed positive attitudes towards physical and virtual experiences, and demonstrated a preference towards inquiry-based experiences, physical or virtual. Students found virtual experiences to have higher equipment usability as well as a higher degree of open-endedness. In regards to student access to inquiry-based lab experiences, virtual and online alternatives were viewed favorably by students.

Keywords

Virtual labs Inquiry-learning Experimentation Hands-on Simulations Chemistry 

Supplementary material

10956_2011_9291_MOESM1_ESM.tif (931 kb)
Supplementary material 1 (TIFF 930 kb)
10956_2011_9291_MOESM2_ESM.tif (966 kb)
Supplementary material 2 (TIFF 965 kb)
10956_2011_9291_MOESM3_ESM.docx (15 kb)
Supplementary material 2 (DOCX 16 kb)

References

  1. Akilli GK (2009) Games and simulations: a new approach in education? In: Ferdig RE (ed) Handbook of research on effective electronic gaming in education (3 volumes), vol 3. Information Science Reference, Hershey, PA, pp 1–1759Google Scholar
  2. Akpan J (2001) Using a computer simulation before dissection to help students’ learn anatomy. In: Price J, Willis DA, Davis N, Willis J (eds) Society for information technology & teacher education international conference 2001. AACE, Norfolk, VA, pp 2467–2472Google Scholar
  3. Akpan J, Strayer J (2010) Which comes first the use of computer simulation of frog dissection or conventional dissection as academic exercise? J Comput Math Sci Teach 29(2):113–138Google Scholar
  4. Aladejana F, Aderibigbe O (2007) Science laboratory environment and academic performance. J Sci Educ Technol 16(6):500–506. doi:10.1007/s10956-007-9072-4 CrossRefGoogle Scholar
  5. Baltzis K, Koukias K (2009) Using laboratory experiments and circuit simulation it tools in an undergraduate course in analog electronics. J Sci Educ Technol 18(6):546–555. doi:10.1007/s10956-009-9169-z CrossRefGoogle Scholar
  6. Barnea N, Dori YJ (1999) High-school chemistry students’ performance and gender differences in a computerized molecular modeling learning environment. J Sci Educ Technol 8(4):257–271. doi:10.1023/a:1009436509753 CrossRefGoogle Scholar
  7. Baxter G (1995) Using computer simulations to assesss hands-on science learning. J Sci Educ Technol 4(1):21–27. doi:10.1007/bf02211578 CrossRefGoogle Scholar
  8. Bayraktar S (2002) A meta-analysis of the effectiveness of computer-assisted instruction in science education. J Res Technol Educ 34(2):173–188Google Scholar
  9. Bell RL, Trundle KC (2008) The use of a computer simulation to promote scientific conceptions of moon phases. J Res Sci Teach 45(3):346–372. doi:10.1002/tea.20227 CrossRefGoogle Scholar
  10. Bhargava P, Antonakakis J, Cunningham C, Zehnder AT (2006) Web-based virtual torsion laboratory. Comput Appl Eng Educ 14(1):1–8. doi:10.1002/cae.20061 CrossRefGoogle Scholar
  11. Bourque DR, Carlson GR (1987) Hands-on versus computer simulation methods in chemistry. J Chem Educ 64(3):232–234CrossRefGoogle Scholar
  12. Burkholder PR, Purser GH, Cole RS (2008) Using molecular dynamics simulation to reinforce student understanding of intermolecular forces. J Chem Educ 85(8): 1071-null. doi:10.1021/ed085p1071 Google Scholar
  13. Clariana RB (1989) Computer simulations of laboratory experiences. J Comput Math Sci Teach 8(2):14–19Google Scholar
  14. Clark R (1994) Media will never influence learning. Educ Technol Res Dev 42(2):21–29. doi:10.1007/bf02299088
  15. de Jong T (2006) Computer simulations: technological advances in inquiry learning. Science 312(5773):532–533. doi:10.1126/science.1127750 CrossRefGoogle Scholar
  16. de Jong T, van Joolingen WR (1998) Scientific discovery learning with a computer simulations of conceptual domains. Rev Educ Res 68(2):179–201Google Scholar
  17. Demmin P, Herron P, Miller G, Mullins J, Zipp A (2010) Guide for the recommended laboratory program, pp 29–39Google Scholar
  18. Demonstration of Restructuring in Public Education (2000). California Code—Division 4: Instruction and services [4600.-64100.] (vol. EDC). State of California, USAGoogle Scholar
  19. Derting TL, Cox JR (2008) Using a tablet PC to enhance student engagement and learning in an introductory organic chemistry course. J Chem Educ 85(12), 1638-null. doi:10.1021/ed085p1638 Google Scholar
  20. Dewey J (1938) Logic, the theory of inquiry. H. Holt and Company, New YorkGoogle Scholar
  21. Dissection Alternatives Act (2000) 105 ILCS 112 (vol. 105). ILL COMP STAT, IllinoisGoogle Scholar
  22. Donovan W, Nakhleh M (2007) Student use of web-based tutorial materials and understanding of chemistry concepts. J Comput Math Sci Teach 26(4):291–327Google Scholar
  23. Dori YJ, Barak M (2001) Virtual and physical molecular modeling: fostering model perception and spatial understanding. J Educ Technol Soc 4(1):61–74Google Scholar
  24. Dori YJ, Barnea N (1997) In-service chemistry teachers’ training: the impact of introducing computer technology on teachers’ attitudes and classroom implementation. Int J Sci Educ 19(5):577–592CrossRefGoogle Scholar
  25. Eylon BS, Linn MC (1988) Learning and instruction: an examination of four research perspectives in science education. Rev Educ Res 58:251–301Google Scholar
  26. Finkelstein ND, Adams WK, Keller CJ, Kohl PB, Perkins KK, Podolefsky NS, et al (2005) When learning about the real world is better done virtually: a study of substituting computer simulations for laboratory equipment. Phy Rev Special Top Phy Educ Res 1(1), 010103-010101–010103-010108Google Scholar
  27. Finkelstein ND, Perkins KK, Adams W, Kohl P, Podolefsky N (2005b) Can computer simulations replace real equipment in undergraduate laboratories? AIP Conf Proc 790(1):101–104CrossRefGoogle Scholar
  28. Flick L (1993) The meanings of hands-on science. J Sci Teacher Educ 4(1):1–8. doi:10.1007/bf02628851 CrossRefGoogle Scholar
  29. Foti S, Ring G (2008) Using a simulation-based learning environment to enhance learning and instruction in a middle school science classroom. J Comput Math Sci Teach 27(1):103–120Google Scholar
  30. Fraser BJ, McRobbie CJ, Giddings GJ (1993a) Development and cross-national validation of a laboratory classroom environment instrument for senior high school science. Sci Educ 77(1):1CrossRefGoogle Scholar
  31. Fraser BJ, McRobbie CJ, Giddings GJ (1993b) Development and cross-national validation of a laboratory classroom environment instrument for senior high school science. Sci Educ 77(1):1–24. doi:10.1002/sce.3730770102 CrossRefGoogle Scholar
  32. Frederiksen JR, White BY, Gutwill J (1999) Dynamic mental models in learning science: the importance of constructing derivational linkages among models. J Res Sci Teach 36(7):808–836CrossRefGoogle Scholar
  33. Hsu YS (2008) Learning about seasons in a technologically enhanced environment: the impact of teacher-guided and student-centered instructional approaches on the process of students’ conceptual change. Sci Educ 92(2):320–344. doi:10.1002/sce.20242 CrossRefGoogle Scholar
  34. Huppert J, Lomask SM, Lazarowitz R (2002) Computer simulations in the high school: students’ cognitive stages, science process skills and academic achievement in microbiology. Int J Sci Educ 24(8):803–821CrossRefGoogle Scholar
  35. Jaakkola T, Nurmi S (2008) Fostering elementary school students’ understanding of simple electricity by combining simulation and laboratory activities. J Comput Assist Learn 24(4):271–283. doi:10.1111/j.1365-2729.2007.00259.x CrossRefGoogle Scholar
  36. Jaakkola T, Nurmi S, Veermans K (2010) A comparison of students’ conceptual understanding of electric circuits in simulation only and simulation-laboratory contexts. J Res Sci Teach n/a-n/a. doi:10.1002/tea.20386
  37. Jensen WB (2003) The origin of stoichiometry problems. J Chem Educ 80(11), 1248-null. doi:10.1021/ed080p1248 Google Scholar
  38. Kennepohl D (2001) Using computer simulations to supplement teaching laboratories in chemistry for distance delivery. J Distance Educ 16:58–65Google Scholar
  39. Kenward MG (2005) Crossover design (encyclopedia of statistics in behavioral science). Wiley, NYGoogle Scholar
  40. Kinzie M, Jean Foss M, Powers S (1993) Use of dissection-related courseware by low-ability high school students: a qualitative inquiry. Educ Tech Res Dev 41(3):87–101. doi:10.1007/bf02297359 CrossRefGoogle Scholar
  41. Kirschner P, Huisman W (1998) ‘Dry laboratories’ in science education; computer-based practical work. Int J Sci Educ 20(6):665CrossRefGoogle Scholar
  42. Klahr D, Nigam M (2004) The equivalence of learning paths in early science instruction. Psychol Sci 15(10):661–667CrossRefGoogle Scholar
  43. Klahr D, Triona LM, Williams C (2007) Hands on what? The relative effectiveness of physical versus virtual materials in an engineering design project by middle school children. J Res Sci Teach 44(1):183–203. doi:10.1002/tea.20152 CrossRefGoogle Scholar
  44. Kumar D, Sherwood R (2007) Effect of a problem based simulation on the conceptual understanding of undergraduate science education students. J Sci Educ Technol 16(3):239–246. doi:10.1007/s10956-007-9049-3 CrossRefGoogle Scholar
  45. Lagowski JJ (2002) The role of the laboratory in chemical education. Retrieved 9 July 2004 from http://www.utexas.edu/research/chemed/lagowski/jjl_beijing_02.pdf
  46. Late Nite Labs (2008). http://www.latenitelabs.com/. Accessed Aug 2007
  47. Marshall JA, Young ES (2006) Preservice teachers’ theory development in physical and simulated environments. J Res Sci Teach 43(9):907–937. doi:10.1002/tea.20124 CrossRefGoogle Scholar
  48. Moore JL, Thomas FH (1983) Computer simulation of experiments: a valuable alternative to traditional laboratory work for secondary school science teaching. Sch Sci Rev 64(229):641–655Google Scholar
  49. Nakhleh MB (1994) A review of microcomputer-based labs: how have they affected science learning? J Comput Math Sci Teach 13(4):368–381Google Scholar
  50. Newby M, Fisher D (1997) An instrument for assessing the learning environment of a computer laboratory. J Educ Comput Res 16(2):179CrossRefGoogle Scholar
  51. NSTA (2007) NSTA position statement: the use of computers in science educationGoogle Scholar
  52. Pyatt KA (2009) Case for simulations. In: I Gibson, R Weber, K McFerrin, R Carlsen, DA Willis (eds) Proceedings of society for information technology & teacher education international conference (SITE), Charleston, South Carolina, USA, (pp 1541–1544). AACE, Chesapeake, VA. doi:http://www.editlib.org/p/30832
  53. Pyatt K, Sims R (2007). Learner performance and attitudes in traditional versus simulated laboratory experiences. In: Atkinson RJ, McBeath C, Soong SKA, Cheers C (eds) ICT: providing choices for learners and learning. Proceedings of ASCILITE Singapore 2007, Singapore, 2007 (pp 870–879). Nanyang Technological University, Nanyang Avenue, Singapore 639798: The Center for Educational Development. doi:http://www.ascilite.org.au/conferences/singapore07/procs/
  54. RC N (2006) America’s lab report: investigations in high school science. National Academy Press, Washington, DCGoogle Scholar
  55. Rivers RH, Vockell E (1987) Computer simulations to stimulate scientific problem solving. J Res Sci Teach 24(5):403–415. doi:10.1002/tea.3660240504 CrossRefGoogle Scholar
  56. Stieff M, Wilensky U (2003) Connected chemistry—incorporating interactive simulations into the chemistry classroom. J Sci Educ Technol 12(3):285–302. doi:10.1023/a:1025085023936 CrossRefGoogle Scholar
  57. Stone DC (2007) Teaching chromatography using virtual laboratory exercises. J Chem Educ 84(9), 1488-null. doi:10.1021/ed084p1488 Google Scholar
  58. Tao PK, Gunstone RF (1999) The process of conceptual change in force and motion during computer-supported physics instruction. J Res Sci Teach 36(7):859–882. doi:10.1002/(sici)1098-2736(199909)36:7<859:aid-tea7>3.0.co;2-j CrossRefGoogle Scholar
  59. Triona LM, Klahr D (2003) Point and click or grab and heft: comparing the influence of physical and virtual instructional materials on elementary school students’ ability to design experiments. Cogn Instr 21(2):149–173CrossRefGoogle Scholar
  60. Watson JF, Evergreen Consulting Associates (2007) A national primer on K-12 online learning. North American Council for Online Learning. www.inacol.org/docs/national_report.pdf
  61. Wieman CE, Adams WK, Perkins KK (2008) Physics: PhET: simulations that enhance learning. Science 322(5902):682–683. doi:10.1126/science.1161948 CrossRefGoogle Scholar
  62. Williamson VM, Abraham MR (1995) The effects of computer animation on the particulate mental models of college chemistry students. J Res Sci Teach 32(5):521–534. doi:10.1002/tea.3660320508 CrossRefGoogle Scholar
  63. 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(1):25–42. doi:10.1002/tea.20097 CrossRefGoogle Scholar
  64. Woodrow JEJ (1994) The development of computer-related attitudes of secondary students. J Educ Comput Res 11(4):307–338CrossRefGoogle Scholar
  65. Zacharia Z (2003) Beliefs, attitudes, and intentions of science teachers regarding the educational use of computer simulations and inquiry-based experiments in physics. J Res Sci Teach 40(8):792–823. doi:10.1002/tea.10112 CrossRefGoogle Scholar
  66. Zacharia Z (2005) The impact of interactive computer simulations on the nature and quality of postgraduate science teachers’ explanations in physics. Int J Sci Educ 27(14):1741–1767CrossRefGoogle Scholar
  67. Zacharia Z (2007) Comparing and combining real and virtual experimentation: an effort to enhance students’ conceptual understanding of electric circuits. J Computer Assist Learn 23(2):120–132CrossRefGoogle Scholar
  68. Zacharia Z, Olympiou G, Papaevripidou M (2008) Effects of experimenting with physical and virtual manipulatives on students’ conceptual understanding in heat and temperature. J Res Sci Teach 45(9):1021–1035. doi:10.1002/tea.20260 CrossRefGoogle Scholar

Copyright information

© Springer Science+Business Media, LLC 2011

Authors and Affiliations

  1. 1.Eastern Washington UniversityCheneyUSA
  2. 2.Capella UniversityMinneapolisUSA

Personalised recommendations