Skip to main content

The Impact of Virtual Laboratory Environments in Teaching-by-Inquiry Electric Circuits in Greek Secondary Education: The ElectroLab Project

  • Chapter
  • First Online:
Research on e-Learning and ICT in Education

Abstract

The present paper presents a review of the results of the ElectroLab project, which is a research and development program on the utilization of virtual laboratory environments in teaching-by-inquiry DC electric circuits to students of secondary education in Greece. The impact of the virtual laboratory environments when embedded in investigative activities is assessed with regard to (a) the students’ conceptual evolution and comprehension of simple and complex phenomena in electric circuits, (b) the students’ ability to transform electric circuits from one form to another (real, virtual, or schematic), and (c) the students’ ability to design and successfully implement experimental procedures with simple electric circuits. Desired features and affordances of virtual laboratory environments emerge from these results, which, when properly utilized, may prove virtual laboratories to be very powerful teaching tools.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 84.99
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 109.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info
Hardcover Book
USD 109.99
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

References

  • Ainsworth, S. (1999). The functions of multiple representations. Computers and Education, 33, 131–152.

    Article  Google Scholar 

  • Ainsworth, S. (2006). DeFT: A conceptual framework for considering learning with multiple representations. Learning and Instruction, 16, 183–198.

    Article  Google Scholar 

  • Ainsworth, S., Bibby, P., & Wood, D. (2002). Examining the effects of different multiple representational systems in learning primary mathematics. Journal of the Learning Sciences, 11(1), 25–61.

    Article  Google Scholar 

  • Ainsworth, S., & van Labeke, N. (2004). Multiple forms of dynamic representation. Learning and Instruction, 14, 241–255.

    Article  Google Scholar 

  • Bisdikian, G., Psillos, D., Hatzikraniotis, E., & Barbas, A. (2006). An open laboratory and learning environment (OLLE) in optics. In V. Dagdilelis & D. Psillos (Eds.), Proceedings of the 5th Panhellenic Conference of ICT in Education (pp. 188–195). Thessaloniki, Greece (in Greek).

    Google Scholar 

  • de Jong, T., Ainsworth, S., Dobson, M., van der Hulst, A., Levonen, J., Reimann, P., et al. (1998). Acquiring knowledge in science and mathematics: The use of multiple representations in technology based learning environments. In M. van Someren, P. Reimann, H. Boshuizen, & T. de Jong (Eds.), Learning with multiple representations (pp. 9–41). Oxford: Elsevier Science.

    Google Scholar 

  • Engelhardt, P. V., & Beichner, R. J. (2004). Students’ understanding of direct current resistive electrical circuits. American Journal of Physics, 72(1), 98–115.

    Article  Google Scholar 

  • Evaggelou, F., & Kotsis, K. (2009). Characteristics of studies in international bibliography regarding learning outcomes from the comparison of virtual and real experiments in teaching and learning of physics. In P. Kariotoglou, A. Spirtou, & A. Zoupidis (Eds.), Proceedings of the 6th Panhellenic Conference of the Union for Education in Physical Sciences and Technology (pp. 335–342) (in Greek).

    Google Scholar 

  • Finkelstein, N. D., Adams, W. K., Keller, C. J., Kohl, P. B., Perkins, K. K., Podolefsky, N. S., et al. (2005). When learning about the real world is better done virtually: A study of substituting computer simulations for laboratory equipment. Physical Review Special Topics-Physics Education Research, 1, 1–8.

    Google Scholar 

  • Garratt, J., & Tomlinson, J. (2001). Experimental design – Can it be learned? University Chemistry Education, 5(2), 74–79.

    Google Scholar 

  • Goldstone, R. L., & Son, J. Y. (2005). The transfer of scientific principles using concrete and idealized simulations. The Journal of the Learning Sciences, 14(1), 69–110.

    Article  Google Scholar 

  • Hofstein, A., & Lunetta, V. N. (2004). The laboratory in science education: Foundations for the twenty-first century. Science Education, 88, 28–54.

    Article  Google Scholar 

  • Jaakkola, T., Nurmi, S., & Lehtinen, E. (2011). A comparison of students’ conceptual understanding of electric circuits in simulation only and simulation-laboratory contexts. Journal of Research in Science Teaching, 48(1), 71–93.

    Article  Google Scholar 

  • Jaakkola, T., & Veermans, K. (2015). Effects of abstract and concrete simulation elements on science learning. Journal of Computer Assisted Learning, 31, 300–313.

    Article  Google Scholar 

  • Johnson, A. M., Reisslein, J., & Reisslein, M. (2013). Representation sequencing in computer-based engineering education. Computers & Education, 72, 249–261. https://doi.org/10.1016/j.compedu.2013.11.010

    Article  Google Scholar 

  • Johnstone, A. H., & Al-Shuaili, A. (2001). Learning in the laboratory; some thoughts from the literature. University Chemistry Education, 5(1), 42–51.

    Google Scholar 

  • Klahr, D., Triona, L., & Williams, C. (2007). Hands on what? The relative effectiveness of physical versus virtual materials in an engineering design project by middle school children. Journal of Research in Science Teaching, 44(1), 183.

    Article  Google Scholar 

  • Kozma, R. (2003). The material features of multiple representations and their cognitive and social affordances for science understanding. Learning and Instruction, 13, 205–226.

    Article  Google Scholar 

  • Kozma, R. B., Russell, J., Jones, T., Marx, N., & Davis, J. (1996). The use of multiple, linked representations to facilitate science understanding. In S. Vosniadou, R. Glaser, E. DeCorte, & H. Mandel (Eds.), International perspectives on the psychological foundations of technology-based learning environments (pp. 41–60). Hillsdale, NJ: Erlbaum.

    Google Scholar 

  • KĂĽhl, T., Scheiter, T., Gerjets, P., & Gemballa, S. (2011). Can differences in learning strategies explain the benefits of learning from static and dynamic visualizations? Computers & Education, 56, 176–187.

    Article  Google Scholar 

  • Lefkos, I., Psillos, D., & Hatzikraniotis, E. (2011). Designing experiments on thermal interactions by secondary students in a simulated laboratory environment. Research in Science and Technological Education, 29(2), 189–204.

    Article  Google Scholar 

  • Mayer, R. E., & Moreno, R. (1998). A split-attention effect in multimedia learning: Evidence for dual processing systems in working memory. Journal of Educational Psychology, 90, 312–320.

    Article  Google Scholar 

  • McDermott, L. C., & Shaffer, P. S. (1992). Research as a guide for curriculum development: An example from introductory electricity. Part I: Investigation of student understanding. American Journal of Physics, 60(11), 994–1003.

    Article  Google Scholar 

  • McNeil, N. M., & Fyfe, E. R. (2012). “Concreteness fading” promotes transfer of mathematical knowledge. Learning and Instruction, 22, 440–448.

    Article  Google Scholar 

  • Moreno, R., Ozogul, G., & Reisslein, M. (2011). Teaching with concrete and abstract visual representations: Effects on students’ problem solving, problem representations, and learning perceptions. Journal of Educational Psycology, 103(1), 32–47.

    Article  Google Scholar 

  • Moreno, R., Reisslein, M., & Ozogul, G. (2009). Pre-College Electrical Engineering Instruction: Do abstract or contextualized representations promote better learning? In Proceedings of the IEEE/ASEE Frontiers in Education Conference, San Antonio, Texas, session M4J (pp. 1–6).

    Google Scholar 

  • Olympiou, G., Zacharia, Z., & de Jong, T. (2012). Making the invisible visible: Enhancing students’ conceptual understanding by introducing representations of abstract objects in a simulation. Instructional Science, 41(3), 575–596. https://doi.org/10.1007/s11251-012-9245-2

    Article  Google Scholar 

  • Psillos, D. (1997). Τeaching electricity (invited paper). In A. Tiberghien, E. L. Jossem, & J. Barojas (Eds.), Connecting research in physics education with teacher education. International Commission on Physics Education, 1997–1998.

    Google Scholar 

  • Psillos, D., Taramopoulos, A., Hatzikraniotis, E., Barbas, A., Molohidis, A., & Bisdikian, G. (2008). An open laboratory learning environment (OLLE) in the field of electricity. In H. Aggeli & N. Valanidis (Eds.), Proceedings of the 6th Panhellenic Conference of the Greek Association for ICT in Education, Cyprus (pp. 384–391) (in Greek).

    Google Scholar 

  • Reisslein, M., Moreno, R., & Ozogul, G. (2010). Pre-College Electrical Engineering Instruction: The impact of abstract vs. contextualized representation and practice on learning. Journal of Engineering Education, 99, 225–235.

    Article  Google Scholar 

  • Rosengrant, D., Etkina, E., & Van Heuvelen, A. (2006). An overview of recent research on multiple representations. In L. McCullough, P. Heron, & L. Hsu (Eds.), Physics Education Research Conference, AIP Conference Proceedings (pp. 149–152).

    Google Scholar 

  • Rutten, N., van Joolingen, W. R., & van der Veen, J. T. (2012). The learning effects of computer simulations in science education. Computers and Education, 58, 136–153.

    Article  Google Scholar 

  • Scaife, M., & Rogers, Y. (1996). External cognition: How do graphical representations work? International Journal of Human-Computer Studies, 45(2), 185–213.

    Article  Google Scholar 

  • Scheiter, K., Gerjets, P., Huk, T., Imhof, B., & Kammerer, Y. (2009). The effects of realism in learning with dynamic visualizations. Learning and Instruction, 19, 481–494.

    Article  Google Scholar 

  • Schnotz, W., & Bannert, M. (2003). Construction and interference in learning from multiple representations. Learning and Instruction, 13(2), 141–156.

    Article  Google Scholar 

  • Seufert, T. (2003). Supporting coherence formation in learning from multiple representations. Learning and Instruction, 13, 227–237.

    Article  Google Scholar 

  • Sweller, J., van Merrienboer, J. J. G., & Paas, F. (1998). Cognitive architecture and instructional design. Educational Psychology Review, 10, 251–296.

    Article  Google Scholar 

  • Taramopoulos, A. (2012). Investigating the effectiveness of simulated virtual laboratory environments in teaching Physics in compulsory education. PhD. thesis, Aristotle University of Thessaloniki, Thessaloniki.

    Google Scholar 

  • Taramopoulos, A., & Psillos, D. (2014). Raising the level of understanding through the use of dynamically linked concrete and abstract representations in virtual laboratory environments in electric circuits. In C. P. Constantinou, N. Papadouris, & A. Hadjigeorgiou (Eds.), E-Book Proceedings of the ESERA 2013 Conference, Nicosia, Cyprus (pp. 157–163). ISBN: 978-9963-700-77-6.

    Google Scholar 

  • Taramopoulos, A., & Psillos, D. (2017). Complex phenomena understanding in electricity through dynamically linked concrete and abstract representations. Journal of Computer Assisted Learning, 33(2), 151–163. https://doi.org/10.1111/jcal.12174

    Article  Google Scholar 

  • Taramopoulos, A., Psillos, D., & Hatzikraniotis, E. (2011a). Designing virtual experiments in electric circuits by high school students. In 9th International ESERA Conference, Lyon, France.

    Google Scholar 

  • Taramopoulos, A., Psillos, D., & Hatzikraniotis, E. (2011b). Teaching by inquiry electric circuits in virtual and real laboratory environments. In A. Jimoyiannis (Ed.), Research on e-learning and ICT in education: Technological, pedagogical and instructional issues (ch. 16, pp. 209–222). New York: Springer.

    Google Scholar 

  • White, R., & Gunstone, R. (1992). Probing understanding. London: Palmer Press.

    Google Scholar 

  • Wieman, C. E., Adams, W. K., & Perkins, K. K. (2008). PhET: Simulations that enhance learning. Science, 322, 682–683.

    Article  Google Scholar 

  • Zacharia, Z. C., & Olympiou, G. (2011). Physical versus virtual manipulative experimentation in physics learning. Learning and Instruction, 21(3), 317–331.

    Article  Google Scholar 

  • Zion, M., & Shedletzky, E. (2006). Overcoming the challenge of teaching open inquiry. The Science Education Review, 5(1), 8–10.

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Athanasios Taramopoulos .

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2018 Springer International Publishing AG, part of Springer Nature

About this chapter

Check for updates. Verify currency and authenticity via CrossMark

Cite this chapter

Taramopoulos, A., Psillos, D. (2018). The Impact of Virtual Laboratory Environments in Teaching-by-Inquiry Electric Circuits in Greek Secondary Education: The ElectroLab Project. In: Mikropoulos, T. (eds) Research on e-Learning and ICT in Education. Springer, Cham. https://doi.org/10.1007/978-3-319-95059-4_17

Download citation

  • DOI: https://doi.org/10.1007/978-3-319-95059-4_17

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-95058-7

  • Online ISBN: 978-3-319-95059-4

  • eBook Packages: EducationEducation (R0)

Publish with us

Policies and ethics