Skip to main content
SpringerLink
Log in

Changes in University Students’ Explanation Models of DC Circuits

  • Published:
Research in Science Education Aims and scope Submit manuscript

Abstract

One well-known learning obstacle is that students rarely use the concepts in the way that scientists use them. Rather, students mix up closely related concepts and are inclined towards matter-based conceptualisations. Furthermore, some researchers have argued that certain difficulties are rooted in the student’s limited repertoire of causal schemes. These two aspects are conveniently represented in the recent proposal of the systemic view of concept learning. We applied this framework in our analyses of university students’ explanations of DC circuits and their use of concepts such as voltage, current and resistance. Our data consist of transcribed group interviews, which we analysed with content analysis. The results of our analysis are represented with directed graphs. Our results show that students had a rather refined ontological knowledge of the concepts. However, students relied on rather simple explanation models, but few students were able to modify their explanations during the interview. Based on the analysis, we identified three processes of change: model switch, model refinement and model elaboration. This emphasises the importance of relevant relational knowledge at a later stage of learning. This demonstrates how concept individuation and learning of relational structures occurs (and in which order) and sets forth interesting research questions for future research.

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

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7
Fig. 8
Fig. 9

Similar content being viewed by others

Notes

  1. Chi et al. (1994) posit that “entities in the world may be viewed as belonging to different ontological categories” such as matter, mental states or processes (p. 28), Consequently, students’ ontologies can be described as knowledge of “what kind of entities there are in the world” (Amin et al., 2014, p. 59).

  2. Here we avoid discussing differences in covariation in models and laws (for a discussion adapted to science education, see Koponen (2007)).

  3. As an example, consider Ohm’s law U = RI, relating current, voltage and resistance or Q = CΔT, relating heat and change in temperature through heat capacity.

  4. Note that the relations are not always causal. It is possible to view the relational structure as constraining laws or covariation of concepts in the form of constrained determination.

  5. Linear causality refers to patterns wherein “A influences B” (Perkins and Grotzer 2005, p. 126). Similarly, direct causality refers to patterns that can be broken into constituent simple relations (Chi et al. 2012).

  6. Related descriptions include Clement’s (2002) intermediate models and the learning paths proposed by Duschl et al. (2011).

References

  • Amin, T. G., Smith, C. L., & Wiser, M. (2014). Student conceptions and conceptual change. In N. G. Lederman & S. K. Abell (Eds.), Handbook of research on science education (vol. 2) (pp. 57–81). New York, NY: Routledge.

    Google Scholar 

  • Andersen, H., Barker, P., & Xiang, C. (2013). The cognitive structure of scientific revolutions. Cambridge: Cambridge University Press.

    Google Scholar 

  • Andersen, H., & Nersessian, N. J. (2000). Nomic concepts, frames, and conceptual change. Philosophy of Science, 67, S224–S241.

    Article  Google Scholar 

  • Borges, A. T., & Gilbert, J. K. (1999). Mental models of electricity. International Journal of Science Education, 21(1), 95–117.

    Article  Google Scholar 

  • Brown, D. E., & Hammer, D. (2008). Conceptual change in physics. In S. Vosniadou (Ed.), International handbook of research on conceptual change (pp. 127–154). New York, NY: Routledge.

    Google Scholar 

  • Chi, M. T. (1997). Quantifying qualitative analyses of verbal data: a practical guide. The Journal of the Learning Sciences, 6(3), 271–315.

    Article  Google Scholar 

  • Chi, M. T. (2008). Three types of conceptual change: belief revision, mental model transformation, and categorical shift. In S. Vosniadou (Ed.), International handbook of research on conceptual change (pp. 61–82). New York, NY: Routledge.

    Google Scholar 

  • Chi, M. T. (2013). Two kinds and four sub-types of misconceived knowledge, ways to change it and the learning outcomes. In S. Vosniadou (Ed.), International handbook of research on conceptual change 2nd ed (pp. 49–70). London: Routledge.

    Google Scholar 

  • Chi, M. T., Feltovich, P. J., & Glaser, R. (1981). Categorization and representation of physics problems by experts and novices*. Cognitive Science, 5(2), 121–152.

    Article  Google Scholar 

  • Chi, M. T., Roscoe, R. D., Slotta, J. D., Roy, M., & Chase, C. C. (2012). Misconceived causal explanations for emergent processes. Cognitive Science, 36(1), 1–61.

    Article  Google Scholar 

  • Chi, M. T., Slotta, J. D., & De Leeuw, N. (1994). From things to processes: a theory of conceptual change for learning science concepts. Learning and Instruction, 4(1), 27–43.

    Article  Google Scholar 

  • Clement, J. J., & Steinberg, M. S. (2002). Step-wise evolution of mental models of electric circuits: a" learning-aloud" case study. The Journal of the Learning Sciences, 11(4), 389–452.

    Article  Google Scholar 

  • De Bock, D., Van Dooren, W., & Verschaffel, L. (2011). Students’ overuse of linearity: an exploration in physics. Research in Science Education, 41(3), 389–412.

    Article  Google Scholar 

  • Duschl, R., Maeng, S., & Sezen, A. (2011). Learning progressions and teaching sequences: a review and analysis. Studies in Science Education, 47(2), 123–182.

    Article  Google Scholar 

  • Elo, S., & Kyngäs, H. (2008). The qualitative content analysis process. Journal of Advanced Nursing, 62(1), 107–115.

    Article  Google Scholar 

  • Gupta, A., Hammer, D., & Redish, E. F. (2010). The case for dynamic models of learners’ ontologies in physics. The Journal of the Learning Sciences, 19(3), 285–321.

    Article  Google Scholar 

  • Hoyningen-Huene, P. (1993). Reconstructing scientific revolutions: Thomas S. Kuhn’s philosophy of science. Chicago, Ill: University of Chicago Press.

    Google Scholar 

  • Koponen, I. T., & Huttunen, L. (2013). Concept development in learning physics: the case of electric current and voltage revisited. Science & Education, 22(9), 2227–2254.

    Article  Google Scholar 

  • Koponen, I. T., & Kokkonen, T. (2014). A systemic view of the learning and differentiation of scientific concepts: the case of electric current and voltage revisited. Frontline Learning Research, 2(3), 140–166. doi:10.14786/flr.v2i2.120.

    Google Scholar 

  • Koumaras, P., Kariotoglou, P., & Psillos, D. (1997). Causal structures and counter-intuitive experiments in electricity. International Journal of Science Education, 19(6), 617–630.

    Article  Google Scholar 

  • Kuhn, T. S. (2012). The structure of scientific revolutions (4th ed.). Chicago, Ill: University of Chicago Press.

    Book  Google Scholar 

  • Lee, Y., & Law, N. (2001). Explorations in promoting conceptual change in electrical concepts via ontological category shift. International Journal of Science Education, 23(2), 111–149.

    Article  Google Scholar 

  • Lewis, A. (1992). Group child interviews as a research tool. British Educational Research Journal, 18(4), 413.

    Article  Google Scholar 

  • Mayring, P. (2000). Qualitative content analysis. Forum Qualitative Sozialforschung/Forum: Qualitative Social Research, 1(2) http://nbn-resolving.de/urn:nbn:de:0114-fqs0002204.

  • 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, 994–994.

    Article  Google Scholar 

  • Miles, M. B., Huberman, M. A., & Saldaña, J. (2014). Qualitative data analysis: a methods sourcebook (3rd ed.). Los Angeles, CA: SAGE Publications.

    Google Scholar 

  • Nersessian, N. J. (1995). Should physicists preach what they practice? Science & Education, 4(3), 203–226.

    Article  Google Scholar 

  • Nersessian, N. J. (2008). Creating scientific concepts. Cambridge, MA: The MIT Press.

    Google Scholar 

  • Perkins, D. N., & Grotzer, T. A. (2005). Dimensions of causal understanding: the role of complex causal models in students’ understanding of science. Studies in Science Education, 41(1), 117–165.

    Article  Google Scholar 

  • Reiner, M., Slotta, J. D., Chi, M. T., & Resnick, L. B. (2000). Naive physics reasoning: a commitment to substance-based conceptions. Cognition and Instruction, 18(1), 1–34.

    Article  Google Scholar 

  • Shipstone, D. (1988). Pupils’ understanding of simple electrical circuits. Some implications for instruction. Physics Education, 23(2), 92.

    Article  Google Scholar 

  • Slotta, J. D., & Chi, M. T. (2006). Helping students understand challenging topics in science through ontology training. Cognition and Instruction, 24(2), 261–289.

    Article  Google Scholar 

  • Slotta, J. D., Chi, M. T., & Joram, E. (1995). Assessing students’ misclassifications of physics concepts: an ontological basis for conceptual change. Cognition and Instruction, 13(3), 373–400.

    Article  Google Scholar 

  • Smith, C., Carey, S., & Wiser, M. (1985). On differentiation: a case study of the development of the concepts of size, weight, and density. Cognition, 21(3), 177–237.

    Article  Google Scholar 

  • Vosniadou, S. (2002). On the nature of naïve physics. In M. Limón & L. Mason (Eds.), Reconsidering conceptual change: issues in theory and practice (pp. 61–76). New York, NY: Kluwer Academic Publishers.

    Chapter  Google Scholar 

  • Vosniadou, S., & Skopeliti, I. (2014). Conceptual change from the framework theory side of the fence. Science & Education, 23(7), 1427–1445.

    Article  Google Scholar 

  • Wilkinson, S. (1998). Focus group methodology: a review. International Journal of Social Research Methodology, 1(3), 181–203.

    Article  Google Scholar 

  • Wiser, M., & Amin, T. (2001). “Is heat hot?” inducing conceptual change by integrating everyday and scientific perspectives on thermal phenomena. Learning and Instruction, 11(4), 331–355.

    Article  Google Scholar 

Download references

Acknowledgements

The authors thank Anu Saari and Johanna Jauhiainen for their contributions in transcribing and analysing the data.

Author information

Authors and Affiliations

  1. Department of Physics, University of Helsinki, P.O. Box 64, 00014, Helsinki, Finland

    Tommi Kokkonen

  2. School of Education, University of Tampere, Åkerlundinkatu 5, 33014, Tampere, Finland

    Terhi Mäntylä

Authors
  1. Tommi Kokkonen
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Terhi Mäntylä
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Tommi Kokkonen.

Appendix 1

Appendix 1

Excerpt From the Analysis of Students 21 and 22

Transcribed text

Condensed

Relations

Attributes (constraints)

Interviewer: “So, they are equally bright. But, why does the same current that goes here [bulb A] also go here [D and E]…?”

   

Student 21: “Is it due to the voltage difference, since the voltage difference here [over D and E] is the same, and they have the same resistance, and that’s why same current goes in there?”

A, D, and E have the same voltage and the same resistances, so the same current goes through both of them. The same voltage comes from the battery.

R2: U ➔ I, when R

i4

u1(c2)

u1(c4)

Interviewer: “So, how would you explain the next one [circuit BC]?”

   

Student 21: “Well, the same voltage that’s here [over bulbs B and C]…is also between here. So, the voltage decreases… or potential.”

The voltage is divided in the series. The battery provides the same voltage.

 

u2(c1)

u1(c4)

Student 22: “So, the resistance is double because they are in a series”

Resistance is greater in a series.

 

r7(c1)

Student 21: “So, the current halves.”

The greater the resistance, the lower the current.

R1: 1 / R ➔ I

 

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Kokkonen, T., Mäntylä, T. Changes in University Students’ Explanation Models of DC Circuits. Res Sci Educ 48, 753–775 (2018). https://doi.org/10.1007/s11165-016-9586-y

Download citation

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11165-016-9586-y

Keywords

Search

Navigation