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Nature of Science Contextualized: Studying Nature of Science with Scientists

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Abstract

Understanding nature of science (NOS) is widely considered an important educational objective and views of NOS are closely linked to science teaching and learning. Thus there is a lively discussion about what understanding NOS means and how it is reached. As a result of analyses in educational, philosophical, sociological and historical research, a worldwide consensus about the content of NOS teaching is said to be reached. This consensus content is listed as a general statement of science, which students are supposed to understand during their education. Unfortunately, decades of research has demonstrated that teachers and students alike do not possess an appropriate understanding of NOS, at least as far as it is defined at the general level. One reason for such failure might be that formal statements about the NOS and scientific knowledge can really be understood after having been contextualized in the actual cases. Typically NOS is studied as contextualized in the reconstructed historical case stories. When the objective is to educate scientifically and technologically literate citizens, as well as scientists of the near future, studying NOS in the contexts of contemporary science is encouraged. Such contextualizations call for revision of the characterization of NOS and the goals of teaching about NOS. As a consequence, this article gives two examples for studying NOS in the contexts of scientific practices with practicing scientists: an interview study with nanomodellers considering NOS in the context of their actual practices and a course on nature of scientific modelling for science teachers employing the same interview method as a studying method. Such scrutinization opens rarely discussed areas and viewpoints to NOS as well as aspects that practising scientists consider as important.

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Notes

  1. These opposites should be seen as heuristic tools, featuring two extreme positions rather than as descriptions of realities of science education (see Roberts 2007).

  2. In science-education literature, the need for scientific literacy is justified with a variety of rationales, such as: usefulness for everyday life; personal autonomy; socio-economic development; democratic participation in public issues related to science and technology; and ethical responsibility of scientists, technicians, politicians and citizens (see Adúriz-Bravo 2005; Laherto 2010; Laugksch 2000).

  3. See for instance Allchin (2014), Hodson (2008), Matthews (1998), and Rudolph (2005).

  4. See for example Cantor (1989), Chang (2004), Darrigol (2000) Gooding (1989), and Naylor (1989).

  5. See for instance Herman et al. (2013), Höttecke and Silva (2011), Koponen and Mäntylä (2006), Kurki-Suonio (2011), Monk and Osborne (1997), Osborne et al. (2003), Rudge and Howe (2009), Sandoval (2005), and Tala (2013b).

  6. The researchers within the STS branch have also been active promoters of a “science for all” emphasis in STL. Some even go beyond traditional definitions of scientific literacy as knowledge and a set of skills, and promote social action as the main goal of science education (DeBoer 2000).

  7. In a society where science and technology are important in public policy and in personal lives, understanding the basis of science supports critical thinking and democracy (see Dewey 1916; Rudolph 2005). For example, when evaluating the benefits and risks of vaccines on the personal and societal level, citizens as parents and decision-makers should understand the role of data and inference used in the scientific assessment of benefits and risks (see Reyna 2004).

  8. See Hanuscin et al. (2006), McComas and Olson (1998), Osborne et al. (2003), and Sandoval (2005).

  9. See for instance Clough (2011), Lederman et al. (2002), Mathews (1998), McComas and Olson (1998), Osborne et al. (2003) and the references therein.

  10. cf. Bell et al. (2000), Guerra-Ramos (2012), and Lederman et al. (2002)

  11. See for example Adúriz-Bravo (2005), Khishfe and Abd-El-Khalick (2002), Jones (1997), Sandoval (2005).

  12. See for instance Abd-El-Khalick (1998), Akerson et al. (2000), Allchin (2011b), Clough (2011), Hanuscin et al. (2006), Matthews (1998, 2005), Sandoval (2005), and Schwartz et al. (2004).

  13. See for example Allchin (2011a), Irwin (2000), Lederman et al. (2002), Clough and Olson (2008), Elby and Hammer (2001), Ford (2008), Osborne et al. (2003), and Schwartz et al. (2004).

  14. By the term ‘study’ we refer both researching and scrutinising for individual understanding: at best research and education go hand in hand.

  15. The list of typical features of science cannot naturally be revised on basis of one case study. Instead, such an approach can be used in order to understand what does the general NOS ideas mean in practice and how does such general description of “nature of science” capture scientists’ reality.

  16. The primary objective of employing them is not to teach NOS and thus most scientific inquiry or design tasks given to students in schools reflect neither the core attributes of authentic scientific or technological reasoning nor the contextual NOS themes of education (e.g., Abd-El-Khalick 2013; Chinn and Malhotra 2002; De Vries 1997; Tala 2009). For example, in the formal lists of NOS themes it is frequently described that science is a creative and theory-laden enterprise constructed by human beings collaborating through the employment of a variety of methods. However, the practices of science education typically support a view of science as an algorithmic activity employing a universal scientific method and neutral instruments, which transform the facts awaiting us in nature (see Chinn and Malhotra 2002; Hacking 1983; Hodson 1996; Tala 2009).

  17. In practice, a general level NOS question asks, for example, ‘what does an atom look like?’ (VNOS-B), ‘what is an experiment?’ (VNOS-C) or ‘what is the difference between scientific law and theory?’ (VNOS-B&C). Then a practice-oriented view elucidates ‘what scientists actually do when constructing and using the methods and tools’, ‘what is the benefit of different activities’ or ‘what does a scientist actually do when (s)he aims to convince peers about the functioning of a certain model, experiment or idea’ and ‘what skills does a novice scientist have to master in order to do that’ (Tala 2013a; cf. Chang 2011).

  18. For different approaches to the interrelationships of science, technology and society, compare Vesterinen et al. (2014) with Tala (2013b).

  19. What is taught about NOS is defined in the curricula in varying degrees. In many countries, the level of NOS understanding is defined by listing statements about NOS in the curricula and students’ understanding of this information is tested in national exams at the appropriate level. In some other countries, such as Finland, teachers are quite free to decide what they teach about NOS.

  20. Knowledge produced by the theoretical methods of cosmologists, in chemists’ wet laboratory, or by hydro-biologists’ fieldwork, are apparently different kinds of knowledge. News of the hunt for the Higgs boson in the LHC has yet a different basis; and still different basis have also knowledge of new features of matter modelled in nanophysics.

  21. As the examples of science studies see articles in the book The Philosophy of Scientific Experimentation edited by Radder (2003) or The Uses of Experiment edited by Daavid Gooding, Trevor Pinch and Simon Schaffer (Gooding et al. 1989). For recent analysis of experimentation for education see Koponen and Mäntylä (2006) and Tala (2009) and references therein.

  22. Already Michael Polanyi (e.g., 1958) wrote the fruitful analysis of scientists’ tacit knowledge. The challenge of learning to do science is not that experts would like to hide something but the essential part of their expertise is unrecognized (see Tala 2013a for an analysis of scientists’ tacit knowledge, and references thereby).

  23. One interview was conducted in English and the others in Finnish. The quotations from interviews in Finnish have been translated into English by the authors.

  24. For comparison of modelling approaches, see Vvedensky (2004).

  25. Nanoscientists have to be creative, when discovering the nanoworld within these limitations of time and scales of length, which is one practical meaning of the NOS theme in referring to the creativity of scientists. Naturally, creativity plays a vital role in developing modelling. This kind of creative modelling also includes “hand-waiving” (E) solutions to un-known situations, namely developing academic guesses to be tested through modelling.

  26. Revolutionary ideas were constructed in recent history: For example, scientists did not have access to the nanoworld and nanophenomena before the invention of the scanning tunnelling microscope (the Nobel Prize in physics in 1986), an instrument for imaging surfaces at the atomic level, which is employed also by those interviewers who have experience working on the experimental side of the field. Additionally, the discovery of fullerenes in 1985 (Nobel Prize in chemistry in 1996) was important for the foundation of nanoscientific research.

  27. An expert modeller stated that “We study mental images. It is what we see”.

  28. The task of these scientists is often a rather technological one; the intimate relation between the scientific research and technological development also encourages discussion around the NOS idea ‘science is an attempt to explain natural phenomena’.

  29. This viewpoint to modelling encourages revising the picture of models and modelling underlining contemporary science education (for details, see Koponen and Tala 2013).

  30. The mutual understanding was checked by asking every interviewee to explain his/her own responses to the questionnaire. In addition, the interviewees also checked the analysis.

  31. Such interaction can also increase the students’ motivation to teach about modelling and the modellers’ understanding about the viewpoints to modelling promoted in recent science education (cf. Caton 2000).

  32. One of the essays was written in English and one in Swedish. The rest of the essays were written in Finnish. Quotations written in Finnish or Swedish have been translated into English by the authors.

  33. Essay based on the interview of the researcher working on bioanalytical chemistry.

  34. Essay based on the interview of the researcher working on marine engineering.

  35. The coarse model(s) become fitted with experimentation and other relevant sources of information and ideas (for details, see Tala 2011), which is a two-way process: also experimental actions become fitted with modelling.

  36. Compare with the results reached by an open approach as employed by Vesterinen and Aksela (2009) in the same context, with different objectives.

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Authors and Affiliations

  1. Physics Teacher Education, Department of Physics, University of Helsinki, POB 64, 00014, Helsinki, Finland

    Suvi Tala

  2. Unit of Chemistry Teacher Education, Department of Chemistry, University of Helsinki, Helsinki, Finland

    Veli-Matti Vesterinen

  3. Department of Mathematics and Science Education, Stockholm University, Stockholm, Sweden

    Veli-Matti Vesterinen

Authors
  1. Suvi Tala
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  2. Veli-Matti Vesterinen
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Corresponding author

Correspondence to Suvi Tala.

Appendix 1: The Questionnaire (Translated by the Author)

Appendix 1: The Questionnaire (Translated by the Author)

About the Research

The philosophy of science and technology address the problem of questions concerning the construction and justification of knowledge. These are the tacit principles guiding, for example, how to prove that the model operates smoothly and how to convince others of the viability of the model. These field-specific principles are rarely discussed explicitly. Understanding these principles in turn helps novices to learn the field and in teaching both content and methods. Such understanding can be supported by pragmatic philosophical approach which itemizes and analyses the views of the scientist practicing in the field. We are going to map the views of selected modellers, to find out how you see knowledge construction and justification in the practices of nanophysics. Thus, we would like to ask you the following questions. We ask that you will explain your viewpoints at the level understandable for a high school student.

THE OBJECTIVE

  1. 1.

    What is the research frame and object of your research? For example, what is modelled in it and what kind of empirical results are sought after?

  2. 2.

    From the broader viewpoint, to which subject matter is your research project related?

  3. 3.

    How would you reason the importance of your research field to a) a wider public or to funders b) a chemist?

  4. 4.

    Could you please sketch out the methods you use? What general problem-solving skills and modelling skills do you exercise in your work?

THE RELATION TO REALITY

  1. 1.

    Which models or what kind of models are central to your project?

  2. 2.

    How would you characterize the relationship between the models, the theory, and the empirical results? For example, do you derive the models from the theories or are those constructed on the basis of empirical results? And how are those developed further?

  3. 3.

    In what respect does the central model or simulation you use represent reality?

  4. 4.

    In what respect does the central model you use relate to the theories already established and in what respect does it not?

  5. 5.

    In what respect does the central simulation you use or develop does differ from the real system? Why have these idealizations or approximations been done? You can give several different examples and reasons why such idealizations and approximations have been done.

  6. 6.

    How could the model or simulation be changed, if there were more effective computers or the technological development would be quickly advanced in some other way?

  7. 7.

    How do you think your work advances the knowledge and understanding of your research field?

  8. 8.

    In what respect does the central model you use relate to the theories already established and in what respect does it not? Why? Please, give several different examples.

FUNCTIONALITY (from a convincing viewpoint)

  1. 1.

    What characteristics make the models you have developed or use important or interesting?

  2. 2.

    How you increase other researchers’ confidence in the functionality and reliability of a model or a simulation method?

YOUR OWN QUESTIONS (what else you want to remember to ask)

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Tala, S., Vesterinen, VM. Nature of Science Contextualized: Studying Nature of Science with Scientists. Sci & Educ 24, 435–457 (2015). https://doi.org/10.1007/s11191-014-9738-2

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  • DOI: https://doi.org/10.1007/s11191-014-9738-2

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