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Some Lessons from Discovery Science

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Uncertainty and Graphing in Discovery Work
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Abstract

In this chapter, I reflect on some of the lessons STEM educators might want to take away from the ethnographic studies of a discovery science. I center the reflections around (a) induction vs. abduction, (b) conceptual change, (c) the becoming salient of “facts,” (d) uncertainty, (e) contradictions in scientific research, (f) control over the (not-) becoming of data, (g) graphs in discovery work, and (h) communication at work (in scientific research work).

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Notes

  1. 1.

    Saying that a process is evolutionary is equivalent to saying that it is nonteleological .

  2. 2.

    Laboratories are places of abstraction , where the contingencies of the world are excluded and controlled . Should scientists actually venture into the field to conduct research equivalent to the one they conduct in the laboratory, they may transform the field setting into something like a laboratory (Latour 1988). The effect of the control over the conditions became quite evident in a study of mathematics where persons were observed in the supermarket while shopping, then were presented with items from the supermarket but on a table outside and apart from the normal shopping for groceries, and a third condition where “problems ” were presented in pencil-and-paper format (Lave 1988).

  3. 3.

    There are exceptions, such as in Queensland, Australia, where the curriculum provides students with opportunities to research some phenomenon for an entire school term (Roth 2013a) or in my own curricular practice , where students conducted independent investigations for a great fraction of their time in class and throughout the entire year (Roth 1995).

  4. 4.

    In Dunbar’s case, he interviewed scientists before and after a laboratory meeting and videotaped the meeting. From the difference between the before and after interviews, he produced inferences about how the meeting changed their thinking. As the present data show, scientists’ after-the-fact accounts often change objectively given historically documented facts and recorded statements.

  5. 5.

    Merleau-Ponty (1996) – whose descriptions and explanations of perception have been shown to be consistent with modern neuroscience – critiques Piaget for writing that “the passage to a superior perception and conduct can be explained by a more complete and more exact registering of experience , whereas this precisely supposes a reorganization of the perceptive field and the arrival of clearly articulated forms” (p. 104, emphasis added). That is, the new perceptual forms arrive rather than being constructed; and this arrival coincides with a reorganization of the perceptual field . That is, the forms are not the causes for the reorganization.

  6. 6.

    Thom provides examples from biology , the symbolic realm of the imaginary, philosophy, analogies , and magic in the use of natural peoples. Others use catastrophe theory to explain the transition from peace to war even when the participants involved do not desire the latter, the emergence of new biological species, or cognitive development.

  7. 7.

    Heidegger (1927/1977) describes the relationship between language (logos) and perception as a dialectical one, where the former lets things be seen in the way they show themselves. This is not another version of the Sapir-Whorf hypothesis , according to which language drives perception. Rather, there is a mutually constitutive and implicative relation, where language allows us to see what shows itself and which is given to us without our intention .

  8. 8.

    We had made measurements but literally not recorded them, even though these were recorded and existed at least momentarily in computer memory. Our decision not to record them permanently excluded their effect on the explanations we could produce.

  9. 9.

    Even many science teachers, in part as a result of deprofessionalization, have to cope “with a top-down, assessment-drive curriculum” (Levinson 2011, p. 113).

  10. 10.

    This approach is diametrically opposite to traditional hypothesis testing, which establishes the probability of the data given a particular hypothesis p(data|H).

  11. 11.

    The most extensive presentation of all issues involved in this case can be found in an article for municipal engineers on the construction of community health and safety (Roth 2008). In that article, I describe the politics that made it possible for community engineers and politicians to stall on the establishment of a water main, supplying the residents of one part of my community with running water. In that process, decisions were made on the grounds of engineers who had collected data on only 1 day during the year; all other data, collected at multiple time points during the year and anecdotal data from nearly 40 years produced by the residents living in the area were disregarded.

  12. 12.

    The totality of practical aspects of activity and language also has been referred to as language-game (Wittgenstein 1953/1997).

  13. 13.

    When I asked in the hatchery about the difference between coho salmon going to one of the machines injecting a coded wire tag rather than into another, the women operators told me “Look!” When I said, “Yea, but what is the difference,” the operators asked me again to “Look!” I found myself in the predicament that I was asked to see the difference in the way these coho salmon looked, and that I asked for some description of what to look for the difference between see those specimens going into one device rather than the other.

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Roth, WM. (2014). Some Lessons from Discovery Science . In: Uncertainty and Graphing in Discovery Work. Springer, Dordrecht. https://doi.org/10.1007/978-94-007-7009-6_8

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