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Intelligibility of Scientific Models

How do scientists go about learning more about the natural world? Many college science professors are actively engaged in the process of creating new scientific knowledge, yet rarely do scientists stop to think about the sociocultural framework in which that knowledge is created. This is often referred to in science education circles as the “nature of science” (NoS) and it is largely absent from introductory science courses. Nature of science typically refers to a philosophical view of science, including what counts as science and how scientists engage in the practice of science. We sometimes fool ourselves into thinking we are teaching nature of science by sneaking it into lab activities or case studies, but the research shows we need to be more explicit about these conversations (see Allchin references below).


I recently read The Intelligibility of Nature by Peter Dear, and I can’t stop recommending it to my colleagues. (I also made my students in both Modern Physics and History and Philosophy of Science read it as well.) The book is excellent, well-written and explores some fundamental questions about the nature of science that really make you stop and think about how we present the scientific enterprise to our students. Dear’s book is an exploration of what it means for scientists to make sense of the natural world.


The trick is the “make sense” part. What does it mean to understand the natural world? He presents two perspectives on science: The first is “science as natural philosophy,” a way of understanding how the world works, what makes it tick on a fundamental level. Natural philosophers in the Middle Ages were driven by a desire to understand God’s creation. Natural philosophers were not developing new dyes or agricultural techniques; their interests were strictly theoretical. These proto-scientists were looking for absolute answers that explain phenomena we observe in the natural world; there is one right way to understand how the world works and they were going to find it. Things started to change in the 18th century when early modern scientists such as Newton and Dalton began to use a scientific understanding of the world in more practical ways.


Enter the other side of science: science as instrumentality; science as a technological achievement of humankind. We use scientific models to describe a particular phenomenon or system and to make predictions about its behavior, but these models don’t necessarily have to reflect the underlying reality. This might seem strange at first because we have been conditioned to accept these scientific models as true. But when you stop and think about it, many scientific models are counter-intuitive. Quantum mechanics is a prime example (and the subject of one of the chapters in Dear’s book). This is a purely mathematical model that makes absolutely no sense with respect to how we interact with the world on a daily basis. Even its founders like Heisenberg and Schrodinger had trouble accepting quantum mechanics because it is so abstract, so divorced from reality. Yet we physicists accept it today because it does a fantastic job predicting the behavior of certain systems. Other examples from farther back in history, such as energy or atomic theory (both chapters in Dear’s book), don’t seem strange to us today because they have become part of our scientific cultural paradigm. Neither of these theories made any intuitive sense to scientists of the day. We use them because they can explain phenomena and make predictions. But not because they purport to be an accurate representation of reality.


Which raises the question, if scientific models don’t have to accurately represent reality, what are they good for? Certainly not fulfilling the role of natural philosophy. But they do serve the purpose of instrumentality – they are useful, so we accept them. We use Newtonian mechanics even though we know it is “wrong” because it is useful for many applications. Scientific models are an attempt (Dear argues) to made the world more intelligible. But they aren’t necessarily intelligible a priori; we have to work to make sense of them.


This leads us back to the classroom. What does it mean for our students to understand science? The understanding we want our students to gain about science is inescapably linked to the understanding that scientists have about the natural world. It’s not really surprising that the hardest concepts for students to understand are those that are the most abstract – energy, atomic theory, quantum mechanics, the list could go on. How are students to find these models intelligible if the most prominent scientists of the day couldn’t?


The theory of conceptual change argues that students undergo a miniature paradigm shift every time they learn a new concept. Key to this theory is that students consciously reject an incorrect idea (a misconception) in favor of a more scientifically correct explanation for a particular phenomenon. In the science education jargon, the status of the idea is elevated through three phases. First, the students must find the new idea intelligible. They must understand what you are arguing in order to engaged further with the new idea. Second, the student must find the idea plausible. In other words, they not only have to understand what you are arguing, but also believe that it might be able to give an adequate explanation of the phenomenon. Finally, to achieve conceptual change, students must find the idea fruitful. This means that the students are able to apply this scientific idea to explain a different phenomenon, and justify why this new idea is better than their old misconception. Unfortunately, many students are stuck in the plausible stage; they are able to perform well on traditional assessments, but do not ever really undergo conceptual change.


The first step towards conceptual change is intelligibility. However, the scientific models that we are asking them to consider are inherently unintelligible. The only reason they seem intelligible to those of who are experts in science is because we are already part of the sociocultural group that created the models. For people who are not members of this elite group, these models are nonsensical. Take atomic theory for example. What evidence does the average student have that the world is made up of tiny particles? None. But they have grown up in a culture in which this is an accepted fact (model of explaining natural phenomenon. They are taught in school from an early age that the world is made of atoms, so they believe us when they get to college and we say the world is made of atoms. But are they at the stage of plausible or fruitful? Probably not. They are likely at the stage of “I can parrot back what I think the teacher wants me to say.”


In light of Dear’s arguments about intelligibility we have to question how we can even get students past the first step. Model-based inquiry is one method of instruction that has been demonstrated to facilitate conceptual change. This method of instruction requires students to build conceptual models that can explain and make predictions about a range of phenomena. For example, the particulate nature of matter is a conceptual model that represents a fundamental principle of science that can be used to explain a variety of observations relating to pressure, temperature, etc. The catch is that we have to help the students build these complex models for themselves. Just presenting them as facts doesn’t help them see the utility of the models to make predictions or describe systems.


We ask our students to choose between competing models – often their own preconceptions vs. the scientifically “correct” model. This is a difficult task. The preconceptions that they bring to the classroom are not always unscientific – the students themselves have conducted a lifetime’s worth of observations and accumulated a lifetime’s worth of explanations about how the world works. They may have conducted these observations and informal experiments with a limited set of tools, and with a limited understanding of how others understand the world, but they are making very real discoveries and building up an understanding of the world that is not unlike the explanations that have been crafted by people throughout history.


Thomas Kuhn in his famous Structure of Scientific Revolution debates what a historian is to do with outdated scientific models, writing “If these out of date beliefs are to be called myths, then myths can be produced by the same sorts of methods and held for the same sorts of reasons that now lead to scientific knowledge. If, on the other hand, they are to be called science, then science has included bodies of belief quite incompatible with the ones we hold today.” (p. 2) He argues that given this choice, we must accept the idea that the body of scientific knowledge includes models that contradict each other. This doesn’t mean that the facts of science have changed over time because there are no facts! Science is about finding explanations and building models based on data, and these models continue to evolve, not because the old conceptions were “wrong,” but because we have better data now. These are the experiences we have to engineer for our students – give them opportunities to undergo a mini scientific revolution (or several), and leave the classroom with a more intelligible view of the world.


References

Allchin, Douglas. Many papers on using history of science to teach nature of science and science content: http://www.tc.umn.edu/~allch001/papers/

Dear, R. (2006). Intelligibility of Nature. University of Chicago Press.

Kuhn, T. (1962). Structure of Scientific Revolution. University of Chicago Press.

Posner et al (1982). Accommodation of a Scientific Conception: Toward a Theory of Conceptual Change. Science Education, 66(2): 211-227.

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