It is often claimed—especially by scientific realists—that science provides understanding of the world only if its theories are (at least approximately) true descriptions of reality, in its observable as well as unobservable aspects. This paper critically examines this ‘realist thesis’ concerning understanding. A crucial problem for the realist thesis is that (as study of the history and practice of science reveals) understanding is frequently obtained via theories and models that appear to be highly unrealistic or even completely fictional. So we (...) face the dilemma of either giving up the realist thesis that understanding requires truth, or allowing for the possibility that in many if not all practical cases we do not have scientific understanding. I will argue that the first horn is preferable: the link between understanding and truth can be severed. This becomes a live option if we abandon the traditional view that scientific understanding is a special type of knowledge. While this view implies that understanding must be factive, I avoid this implication by identifying understanding with a skill rather than with knowledge. I will develop the idea that understanding phenomena consists in the ability to use a theory to generate predictions of the target system’s behavior. This implies that the crucial condition for understanding is not truth but intelligibility of the theory, where intelligibility is defined as the value that scientists attribute to the theoretical virtues that facilitate the construction of models of the phenomena. I will show, first, that my account accords with the way practicing scientists conceive of understanding, and second, that it allows for the use of idealized or fictional models and theories in achieving understanding. (shrink)

Teaching false theories goes against the general pedagogical and philosophical belief that we must only teach and learn what is true. In general, the goal of pedagogy is taken to be epistemic: to gain knowledge and avoid ignorance. In this article, I argue that for realists and antirealists alike, epistemological and pedagogical goals have to come apart. I argue that the falsity of a theory does not automatically make it unfit for being taught. There are several good reasons for teaching (...) false theories in school science. These are false theories can bring about genuine understanding of the world; teaching some false theories from the history of science that line up with children’s ideas can provide students “intellectual empathy” and also aid in better grasp of concepts; teaching false theories from the history of science can sharpen students’ understanding of the nature of science; scientists routinely use false theories and models in their practice and it is good sense for science education to mirror scientific practice; and learning about patently non-scientific and antiscientific ideas will prepare students to face and respond to them. In making arguments for the foregoing five points, I draw upon the work of a variety of philosophers and historians of science, cognitive scientists, science education scholars, and scientists. My goal here is not only to justify theories considered false already being taught, but also to actively endorse the teaching of some theories considered false that are by and large not currently taught. (shrink)

In the 1950s–60s biochemists searched intensively for a series of high-energy molecules in the cell. Although we now believe that these molecules do not exist, biochemists claimed to have isolated or identified them on at least sixteen occasions. The episode parallels the familiar eighteenth-century case of phlogiston, in illustrating how error is not simply the loss of facts but, instead, must be actively constructed. In addition, the debates surrounding each case demonstrate how revolutionary-scale disagreement is sometimes resolved by differentiating or (...) partitioning empirical domains, rather than by replacement of one theory by another. (shrink)

This thesis consists of two essays and an introduction. The main theme is technological knowledge that is not based on the natural sciences.The first essay is about rules of thumb, which are simple instructions, used to guide actions toward a specific result, without need of advanced knowledge. Knowing adequate rules of thumb is a common form of technological knowledge. It differs both from science-based and intuitive technological knowledge, although it may have its origin in experience, scientific knowledge, trial and error, (...) or a combination thereof. One of the major advantages of rules of thumb is the ease with which they can be learned. One of their major disadvantages is that they cannot easily be adjusted to new situations or conditions. Engineers commonly use rules, theories and models that lack scientific justification. How to include these in introductory technology education is the theme of the second essay. Examples include rules of thumb based on experience, but also models based on obsolete science or folk theories. Centrifugal forces, heat and cold as substances, and sucking vacuum all belong to the latter group. These models contradict scientific knowledge, but are useful for prediction in limited contexts where they are used when found convenient. The role of this kind of models in technology education is the theme of the second essay. Engineers’ work is a common prototype for pupils’ work with product development and systematic problem solving during technology lessons. Therefore pupils should be allowed to use the engineers’ non-scientific models when doing design work in school technology. The acceptance of these could be experienced as contradictory by the pupils: a model that is allowed, or even encouraged in technology class is considered wrong when doing science. To account for this, different epistemological frameworks must be used in science and technology education. Technology is first and foremost about usefulness, not about the truth or even generally applicable laws. This could cause pedagogical problems, but also provide useful examples to explain the limitations of models, the relation between model and reality, and the differences between science and technology. (shrink)

Technological knowledge is of many different kinds, from experience-based know-how in the crafts to science-based knowledge in modern engineering. It is inherently oriented towards being useful in technological activities, such as manufacturing and engineering design. The purpose of this thesis is to highlight special characteristics of technological knowledge and how these affect how technology should be taught in school. It consists of an introduction, a summary in Swedish, and five papers: Paper I is about rules of thumb, which are simple (...) instructions, used to guide actions toward a specific result, without need of advanced knowledge. One off the major advantages of rules of thumb is the ease with which they can be learnt. One of their major disadvantages is that they cannot easily be adjusted to new situations or conditions. Paper II describes how Gilbert Ryle's distinction between knowing how and knowing that is applicable in the technological domain. Knowing how and knowing that are commonly used together, but there are important differences between them which motivate why they should be regarded as different types: they are learnt in different ways, justified in different ways, and knowing that is susceptible to Gettier type problems which technological knowing how is not. Paper III is based on a survey about how Swedish technology teachers understand the concept of technological knowledge. Their opinions show an extensive variation, and they have no common terminology for describing the knowledge. Paper IV deals with non-scientific models that are commonly used by engineers, based on for example folk theories or obsolete science. These should be included in technology education if it is to resemble real technology. Different, and partly contradictory, epistemological frameworks must be used in different school subjects. This leads to major pedagogical challenges, but also to opportunities to clarify the differences between technology and the natural sciences and between models and reality. Paper V is about explanation, prediction, and the use of models in technology education. Explanations and models in technology differ from those in the natural sciences in that they have to include users' actions and intentions. (shrink)