A wide variety of skills, abilities and knowledge are used in technological activities such as engineering design. Together, they enable problem solving and artefact creation. Gilbert Ryle’s division of knowledge into knowing how and knowing that is often referred to when discussing this technological knowledge. Ryle’s view has been questioned and criticised by those who claim that there is only one type, for instance, Jason Stanley and Timothy Williamson who claim that knowing how is really a form of knowing that (...) and Stephen Hetherington who claims that knowing that is knowing how. Neither Ryle himself nor any of his critics have discussed technological knowledge. Exposing both Ryle’s and his critics’ ideas to technological knowledge show that there are strong reasons to keep the knowing how–knowing that dichotomy in technological contexts. The main reasons are that they are justified in different ways, that Stanley’s and Williamson’s ideas have great difficulties to account for learning of technological knowing how through training, and that knowing that is susceptible to Gettier problems, which technological knowing how is not. (shrink)

How engineers know, and act on that knowledge, has a profound impact on society. Consequently, the analysis of engineering knowledge is one of the central challenges for the philosophy of engineering. In this article, we present a thematic multidisciplinary conceptual survey of engineering epistemology and identify key areas of research that are still to be comprehensively investigated. Themes are organized based on a survey of engineering epistemology including research from history, sociology, philosophy, design theory, and engineering itself. Five major interrelated (...) themes are identified: the relationship between scientific and engineering knowledge, engineering knowledge as a distinct field of study, the social epistemology of engineering, the relationship between engineering knowledge and its products, and the cognitive aspects of engineering knowledge. We discuss areas of potential future research that are underdeveloped or “undone.”. (shrink)

How engineers know, and act on that knowledge, has a profound impact on society. Consequently, the analysis of engineering knowledge is one of the central challenges for the philosophy of engineering. In this article, we present a thematic multidisciplinary conceptual survey of engineering epistemology and identify key areas of research that are still to be comprehensively investigated. Themes are organized based on a survey of engineering epistemology including research from history, sociology, philosophy, design theory, and engineering itself. Five major interrelated (...) themes are identified: the relationship between scientific and engineering knowledge, engineering knowledge as a distinct field of study, the social epistemology of engineering, the relationship between engineering knowledge and its products, and the cognitive aspects of engineering knowledge. We discuss areas of potential future research that are underdeveloped or “undone.”. (shrink)

Unlike basic sciences, scientific research in advanced technologies aims to explain, predict, and (mathematically) describe not phenomena in nature, but phenomena in technological artefacts, thereby producing knowledge that is utilized in technological design. This article first explains why the covering-law view of applying science is inadequate for characterizing this research practice. Instead, the covering-law approach and causal explanation are integrated in this practice. Ludwig Prandtl's approach to concrete fluid flows is used as an example of scientific research in the engineering (...) sciences. A methodology of distinguishing between regions in space and/or phases in time that show distinct physical behaviours is specific to this research practice. Accordingly, two types of models specific to the engineering sciences are introduced. The diagrammatic model represents the causal explanation of physical behaviour in distinct spatial regions or time phases; the nomo-mathematical model represents the phenomenon in terms of a set of mathematically formulated laws. (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)