羟氨苄青霉素引起大疱性类天疱疮样疹

The range of terminology used in the field of ‘visualization’ is reviewed and, in the light of evidence that it plays a central role in the conduct of science, it is argued that it should play a correspondingly important role in science education. As all visualization is of, and produces, models, an epistemology and ontology for models as a class of entities is presented. Models can be placed in the public arena by means of a series of ‘modes and sub-modes of representation’. Visualization is central to learning, especially in the sciences, for students have to learn to navigate within and between the modes of representation. It is therefore argued that students -science students’ especially - must become metacognitive in respect of visualization, that they must show what I term ‘metavisual capability’. Without a metavisual capability, students find great difficulty in being able to undertake these demanding tasks. The development of metavisual capability is discussed in both theory and practice. Finally, some approaches to identifying students’ metavisual status are outlined and evaluated. It is concluded that much more research and development is needed in respect of visualization in science education if its importance is to be recognised and its potential realised.

Visualization: A Metacognitive Skill in Science and Science Education

It is argued that a central role for models and modelling would greatly increase the authenticity of the science curriculum. The range of ontological states available for the notion of ‘model’ is outlined, together with the modes available for their representation. Issues in the selection of models for and the development of modelling skills within the model-based curriculum are presented. It is suggested that learning within such a curriculum entails: acquiring an acceptable understanding of what a model is and how modelling takes place; having a developed capacity to mentally visualise models; understanding the natures of analogy and of metaphor, processes which are central to models and modelling. The emphases required in teaching for this learning to be supported are discussed. Finally, implications of the model-based curriculum for teacher education are evaluated. It is concluded that a great deal of detailed research and development will be needed if the potential of this change in emphasis within the science curriculum is to be realised.

Models and Modelling: Routes to More Authentic Science Education

Nature's capacities and their measurement

Robert Eisberg and Robert Resnick Chichester: J Wiley 1974 pp xii + 713 price £7.75 It is by no means invariably the case that two authors who each have a well deserved reputation can combine to form an effective writing team. In this particular case, however, any such concern can be put aside.

https://iopscience.iop.org/article/10.1088/0031-9112/26/7/030/pdf

Quantum Physics of Atoms, Molecules, Solids, Nuclei and Particles

Scientific models represent aspects of the empirical world. I explore to what extent this representational relationship, given the specific properties of models, can be analysed in terms of propositions to which truth or falsity can be attributed. For example, models frequently entail false propositions despite the fact that they are intended to say something "truthful" about phenomena. I argue that the representational relationship is constituted by model users "agreeing" on the function of a model, on the fit with data and on the aspects of a phenomenon that are modelled. Model users weigh the propositions entailed by a model and from this decide which of these propositions are crucial to the acceptance and continued use of the model. Thus, models represent phenomena when certain propositions they entail are true, but this alone does not exhaust the representational relationship. Therefore, the constraints that produce the choice of the relevant propositions in a model must also be examined and their an...

When scientific models represent

Scientists have used models for hundreds of years as a means of describing phenomena and as a basis for further analogy In "Scientific Models in Philosophy of Science", Daniela Bailer-Jones assembles an original and comprehensive philosophical analysis of how models have been used and interpreted in both historical and contemporary contexts Bailer-Jones delineates the many forms models can take (ranging from equations to animals; from physical objects to theoretical constructs), and how they are put to use She examines early mechanical models employed by nineteenth-century physicists such as Kelvin and Maxwell, describes their roots in the mathematical principles of Newton and others, and compares them to contemporary mechanistic approaches Bailer-Jones then views the use of analogy in the late nineteenth century as a means of understanding models and to link different branches of science She reveals how analogies can also be models themselves, or can help to create them The first half of the twentieth century saw little mention of models in the literature of logical empiricism Focusing primarily on theory, logical empiricists believed that models were of temporary importance, flawed, and awaiting correction The later contesting of logical empiricism, particularly the hypothetico-deductive account of theories, by philosophers such as Mary Hesse, sparked a renewed interest in the importance of models during the 1950s that continues to this day Bailer-Jones analyzes subsequent propositions of: models as metaphors; Kuhn's concept of a paradigm; the Semantic View of theories; and the case study approaches of Cartwright and Morrison, among others She then engages current debates on topics such as phenomena versus data, the distinctions between models and theories, the concepts of representation and realism, and the discerning of falsities in models

Scientific Models in Philosophy of Science

An overview is provided of how the concept of a scientific model has devel-oped and changed in the philosophy of science in the course of this Century. I identify three shifts of interest in the treatment of the topic of scientific models. First, only from the 1950s did models begin to be considered relevant to the scientific enterprise, motivated by the desire to account for issues such as theory change and creativity in scientific discovery. Second, I examine how philosophers then increasingly concentrated on the analysis of the functions of models, e.g. for explanation or for guiding and suggesting new experiments. Finally, I show how an analysis of the functions of models could lead to the consideration of their function not just within science, but also in human cognition, so that models are now sometimes viewed as tools of actual (rather than logically reconstructed) scientific thinking.

Tracing the Development of Models in the Philosophy of Science

This paper contains the analysis of nine interviews with UK scientists on the topic of scientific models. Scientific models are an important, very controversially discussed topic in philosophy of science. A reasonable expectation is that philosophical conceptions of models ought to be in agreement with scientific practice. Questioning practicing scientists on their use of and views on models provides material against which philosophical positions can be measured.

Scientists' Thoughts on Scientific Models

This paper examines the process of modelling a complex empirical phenomenon in modern astrophysics: extended extragalactic radio sources. I show that modelling is done piecemeal, addressing selected striking or puzzling features of that phenomenon separately and individually. The result is various independent and separate sub-models concerned only with limited aspects of the same phenomenon. Because the sub-models represent features of the same physical phenomenon, they need to be reasonably consistent with each other — a criterion not always fully adhered to — and there needs to be a way to conceptually `re-unite’ the sub-models to form an overall-model. Visualisation, that is, supplying a concrete interpretation of abstract, theoretical sub-models, aids this modelling process. My case study further endorses the view that modelling is `work in progress', i.e. a form of developing knowledge whereby models represent, not replicate, a phenomenon.

Daniela M. Bailer-Jones

Papers

When scientific models represent

Scientific Models in Philosophy of Science

Tracing the Development of Models in the Philosophy of Science

Scientists' Thoughts on Scientific Models

Modelling Extended Extragalactic Radio Sources