This inaugural handbook documents the distinctive research field that utilizes history and philosophy in investigation of theoretical, curricular and pedagogical issues in the teaching of science and mathematics. It is contributed to by 130 researchers from 30 countries; it provides a logically structured, fully referenced guide to the ways in which science and mathematics education is, informed by the history and philosophy of these disciplines, as well as by the philosophy of education more generally. The first handbook to cover the (...) field, it lays down a much-needed marker of progress to date and provides a platform for informed and coherent future analysis and research of the subject. -/- The publication comes at a time of heightened worldwide concern over the standard of science and mathematics education, attended by fierce debate over how best to reform curricula and enliven student engagement in the subjects There is a growing recognition among educators and policy makers that the learning of science must dovetail with learning about science; this handbook is uniquely positioned as a locus for the discussion. -/- The handbook features sections on pedagogical, theoretical, national, and biographical research, setting the literature of each tradition in its historical context. Each chapter engages in an assessment of the strengths and weakness of the research addressed, and suggests potentially fruitful avenues of future research. A key element of the handbook’s broader analytical framework is its identification and examination of unnoticed philosophical assumptions in science and mathematics research. It reminds readers at a crucial juncture that there has been a long and rich tradition of historical and philosophical engagements with science and mathematics teaching, and that lessons can be learnt from these engagements for the resolution of current theoretical, curricular and pedagogical questions that face teachers and administrators. (shrink)

Abstract Recent criticisms of intuition from experimental philosophy and elsewhere have helped undermine the authority of traditional conceptual analysis. As the product of more empirically informed philosophical methodology, this result is compelling and philosophically salutary. But the negative critiques rarely suggest a positive alternative. In particular, a normative account of concept determination—how concepts should be characterized—is strikingly absent from such work. Carnap's underappreciated theory of explication provides such a theory. Analyses of complex concepts in empirical sciences illustrates and supports this (...) claim, and counteracts the charge explication is only suitable for highly mathematical, axiomatic contexts. Explication is also defended against the influential criticism it is “philosophically unilluminating”. Content Type Journal Article Category Original paper in Philosophy of Science Pages 1-19 DOI 10.1007/s13194-011-0027-5 Authors James Justus, Philosophy Department, Florida State University and University of Sydney, Tallahassee, FL 32306, USA Journal European Journal for Philosophy of Science Online ISSN 1879-4920 Print ISSN 1879-4912. (shrink)

In his 1966 paper “The Strategy of model-building in Population Biology”, Richard Levins argues that no single model in population biology can be maximally realistic, precise and general at the same time. This is because these desirable model properties trade-off against one another. Recently, philosophers have developed Levins’ claims, arguing that trade-offs between these desiderata are generated by practical limitations on scientists, or due to formal aspects of models and how they represent the world. However this project is not complete. (...) The trade-offs discussed by Levins had a noticeable effect on modelling in population biology, but not on other sciences. This raises questions regarding why such a difference holds. I claim that in order to explain this finding, we must pay due attention to the properties of the systems, or targets modelled by the different branches of science.Keywords: Trade-offs; Population biology; Scientific models; Generality; Precision. (shrink)