Towards Scientific Literacy [1 ed.] 9789087905071, 9789087905057, 9789087905064

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Towards Scientific Literacy A Teachers’ Guide to the History, Philosophy and Sociology of Science

Derek Hodson - 978-90-8790-507-1 Downloaded from Brill.com11/09/2020 11:12:23AM via free access

Derek Hodson - 978-90-8790-507-1 Downloaded from Brill.com11/09/2020 11:12:23AM via free access

Towards Scientific Literacy A Teachers’ Guide to the History, Philosophy and Sociology of Science

Derek Hodson Ontario Institute for Studies in Education, University of Toronto, Canada

SENSE PUBLISHERS ROTTERDAM / TAIPEI Derek Hodson - 978-90-8790-507-1 Downloaded from Brill.com11/09/2020 11:12:23AM via free access

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ISBN: 978-90-8790-505-7 (paperback) ISBN: 978-90-8790-506-4 (hardback) ISBN: 978-90-8790-507-1 (e-book)

Published by: Sense Publishers, P.O. Box 21858, 3001 AW 3001 AW Rotterdam Rotterdam, The Netherlands http://www.sensepublishers.com

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All Rights Reserved © 2008 Sense Publishers No part of this work may be reproduced, stored in a retrieval system, or transmitted in any form or by any means, electronic, mechanical, photocopying, microfilming, recording or otherwise, without written permission from the Publisher, with the exception of any material supplied specifically for the purpose of being entered and executed on a computer system, for exclusive use by the purchaser of the work.

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To Susie, for your unwavering love, inspiration and support

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CONTENTS

Dedication…………………………………………………………………………..v Preface…………………………………………………………………………...... ix Acknowledgements……………………………………………………………….. xi Chapter 1 In Pursuit of Scientific Literacy: The Case for History, Philosophy and Sociology of Science………………………………………………1 Chapter 2 Exploring Nature of Science Issues: Students’ Views and Curriculum Images……………………………………………..... 23 Chapter 3 The Traditional View of Science: Recognizing the Myths…………... 41 Chapter 4 Exploring Alternative Views of Science: The Ideas of Popper, Lakatos and Kuhn…………………………………………………......67 Chapter 5 Scientific Inquiry, Experiment and Theory: What Should We Tell Our Students?.......................................................................... 85 Chapter 6 Realism or Instrumentalism: What Position for School Science?.......103 Chapter 7 Insight from the Sociology of Science: Science is What Scientists Do…………………………………………………..123 Chapter 8 Making a case for History of Science: Going Beyond Dates and Anecdotes …………………………………………………….…149 Chapter 9 Looking for Balance in the Curriculum: Essential Elements in a Curriculum for Critical Scientific Literacy…………….…….....173 Chapter 10 Further Thoughts on Social Construction and Scientific Rationality: A View for School Science…………………………….199 References………………………………………………………………………..211 Index…………………………………………………………………………….. 239

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PREFACE

My interest in history of science came early. As a schoolboy in the 1950s I always looked forward to the frequently dull science lessons being enlivened by the stories about scientists that sprinkled the pages of science textbooks by E.J. Holmyard and F. Sherwood Taylor. Later, as an undergraduate at the University of Manchester Institute of Science and Technology (UMIST)), I had the great good fortune to attend a series of lectures on the philosophy of science by David Theobald (a natural products chemist) and a wide-ranging course in history of science, from Thales to Dalton, by Brian Pethica (a physical chemist). These were arranged as part of a general studies course requirement, a curriculum planning decision by UMIST for which I will always be grateful. Subsequently, I attended a course in history of technology at UMIST taught by D.S.L. Cardwell, pioneer of history of technology and author of The Organization of Science in England (1957) and Turning Points in Western Technology (1972). Later still, as a student teacher at the University of Exeter, I was privileged to study with the eminent historian of science, H.J.J. Winter, author of Eastern Science: An Outline of its Scope and Contribution (published in 1952). I hereby acknowledge my gratitude to the dedicated and inspired teaching of all these scholars. These rich learning experiences have led me to a lifelong interest in the history and philosophy of science, and more recently in the sociology of science, and to efforts over many years to instill elements of these vast subject areas into school science curricula, courses for teachers at both pre-service and graduate level, professional development programmes for serving teachers, and research agenda of graduate students. This book is an outcome of those efforts. It is intended as a journey through the literature, picking and choosing items that I consider of particular importance in developing students’ scientific literacy, as defined in chapter 1, and teachers’ capacity to present curricula that afford a much higher profile to HPS than has been traditional – a goal that is in line with much recent writing in science education and a number of prominent reports on science education published in recent years in the United States, United Kingdom and elsewhere. There are a number of books that cover essentially the same ground – notably works by Chalmers (1978, 1999), O’Hear (1989), Olby et al. (1990), Riggs (1992) and Ladyman (2002). In contrast to the approach taken by these authors, this book is written specifically from the perspective of science education. Its principal concern is to identify what teachers, teacher educators, curriculum developers and science education policy makers should know about the history, philosophy and sociology of science in order to teach more effectively about the nature of science and scientific activity. It is important to state at the outset that this is not a ‘how to’ book. It does not focus specifically on ways to design effective teaching and learning activities, although such a book is currently in preparation. Rather, it is a ‘what’ and ‘why’ book, intended as a guide for making an appropriate selection from the history, philosophy and sociology of science literature for presentation to students. ix

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PREFACE

Although the original sources of the figures used in chapter 3 have been acknowledged, I wish to state here that many of them first came to my attention in the marvellous collection of images, photographs and quotations assembled by David Wade Chambers (1984a,b) under the titles Putting Nature in Order and Is Seeing Believing? These books constitute an invaluable resource in the design of courses on the nature of science. Derek Hodson Toronto November, 2007

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ACKNOWLEDGEMENTS

Writing can be a very solitary pursuit, though it was not so in this case. In preparing this book I drew on a lifetime of reading, thinking, teaching, researching, writing and arguing about issues in science, philosophy of science, history of science, sociology of science and science education, and on a lifetime of thinking about how to organize and present these ideas to students at primary, secondary, tertiary and graduate study level. So many memories of lively and interesting people, encounters and incidents came flooding back – some pleasant, some stressful and emotionally challenging, some amusing and some sad, but always enlightening. In my mind’s eye, many people, from many different schools and universities, were my constant companions as I struggled to make coherent sense of difficult issues. I am immeasurably indebted to all those people and events, spread over many years, for informing and influencing my thoughts about science. There is no doubt that my thinking has been sharpened and my views refined through numerous discussions with colleagues and graduate students, particularly at the Ontario Institute for Studies in Education and the University of Hong Kong. I hereby acknowledge my indebtedness to all those people, too numerous to identify by name. I also extend my thanks to the British Psychological Society, Houghton Mifflin Harcourt Publishing Company, Wiley-Liss Inc., University of California Press, University of Illinois Press and Dr. Richard Duschl for permission to reproduce figures and tables previously published elsewhere. – Figure 3.1b, titled Counterchange, is attributed to Michio Kubo. Source: E.H. Gombrich (1978) The Sense of Order: A Study in the Psychology of Decorative Art (figure 105, page 91), London: Phaidon Press. The citation in this book reads: “from Hide and Seek, Osaka, 1968”. The same citation is given for this illustration (figure 1.1, page 2) in D.W. Chambers (1984) Putting Nature in Order, Geelong: Deakin University. – Figure 3.4 is reproduced with permission of the author and the University of Illinois Press. Source: E.G. Boring (1930) A new ambiguous figure. American Journal of Psychology, 42, 444. Copyright 1930 by the Board of Trustees of the University of Illinois. – Figure 3.7 is reproduced by permission of Houghton Mifflin Harcourt Publishing Company. Source: James J. Gibson (1977) The Perception of the Visual World. Boston, MA: Houghton Mifflin (p. 182). Copyright © 1971, 1950 by Houghton Mifflin Company. – Figure 3.8a is reproduced with permission from the British Journal of Psychology, © The British Psychological Society. Source: L.S. Penrose & R. Penrose (1958) Impossible objects: A special type of visual illusion. British Journal of Psychology, 49(1), 31-33 (p. 32).

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ACKNOWLEDGEMENTS

– Figure 3.9 is reproduced with permission of the author and the University of Illinois Press. Source: P.B. Porter (1954) Another puzzle picture. American Journal of Psychology, 67, 550-551. Copyright 1954 by the Board of Trustees of the University of Illinois. – Figure 3.10 is reproduced with permission of the author and the University of Illinois Press. Source: K.M. Dallenbach (1951) A puzzle picture with a new principle of concealment. American Journal of Psychology, 64(3), 431-433. Copyright 1951 by the Board of Trustees of the University of Illinois. – Table 9.2 is reprinted with permission of Wiley-Liss, Inc., a subsidiary of John Wiley & Sons, Inc. Source: Osborne, J., Collins, S., Ratcliffe, M., Millar, R. & Duschl, R. (2003) What “ideas-about-science” should be taught in school science? A Delphi study of the expert community. Journal of Research in Science Teaching, 40(7), 692-720. Copyright (2003) National Association for Research in Science Teaching. – Figure 10.2 is reproduced with permission from Dr. Richard Duschl, Graduate School of Education, Rutgers University, New Brunswick, NJ, and the University of California Press. Source: R.A. Duschl (1990) Restructuring Science Education: The Importance of Theories and their Development. New York: Teachers College Press (p. 87). The figure was adapted from L. Laudan (1984) Science and Values: The Aims of Science and their Role in Scientific Debate. Berkeley, CA: University of California Press (p. 63). Most importantly, no words can fully express my gratitude to my wife, Sue Hodson, for her constant and unwavering love, support and encouragement throughout our years together. You, Susie, make everything worthwhile.

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CHAPTER 1

IN PURSUIT OF SCIENTIFIC LITERACY The Case for History, Philosophy and Sociology of Science

Nearly forty years ago, as a young and idealistic science teacher, I enthusiastically embraced the Nuffield Science Teaching Project’s catchphrase “Being a scientist for the day”.1 Since those heady days, other slogans and rallying calls have come and gone, with varying degrees of impact on classroom practice – among them: Process, not Product, Science for All, Less is More and Children Making Sense of the World. Since the early to mid-1990s, the most prominent has been the call for greater scientific literacy. Indeed, the notion of scientific literacy has assumed centre-stage in science education debate in several parts of the world and organizations such as the American Association for the Advancement of Science (AAAS, 1989, 1993), the Council of Ministers of Education, Canada (CMEC, 1997) and UNESCO (1993) have used it to frame major efforts to reform the science curriculum. Three questions immediately spring to mind: – What is scientific literacy? – Why do we need it? – What are the curricular implications? Given its lengthy history in the rhetoric of science education, we could perhaps expect there to be a clear and well articulated definition of scientific literacy. Sadly, this is not the case. While the attainment of scientific literacy has been almost universally welcomed as a desirable goal, there is still little clarity about its meaning (Jenkins, 1990, 1994a, 1997; Krugly-Smolska, 1990; Eisenhart et al., 1996; Millar, 1996; Sutman, 1996; Galbraith et al., 1997; Graber & Bolte, 1997; Hurd, 1998; DeBoer, 2000; Kolsto, 2000; Laugksch, 2000; Solomon, 2001; Tippens et al., 2000; Cajas, 2001; Ryder, 2001; Rudolph, 2005), little consensus about why we need it, and little agreement about precisely what it means in terms of curriculum provision. As Laugksch (2000) observes, significantly different answers to these questions are proferred by the various stakeholders in education, or “interest groups” as he calls them. For example, he argues that the science education community (science teachers, teacher educators and curriculum developers, for example) regard scientific literacy as a kind of code for the goals of science education and frame their discussion in terms of curriculum content, pedagogy and assessment/evaluation procedures, while those with responsibility for science policy are more concerned with public perception of, and support for, the scientific enterprise. Yet others are concerned with the nature of control and priority setting for science, access to science, or keeping the wider public up-to-date on significant scientific development via the media, zoos and museums. As will become apparent in this and succeeding chapters, I have interests in common with each of Laugksch’s “interest groups”. My principal goal is that all students, regardless of gender, ethnicity, religion, sexual orientation, geographical location and current attainment levels, achieve a 1

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measure of critical scientific literacy. I also subscribe to the view, outlined at length in Hodson (2003), that science education is incomplete if it does not involve students in preparing for and taking action on matters of social and political importance – a position that Miller (1993) characterizes as transformational education.2 My use of the term “universal critical scientific literacy” signals my rejection of the longstanding differentiation of science education into high status, academic/ theoretical courses for those deemed (on the basis of attainment tests) to be ‘high ability students’ and low status courses oriented towards ‘life skills’ for the rest (Hodson & Reid, 1988). In my view, we should draw later science specialists from a much wider pool – hopefully approaching 100% of each age cohort – of successful, enthusiastic students who have already achieved critical scientific literacy. If the knowledge, skills and attitudes embodied in the notion of scientific literacy are important, as I claim, they are important for everyone. Use of the term “universal critical scientific literacy” carries with it a commitment to a much more rigorous, analytical, skeptical, open-minded and reflective approach to science education than many schools provide and signals my advocacy of a much more politicized and issues-based science education, a central goal of which is to equip students with the capacity and commitment to take appropriate, responsible and effective action on matters of social, economic, environmental and moral-ethical concern (Hodson, 1999, 2003). It almost goes without saying that scientific literacy presupposes a reasonable level of literacy in its fundamental sense (Wellington & Osborne, 2001; Fang, 2005). Engagement in science, contribution to debate about science and access to science education are not possible without a reasonable level of literacy. As Anderson (1999, p. 973) states: “reading and writing are the mechanisms through which scientists accomplish [their] task. Scientists create, share, and negotiate the meanings of inscriptions – notes, reports, tables, graphs, drawings, diagrams”. Scientific knowledge cannot be articulated and communicated except through text, and its associated symbols, diagrams, graphs and equations. The specialized language of science makes it possible for scientists to construct an alternative interpretation and explanation of events and phenomena to that provided by ordinary, everyday language. Indeed, it could be said that learning the language of science is synonymous with (or certainly coincident with) learning science, and that doing science in any meaningful sense requires a reasonable facility with the language. It is scientific language that shapes our ideas, provides the means for constructing scientific understanding and explanations, enables us to communicate the purposes, procedures, findings, conclusions and implications of our inquiries, and allows us to relate our work to existing knowledge and understanding. Because of the dependence of science on text, access to science also depends on basic literacy, and those whose ability to read and write is poorly developed are unlikely to achieve even a rudimentary level of scientific literacy, despite the prodigious efforts of some teachers to convey scientific understanding through drama, dance, film and other media. Proficient reading of science text involves more than just recognizing all the words and being able to locate specific information, it also involves the ability to infer meaning from the text – in particular, the meaning intended by the author – and to establish relationships between ideas, link personal 2 Derek Hodson - 978-90-8790-507-1 Downloaded from Brill.com11/09/2020 11:12:23AM via free access

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experiences with text, and transfer understanding from one context to another. Thus, it involves analysis, interpretation and evaluation. In consequence, it depends (in part) on what the reader brings to the task in terms of text interpretation strategies. Despite the often considerable substantive content and the highly specialized language of science, the abilities required to extract meaning from scientific text are largely those required to extract meaning from any text, and while content knowledge is vitally important, it is by no means sufficient for a proper understanding of scientific text. Indeed, Norris and Phillips (1994) and Phillips and Norris (1999) have shown that high school students who score highly on traditional measures of science attainment sometimes perform very poorly when asked to interpret media reports of scientific matters. To paraphrase the conclusions of Norris and Phillips (2003), understanding of science text resides in the capacity to determine when something is an inference, a hypothesis, a conclusion or an assumption, to distinguish between an explanation and the evidence for it, and to recognize when the author is asserting a claim to ‘scientific truth’, expressing doubt or engaging in speculation. Without this level of interpretation, the reader will fail to grasp the essential scientific meaning. Put simply, learning to think and reason scientifically requires a measure of facility with the forms and conventions of the language of science. It is not solely a matter of recognizing the words, and using them appropriately, but also the ability to comprehend, evaluate and construct arguments that link evidence to ideas and theories. Thus, teaching about the language of science, and its use in scientific argumentation should be a key element in science education at all levels and there is a clear need for much closer cooperation between science teachers (who need to know much more about the role and function of language) and language arts teachers (who need to know much more about the specific characteristics of scientific language). If it is correct that most people, including many still in school, obtain most of their knowledge of contemporary science and technology from television, newspapers, magazines and the Internet (National Science Board, 1998; Select Committee, 2000), then the capacity for active critical engagement with text is not only a crucial element of scientific literacy, it is perhaps the fundamental element. In that sense, education for scientific literacy has striking parallels with education in the language arts. At the very least, students need to be able to read, understand and evaluate scientific text in a wide variety of forms and styles (textbooks, teacher handouts, newspaper and magazine articles, press releases and news briefs, Internet postings and product labels, as well as graphs, diagrams, tables, chemical equations and mathematical representations), convert empirical data acquired in laboratory and fieldwork activities into text, and articulate and communicate their thoughts, ideas, beliefs and feelings in ways that are intelligible to the intended audience, whether it be peers, parents, teachers or the wider public. To be fully scientifically literate, students need to be able to distinguish among good science, bad science and non-science, make critical judgements about what to believe, and use scientific information and knowledge to inform decision making at the personal, employment and community level. In other words, they need to be critical consumers of science. This entails recognizing that scientific text is a cultural artifact, and so may carry implicit messages relating to interests, values, power, class, gender, 3 Derek Hodson - 978-90-8790-507-1 Downloaded from Brill.com11/09/2020 11:12:23AM via free access

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ethnicity and sexual orientation. In the words of Yore and Treagust (2006), “No effective science education programme would be complete if it did not support students in acquiring the facility of oral science language and the ability to access, produce, and comprehend the full range of science text and representations” (p. 296). What both these authors and I have in mind is a science education very different from the traditional uncritical and unquestioning approach that presents science as dogmatic, fixed and certain. Scientific literacy also presupposes some basic understanding of mathematics, such as familiarity with simple algebraic equations, the capacity to interpret graphical and statistical data, and sufficient knowledge of the mathematics of probability to understand issues of risk and cost-benefit analysis. It also presupposes some understanding of the dependence of science on mathematics. For example, Kepler would not have derived his Laws of Planetary Motion without Greek knowledge of conic sections accumulated some 1800 years earlier, Hilbert’s theory of integral equations was essential for quantum mechanics and Riemann’s differential geometry for Einstein’s theory of relativity. We can reasonably conclude that the great surge in scientific knowledge since the 17th Century can be attributed, in large part, to developments in mathematics and, in particular, the invention of differential and integral calculus. What else should be regarded as crucial to a claim of being scientifically literate? Understanding the nature of science? Understanding the major theoretical frameworks of biology, chemistry and physics? Understanding the complex relationships among science, technology, society and environment? Knowing about the historical development of the ‘big ideas’ of science and the circumstances that led to the development of key technologies? Being aware of contemporary applications of science? Having the ability to use science in everyday problem solving? Holding a personal view on controversial issues that have a science and/or technology dimension? Possessing a basic understanding of global environmental issues? WHAT IS SCIENTIFIC LITERACY?

The term scientific literacy seems to have first appeared in the US educational literature in papers by Paul Hurd (1958) and Richard McCurdy (1958).3 It was enthusiastically taken up by others as a useful rallying call (see Roberts, 1983, 2007), but had little in the way of precise or agreed meaning until Pella et al. (1966) suggested that it comprises an understanding of the basic concepts of science, the nature of science, the ethics that control scientists in their work, the interrelationships of science and society, the interrelationships of science and the humanities, and the differences between science and technology – with the first three categories being designated as the most significant. Almost a quarter century later, Science for All Americans (AAAS 1989, p. 4) drew upon very similar categories to define a scientifically literate person as “one who is aware that science, mathematics, and technology are interdependent human enterprises with strengths and limitations; understands key concepts and principles of science; is familiar with the natural world and recognizes both its diversity and unity; and uses scientific knowledge and scientific ways of thinking for individual and social purposes.” 4 Derek Hodson - 978-90-8790-507-1 Downloaded from Brill.com11/09/2020 11:12:23AM via free access

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However, to suggest that debate had been stagnant during the intervening years would be to seriously misinterpret matters. Indeed, following the work of Milton Pella and his co-workers, there was a period of intense debate, definition and counter-definition, marked by notable contributions from Daugs (1970), Agin (1974), Showalter (1974), Klopfer (1976), O’Hearn (1976) and Pella (1976), and culminating in Gabel’s (1976) detailed analysis of the literature in terms of eight dimensions (organization of knowledge, intellectual processes, values and ethics, process and inquiry, human endeavour, interaction of science and technology, interaction of science and society, interaction of science, technology and society) and nine categories of educational objectives (Bloom’s six categories of cognitive objectives plus three affective objectives – valuing, behaving and advocating). As Roberts (1983) comments, “What is immediately striking about Gabel’s model is that it includes, under the definition of scientific literacy, every category of science education objectives… it now means virtually everything to do with science education” (p. 22). Of course, interest in the notion of scientific literacy has not been restricted to those concerned with science education in school and university. As Fitzpatrick (1960) remarked, “If the Zeitgeist is to be favorable to the scientific enterprise, including both academic and industrial programs, the public must possess some degree of scientific literacy, at least enough to appreciate the general nature of scientific endeavor and its potential contributions to a better way of life… no citizen, whether or not he is engaged in scientific endeavors, can be literate in the modern sense until he has understanding and appreciation of science and its work” (p. 6). He concludes: “The ultimate fate of the scientific enterprise is in no small degree dependent upon establishing a species of scientific literacy in the general population” (Fitzpatrick, 1960, p. 169). At about the same time, Alan Waterman (Director of the National Science Foundation) noted that it was a matter of urgency that “the level of scientific literacy on the part of the general public be markedly raised… progress in science depends to a considerable extent on public understanding and support” (Waterman, 1960, p. 1349). In the United Kingdom there has been a tradition of concern for the public understanding of science dating back to the early years of the 19th Century (Shen, 1975; Jenkins, 1990). In more recent times the Royal Society (1985) noted that “Improving the public understanding of science is an investment in the future; not a luxury to be indulged in if and when resources allow” (p. 9). The Royal Society’s argument that scientific literacy “can be a major element in promoting national prosperity, in raising the quality of public and private decision making and in enriching the life of the individual” (p. 9) serves to underline the key distinction between those who see scientific literacy as the possession of knowledge, skills and attitudes essential to a career as a professional scientist, engineer or technician and those who see it as the capacity to access, read and understand material with a scientific and/or technological dimension, make a careful appraisal of it, and use that evaluation to inform everyday decisions, including those made at the ballot box. According to Klopfer (1969), this distinction should be reflected in a differentiated school science curriculum: “One curricular stream… designed for students planning to enter careers as scientists, physicians, and engineers… the other… designed for 5 Derek Hodson - 978-90-8790-507-1 Downloaded from Brill.com11/09/2020 11:12:23AM via free access

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students who will become the nonscientist citizenry… housewives, service workers, salesmen etc…. Differentiation of students (should) begin at about age fourteen when they choose the high school they will attend” (p. 203). Distinctions are drawn somewhat differently by Shen (1975), who sees scientific literacy as falling into three categories: practical, civic and cultural. Practical scientific literacy is knowledge that can be used to help solve life’s everyday problems; civic scientific literacy is the knowledge necessary to play a full part in key decision-making in areas such as health, use of natural resources, energy policy and environmental protection; cultural scientific literacy involves knowing those ideas in science that represent major cultural achievements. Essentially the same categorization lies behind the exercise devised by Robin Millar (1993) for teachers and others in science education to justify (or not) the inclusion of particular topics in the school science curriculum on utilitarian, democratic or cultural grounds. Wellington (2001) makes a similar point when he argues that there are three sets of arguments for justifying curriculum content: (i) the intrinsic value of science education; (ii) the citizenship argument; (iii) utilitarian arguments. (i) Intrinsic Value – Making sense of natural phenomena; de-mystifying them. – Understanding our own bodies, our own selves. – Interesting, exciting, and intellectually stimulating. – Part of our culture, our heritage. (ii) Citizenship Arguments – Science knowledge and knowledge of scientists’ work are needed for all citizens to make informed decisions in a democracy. – Key decision makers (e.g., civil servants, politicians) need knowledge of science, scientists’ work and the limitations of scientific evidence to make key decisions, e.g., on foods, energy resources. (iii) Utilitarian Arguments – Developing generic skills that are of value to all, e.g., measuring, estimating, evaluating. – Preparing some for careers and jobs that involve some science. – Preparing a smaller number for careers using science or as ‘scientists’. – Developing important attitudes/dispositions: i.e., the ‘scientific attitude’ of curiosity, wonder, healthy skepticism, an enquiring mind, a critical/analytical disposition. In contrast to Klopfer’s advocacy of a differentiated curriculum, Wellington states that each orientation is important for every student. As a variant on this principle of common provision, the authors of Beyond 2000: Science Education for the Future (Millar & Osborne, 1998) state that science education between the ages of 5 and 16 (the years of compulsory schooling in the UK) should comprise a course to enhance general scientific literacy, with more specialized science education delayed to later years: “the structure of the science curriculum needs to differentiate more explicitly between those elements designed to enhance ‘scientific literacy’, and those designed as the early stages of a specialist training in science, so that the requirement for the latter does not come to distort the former” (p. 10).4 6 Derek Hodson - 978-90-8790-507-1 Downloaded from Brill.com11/09/2020 11:12:23AM via free access

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While Branscomb (1981) expanded Shen’s categorization into eight forms of scientific literacy (methodological science literacy, professional science literacy, universal science literacy, technological science literacy, amateur science literacy, journalistic science literacy, science policy literacy and public science policy literacy), each related to a particular role in society, Shamos (1995) maintained a three-fold categorization. However, unlike other writers, Shamos sees his categories as hierarchical. For him, cultural scientific literacy is the simplest, most basic level of literacy. It comprises the basic understanding needed to (i) make sense of articles in newspapers and magazines, and programmes on television, (ii) communicate with elected representatives, and (iii) follow debates on public issues with a science and technology dimension. Functional scientific literacy builds on cultural scientific literacy by “requiring that the individual not only have command of a science lexicon, but also be able to converse, read, and write coherently, using such science terms in a perhaps non-technical but nevertheless meaningful context” (Shamos, 1995, p. 8). True scientific literacy, as Shamos calls it, involves knowledge and understanding of major scientific theories, including “how they were arrived at, and why they are widely accepted, how science achieves order out of a random universe… the role of experiment… the importance of proper questioning, of analytical and deductive reasoning, of logical thought processes, and of reliance on objective evidence” (p. 89). Substantially the same hierarchy is proposed by Bybee (1997): nominal scientific literacy (knowing scientific words but not their meaning), functional scientific literacy (reading and writing science using simple and appropriate vocabulary) and conceptual and procedural scientific literacy (a thorough understanding of both the conceptual and procedural bases of science). Bybee adds a fourth category: multidisciplinary scientific literacy – a thorough and robust understanding of the conceptual and procedural structures of science, together with knowledge of the history of science, an understanding of the nature of science and appreciation of the complex interactions among science, technology and society. As Fensham (2002) argues, the first category is no literacy at all, the second is “functional only in a direct vocabulary sense, and not in any generalized operational sense” (p. 17), while the fourth may comprise an unrealistic target for many students. A general criticism of these attempts to define scientific literacy is that they are couched in terms of what scientists and/or science educators regard as essential knowledge and understanding. An entirely different approach to the notion of functional scientific literacy was taken by researchers at the University of Leeds. Loosely structured interviews were used to ascertain the “practical knowledge in action” assembled and deployed by individuals or groups of adults engaged in understanding and/or acting upon some issue with a scientific dimension, such as managing a domestic energy budget within a low, fixed income or raising a child born with Down’s Syndrome (Layton et al., 1986, 1993; Jenkins, 1996a, 1999). It quickly became clear that the science needed for solving the problems of everyday life is very different in form from the science presented in the school curriculum. For example, says Jenkins (1999, p. 705), it makes more sense in a practical context to regard heat as “something which ‘flows’ rather than in terms of the ‘more correct’ kinetic theory of matter”. The ways in which everyday problems 7 Derek Hodson - 978-90-8790-507-1 Downloaded from Brill.com11/09/2020 11:12:23AM via free access

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are confronted and solved is also very different from the way problem-solving is approached in school science lessons. ‘Citizen thinking’, i.e., everyday thinking, turns out to be much more complex and less well understood than scientific thinking and, as might be expected, well adapted to decision-making in an everyday world which, unlike science itself, is marked by uncertainty, contingency and adaptation to a range of uncontrolled factors. (Jenkins, 1999, p. 704) This conclusion, which has much in common with the now extensive literature in situated cognition, has prompted Peter Fensham (2002) to state that it is “time to change drivers for scientific literacy” and to abandon the traditional ways of identifying science content knowledge for the school curriculum. More in line with Fensham’s recommendation than most contemporary science education programmes would be a curriculum designed in accordance with the findings described by Law (2002) arising from a study in which she and her co-researchers asked leading scientists, health care professionals, local government representatives, managers and personnel officers in manufacturing industry, and the like, about the kind of science and the kind of personal attributes and skills that are of most value in persons employed in their field of expertise. Similarly, Duggan and Gott (2002) sought to identify the science used by employees in five science-based industries: a chemical plant manufacturing cosmetics and pharmaceuticals, a biotechnology company producing diagnostic kits for medical use, an environmental analysis laboratory, an engineering company manufacturing pumps for the petrochemical industry and an arable farm. What they found was that most of the necessary science was learned on-the-job rather than in school. This finding is mirrored in work by Chin et al. (2004) and Aikenhead (2005). The latter study concluded that school science is “focused predominantly on declarative knowledge while workplace knowledge is focused predominantly on procedural knowledge” (p. 129) – that is, ‘knowing that’ is emphasized in school and ‘knowing how’ in the workplace. These studies raise important questions about the purpose of scientific literacy and the motives of the different stakeholders in promoting it. Before proceeding to discussion of these matters, it is worth noting that scientific literacy has a significant metacognitive dimension. Students need to know what they know, how and when that knowledge can and should be utilized, how to recognize deficiencies in their knowledge and how to compensate for them. It is metacognitive knowledge and skills that enable an individual to promote and monitor her or his learning. Pintrich (2002) refers to three categories of metacognitive knowledge: (i) strategic knowledge – knowledge of general thinking skills to facilitate learning and problem solving; (ii) knowledge about cognitive tasks – understanding when and how to apply various strategies; and (iii) self knowledge – knowledge of one’s own strengths and weaknesses. A number of authors have argued that all meaningful construction and evaluation of knowledge, whether by means of reading, talking or writing, depend largely on metacognition (Holliday et al., 1994; Keys, 1999; Wallace et al., 2003; Wallace, 2004). Effective readers apply a knowledge of their own strengths and weaknesses to organize prior knowledge and relate it to new 8 Derek Hodson - 978-90-8790-507-1 Downloaded from Brill.com11/09/2020 11:12:23AM via free access

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information, and to elaborate on the ideas they locate in the text; effective writers consistently judge the match between the information and ideas they are trying to articulate and the language they are using to represent them. To construct a scientific argument, whether it is delivered orally or in written form, it is necessary to monitor and evaluate the match among the various components of the argument WHY DO WE NEED SCIENTIFIC LITERACY?

Reviewing what they describe as an extensive and diverse literature, Thomas and Durant (1987) identify a range of arguments for promoting the public understanding of science, including benefits to science, benefits to individuals and benefits to society as a whole. Benefits to science are seen largely in terms of increased numbers of recruits, greater support for scientific research and more realistic public expectations of science. Notwithstanding the massive research endeavours of the pharmaceutical industry, the electronics industry, the armaments and aircraft industry, and other business enterprises, a great deal of the financial support for fundamental scientific research derives from public funds.5 Thus, it is argued, the self-interests of scientists demands that they keep the tax-payer well informed about what scientists do, and how they validate their research findings and theoretical conclusions, because a well-informed public is more likely to be supportive of such high levels of financial investment. In developing this line of argument, Schwab (1962) advocated a shift of emphasis away from the learning of scientific knowledge (the products of science) towards an understanding of the processes of scientific inquiry because it can ensure “a public which is aware of the conditions and character of scientific enquiry, which understands the anxieties and disappointments that attend it, and which is, therefore, prepared to give science the continuing support which it requires” (p. 38). Jenkins (1994b) makes the related point that enhanced public understanding of science enables scientists to be more effective in countering opposition from religious fundamentalist groups, animal rights activists and others who might seek to constrain or curtail scientific inquiry (and science education). A related argument advanced by Shamos (1993) is that enhanced scientific literacy is a defence against what he sees as the anti-science and neo-Luddite movements that are (in his words) “threatening to undermine science”. The school science curriculum, he argues, “should be the forum for debunking the attempts of such fringe elements to distort the public mind, first by exposing their tactics, and then by stressing over and over again the central role in science of objective, reproducible evidence” (p. 71). Some years ago, Isaac Asimov (1983) suggested that “without an informed public, scientists will not only be no longer supported financially, they will be actively persecuted” (p. 109). More recently, Stuewer (1998) has provided a wonderfully colourful description of the scientist as “exactly what the medicine-man is for the savage: namely, a mysterious ambivalent figure, who is to be worshipped as the carrier of recondite knowledge and the agent of recondite powers; and who is at the same time to be feared, even hated, and to be put in his place. The medicine-man may be a power, but he is a very acceptable sacrifice to the gods” (Wiener (1950), cited by Stuewer, p. 25). While open hostility towards science and scientists is still 9 Derek Hodson - 978-90-8790-507-1 Downloaded from Brill.com11/09/2020 11:12:23AM via free access

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rare and the prospect of sacrifice remote, there is certainly much public suspicion of science and a significant decline in public confidence in scientists, largely as a consequence of the BSE (bovine spongiform encephalopathy) or ‘Mad Cow Disease’ episode in the United Kingdom, anxiety about the environmental impact of genetically engineered crops, the conspicuous failure of scientists over many years to reach consensus about the causes and significance of global warming and climate change,6 the appearance of scientists as ‘expert witnesses’ for both sides in legal disputes (for example, concerning the practices of tobacco companies), the use of ‘purpose-built’ scientific research in advertizing to promote particular business interests, increasing domination of scientific research by industrial and military interests, and the sometimes cavalier disregard that some scientists exhibit towards the social and ethical issues raised by contemporary science and technology. As Barad (2000) comments, “the public senses that scientists are not owning up to their biases, commitments, assumptions, and presuppositions, or to base human weaknesses such as the drive for wealth, fame, tenure, or other forms of power” (p. 229). In making his case for increased levels of scientific literacy, Shortland (1988) states that confidence in scientists and public support for science depend on “at least a minimum level of general knowledge about what scientists do” (p. 307). More significantly, support depends on whether the public values what scientists do. It is naïve to assume that enhanced scientific literacy will inevitably translate into simple trust of scientists and unqualified support for the work they choose to do. A scientifically literate population, with a rational view of the world, a predisposition to think critically and the capacity to appraise scientific evidence for themselves, is perhaps much more likely to be skeptical, suspicious or even distrustful of scientists, and much more likely to challenge the nature of scientific research and the direction of technological innovation. Of course, while increased critical scrutiny of science may ensue, increased public control of the scientific enterprise is not guaranteed by enhanced scientific literacy alone, even if universal. What is needed is scientific literacy allied to political literacy and a commitment to sociopolitical involvement – hence my arguments elsewhere (Hodson, 1994, 2003) for a curriculum oriented toward citizen action. Arguments that scientific literacy confers benefits on individuals come in a variety of guises. For example, it is commonly argued that scientifically literate individuals have access to a wide range of employment opportunities and are well-positioned to respond positively and productively to the introduction of new technologies into the workplace: “More and more jobs demand advanced skills, requiring that people be able to learn, reason, think creatively, make decisions, and solve problems. An understanding of science and the process of science contributes in an essential way to these skills” (National Research Council, 1996, p. 2). Moreover, those who are scientifically literate are better able to cope with the demands of everyday life in an increasingly technology-dominated society, better positioned to evaluate and respond appropriately to the supposed “scientific evidence” used by advertizing agencies and politicians, and better equipped to make important decisions that affect their health, security and economic wellbeing. 10 Derek Hodson - 978-90-8790-507-1 Downloaded from Brill.com11/09/2020 11:12:23AM via free access

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Personal decisions, for example about diet, smoking, vaccination, screening programmes or safety in the home and at work, should all be helped by some understanding of the underlying science. Greater familiarity with the nature and findings of science will also help the individual to resist pseudo-scientific information. An uninformed public is very vulnerable to misleading ideas on, for example, diet or alternative medicine. (Royal Society, 1985, p. 10) When people know how scientists go about their work and reach scientific conclusions and what the limitations of such conclusions are, they are more likely to react thoughtfully to scientific claims and less likely to reject them out of hand or accept them uncritically. (AAAS, 1993, p. 3) There is a cluster of arguments that focus on the intellectual, aesthetic and moral-ethical benefits conferred on individuals by scientific literacy. In the first two arguments there are strong echoes of C.P. Snow’s (1962) assertion that science is “the most beautiful and wonderful collective work of the mind of man” (p. 14) and, therefore, as crucial to contemporary culture as literature, music and fine art. Indeed, Dawkins (1998) asserts that “the feeling of awed wonder that science can give us is one of the highest experiences of which the human psyche is capable. It is a deep aesthetic passion to rank with the finest that music and poetry can deliver” (p. x). Notwithstanding the sexist language so common forty years ago, Warren Weaver perfectly encapsulates this particular rationale for scientific literacy: The capacity of science progressively to reveal the order and beauty of the universe, from the most evanescent elementary particle up through the atom, the molecule, the cell, man, our earth with all its teeming life, the solar system, the metagalaxy, and the vastness of the universe itself, all this constitutes the real reason, the incontrovertible reason, why science is important, and why its interpretation to all men is a task of such difficulty, urgency, significance and dignity. (Weaver, 1966, p. 50) The assertion that the ethical standards and code of responsible behaviour acquired through scientific literacy will lead to more ethical behaviour in the wider community is a particularly fascinating one. Paraphrasing the arguments of Jacob Bronowski, Shortland (1988) summarizes the rationale as follows: “the internal norms or values of science are so far above those of everyday life that their transfer into a wider culture would signal a major advance in human civilization” (p. 310). Harre (1986) presents a similar argument: “the scientific community exhibits a model or ideal of rational cooperation set within a strict moral order, the whole having no parallel in any other human activity” (p. 1). The authors of Science for All Americans (AAAS, 1989) spell out some of these moral values as follows: “Science is in many respects the systematic application of some highly regarded human values – integrity, diligence, fairness, curiosity, openness to new ideas, skepticism, and imagination” (p. 201). Studying science, scientists and scientific practice will, they argue, help to instill these values in students.

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In other words, the pursuit of scientific truth regardless of personal interests, ambitions and prejudice (part of the traditional image of the objective and dispassionate scientist) makes science a powerful carrier of ethical principles. Scientific literacy doesn’t just result in more skilled and more knowledgeable people, it results in wiser people, well equipped to make morally and ethically superior decisions. Given the findings from sociology of science to be discussed in chapter 7, there are good reasons to dismiss this claim as a ludicrous flight of fancy and to argue, instead, that science would benefit from transfer of ethical standards in the opposite direction. Arguments that increased scientific literacy would confer benefits on society as a whole include (i) the familiar and increasingly pervasive economic argument (closely linked, of course, with military and ideological arguments7), (ii) claims that it enriches of the cultural health of the nation and intellectual life in general, and (iii) belief in its capacity to enhance democracy and promote responsible citizenship In recent years, the economic argument has become the predominant rationale for scientific literacy in North America (Garrison & Lawwill, 1992). It is a powerful and persuasive one, as illustrated by the Government of Canada’s (1991) attempt to establish a link between school science education and a culture of lifelong learning as the key to the country’s prosperity. Our future prosperity will depend on our ability to respond creatively to the opportunities and challenges posed by rapid change in fields such as information technologies, new materials, biotechnologies and telecommunications... To meet the challenges of a technologically driven economy, we must not only upgrade the skills of our work force, we must also foster a lifelong learning culture to encourage the continuous learning needed in an environment of constant change. (Government of Canada, 1991, pp. 12 & 14) Similarly, the authors of an Ontario Ministry of Education and Training (2000a) document on curriculum planning and assessment state that the curriculum has been designed to ensure that its graduates are well prepared “to compete successfully in a global economy and a rapidly changing world” (p. 3). Thus, scientific literacy is regarded as a form of human capital that sustains and develops the economic wellbeing of a nation. Put simply, continued economic development brought about by enhanced competitiveness in international markets (regarded as incontrovertibly a “good thing”) depends on science-based research and development, technological innovation and a steady supply of scientists, engineers and technicians, all of which ultimately depend on public support for state-funded science and technology education in school. Moreover, the argument goes, increased scientific literacy is likely to sustain high levels of consumer demand for technologies perceived by such scientifically literate individuals as desirable. An indication of the extent to which this ideology has permeated the Ontario (Canada) curriculum can be gleaned from a simple count of key words in the Technological Education Curriculum for Grades 11 and 12 (Ministry of Education & Training, 2000b): markets/marketing = 46, consumer = 15, client/customer = 72, management = 59, industry = 217, sustainability = 0, recycle = 0, ecosystem = 0, interdependence = 0, values = 0 12 Derek Hodson - 978-90-8790-507-1 Downloaded from Brill.com11/09/2020 11:12:23AM via free access

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(Elshof, 2001). It is also worth noting that the People and Skills in the New Global Economy report (Ontario Premier’s Council, 1990) was prepared by a panel comprising five academics, seven politicians three trade union leaders and nineteen company presidents (Davis, 2000). It is also noteworthy that there were only four women among the 34 council members. Before proceeding further, it is worth noting that language is not neutral. Those who gain control of common language usage determine how we conceptualize important issues; they set the agenda for debate and, in effect, determine the way we think and what we value. All language carries a substantial sub-textual cargo of meaning intended to create a particular view of the world.8 Its power is located in the ways in which it determines how we think about society and our relations with others, and in its impact on how we act in the world. When deployed effectively, it creates a particular social reality. Indeed, rhetoric becomes reality and those who think differently, and have different values, are regarded as deviant or aberrant. Strategies include presenting one’s own position as natural or as plain common sense, thus implying that there is a conspiracy among one’s opponents to deny the truth or to promote what is fashionable or ‘politically correct’ (itself a term that has acquired substantial pejorative connotations). This is a powerful technique. First, it assumes that there are no genuine arguments against the chosen position; any opposing views are thereby positioned as false, insincere or self-serving. Second, the technique presents the speaker as someone brave or honest enough to speak the (previously) unspeakable. Hence the moral high ground is assumed and opponents are further denigrated. (Gillborn, 1997, p. 353) Hence, when school science lessons present students, almost daily, with a language that (i) promotes economic globalization, increasing production and unlimited expansion, (ii) sees unfettered technological production and spiraling consumption as “progress”, (iii) regards job satisfaction as the accumulation of wealth and material goods, and (iv) equates excellence with competition and “winning at any cost”, it is co-opted into the manufacture and maintenance of what Bowers (1996, 1999) calls the myths of modernity: “that the plenitude of consumer goods and technological innovation is limited only by people’s ability to spend, that the individual is the basic social unit… that science and technology are continually expanding humankind’s ability to predict and control their own destiny” (1996, p. 5). At risk from this new “reality” are the freedoms of individuals who think differently, the spiritual well-being of those who would live differently, and the integrity of the planet’s complex and delicate ecosystems. In Edmund O’Sullivan’s (1999) words: Our present educational institutions which are in line with and feeding into industrialism, nationalism, competitive transnationalism, individualism, and patriarchy must be fundamentally put into question. All of these elements together coalesce into a world view that exacerbates the crisis we are now facing. (p. 27)

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Many in the economically under-developed parts of the world see globalization as a renewed form of colonization, a form of cultural and economic imperialism that threatens to destroy rather than foster their economic and social well-being, that commodifies both natural resources and people, locates them on the periphery of key decision-making (or excludes them entirely) and compounds their powerlessness, poverty and dispossession (Muchie & Xing, 2006). As Roseneau (1992) observes, the self-serving policies of international organizations such as the IMF, World Bank, OECD and G-7 in many under-developed and developing nations constitute “governance without government”. While neo-liberalism may mean less government, it does not follow that there is less governance. While… neo-liberalism problematises the state and is concerned to specify its limits through the invocation of individual choice… it involves forms of governance that encourage both institutions and individuals to conform to the norms of the market. (Larner, 2000, p. 12 – cited by Bencze & Alsop, 2007, p. 3) On the surface, [globalization] is instant financial trading, mobile phones, McDonald’s, Starbuck’s, holidays booked on the net. Beneath this gloss, it is the globalization of poverty, a world where most human beings never make a phone call and live on less than two dollars a day, where 6,000 children die every day from diarrhoea because most have no access to clean water. (Pilger, 2002, p. 2) It is clear that little of the world’s poverty, injustice, terrorism and war will be eliminated, and few among the litany of environmental crises (ozone depletion; global warming; land, air and water pollution; deforestation; desertification; and so on) will be solved, without a major shift in the practices of western industrialized society and the values that sustain them. Interestingly, one of the keys to ameliorating the current situation may lie in increased levels of scientific literacy among the world’s citizens – an idea explored a little in the following section and at length in Hodson (2003). The life-enhancing potential of science and technology cannot be realized unless the public in general comes to understand science, mathematics and technology and to acquire scientific habits of mind; without a scientifically literate population, the outlook for a better world is not promising. (AAAS, 1989, p. 13) The case for scientific literacy as a means of enhancing democracy and responsible citizenship, and resisting the consumer juggernaut, is just as strongly made as the economic argument, though by different stakeholders and interest groups. Thomas and Durant (1987) note that increased scientific literacy “may be thought to promote more democratic decision-making (by encouraging people to exercise their democratic rights), which may be regarded as good in and of itself; but in addition, it may be thought to promote more effective decision-making

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(by encouraging people to exercise their democratic right wisely” (p. 5). Whether wisdom is the likely outcome of enhanced scientific literacy in the wider community depends crucially, of course, on how notions of scientific literacy are translated into curriculum practice. In similar vein, Chen and Novick (1984) express concern about the fragility of democracy and see enhanced scientific literacy as a means “to avert the situation where social values, individual involvement, responsibility, community participation and the very heart of democratic decision making will be dominated and practiced by a small elite” (p. 425). This, of course, presupposes that we aim for universal scientific literacy, as argued above. What is clear is that democracy is strengthened when all citizens are equipped to evaluate Socioscientific issues (SSI) and make informed decisions on matters of personal and public concern. Enhancing scientific literacy might also be the most effective way to combat (i) the naïve trust that many students have in the Internet, accepting almost anything and everything as equally valid and reliable, and forming their views on all manner of topics on the basis of half an hour of exploration with Google, (ii) the distrust with which many people regard any argument that deploys statistics (because, they say, “statistics can prove anything!”), (iii) the increasing tendency to succumb blindly to the seductions of the now all-too-prevalent “alternative sciences” such as iridology and reflexology, (iv) the increasing susceptibility of people to the blandishments of purveyors of “miracle cures”, “revolutionary diets”, “body enhancement” techniques and procedures, and the healing properties of crystals, and (v) the continuing fascination of so many with astrology, ESP, “ancient astronaut” theories and spurious “mysteries” such as the Bermuda Triangle. Interestingly, and with characteristic idiosyncrasy, Dawkins (1998) develops the argument that enhanced scientific literacy results in better decision making into an assertion that “lawyers would make better lawyers, judges better judges, parliamentarians better parliamentarians and citizens better citizens if they knew more science, and more to the point, if they reasoned more like scientists”. This is, in essence, the case being argued in this chapter, although my focus is better decisions by all citizens (whether they are journalists, business people, civil servants, teachers, police officers, or whatever) in the context of SSI. It is also my contention that the kind of critical scientific literacy I have in mind will serve to help scientists make better decisions, in the sense that their judgements focus more attention on the economic, social, cultural, political and moral-ethical dimensions of their work. WHAT CAN WE CONCLUDE?

Where does all this propaganda for scientific literacy leave us? Can we be confident that almost half a century of debate has finally answered the three questions posed at the beginning of the chapter? It seems that the case for greater scientific literacy, and the kind of curriculum proposals that would follow from it, change with social context. They are a product of their time and place: they do not easily cross national or cultural boundaries (Tippens et al., 2000) and do not transfer comfortably from one era to another. Ogawa (1989), for example, expresses grave reservations about the inherent neo-colonialist aspects of ‘transplanting’ Western conceptions of scientific literacy into the education systems of non-Western 15 Derek Hodson - 978-90-8790-507-1 Downloaded from Brill.com11/09/2020 11:12:23AM via free access

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countries, and Clay (1996) remarks: “In its very structure our view of the world is so deeply imbued with the dominant scientific method that to encompass the multiplicity of other equally valid views held in societies beyond our own, we need to encompass different scientific literacies” (p. 190). These issues, the validity of Clay’s claim that there are such alternative literacies, and discussion of various attempts to incorporate traditional knowledge into a curriculum that also presents Western science are outside the scope of this book (but see Aikenhead, 2002; Gitari, 2003, 2006; Palefau, 2005). It almost goes without saying that as science itself changes and develops, so our view about what counts as legitimate scientific literacy also changes. Apart from the need to update curriculum content to keep pace with our rapidly expanding scientific knowledge, there is an urgent need to acknowledge and respond to the many changes in the “social and economic characteristics, ethos, practice, and culture of science” (Hurd, 2002, p. 5). The way science is presented in many conventional science curricula bears very little resemblance to the kind of research carried out in the laboratories of the early 21st century, and the values that underpin this research are very far removed from the traditional portrayal of science as the disinterested pursuit of objective truth. With the increasing industrialization and militarization of the scientific enterprise, for example, previous claims for the cultural and ethical value of scientific literacy seem hopelessly misplaced, if not downright dishonest (Jenkins, 1990), and while the claims that scientific literacy builds economic prosperity may have become more plausible and inviting to some, they have become less morally and ethically defensible in respect of environmental impact and social, cultural and economic consequences for the less fortunate members of society, both within and beyond the developed world. So are there, one might ask, any elements of scientific literacy that are valid in all contexts and for all time? My answer is “Yes”, if scientific literacy means knowing what scientific resources to draw on, where to find them and how to use them (Fourez, 1997) – including the “proper use of scientific experts” (Shamos, 1995, p. 217). My answer is “Yes”, if the real function of scientific literacy is to confer a measure of intellectual independence, to help people learn how to think for themselves and to reach their own conclusions about a range of issues that have a scientific and/or technological dimension. My answer is “Yes”, if scientific literacy is sought not because it improves the economy, produces more “technological goodies” or provides more job opportunities for individuals, but because it liberates the mind. As the authors of Benchmarks for Scientific Literacy (AAAS, 1993) suggest, “People who are literate in science... are able to use the habits of mind and knowledge of science, mathematics, and technology they have acquired to think about and make sense of many of the ideas, claims, and events that they encounter in everyday life” (p. 322). More recently, the OECD’s Programme for International Student Achievement (PISA) proposed that a scientifically literate person is “able to combine science knowledge with the ability to draw evidencebased conclusions in order to understand and help make decisions about the natural world and the changes made to it through human activity” (OECD, 1998, p. 5) and has “a willingness to engage in science-related issues, and with the ideas of science, as a reflective citizen… having opinions and participating in… current and future 16 Derek Hodson - 978-90-8790-507-1 Downloaded from Brill.com11/09/2020 11:12:23AM via free access

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science-based issues” (OECD, 2006, p. 24). There are strong echoes here of Arons’ (1983) emphasis on the ability to “discriminate, on the one hand, between acceptance of asserted and unverified end results, models, or conclusions, and on the other, understand their basis and origin; that is, to recognize when questions such as “How do we know?” “Why do we believe it?” “What is the evidence for it?” have been addressed, answered, and understood, and when something is being taken on faith” (p. 93). Similar capabilities have sometimes been included in the notion of intellectual independence (Munby 1980; Aikenhead 1990; Norris 1997). Without such capabilities, citizens are “easy prey to dogmatists, flimflam artists, and purveyors of simple solutions to complex problems” (AAAS, 1989, p. 13) – including, one might add, some otherwise respectable scientists, politicians and commentators who seek to intimidate the public through their facility in a mode of discourse unfamiliar to many citizens. Dearden (1968) argued that personal autonomy (the achievement of which, for him, was the prime purpose of education) has three major elements: first, an independence from authorities; second, a disposition to test the truth of things for oneself; third, an ability to deliberate, form intentions and choose in accordance with a scale of values that is self-formulated. In Guy Claxton’s (1991) words, “Nothing could be of greater value than the ability to make your own life up as you go along: to find for yourself what is satisfying; to know your own values and your own mind; to meet uncertainty with courage and resourcefulness; and to appraise what others tell you with an intelligent and healthy skepticism” (p. 130). Of course, in many aspects of modern life we are increasingly dependent on ‘experts’ and ‘authorities’ of various kinds. When dealing with socioscientific issues and appraising new technologies, individuals will only rarely have access to all the relevant data. In consequence, we depend on others to inform us and advise us. For example, we are increasingly dependent on scientists, the inquiries they conduct, and the agencies that report their studies, to tell us about the safety hazards associated with various products and procedures, the toxic effects of pesticides, pharmaceuticals and other materials we encounter in everyday life, the risks associated with post-menopausal HRT and the optimal frequency of mammograms, the threats to our health posed by the proximity of toxic waste dumps, nuclear power plants and overhead power lines, and the large scale compromising of environmental health through loss of biodiversity, increasing desertification, pollution and global warming. It is crucial, therefore, that each of us understands how reliable and valid data are collected and interpreted, and that each of us recognizes the tentative character of scientific knowledge. It is crucial, too, that we understand the ways in which all manner of human interests can and do shape the inquiry and its interpretation and reporting. Without this insight, we have no alternative but to take reports that blame or exonerate at face value, and to accept all claims to scientific knowledge as ‘proven’. In a very real way, critical scientific literacy, and the intellectual independence it bestows, enables us to decide which experts we can trust and rely on. As Ungar (2000) remarks, “after a decade of clipping articles from Science and Nature, my sense that climate change is real ultimately boils down to picking the experts you think you can rely on” (p. 297). Ratcliffe and Grace (2003) cite a study published by the Office of Science and Technology and 17 Derek Hodson - 978-90-8790-507-1 Downloaded from Brill.com11/09/2020 11:12:23AM via free access

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the Wellcome Trust, in 2000, indicating that people tend to trust sources seen as neutral and independent, such as university scientists, scientists working for research charities or health campaigning groups, television news and documentaries, for example. The least trusted sources are politicians and newspapers. Sources seen as having a vested interest, such as environmental activist groups, wellknown scientists and the popular scientific press, rank somewhere in between in terms of trustworthiness. In Elliott’s (2006) study, students were particularly skeptical about the relationship between science, the media and government. There is also an ‘asymmetry of trust’: episodes that weaken or threaten trust in science tend to receive greater exposure in the media and live longer in the public memory than episodes that build or consolidate confidence in science and scientists. My interpretation of the notion of critical scientific literacy encompasses the capacity to read reports involving science (in all forms of communication in an informed and critical way in order to form one’s own judgement about what to believe, what to doubt and what to reject. Hurd (1998) sums up this critical dimension of scientific literacy, and its roots in learning about science, when he defines a scientifically literate person as someone who “distinguishes and recognizes expertise, dogma, pseudoscience, the temporal nature of knowledge, effective argumentation, and relationships among claims, evidence, and warrants” (p. 24). What Hurd doesn’t mention is that this kind of understanding needs to be developed in such a way that students can see the sociopolitical embeddedness of science and technology. If science continues to be presented as an exercise in abstract puzzle solving, devoid of social, political, economic and cultural influences and consequences, citizens will continue to see contemporary SSI as largely ‘technical problems’, for which experts can be relied upon to provide the answers. What we should be seeking is political engagement of citizens in monitoring and, to an extent, directing the course of scientific and technological development. It is timely, then, that the so-called Crick Report, Education for Citizenship and the Teaching of Democracy in Schools, has prompted the establishment of citizenship education comprising three strands – social and moral responsibility, community involvement, political literacy – as a mandatory part of the curriculum of all subjects in England and Wales. The declared aim of this initiative is: … a change in the political culture of this country both nationally and locally: for people to think of themselves as active citizens, willing, able and equipped to have an influence in public life and with the critical capacities to weigh evidence before speaking and acting; to build on and to extend radically to young people the best in existing traditions of community involvement and public service, and to make them individually confident in finding new forms of involvement and action. (Qualifications & Curriculum Authority, 1998, p. 8) In practice, as Davies (2004) reminds us, not all science educators who are keen to implement science education for citizenship have a clearly articulated notion of what responsible citizenship entails and how science education can play a part in helping students achieve it. He quotes at length from Gamarnikow and Green’s 18 Derek Hodson - 978-90-8790-507-1 Downloaded from Brill.com11/09/2020 11:12:23AM via free access

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(2000) argument that it so often “reproduces a version of citizenship education unlikely to challenge the social mechanisms of inequality reproduction” (p. 1757). I tend to agree that there is a depressing tendency to equate science education for citizenship with the inclusion of common everyday examples as a way of motivating students and enhancing conceptual (and possibly procedural) understanding. In other words, the citizenship element is a mere enabling tactic; the real goal is enhanced understanding of science content. However, I am enormously encouraged by the authors of Science For All Americans (AAAS, 1989, p. 12), who direct attention towards scientific literacy for a more socially compassionate and environmentally responsible democracy when they assert that science can provide knowledge “to develop effective solutions to… global and local problems” and can foster “the kind of intelligent respect for nature that should inform decisions on the uses of technology” and without which, they say, “we are in danger of recklessly destroying our life-support system”. I am even more encouraged by the radical scholarship of Roth and Désautels (2002, 2004) and Roth and Barton (2004) – in particular, their vision of science education as and for sociopolitical action. Not only is responsible social action the motive for achieving scientific literacy it is also, sometimes, the means of achieving it. What are the essential elements of this kind of scientific literacy? Perhaps, and somewhat paradoxically for an overall argument so politically distant from my own, the answer can be found in the writing of Longbottom and Butler (1999): Science education provides ideal opportunities to engage in a wide range of careful investigations and problem-solving activities, where mistakes and wishful thinking are readily exposed. Science education can value creativity but not accept personal theories as an endpoint. The ability to adjudicate between knowledge claims in ways independent of human desires is a special feature of science that has allowed it to build up a public body of reliable knowledge. Science education should convey these aspects of science. (p. 488) In common with several others, these authors seem to be saying that scientific literacy for active citizenship, responsible environmental behaviour and social reconstruction lies more in learning about science and in doing science than it does in learning science.9 No science curriculum can equip citizens with thorough first-hand knowledge of all the science underlying all important issues. Moreover, much of the scientific knowledge learned in school, especially in the rapidly expanding fields of the biological sciences, will be out-of-date within a few years of leaving school. However, science education can enable students to understand the significance of knowledge presented by others and it can enable them to evaluate the validity and reliability of that knowledge and to understand why scientists often disagree among themselves on such major matters as climate change (and its causes) without taking it as evidence of bias or incompetence. Of course, they also need to know that bias and incompetence do sometimes occur. Thus, students need to have a clear understanding of what counts as good science (i.e., a well designed inquiry and a well argued conclusion) and be able to detect bias and self-interest. As Geddis (1991) comments students need to be able to “uncover how particular knowledge claims may serve the 19 Derek Hodson - 978-90-8790-507-1 Downloaded from Brill.com11/09/2020 11:12:23AM via free access

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interests of different claimants… they need to attempt to unravel the interplay of interests that underlie these other points of view” (p. 171). It is certainly not my intent to argue that knowledge of the major concepts, ideas and theories of science is unimportant.10 It would be a very curious state of affairs indeed to claim scientific literacy and admit to knowing no science at all! Nevertheless, the science content of scientific literacy is not my concern here. Of pertinence here are those elements of the history, philosophy and sociology of science that would enable students to leave school with robust knowledge about the nature of scientific inquiry and theory building, an understanding of the role and status of scientific knowledge, an ability to understand and use the language of science appropriately and effectively, the capacity to analyze, synthesize and evaluate knowledge claims, some insight into the sociocultural, economic and political factors that impact the priorities and conduct of science, a developing capacity to deal with the moralethical issues that attend some scientific and technological developments, and some experience of conducting authentic scientific investigations for themselves and by themselves (Hodson, 2006). While we cannot provide all the science knowledge that our students will need in the future (indeed, we do not know what knowledge they will need) and while much of the science they will need to know has yet to be discovered,11 we do know what knowledge, skills and attitudes will be essential to appraising and forming a personal opinion about the science and technology dimensions of real world issues. If students acquire good learning habits and attitudes towards science during the school years, it will be relatively easy for them to acquire additional scientific knowledge later on, as and when the need arises, provided that they have also acquired the language skills to access and evaluate relevant information from diverse sources. Of course, to be scientifically literate in the sense I am arguing for in this chapter, students will also need the language skills to express their knowledge, views, opinions and values in a form appropriate to their purpose and the audience, and to participate in public debate about SSI. Learning about science is rather different. Gaining robust familiarity with key issues in the history, philosophy and sociology of science requires lengthy and close contact with someone already familiar with them – that is, a teacher or scientist who can provide appropriate guidance, support, experience and criticism. Of course, not everyone shares the view that understanding about the nature of science is central to science education and the notion of critical scientific literacy. Without much in the way of justification of their view, Wilson and Cowell (1982) assert that “anyone who believed that what (say) Popper or Kuhn were concerned with was central to education in science would, surely, either not know the kinds of issues these philosophers were trying to tackle or not have a firm grasp on the idea of education” (p. 39). I will leave readers to form their own views, content in the persuasiveness of arguments presented in this chapter. Chapters 3 to 8 identify some of the ideas in the vast literature of history of science, philosophy of science and sociology of science that are of value in constructing a science curriculum capable of attaining universal scientific literacy, in the sense defined here. First, though, it is important to consider the understanding that many students currently hold about science and scientists, the views promoted by their teachers and textbooks, and the ways in which this research in this area is conducted. 20 Derek Hodson - 978-90-8790-507-1 Downloaded from Brill.com11/09/2020 11:12:23AM via free access

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ENDNOTES 1

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In the Nuffield approach, learning science and doing science were regarded as equivalent activities. Indeed, teachers were encouraged to believe that “intellectual activity is the same whether it is at the frontier or in a third grade classroom… The schoolboy learning physics is a physicist” (Bruner, 1960, p. 14, emphasis added). Similarly, students following the ChemStudy courses in the United States were told that “they would see the nature of science by engaging in scientific activity, thereby ‘to some extent’ becoming scientists themselves” (Pimental (1960, p. 1 and Preface) – cited by Jenkins, 1996b, p. 137). Interestingly, some advocates of constructivist pedagogy adopt an even more ludicrous and educationally dangerous position when they declare that science is “an activity that is carried out by all people as part of their everyday life” (Ministry of Education, New Zealand, 1993, p. 9). Miller (1993) outlines three basic positions for analysing and describing curricula: transmission, with its focus on traditional subjects taught largely through traditional didactic methods; transaction, in which education is seen as a dialogue between student and curriculum, and through which the student reconstructs knowledge; transformation, which is concerned primarily with individual and social change. DeBoer (2001) also cites the Rockefeller Brothers Fund (1958) report The Pursuit of Excellence (p. 369) as a pioneer user of the term: “Just as we must insist that every scientist be broadly educated, so we must see to it that every educated person be literate in science” (p. 586). Millar (2006) describes some initial responses to Twenty First Century Science, a major curriculum project in England. Aimed at 15 and 16 year olds, the course comprises two equal parts: a “core science course” focused on science education for citizenship, and a more content-oriented “additional science” course, which is offered with either a “pure” or “applied” emphasis. According to Millar, teachers generally perceive the citizenship emphasis of the core science course as having a marked beneficial impact on student interest and engagement, they report favourably on the relevance of the course, incorporation of moral-ethical issues, emphasis on ICT and its use of case studies and debate to promote critical thinking, though the latter activities and the language demands of the curriculum resources are reported to have created major new demands on both students and teachers. In the United States, federal funding for research carried out by the National Science Foundation, the National Institutes of Health, the Department of Defense, the Department of Agriculture and NASA amounts to approximately $80 billion per annum. Thankfully, 2007 saw a welcome but cautious dawning of awareness of these matters, prompted in part by Al Gore’s film documentary An Inconvenient Truth and the publication of the 4th assessment report of the Intergovernmental Panel on Climate Change (IPCC) under the title “Climate Change 2007”. Speaking of the earlier publication of the IPCC Assessment Report for 2007, Achim Steiner (Executive Director of the UN Environment Programme) said: “February 2nd 2007 may be remembered as the day the question mark was removed from whether people are to blame for climate change” (reported by Adam, 2007, p. 7) Nearly 50 years ago, and writing from a US perspective, LeCorbeiller (1959) noted that economic power is underpinned by military power (which, of course, is maintained by advances in science and technology) and that the United States (in common with many other nations) exports scientific, engineering and technological ‘know-how’ abroad in order to spread American influence. Nowhere is this more in evidence than in A Nation at Risk (National Commission on Excellence in Education, NCEE, 1983): “our once unchallenged preeminence in commerce, industry, science, and technological innovation is being overtaken by competitors throughout the world… If an unfriendly power had attempted to impose on America the mediocre educational performance that exists today, we might well have viewed it as an act of war. As it stands, we have allowed this to happen to ourselves. We have even squandered the gains in achievement made in the wake of the Sputnik challenge. Moreover, we have dismantled essential support systems which helped make those gains possible. We have, in effect, been committing an act of unthinking, unilateral, educational disarmament.” (p. 5) In a number of publications (Hodson, 1992a, 1994, 1998a), I have argued that science education is best regarded as comprising three major elements:

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10

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– Learning Science – acquiring and developing conceptual and theoretical knowledge. – Learning about science – developing an understanding of the nature and methods of science; appreciation of its history and development; awareness of the complex interactions among science, technology, society and environment; and sensitivity to the personal, social and ethical implications of particular technologies. – Doing science – engaging in and developing expertise in scientific inquiry and problem-solving; developing confidence in tackling a wide range of “real world” tasks and problems. In recent years (Hodson, 2003), I have added a fourth component: Engaging in sociopolitical action – acquiring (through guided participation) the capacity and commitment to take appropriate, responsible and effective action on science/technology-related matters of social, economic, environmental and moral-ethical concern. I emphatically reject the argument made by Shamos (1995) that, for the majority of students, science content is only of value in its exemplification of the nature of science, though I do share his view that technology is often a more accessible subject area for scientific literacy than is science itself. The BSE episode provides a graphic illustration. As Solomon and Thomas (1999) remind us, the nature of the prion agent that most scientists consider to be a cause of the disease was unknown to biology when most of today’s adults received their science education.

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EXPLORING NATURE OF SCIENCE ISSUES Students’ Views and Curriculum Images

In chapter 1, I argued that a significant element of scientific literacy for the 21st Century comes under the umbrella of what I called learning about science – that is, developing an understanding of the nature and methods of science, an appreciation of its history and development, and an awareness of the often complex interactions among science, technology, society and environment. Students can only be considered scientifically literate, I argued, if they possess a robust and authentic understanding of what science is, how science functions, what scientists do, and how science develops and changes over time in response to sociocultural and economic pressures. Indeed, I proffered the idea that in the complex 21st Century world in which we live, this aspect of scientific literacy is at least as significant, if not more significant, than acquisition of conceptual understanding. It is reasonable to suppose that students’ views about science are the outcome of two interacting influences: − Curriculum experiences – what students encounter in school science lessons; − Informal learning experiences – what they learn via the popular media (movies, TV and radio, newspapers, Internet sites, advertizing) and from visits to museums, zoos, aquaria, nature reserves, field centres, and the like. This book is concerned with the learning about science content of curriculum experiences: the kind of experiences we provide; the kind of experiences we should provide, but don’t; the kind of experiences we do provide, but shouldn’t. Although I am restricting the focus of the book in this way, I remain cognizant of the need for teachers to address the other influences on students’ views about science and, whenever necessary, to attempt to counter them.1 I intend to argue that curriculum experiences are of two kinds: those that we explicitly plan and those that we do not. There are many explicit messages about science in textbooks, especially in those early chapters that tell students what science is about and what scientists do when they are conducting investigations; there are lots of explicit references to the nature of science and the history of science in STS-oriented materials; on occasions, teachers take time and trouble to emphasize particular features of science and scientific inquiry during laboratory activities or in class discussions. Just as frequently, however, ‘messages’ about the nature of science and scientific practice are not consciously planned by the teacher. Rather, they are implicit messages located in the language we use, the kind of teaching and learning activities we employ (especially in laboratory work), the examples of science and scientists we utilize, the illustrative and biographical material in textbooks, and so on. What is at issue here is a very powerful hidden or implicit curriculum. In the words of Cawthron and Rowell (1978): 23

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… any science curriculum and its translation into practice embody images of the nature of man as scientist, of scientific knowledge and of the relationships between them. These are communicated, albeit implicitly and incidentally, just as surely as the subject matter itself. (p. 31) Because it says science on the school timetable, students regard what they experience during that lesson as science, not as learning science. Many assume that what they do in science lessons, particularly during hands-on activities, is what scientists themselves do as they conduct investigations. These experiences build, over time, into a particular set of messages about science, scientists and the scientific enterprise. Everything that is part of the science lesson becomes an element in this continuous ‘story building’ about science, whether it is explicitly planned by the teacher or not. It follows that because many of the individual messages about science are ‘transmitted’ implicitly, simply as a consequence of teachers’ day-to-day, shortterm decisions about the conduct of lessons, a major element of the overall story about science is the teacher’s views about the nature of science. All teachers, therefore, need to be cognizant of the responsibility they carry for helping to form their students’ views about science. As a first step in treating that responsibility seriously, teachers should attempt to ascertain, examine and critique their own views. The traditional way of ascertaining views about the nature of science is by means of questionnaire and survey instruments using multiple choice items or Likert scales. A large number of such instruments, mainly for use with students but perfectly applicable for research on teachers’ views as well, have been developed. In fact, even 25 years ago, a literature survey by Mayer and Richmond (1982) identified at least 32 NOS-oriented instruments, among which the best known are the Test on Understanding Science (TOUS) (Cooley & Klopfer, 1961), the Nature of Science Scale (NOSS) (Kimball, 1967), the Nature of Science Test (NOST) (Billeh & Hasan, 1975) and the Nature of Scientific Knowledge Scale (NSKS) (Rubba, 1976; Rubba & Anderson, 1978), together with a modified version (M-NSKS) developed by Meichtry (1992). Instruments dealing with the processes of science, such as the Science Process Inventory (SPI) (Welch, 1969a), the Wisconsin Inventory of Science Processes (WISP) (Welch, 1969b) and the Test of Integrated Process Skills (TIPS) (Burns et al., 1985; Dillashaw & Okey, 1980) could also be regarded as providing information on understanding of the nature of science. In general, these instruments are constructed in accordance with a particular philosophical perspective and are predicated on the assumption that all scientists behave in the same way. Hence teacher and/or student responses that do not correspond to the model of science assumed in the test are adjudged to be ‘incorrect’ (see Lucas (1975), Koulaidis & Ogborn (1995), Alters (1997a) and Lederman et al. (2002) for an extended discussion of this issue). Moreover, as later chapters will show, many of these instruments pre-date significant work in the philosophy and sociology of science, and so are of severely limited value in further studies. Like research in science itself, research in science education is a product of its time and place. More recent reviews by Lederman (1992, 2007), Lederman et al. (1998) and Abd-El-Khalick & Lederman (2000) describe several additional NOS instruments that take into account the work of more recent, and even contemporary, scholars in 24

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philosophy and sociology of science. Most notable among these newer instruments are Conceptions of Scientific Theories Test (COST) (Cotham & Smith, 1981), Views on Science-Technology-Society (VOSTS) (Aikenhead et al., 1989), the Nature of Science Survey (Lederman & O’Malley, 1990), the Views of Nature of Science Questionnaire (VNOS) (Lederman et al., 2002) and several subsequent modifycations (see Lederman, 2007). A particularly useful tool for use with teachers in both pre-service and in-service programs is the Nature of Science Profile developed by Nott and Wellington (1993).2 Its value lies in its ease of administration, wide scope and non-judgmental nature – key factors when dealing with student teachers and their apprehensions about impending teaching practice placements. Of particular value when student teachers have gained some classroom experience is Nott and Wellington’s (1996, 1998, 2000) “Critical Incidents” approach. In group settings, or in one-on-one interviews, teachers are invited to respond to descriptions of classroom events, many related to hands-on work in the laboratory, by answering three questions: What would you do? What could you do? What should you do? Responses, and the discussion that ensues, may indicate something about the teachers’ views of science and scientific inquiry and, more importantly perhaps, how this understanding is deployed in class-room decision making. Similar approaches using video and multimedia materials have been used by Hewitt et al. (2003) and Wong et al. (2008a,b). An interesting variation adopted by Murcia and Schibeci (1999) uses a science-oriented newspaper article as a stimulus to thinking about questionnaire items. It almost goes without saying that teachers’ views about the importance of NOS in the curriculum will also play a major part in their decisions about the extent to which they will emphasize learning about science in their enacted curriculum and the nature of the learning activities they provide (Bell et al., 2000; Schwartz & Lederman, 2002). Interestingly, Nott and Wellington (1995) comment that “teachers’ knowledge of the nature of science may be as much formed by their teaching of science as informing their teaching of science” (p. 865, emphases added) – a conclusion that has major implications for both pre-service and in-service teacher education. There is also a substantial body of research to show that teachers’ nature of science beliefs are sometimes over-ridden in the curriculum decision making process by more immediate concerns with classroom management, the priority afforded to concept acquisition and development, apprehension about student interest in philosophical and sociological issues and the lack of good NOS teaching resources (Mitman et al., 1987; Carey & Smith, 1993; Hodson, 1993a; Abd-El-Khalick et al., 1998; Lederman, 1999; Smith et al., 2000; Lederman et al., 2001) – all of which have major implications for teacher education and teacher professional development STUDENTS’ VIEWS ABOUT SCIENCE AND SCIENTISTS

Three decades of research into students’ alternative frameworks of understanding in science have shown us that students come to science lessons with some prior understanding of many of the concepts and ideas included in the curriculum, and that it would be a mistake to assume that these views are identical to scientists’ 25

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views. Often they are significantly different. It would be a mistake, also, to assume that these views can be easily displaced by the ‘correct’ or preferred views embedded in the curriculum goals. Often they are very strongly held and resistant to change. Necessarily, the understanding students have of any phenomenon under investigation will profoundly influence the way in which they conduct that investigation, the significance they attach to their findings and the conclusions they reach. It was this realization that led to the development of constructivist pedagogy – an approach that, in many parts of the world, has become the ‘new orthodoxy’ of science teaching.3 Its essential steps are: – Identify students’ ideas and views – Create opportunities for students to explore their ideas and test their robustness in explaining phenomena, accounting for events and making predictions – Provide stimuli for students to develop, modify, and where necessary change their ideas and views – Support their attempts to re-think and reconstruct their ideas and views. Similar strategies might apply to learning about science. At the outset, teachers following such a strategy would ascertain what views about science and scientists students already hold in order to encourage students to explore them, challenge them and perhaps develop, augment or replace them. One could, of course, try to ascertain students’ views about science by giving them a questionnaire to complete. As discussed earlier, with respect to teachers’ views about science, there are several such instruments in existence, some of which provide much valuable information, others of which do not. Despite some interesting recent developments in questionnaire design, one problem remains unsolved: students do not always interpret questionnaire items in the way the designers intended or, as Lederman and O’Malley (1990) put it, “language is often used differently by students and researchers” (p. 237). The designers of VOSTS attempted to circumvent this problem by using multiple choice items derived from student writing and interviews to provide a number of different ‘position statements’ (sometimes up to 10 positions per item), including “I don’t understand” and “I don’t know enough about this subject to make a choice” (Aikenhead et al., 1987; Aikenhead & Ryan, 1992). It is the avoidance of the forced choice and the wide range of aspects covered (definitions, influence of society on science/technology, influence of science/technology on society, influence of school science on society, characteristics of scientists, social construction of scientific knowledge, social construction of technology, nature of scientific knowledge) that give the instrument such enormous research potential. Nevertheless, as Abd-El-Khalick and BouJaoude (1997) point out, VOSTS was conceived and written within a North American sociocultural context and, in consequence, may have limited validity in non-Western contexts.4 In response to concerns like these, Tsai and Liu (2005) have developed a survey instrument that is more sensitive to sociocultural influences on science and students’ views of science. Rooted in similar concerns about the socioculturally-determined dimensions of NOS understanding is the Thinking about Science instrument designed by Cobern and Loving (2002) as both a pedagogical tool (for pre-service teacher education programs) and a research tool

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for assessing views of science in relation to economics, the environment, religion, aesthetics, race and gender. Lederman and O’Malley (1990) utilized some of the design characteristics of VOSTS to develop an instrument comprising just seven fairly open-ended items (e.g. “Is there a difference between a scientific theory and a scientific law? Give an example to illustrate your answer”), to be used in conjunction with follow-up interviews. Not all students were prompted to focus their answers on the tentativeness of science, as the authors intended, and although the interview stage was able to go some way towards re-focusing attention, these findings serve to reiterate the difficulty of attempting to interpret students’ understanding from their written responses to researcher-generated questions.5 In consequence, some researchers and teachers believe that more useful information can be obtained, especially from younger students, by relying solely on open-ended methods such as the Draw-a-Scientist Test (DAST) (Chambers, 1983). In his initial study, Chambers used this test with 4807 primary (elementary) school children in Australia, Canada and the United States. He identified seven common features in their drawings, in addition to the almost universal representation of the scientist as a man: laboratory overall; spectacles (glasses); facial hair; ‘symbols of research’ (specialized instruments and equipment); ‘symbols of knowledge’ (books, filing cabinets, etc); technological products (rockets, medicines, machines); and captions such as ‘Eureka’ (with its attendant lighted bulb), E = mc2 and think bubbles saying “I’ve got it” or “A-ah! So that’s how it is”.6 In many ways, little has changed since high school students in the United States told Margaret Mead, almost fifty years ago, that a scientist is: … a man who wears a white coat and works in a laboratory. He is elderly or middle aged and wears glasses. He is small, sometimes small and stout, or tall and thin. He may be bald. He may wear a beard, may be unshaven and unkempt. He may be stooped and tired. He is surrounded by equipment: test tubes, Bunsen burners, flasks and bottles, a jungle gym of blown glass tubes and weird machines with dials. The sparkling white laboratory is full of sounds: the bubbling of liquids in test tubes and flasks, the muttering voice of the scientist… He spends his days doing experiments. He pours chemicals from one test tube into another. He peers raptly through microscopes. He scans the heavens through a telescope. He experiments with plants and animals, cutting them apart, injecting serum into animals. He writes neatly in black books. (Mead & Metraux, 1957, pp. 386 & 387) In the twenty or so years since Chambers’ original work, students’ drawings have changed very little (Ward, 1986; Fort & Varney, 1989; Symington & Spurling, 1990; Jackson, 1992; Newton & Newton, 1992, 1998; Matthews, 1996; Barman, 1999; Finson, 2002),7 with research indicating that the stereotype emerges round about grade 2 and is well-established and held by the majority of students by grade 5. Matthews (1996) claims that the stereotype is beginning to be eroded, at least in the United Kingdom, by the increased emphasis on science in the National Curriculum for primary schools, though this view is not shared by Newton and Newton (1998). Not only are these images stable across genders, they seem to be relatively 27

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stable across cultural differences (Chambers, 1983; Parsons, 1997; She, 1998; Song & Kim, 1999; Finson, 2002). There are some encouraging indications that students, and especially male students in the age range 9–12, produce drawings with fewer stereotypical features following the implementation of gender-inclusive curriculum experiences (Mason et al., 1991; Huber & Burton, 1995). It may be, however, that many researchers are seriously misled by the drawings children produce. As Newton and Newton (1998) point out, “their drawings reflect their stage of development and some attributes may have no particular significance for a child but may be given undue significance by an adult interpreting them” (p. 1138). Although very young children invariably draw scientists as bald men with smiling faces, regardless of the specific context in which the scientist is placed; it should not be assumed that children view scientists as especially likely to be bald and contented. Many children seem unable or disinclined to draw a distinction between science in the outside world and science lessons in school, such that their drawings simply reproduce caricatures of school science activities (Brandes, 1996). Perhaps somewhat older students are consciously and purposefully presenting the stereotypical or ‘comic book’ cartoon image of the scientist rather than giving insight into what they really believe. As Claxton (1990) reminds us, children compartmentalize their knowledge and so may have at least three different versions of the scientist at their disposal: the everyday comic book version, the ‘official’, approved version for use in school, their personal (and perhaps private) view. It is not always clear which version DAST is accessing, nor how seriously the ‘artists’ took the task. There is also the possibility, with students in secondary school or university, that the response is intended to make a sociopolitical point – for example, that there are too few women or members of ethnic minority groups engaged in science. One way to clarify matters is to talk to students about their drawings and the thinking behind them, ask them if they know anyone who uses science in their work (and what this entails) or present them with writing tasks based on scientists and scientific discovery.8 Even very young children will provide detailed explanations when given the opportunity to discuss their drawings and stories with the teacher (Sharkawy, 2006). Interestingly, discussion seems to take a different course when this task is set in science lessons than it does in other areas of the curriculum – perhaps because of the influence of the ‘official’ or known-to-be-approved view referred to earlier. It is also becoming increasingly clear that young children’s responses to open-ended writing tasks involving science, scientists and engineers are not stable and consistent: accounts and stories produced in science lessons are very different from those produced in the language arts (Hodson, 1993a). Interestingly, it seems that students responding to nature of science questions sometimes provide significantly different oral and written responses (Roth & Roychoudhury, 1994). Despite these caveats, there is still cause for concern about the views expressed by students. There is particular cause for concern about the kind of responses students make when they are asked to “imagine you are a scientist… write about your work, about the discoveries you have made and the things you have invented”.9 Just over 50% of students report accidental discovery or what one might call the ‘Alexander Fleming syndrome’: materials are left lying around in the laboratory 28

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and suddenly, one day, the ‘answer’ appears. There is no suggestion that significant scientific results are a consequence of a carefully planned and systematic inquiry, no suggestion of prior theorizing; instead, scientific breakthroughs just happen, by chance. In addition, science is widely perceived by students to be a solitary activity: the lone scientist labours long and hard to make discoveries of heroic stature – a view that is reinforced by questionnaire studies of students’ views about ‘doing science’ or ‘being a scientist’. Furthermore, scientists are regarded by many students as withdrawn and remote from real life, sometimes selfish and antisocial, and certainly less friendly than ‘normal’ people. Recently, one of my students asked me: “How can you tell when a scientist is an extrovert?” Answer: “He looks at your shoes when he is talking to you”. Scientists have few interests, and certainly not in music, movies or the arts in general. Most scientists don’t have a ‘normal’ family life: they may neglect their family (many don’t have a family) because of their preoccupation with work. Indeed, they often go into the laboratory on their day off. Often, they are seen as careless of their appearance, generally untidy and disorganized; sometimes they even forget to eat because of their obsession with work. This image is remarkably similar to that given by Fournier d’Albe (1923): To the general public the man of science is a man of mystery, a man of inhuman and somewhat unaccountable tastes. Not everyone goes so far as to maintain that he is a freak because he indulges in an activity “with no money in it”. But it seems to be generally agreed that the “scientist” is a being living outside ordinary human spheres, not amenable to ordinary human standards, a being who is usually harmless but may conceivably become dangerous. (cited in Stuewer, 1998, p. 25, emphasis added) Carl Sagan (1995) describes the common stereotypical image of the scientist in even less complimentary terms: “Scientists are nerds, socially inept, working on incomprehensible subjects that no normal person would find in any way interesting – even if he were willing to invest the time required, which, again, no sensible person would. ‘Get a life’, you might wish to tell them” (p. 362). And what do students believe that scientists do when they go into the lab? They do experiments; they find out about things; they find out new information and new facts; they find out how things are. Scientists do lots of “finding out” and “working things out”; they also “invent things” and “discover new stuff ”. In a study by Coleman (1998), a number of students regard an explanation as scientific if it includes information that not everyone knows or is immediately obvious, or information that has to be discovered rather than looked up in a book or found from an Internet search. For many students, it is also the case that scientists use “big words that only they can understand”. Predictably, perhaps, many students state that experiments are conducted to prove that such and such is the case – a view that is regularly reinforced by the television or newspaper advertisers’ insistence that product X is proven by experiment to do the job better than any similar product. The notion that well conducted experiments reveal the truth is very common. Interestingly, some students take the radically different view that experiments are entirely

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open-ended, a kind of “shot-in-the-dark” during which “anything can happen” – for example, “they give stuff to rats to see what happens”. Using interview methods and writing tasks, Joan Solomon and her colleagues have researched students’ understanding of the nature of theory and its relationship to experiments. Ideas about theories appear to fall into three major categories: (a) a theory is a hunch or guess about what will happen, (b) a theory is an explanation for why things happen (close to the view we might wish students to hold), (c) a theory is a fact. In these studies, students sometimes referred to “proper theories” as those theories that have been shown by tests and experiments to be true (Duveen et al., 1993; Solomon et al., 1994, 1996). Interestingly, some students in my Torontobased study took the view that theories are just guesses or speculations. Comments such as “that’s just a theory… it isn’t true” and “It’s something that you think” were widespread, in some sense reflecting the everyday expression that “it may be OK in theory but it doesn’t work in practice”. Intriguingly, some students in the Solomon et al (1994) study seemed to see experiment as a ‘last resort’ when no-one knows what to do – as in, “We’ll just have to experiment” (p. 365). Among older students in my Toronto-based study there was sometimes a distinction drawn between “science as it ought to be” (the kind of science that is described in text-books) and “science as it is”. Students were not expressing the view that scientists behave differently when self interest, commercial interests or military interests intervene (however desirable this awareness might be); rather, they were suggesting that the ideals of scientific inquiry are so demanding that they are beyond the reach of most ‘mere mortals’. Interviews with students undertaking research projects as part of their final year programme at the University of Leeds revealed that undergraduates resemble secondary school students in regarding scientific knowledge as ‘provable beyond doubt’ on the basis of experimentally acquired data (Ryder et al., 1999). In most cases, scientific inquiry was seen in terms of individual scientists seeking reliable data (usually via experiment) on which to base their conclusions. Encouragingly, their appreciation of the role of theory in directing the nature of scientific inquiry became markedly more sophisticated during the course of the project work, though they remained relatively unaware of the internal and external social dimensions of scientific practice. CURRICULUM IMAGES OF SCIENCE AND SCIENTISTS

Often, the confused and confusing views of science held by students are compounded by conventional science education. There are particularly powerful messages about science embedded in laboratory activities conducted in class. As subsequent chapters will make clear, these messages too often convey distorted or over-simplified views of the nature of scientific investigations, especially with respect to the role of theory. These “folk theories” of science, as Windschitl (2004) calls them, are also held by teachers (as a consequence of their own science education) and have substantial influence on their day-to-day curriculum decision making, thus reinforcing similar messages embedded in school science textbooks and 30

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other curriculum materials. Such messages are not restricted to comments on ‘scientific method’. More than a quarter century ago, Smolicz and Nunan (1975) identified four “ideological pivots” inherent in the image of science presented through the science curriculum. First anthropocentrism: the view of mankind as the technologically powerful manipulator and controller of nature, with science as the means by which we control the environment and shape it to meet our interests and needs.10 Second, quantification: scientists are regarded not just as observers but as measurers and quantifiers. Whatever exists in nature can (and should) be explained in mathematical terms, best of all by means of equations. Hence, Lord Kelvin’s dictum that we do not understand a thing until we can measure it. Third, positivistic faith: faith in the inevitable linear progress of science towards truth about the world, with the certainty of this knowledge being underpinned by the all-powerful scientific method. Fourth, the analytical ideal: the assumption that phenomena and events are best studied and explained via analysis; an entirely mechanistic view of the world which assumes that the whole is simply, and no more than, the sum of its parts. Two major questions spring to mind. First, are these “ideological pivots” promoted through science education? In other words, are Smolicz and Nunan (1975) correct in their analysis? Second, are these the underlying values of science? In other words, is this a faithful representation of science and, therefore, an appropriate set of values to promote? A decade later, as part of a major survey of Canadian science education conducted by the Science Council of Canada, Nadeau and Désautels (1984) identified what they called five mythical values stances suffusing science education: – Naïve realism – science gives access to truth about the universe. – Blissful empiricism – science is the meticulous, orderly and exhaustive gathering of data. – Credulous experimentation – experiments can conclusively verify hypotheses. – Excessive rationalism – science proceeds solely by logic and rational appraisal. – Blind idealism – scientists are completely disinterested, objective beings. The cumulative message is that science has an all-purpose, straightforward and reliable method of ascertaining the truth about the universe, with the certainty of scientific knowledge being located in objective observation, extensive data collection and experimental verification. Moreover, scientists are rational, logical, openminded and intellectually honest people who are required, by their commitment to the scientific enterprise, to adopt a disinterested, value-free and analytical stance. In Cawthron and Rowell’s (1978) words, the scientist is regarded by the science curriculum as “a depersonalized and idealized seeker after truth, painstakingly pushing back the curtains which obscure objective reality, and abstracting order from the flux, an order which is directly revealable to him through a distinctive scientific method” (p. 32). In quite startling contrast, Siegel (1991) states that: Contemporary research… has revealed a more accurate picture of the scientist as one who is driven by prior convictions and commitments; who is guided by group loyalties and sometimes petty personal squabbles; who is frequently quite unable to recognize evidence for what it is; and whose personal career

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motivations give the lie to the idea that the scientist yearns only or even mainly for the truth. (p. 45) A number of questions spring to mind. 1. Does the curriculum project the images identified here, and questioned by Siegel’s remarks? 2. Are these images faithful to the nature of real science and the characteristics and behaviour of real scientists engaged in ‘doing science’? In other words, do these descriptions provide an authentic view of science? 3. Do students internalize these views? 4. Does it matter what image we project or what image of science students acquire? At the time Nadeau and Désautels were writing, the answer to the first question was undoubtedly “Yes”. While much has changed in the intervening years, thanks largely to the STS thrust in curriculum debate, many school science curricula and school textbooks continue to project these images (Lakin & Wellington, 1994; Cross, 1995; Knain, 2001; Clough, 2006). Loving (1997) laments that all too often – (a) science is taught totally ignoring what it took to get to the explanations we are learning – often with lectures, reading text, and memorizing for a test. In other words, it is taught free of history, free of philosophy, and in its final form. (b) Science is taught as having one method that all scientists follow stepby-step. (c) Science is taught as if explanations are the truth – with little equivocation. (d) Laboratory experiences are designed as recipes with one right answer. Finally, (e) scientists are portrayed as somehow free from human foibles, humor, or any interests other than their work.” (p. 443) It would be a fairly simple task to locate passages in school science textbooks that continue to promote discredited views about nature of science issues. I have resisted the temptation because I regard it as much more important for readers to look carefully and critically at the science textbooks in use in their own school or recommended by the local Ministry of Education, School Board or Local Education Authority, especially in light of the discussion of issues in the following several chapters. Indeed, this is a task I set for all my graduate students at the outset of my course dealing with nature of science and science education. As an aside, it is perhaps worth mentioning that my own research shows that teachers frequently change the model of science they project through the curriculum in accordance with the particular topic being studied (in particular, its conceptual difficulty) and in relation to the perceived ability level of the students (Hodson, 1993a), sometimes in disregard of the views promoted by the textbook. My answer to question 2 (with respect to the Cawthron and Rowell image) is an unequivocal “No”, as subsequent chapters in this book will demonstrate. The question of whether Siegel’s alternative image of science is any more authentic than Cawthron and Rowell’s will be considered in chapter 7. Of course, expressing dissatisfaction with current messages about science is all very well, but teachers and curriculum developers need access to an alternative set of messages. This book will attempt to provide such alternatives. What will become apparent in subsequent dis32

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cussion is that while there is no universally accepted view of the nature of science, especially in regard to the sociocultural dimensions of the scientific endeavour, there is a measure of agreement about a number of key issues relating to the conduct of scientific inquiry and the nature of scientific observation (McComas et al., 1998). Chapters 3 to 8 explore some of the literature in the history, philosophy and sociology of science that I subsequently use in chapter 9 to underpin an alternative view of science, scientists and scientific practice suitable for the school science curriculum. Given the earlier description of students’ images of scientists and understanding of experiments, the realistic answer to question 3 is likely to be “Yes”. Although not all students will internalize all the misunderstandings of science embedded in less enlightened science curricula, there is ample evidence that many students do leave school with a confused, confusing, deficient or distorted view of the nature of science and the activities of practising scientists (Ryan, 1987; Carey et al., 1989; Larochelle & Désautels, 1991; Lederman, 1992; Duveen et al., 1993; Abell & Smith, 1994; Solomon et al., 1994, 1996; Griffiths & Barman, 1995; Driver et al., 1996; Lubben & Millar, 1996; Barman, 1997; Leach et al., 1997; Hogan & Maglienti, 2001; Moss et al., 2001). Of course, there are encouraging signs that some teachers, in some schools, are able to ensure that students develop a more authentic view of scientific practice, sometimes as a consequence of an explicit program of study in the history, philosophy and sociology of science, sometimes as a consequence of practically oriented experiences in laboratories, in the field or in zoos and museums. This leaves question 4: Does it matter what image of science is presented and assimilated? It matters insofar as it influences career choice, and so may have long term consequences for individuals. It matters if the curriculum image of science is such that it dissuades creative, non-conformist and politically conscious individuals from choosing to pursue science at an advanced level. It matters if the image of science is such that it dissuades women, members of visible minority groups and students from lower socioeconomic status homes from entering science-related careers or seeking access to higher education in science and engineering because they don’t see themselves included and represented in the science curriculum. It matters if our politicians, public servants and industrialists are so ignorant of scientific and technological issues that their decision-making is ill-informed and uncritical. It matters if the general population is unable to respond knowledgeably and critically to the claims and proposals of those in society who might use scientific arguments (and sometimes pseudoscientific or scientifically spurious arguments) to persuade, manipulate and control. It matters simply because a significant part of humankind’s cultural achievement is so poorly understood. To echo and adapt some of the discussion in chapter 1 for the desirability of scientific literacy itself, arguments for equipping students with a more authentic view of science can be made on intrinsic, utilitarian and citizenship grounds. There is ample evidence, for example, that the unfavourable image of science and scientists to which many students are exposed is one of the major reasons why many students turn away from science at an early age (Holton, 1992; Wang, 1995; Gardner, 1998). Thus, it prematurely limits the pool of talent from which future scientists are drawn, with potentially damaging effect 33

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on society’s economic and cultural well-being. Moreover, failing to provide every student with an adequate understanding of the nature of science runs counter to the demand for an educated citizenry capable of responsible and active participation in a democratic society. As I argued in chapter 1, a proper understanding of science and the scientific enterprise is just as essential as scientific knowledge (i.e., conceptual understanding) in ensuring and maintaining a socially-just democratic society. [Scientific literacy] should help students to develop the understandings and habits of mind they need to become compassionate human beings able to think for themselves and to face life head on. It should equip them also to participate thoughtfully with fellow citizens in building and protecting a society that is open, decent, and vital. (AAAS, 1989, p. xiii) REITERATING THE POLITICAL ARGUMENT FOR NOS UNDERSTANDING

Many of us have realized to our cost that a little knowledge can be dangerous thing. Those with little knowledge of science, especially with little knowledge of the nature of science, can be led to accept as dogma almost any knowledge that they don’t fully understand, led to accept way too much on faith and on trust, led to believe that science has all the answers to all of our problems. Central to this disturbing situation, of course, is uncritical acceptance of the myth of the all-powerful route to certain knowledge via the scientific method. While a lack of public understanding of science is clearly an obstacle to proper democracy, so also is an understanding of science rooted in myths and falsehoods about scientific method. The underlying values and ideological pivots described by Nadeau and Désautels (1984) and Smolicz and Nunan (1975) do not equip students with the critical skills necessary to challenge science and scientists on matters of sociopolitical, economic and environmental significance. Worryingly, through widespread acceptance of the myth of scientific method, scientists can sometimes achieve a level of acclaim that leads the public to seek their advice on matters outside the sphere of science. Nor are scientists themselves always immune to the false logic that high scientific achievement necessarily equates to wisdom on all other matters. As Bauer (1992, p. 40) remarks: “Instances are common enough in which successful scientists succumb to the temptation to see themselves as authorities not only in their own tiny field but over science as a whole and even beyond that”. Conversely, belief in the certainty of knowledge produced by the scientific method and the inevitability of successful outcomes to research can lead to unrealistic expectations of science and impatience when scientists do not immediately ‘deliver’ on society’s wants and needs. Science in textbooks, the only science that some people know, is very different from ‘real’ science, from science at the theoretical cutting edge or science at the frontier of research and development, and from science that informs (or should inform) key decision-making on matters of public interest. Quite rightly, only knowledge that has stood the test of time as worthwhile knowledge is incorporated into textbooks for the primary and secondary school levels, and because it has proved its value over many years, this knowledge is retained and reinforced. In 34

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consequence, it gives the appearance of being objective and true. While scientific knowledge in undergraduate texts, reviews and monographs is closer to ‘real’ contemporary scientific knowledge than the science in school textbooks, only the research literature reveals the true nature of scientific knowledge, with its characteristic subjectivity, inconsistency, controversy and uncertainty. This is not so much an argument for confronting students in school with the primary research literature, though I do see value in providing some guided access to some of that literature, as it is an argument for assisting students to understand the status of scientific knowledge, the ways in which it is generated, communicated and scrutinized by the community of scientists, and the extent to which it can be relied upon to inform critical decisions. A literate citizen should be able to evaluate the quality of scientific information on the basis of its source and the methods used to generate it. Scientific literacy also implies the capacity to pose and evaluate arguments based on evidence and to apply conclusions from such arguments appopriately (National Research Council, 1996, p. 22). These are the elements of scientific literacy to be addressed in the following chapters. According to Kolsto (2001), the aspects of scientific literacy essential for dealing adequately with controversial socioscientific issues are: understanding of science as a social process, recognition of the limitations of science, familiarity with the values of science and the cultivation of a critical attitude. I will argue throughout the course of this book that the last of these elements necessarily presupposes the others and constitutes the principal goal of science education. However, there are those, such as Michael F.D. Young (1976), who claim that the real goal of science education is scientific illiteracy and the cultivation of an uncritical attitude. These goals are achieved, Young argues, by making science in the early years of schooling very abstract, boring and difficult, thus ensuring that most students will fail to learn satisfactorily and will leave school afraid of science, unable to read scientific material in a critical way, and easily intimidated by those who are adept at using scientific language. Science can then be used as a tool of policy. When the language of science and technology is used in advertizing, political addresses and official communications of any kind these scientific illiterates are unable to ‘read between the lines’, to question or to oppose what is being presented to them. They have little choice but to accept the word and the decisions of ‘experts’ on seal culling, forestry clear cutting, genetically modified food, BSE, health risks from cellphone use, or any of the other 1001 issues that confront citizens in their everyday lives. They have, in effect, been disenfranchised. (They) see themselves as dependent on experts in more and more aspects of their lives… Except in the specific context of their work, and possibly in leisure pursuits such as car maintenance, our increasingly technologically dominated world remains for the majority as much a mystery as the theological mysteries of feudal times. (Young, 1976, pp. 51 & 53)

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Arguing along similar lines, Neil Postman (1992) described American society as a “technopoly” in which citizens are socialized into accepting without question any statement by a supposed scientific ‘expert’ if it is presented in a way that readers or listeners perceive to be ‘scientific’ and is claimed to derive from a research study conducted at a reputable university (no matter whether that claim is true or false). The world we live in is very nearly incomprehensible to most of us. There is almost no fact, whether actual or imagined, that will surprise us for very long, since we have no comprehensive and consistent picture of the world that would make the fact appear as an unacceptable contradiction. We believe because there is no reason not to believe. (p. 58). More recently, Bencze (2001) has argued that contemporary science education for the majority of students is, in effect, an apprenticeship for consumership – that is, it seeks to create “a large mass of relatively scientifically and technologically illiterate citizens who simultaneously serve as loyal workers and voracious, unquestioning consumers” (p. 350). There are strong echoes here of Michael Apple’s (1993) assertion that in the new economy-driven educational climate, students are no longer seen as people who will participate in the struggle to build and rebuild the social, educational, political and economic future, but as consumers: freedom is “no longer defined as participating in building the common good, but as living in an unfettered commercial market, with the education system… integrated into the mechanisms of such a market” (p. 116). In similar vein, Lee and Roth (2002) assert that in contemporary science education “both the subject matter and the method of instruction are not geared toward generating a scientifically literate populace, but rather function like a Fordian production line in a Foucauldian (disciplining) institution that forms employees of a certain class for a limited number of powerful institutions” (p. 42). Marshall (1995) uses the term “busnocratic rationality” to describe the curriculum emphasis on acquisition of skills rather than knowledge building, and on information and information retrieval rather than knowledge, understanding and wisdom, allied with the notion that it should be consumers of education (i.e., business interests and employers) rather than the clients (students) or providers (educators) who determine curriculum, define and measure quality in education, and set standards of attainment. Moreover, he argues, these standards are set in such a way that they ensure a largely uneducated, uncritical and undemanding workforce to fill society’s low-paid jobs, with any shortfall being filled by immigration (see also Larner (2000) and Stromquist & Monkman (2000)). Apple (2001a) sees a powerful alliance among enthusiasts for the neo-liberal marketization of education, neo-conservatives who want “a return to higher standards and a ‘common culture’, authoritarian populist religious fundamentalists deeply worried about secularity and the preservation of their own traditions, and particular factions of the professionally oriented new middle class who are committed to the ideology and techniques of accountability, measurement and ‘management’” (p. 103). Carter (2005) argues along similar lines: Neoliberalism ‘marketizes’ everything, even notions of subjectivity, desire, success, democracy, and citizenship, in economic terms at the same time neo36

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conservatism works to preserve traditional forms of privilege and marginalize authentic democratic and social justice agendas. More sinister still is the success with which both ideologies have colonized the rhetoric so at the very time reforms appear to be more just and equitable, they actually work in opaque ways against those they purport to help… Neoliberal and neoconservative forces work in tandem to marketize and reform and, as reform proceeds, to (re)distribute power back to traditional elites, effectively rejecting recent progressive liberal moves to increase equality and social redress… Democracy [has been] redefined] as largely synonymous with capitalism, so that consumption becomes the new form of democratic participation, and equity becomes isomorphic with increased choice. (p. 571) In the so-called ‘knowledge economy’, businesses need only a relatively small number of people who are knowledge creators and managers, whom Apple (2001b) calls “symbolic analyzers” (those who can analyze and manipulate words, numbers, visual representations and other symbols) and a much larger number of less skilled and less knowledgeable workers who can and will follow instructions (Gee et al., 1996; Lankshear, 2000; Bencze & Alsop, 2007). Thus school science education functions to select and educate the “relatively small group of students who may work as engineers and scientists to help companies develop and manage mechanisms of production (and consumption) of goods and services… (and) large groups of citizens who may function best as compliant workers and as enthusiastic purchasers of products and services of business and industry” (Bencze, 2004, p. 193). For the majority, emphasis is not on the development of critical thinking but on the mastery of a given body of knowledge. Assessment and evaluation are seen as a means of monitoring the system to determine its efficiency. The result is an education that focuses on that which is easily and reliably assessed. As Noble (1998) comments, business benefits from “a school system that will utilize sophisticated performance measures and standards to sort students and to provide a relatively reliable supply of… adaptable, flexible, loyal, mindful, expendable, ‘trainable’ workers” (p. 281). Hence the rush in many countries around the world to establish ‘standards of performance’ monitored by an imposed regime of systematic and regular assessment via standardized tests. Education authorities insist that students, classes, schools and whole education systems show quantifiable results, with testing regimes monitoring outcomes and positioning everyone so that improvements can be claimed by the authorities and shortfalls or deficiencies blamed on teachers (Carter, 2005). Apple (1999, 2000, 2001a) argues that these educational standards embody both neoliberal concerns for increased accountability, surveillance and regulation and neoconservative desires for a return to ‘real learning’ and ‘real knowledge’. In this kind of technocratic approach to education, efficiency, marketability and accountability are regarded as the ultimate virtues. While not everyone would subscribe to the view that there is an intention to ensure that the vast majority of the population remains scientifically illiterate as a means to control, manipulate and oppress them, many would recognize that this is the outcome of much contemporary science education. Scientific illiteracy is, for many students, the consequence of what and how we teach science and technology 37

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in school, and makes possible the mass manipulation of scientifically illiterate people via the popular media. Citizens who do not understand how scientific research is done and how scientific research is scrutinized for validity and reliability, have little option but to accept the recommendations of those they perceive to be experts, or are persuaded to accept as such. Hence my argument is that it does matter what we teach students about science. It does matter that we teach them to understand the nature of science and the scientific enterprise at a critical level. It does matter that ordinary citizens have the capacity to read scientific text in journals such as Scientific American, New Scientist, Discovery and Science Digest with understanding, and can make sense of scientific arguments wherever and whenever they encounter them. It does matter that citizens have some understanding of the ontological status of scientific knowledge and the ways in which scientific knowledge is generated and validated by the community of practitioners. It does matter that they have some sense of the historical development and cultural context of science. Above all, it matters that future citizens are able to judge the validity of a knowledge claim independently of other people, that they can tell the difference between good science and bad science, and between science and non-science, and can recognize fraudulent science and unwarranted claims when they encounter them. It matters for social reasons; it matters for political reasons; it matters for economic reasons; it matters, perhaps most of all, for environmental reasons. The planet can no longer accommodate a scientifically and technologically illiterate, uncritical, yet technologically powerful species. In the words of Carl Sagan (1995): The consequences of scientific illiteracy are far more dangerous in our time than in any that has come before. It’s perilous and foolhardy for the average citizen to remain ignorant about global warming, say, or ozone depletion, air pollution, toxic and radioactive wastes, acid rain, topsoil erosion, tropical deforestation, exponential population growth. (p. 6) Beyer (1998) paints a particularly bleak picture of contemporary society when he says that we live “in a democratic-capitalist social order in which commodity fetishism, the rule of the market, patriarchy, and White Supremacy constrain, distort, and oppress the expression of many individuals’ humanity and their ability to act democratically” (p. 260). Dobbin (1998) is equally dark in his vision: “Thousands of years of human development and progress are reduced to the pursuit of ‘efficiency’, our collective will is declared meaningless compared to the values of the marketplace, and communitarian values are rejected in favour of the survival of the fittest. A thinly disguised barbarism now passes for, is in fact promoted as, a global human objective” (p. 1). I don’t believe that the world is quite so grim as these authors contend, though I admit that there is no more room for complacency on the sociopolitical front than on the environmental front. It is perhaps an opportune time, then, lest this nightmare vision comes to pass, to restate the argument for enhanced scientific literacy (that is both universal and critical) in terms of the politicization of students, thus equipping them to resist technological determinism and the culture of consumerism and compliance, to fight for social justice, and to conduct their lives in an environmentally responsible way. 38

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To say that we are living in an era of rapid and far-reaching change, the outcomes of which are beyond prediction, is not to say anything new or particularly startling. But it is something to which educators, and especially science educators, need to respond. These major social, economic and political changes, many occurring on a global scale, are coincident with equally profound changes in the generation, organization and transmission of knowledge and information. Previous barriers of time and space have been largely overcome. This instant interconnectivity has intensified all aspects of human life, requiring that we respond to changes and proposals for change within a very short period of time. Moreover, we live in an era that generates increasing numbers of moral-ethical dilemmas but offers fewer moral certainties. My argument thus far is that universal critical scientific literacy, interpreted in this book in terms of learning about science, is one of the educational imperatives in helping students to cope with life in this constantly changing and uncertain world. It is a way of diverting us from the nightmare world of widespread scientific illiteracy that Carl Sagan (1995) so gloomily speculated on in his book The Demon-Haunted World. I have a foreboding of… when awesome technological powers are in the hands of the very few, and no one representing the public interest can even grasp the issues; when the people have lost the ability to set their own agendas or knowledgeably question those in authority; when, clutching our crystals and nervously consulting our horoscopes, our critical faculties in decline, unable to distinguish between what feels good and what’s true, we slide, almost without noticing, back into superstition and darkness. (p. 25) The curriculum I have in mind is aimed at far-reaching social change through critical consideration of socioscientific issues (Hodson, 2003). In a number of respects, it overlaps with futures studies (Lloyd & Wallace, 2004) – particularly in respect of the guiding principles of futures education set out by Cornish (1977, p. 223): – The future is not fixed, but consists of a variety of alternatives among which we can choose. – Choice is necessary. Refusing to choose is itself a choice. – Small changes through time can become major changes. – The future world is likely to be different in many respects from the present world. – People are responsible for their future; the future doesn’t just happen to them. – Methods successful in the past may not necessarily work in the future, due to changed circumstances. As a first step in building a future-oriented curriculum, it is necessary to consider the extensive literature in the philosophy of science, the sociology of science and the history of science, from which an appropriate selection of key issues can be identified.

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ENDNOTES 1

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To intervene effectively, of course, teachers need to be aware of these ‘popular images’ of science. Sadly, constraints on space preclude a detailed consideration of key aspects of the ‘popular images’ of science and scientists here. Dunwoody (1993), Gough (1993), Wellington (1993), McSharry & Jones (2002), Dimopoulos & Koulaidis (2003) and Shibley (2003) provide a useful starting point for this exploration. There may be some value in readers who are so inclined completing this profile now and then doing so again after reading through this book. This is the kind of exercise I encourage my graduate students to undertake. It is interesting that some students change their views substantially in response to the history and philosophy of science issues we discuss, while others are confirmed in the views they held at the outset. This is not the appropriate place to discuss the nature of constructivist pedagogy, its strengths and weaknesses as an approach to successful learning, or its problematic epistemology. There is already an extensive literature dealing with these matters (see, for example, Faire & Cosgrove, 1988; Saunders, 1992; Appleton, 1993; Bell, 1993; Matthews, 1993, 1997, 1998a; Driver et al., 1994; Fensham et al., 1994; Solomon, 1994; Phillips, 1995; Osborne, 1996; Nola, 1997; Tyson et al., 1997; Hewson et al., 1998; Turner & Sullenger, 1999; Jenkins, 2000; Tobin, 2000; Gil-Perez et al., 2002). My own views are elaborated in Hodson (1998a) and Hodson and Hodson (1998a,b). VOSTS does appear to be robust enough to function reliably in a British context (Botton & Brown, 1998). This instrument has subsequently been modified to produce the Views of Nature of Science questionnaire (Lederman et al., 2002), and further modified by Lederman and his co-workers (Lederman, 2007) and by Wong et al. (2008a,b). Interestingly, Chambers found that scientists themselves also tend to draw these stereotyped pictures. Finson et al. (1995) have developed a checklist for identifying and quantifying the components of students’ drawings for more efficient data analysis. Miller (1992, 1993) advocates the following approach: “Please tell me, in your own words, what does it mean to study something scientifically?” The views of science and scientists presented here were collected from students aged 11-17 in a number of schools in the greater Toronto area over the 5-year period 1999 to 2004. I am consciously using mankind rather than humankind to lend increased force to Smolicz and Nunan’s proposition. They used the term man, but at a time when authors were less sensitive to gendered language. Of particular interest in this ‘nature in the service of man’ view is that we have the right to control and manipulate the natural environment.

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THE TRADITIONAL VIEW OF SCIENCE Recognizing the Myths

I stated in chapter 2 that school science education continues to promote and perpetuate some grossly distorted views of science and scientists, many of which are neatly encapsulated in Siegel’s (1991) description of the traditional image of science: Science has traditionally been seen as the apex of rationality. The scientist, as the traditional image has it, is the dispassionate seeker of the truth – the person in the lab coat, untroubled by passion or emotion, unbiassed by prior conviction, guided only by reason, patiently observing, experimenting, following the evidence wherever it leads. In this image, the scientist believes and acts entirely on the basis of evidence and reason. What better personification of rationality could there be? (p. 9) This chapter deals with three of the more persistent myths and falsehoods promoted through the science curriculum: – Observation provides a secure base of facts from which knowledge can be derived. – Science starts with observation. – Science proceeds by induction – from single observations (or a series of them) to generalizations, laws and theories, which can be confirmed through further observations. MYTH 1: OBSERVATION PROVIDES DIRECT AND RELIABLE ACCESS TO SECURE KNOWLEDGE OF THE WORLD

A significant part of the model of science projected by many school science curricula is the assertion that the validity and reliability of observations are independent of the opinions and expectations of the observer, and can be confirmed by direct use of the senses by other observers. In other words, there is an assumption that when we observe a phenomenon or event we all see the same thing. This assumption that human observers have direct access to the properties of the external world implies that nothing enters the mind except by way of the senses and that the mind is a tabula rasa on which our senses inscribe a true and faithful record of the world. This is quite simply not true, as Virginia Woolf so eloquently describes in her 1925 essay on Modern Fiction. Examine for a moment an ordinary mind on an ordinary day. The mind receives a myriad impressions – trivial, fantastic, evanescent, or engraved with the sharpness of steel. From all sides they come, an incessant shower of innumerable atoms; and as they fall, as they shape themselves into the life of Monday or Tuesday, the accent falls differently from of old. (Woolf, 1925, p. 149) 41

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We see things differently because we are now different, as a consequence of our experiences. Our minds are not blank slates. Rather, we interpret the sense data that enters our consciousness in terms of previous experiences (and the sense we made and continue to make of them), prior knowledge, beliefs and expectations. As Friedrich Nietzsche (1906/1968) said, “Everything of which we become conscious is arranged, simplified, schematized, interpreted through and through” (para. 477, p. 463). Immanuel Kant (1929) expresses it as follows: “Our empirical knowledge is a compound of that which we receive through impressions, and that which the faculty of knowledge supplies… Experience itself is a mode of knowledge which involves understanding” (pp. 22 & 16). In attaching meaning to visual stimuli, or any other kind of stimulus, there are two significant influences: first, our ability to discriminate – that is, our capacity to attach meaning; second, our past experiences and, therefore, our expectations of what we will see – that is, the meaning we are able to attach. Discrimination refers to our capacity to detect differences between and among stimuli. For example, we can perceive a shape either as a background or as a figure, though it is sometimes difficult, in the absence of other stimuli, for our brains to ‘decide’ which is which. In Figure 3.1a, for example, we may see a white vase on a black field or two black faces, almost nose to nose, on a white field; in Figure 3.1b we may see black cats or white cats, and sometimes both together. To an extent we can ‘choose’ what we see; we can make the picture flip from one version to the other, almost at will.

Figure 3.1a. White vase or blacks faces in profile? 42

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Figure 3.1b. Black cats or white cats?

Figure 3.2 is somewhat more interesting and illustrates quite neatly how prior knowledge (or its absence) influences perception. About eighteen years ago, when this symbol began to appear in the popular press as advance publicity for an upcoming movie, many adults wondered why newspapers were reproducing pictures of someone’s tonsils. They had attached a particular meaning to the symbol. After seeing the movie or simply becoming aware of all the surrounding publicity and

Figure 3.2. Batman logo 43

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merchandising most people easily recognized the Batman logo. They now had a different meaning to attach.1 Those with previous experience of seeing 3-dimensional objects represented by 2-dimensional diagrams (as in science textbooks, for example) will readily interpret Figure 3.3a as a cube, but what, one wonders, would those unfamiliar with the convention make of this drawing? What is particularly intriguing is that we can see the cube with either the bottom left square or the top right square as the front of the cube. According to Gillies (1993), this effect was first noticed by the Swiss crystallographer, L.A. Necker, as he attempted to draw a crystal he was observing through a microscope. Exactly the same factors impact on our response to Figure 3.3b. Those unfamiliar with 2-dimensional line drawings and with flights of steps would almost certainly interpret this diagram in other ways. Again, it is possible to see this flight of steps from ‘on top’ or ‘from underneath’.2 Similarly, we can see Figure 3.3c as a rabbit’s head facing left or a duck’s head facing right. For all three figures, most people find one way of seeing the picture easier than the other, though they can (with an effort) make the picture ‘flip’ from one to the other. In other words, we can learn to see things differently when we know that alternatives are possible.

Figure 3.3a. Which face is the front of the cube?

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Figure 3.3b. Steps can be seen from ‘on tope’ or ‘from underneath’

Figure 3.3c. Rabbit or duck?

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Whether one sees an old woman or a young woman in Figure 3.4 also depends on something other than the image falling on the retina. Significantly, it has been found that the likelihood of a particular response (old woman or young woman) can be increased by prior presentation of unambiguous pictures of old or young women (Leeper, 1935). Clearly, pre-existing mental constructs cause us to see things in a particular way. As Barlex and Carre (1985) put it: “We don’t see things as they are, we see things as we are” (p. 4).

Figure 3.4. Old woman or young woman? 46

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Conversely, there are occasions when we do not see what we expect to see and cannot exert conscious control on our perception. Even when we measure the lines in the Muller-Lyer illusion (Figure 3.5) to convince ourselves that they are of equal length, we still perceive the lower line to be longer. In this situation, what we see is clearly not influenced by what we know. Try as we will, our knowledge, and therefore our expectations, cannot determine our perception.

Figure 3.5. Muller-Lyer illusion

Optical illusions created when incoming sense data are incompatible with existing mental constructs can be a source of amusement, as in Figures 3.6a and 3.6b. They can also be very irritating and sometimes very disconcerting because they violate our pre-existing understanding about how things are constructed. An Ames room, where people appear to change size as they walk across the room, is particularly puzzling. We know that this is not happening but our expectations about the structure of a room override our interpretation of what we see. Figure 3.7 is a variant of the Ames room illusion that illustrates the effect quite well. We expect Figure 3.8a and Figure 3.8b to represent real three-dimensional objects, and when that expectation is not met we try to rationalize it, and again we fail. Our emotional response to this continued frustration may be very illuminating about our character and may provide interesting potential for a research project. In some extreme cases, human brains can reject sense perceptions on the grounds of logic and prior experience. Experiments have shown that when someone is fitted with a pair of spectacles having lenses that invert everything, they will initially be quite unable to make sense of what they see, and will find it almost impossible to move around in a safe and predictable way. However, after a while, the brain adapts and they see everything the right way up again. Subsequently, when the spectacles are removed, the world once more appears inverted, leading to a further period of readjustment (see Gregory, 1977). What I am arguing here is that observation is not reliable. It is not always indicative of the true state of affairs, as in these optical illusions. This creates a problem for scientists: how can they know when to rely on what they see? Furthermore, a change in mental construct (existing knowledge) will often bring about a change in perception. Thus, once you have seen the faces hidden in the foliage in the puzzle pictures often found in children’s comics, you can no longer see the trees without seeing the faces. It is not the image falling on the retina that has changed, but the observer. The observer now has a different perspective, a different view of the world. For years, I was unable to see the face hidden in the snowy landscape of Figure 3.9. For me, it remained simply a series of blotches, despite the 47

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insistence of a colleague that it reveals the face of Jesus of Nazareth. Then, a few years ago, confronted by a giant reproduction of the picture at the Ontario Science Centre and urged by my wife to squint, stare hard and think of that familiar picture of Che Guevara, I finally saw the face. Now I cannot look at the picture without seeing the face. My world is forever changed! What was needed in order for me to see the face was a suitable frame of reference. For some, this frame of reference is a Christian one; for others, including myself, it is an interest in sociopolitical revolution. Perhaps there is scope for another research project here.

Figure 3.6a. Are the horizontal lines parallel?

Figure 3.6b. Which vase is wider? 48

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Figure 3.7. All three pillars are of equal height

Readers who wish to experience this kind of “perceptual revelation” for themselves should spend some time trying to discern what is hidden in Figure 3.10. If success is not achieved within 10 minutes or so, and frustration levels are becoming unbearable, the ‘answer’ can be found at the end of the chapter.3 Looking at the picture when given this information makes all the difference.

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Figure 3.8a. Impossible figure 1

Figure 3.8b. Impossible figure 2 50

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Figure 3.9. Find the hidden man

Figure 3.10. What is hidden in this drawing? 51

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These simple examples are illustrative of the way in which scientific observers have to learn how to interpret what they see through a microscope or a telescope, observe on an oscilloscope screen or in a cloud chamber, or obtain via any of the modern instrumental devices used by scientists. Michael Polanyi (1958) makes this point superbly in his graphic description of a medical student struggling to make sense of X-ray photographs. He watches in a darkened room shadowy traces on a fluorescent screen placed against a patient’s chest, and hears the radiologist commenting to his assistants, in technical language, on the significant features of these shadows. At first the student is completely puzzled. For he can see in the X-ray picture of a chest only the shadows of the heart and the ribs, with a few spidery blotches between them. The experts seem to be romancing about figments of their imagination; he can see nothing that they are talking about. Then, as he goes on listening for a few weeks, looking carefully at ever new pictures of different cases, a tentative understanding will dawn on him; he will gradually forget about the ribs and begin to see the lungs. And eventually, if he perseveres intelligently, a rich panorama of significant details will be revealed to him: of physiological variations and pathological changes, of scars, of chronic infections and signs of acute disease. He has entered a new world. He still sees only a fraction of what the experts can see, but the pictures are definitely making sense now and so do most of the comments made on them. (p. 101) Of course, the X-ray pictures have not changed at all. What has changed is the observer (the medical student) and the observer’s ability to interpret observations using theoretical knowledge. It is knowledge (concepts and theories) that enable us to make meaningful, significant, scientific observations. As N.R. Hanson (1958) puts it: “there is more to seeing than meets the eyeball”. He goes on to ask: Would Sir Lawrence Bragg and an Eskimo baby see the same thing when looking at an X-ray tube? Yes and no. Yes – they are visually aware of the same object. No – the ways in which they are visually aware are profoundly different. Seeing is not only the having of a visual experience; it is also the way in which visual experience is had. (p. 15) It follows that unless teachers provide extensive guidance, there can be no guarantee that students in school science lessons will observe even the readily observable. For example, Stevens (1978) describes how students lacking the necessary theoretical background will fail to make even the simple observation that evaporation of distilled water and tap water on separate microscope slides produce different results. This seems a simple enough observation to make, but in practice few children succeed, and they only notice then after considerable prompting from the teacher. The reason is not difficult to appreciate. The difference between a clean and ‘dirty’ slide is of no interest whatever – and will therefore not be noticed – unless the pupil already has the idea that water is a solvent, and may contain dissolved substances. (p. 104) 52

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The key to scientific observation, as distinct from simple everyday ‘looking at things’, is a sound theoretical frame of reference. As Peter Medawar (1967) says, what a child sees “conveys no information until he knows beforehand the kind of thing he is expected to see” (p. 133). Thus, it is the science teacher’s job to ensure that students perceive the world in the appropriate way – that is, the way in which currently accepted science (or the school version of it) deems appropriate. MYTH 2: SCIENCE STARTS WITH OBSERVATION

The inductive process outlined in the traditional view of scientific method, and represented diagrammatically in Figure 3.11, requires the assembly of all relevant observations and information, from which a generalization will eventually emerge through application of logical analysis. How, one might ask, does an innocent and unbiased observer know what is relevant and, therefore, what to observe? The inductive method offers no guidance on the restriction of observations to anything less than the whole universe. As Medawar (1969) reminds us, “We cannot browse over the field of nature like cows at pasture” (p. 29). Observation, especially scientific observation, is a selective process and so requires a focus of attention and a purpose. An observer needs an incentive to make one observation, rather than another. Induction does not provide that incentive.

Figure 3.11. Science as induction

Making a scientific observation presupposes a view of the world that suggests particular observations can be made and are worth making – i.e., they are of scientific significance. In other words, scientific observation is neither innocent nor unbiased. It is not ‘objective’ in the sense that school science curricula imply. Rather, it is purposeful, theory-dependent and theory-driven. In practice, some view of the world (some theoretical perspective) precedes observation and guides it. It is simply 53

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not possible to observe things for which you are conceptually unprepared – a position admirably summed up by David Theobald (1968): “If we confront the world with an empty head, then our experience will be deservedly meaningless. Experience does not give concepts meaning, if anything concepts give experience meaning” (p. 26). Heisenberg (1971) makes the point that theory and theoretical speculation create the possibility of new observations that lead to scientific advances: “On principle, it is quite wrong to try founding a theory on observable magnitudes alone. In reality the very opposite happens. It is the theory which decides what we can observe” (p. 63). As Hanson (1958) points out, until Paul Dirac postulated the existence of positrons, the tracks they leave in cloud chambers were not seen at all or were dismissed as mere experimental noise. When armed with the new knowledge Dirac gave them, physicists found clear evidence in those same cloud chamber experiments of the existence of positrons. Likewise, sunspots went unrecorded in Europe until Galileo’s work overthrew belief in the perfection of the heavens, whereas Chinese astronomers (with no such over-riding beliefs) had been recording them for centuries. It seems to follow that there cannot be a piece of absolutely indisputable observational knowledge whose meaning is not impregnated in some way by prior belief about the world. Bauer (1992) expresses this conclusion as follows: A mountain is, variously and for different people, an illustration of plate tectonics, or a demonstration of God’s handiwork, or an example of the incomprehensibility of the world, or the abode of certain spirits, or something else again; and each of these possible connotations determines how we see a mountain – as old or young or eternal, as generic or idiosyncratic, and so on. Whatever the characteristic involved, to each of us the mountain is something different; even though we all agree that it is a fact, it is not quite the same fact for each of us. (p. 65, emphasis in original) Arguing along similar lines, Bohm and Peat (1987) suggest that, in respect of making observations, it might make more sense to regard scientists as being “somewhat like artists who produce quite different paintings of the same sitter… Some interpretations may show creative originality while others may be mediocre. Yet none give the final ‘truth’ about the subject” (p. 102). For the purposes of this chapter, it is sufficient to conclude that our sensory perception of the world is profoundly affected by the beliefs we hold and the theories to which we subscribe. When we change our theories, we open up new ways of seeing and explaining the world. While it would be tempting to believe that the use of scientific instruments will simultaneously extend our capacity to observe and reduce the subjectivity of our observations, it should be remembered that theoretical assumptions underpin the design and construction of all scientific instruments. In short, there seems to be no easy escape from our theoretical preconceptions. It is the technical language of science, to which Polanyi refers in the quotation given earlier, that conveys the meaning with which we invest our observations. All observation statements employ theoretical language. Even an apparently simple factual statement such as “Anhydrous copper sulphate has a solubility of 205 54

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grams per litre at 20C” only makes sense in the light of a pre-existing theoretical framework involving concepts such as dissolving, temperature, hydration, volume and so on. Moreover, the quality and usefulness of observation statements depend crucially on the level of sophistication of the theoretical language available to the observer. Without such a language, perceptions cannot be given meaning and observations cannot be recorded and subjected to critical scrutiny.4 What is described in scientific observations is never ‘pure phenomena’ (whatever that might mean), but phenomena seen through particular ‘theoretical eyes’. Theoretical knowledge opens up possibilities that otherwise would not exist and, as a science develops and builds new theoretical knowledge, scientists are able to generate knowledge by making different observations.5 Thus, we learn about nature and we also learn how to learn about it, by learning (i) what constitutes significant information, (ii) how to collect it, and (iii) how to interpret it and communicate it to others. Smart (1968) provides the following illustrative example. A scientifically untutored peasant could certainly make a report that a black needle-like thing pointed to the figure ‘35’ on a round clock-like thing. He could not report that the current through a milliammeter was thirty-five milliamperes, since he would not have the concept of an electric current, and still less would he have the concept of an ampere. (p. 80) To summarize, scientists work within a theoretical framework that guides their actions and invests observational data with particular meaning. In a sense, theory is both a boon and a curse: it opens up new possibilities for observation and experiment but it also constrains thought and possibilities. By accepting its premises, one accepts its particular way of looking at the world, making it difficult to make theoretical progress. Conversely, being ‘open-minded’ sounds fine, and is extolled as a virtue in school science because it seems to ensure that observations are unprejudiced by prior expectations. But if we are too ‘open-minded’ we may miss what a particular theoretical stance would tell us. Open-minded can easily become ‘nominded’, leaving us with no theory with which to make sense of the world. Because observation is theory-impregnated, it follows that observations have to be checked for acceptability by recourse to theory. In Arthur Eddington’s words, “It is also a good rule not to put overmuch confidence in the observational results that are put forward until they have been confirmed by theory” (cited by Stent, 1969, p. 31). This is the reverse of what science teachers usually tell students. The usual message is that we have to test our theories for acceptability against reliable observations – i.e., against ‘the facts’. In practice, scientists, and students in school science lessons, often have to reject sense data on theoretical grounds: a stick partially immersed in water is not bent, nor does Mars travel backwards in its orbit from time to time, whatever appearances might suggest. Theory tells us when observations are mistaken and should be rejected. The objects seen through the magnifying glass appear circled by colours of the rainbow; is it not the theory of dispersion which teaches us to regard these colours as created by the instrument, and to disregard them when we describe the object observed? And how much more important this remark is when it is 55

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no longer a matter of a simple magnifying glass but of a powerful microscope! (Duhem, 1962, p. 154) The theory dependence of observations may, on occasions, lead scientists to make false and misleading observations simply because the theoretical position they have adopted is incorrect. As Beveridge (1961) remarked, more than forty years ago, “Not only do observers frequently miss seemingly obvious things, but what is even more important, they often invent quite false observations” (p. 98). This ‘invention’ is not an attempt to perpetrate a deliberate falsehood, merely a consequence of a mistaken theoretical perspective. It is a phenomenon well known in school science lessons, where students will often see what they expect to see and miss that which they do not anticipate. When students have a different theoretical framework from that assumed by the teacher in the design of a laboratory activity they may look in a different place (the ‘wrong’ place), in a different way (the ‘wrong’ way) and make different interpretations (incorrect ones), sometimes even vehemently denying observational evidence that conflicts with their expectations. Just as frequently, they may adjust or modify their observations to conform with the expectations their existing theoretical framework gives rise to – just like the scientists described by Beveridge. In consequence, students may go through the entire lesson misunderstanding the purpose of the activity, the procedure and the findings, and further compounding the misconceptions they brought to the lesson. As Hodson (1998a) comments, “It is not too much of an exaggeration to say that, because predictions, perceptions and explanations are all strongly influenced by prior conceptual understanding, students who hold different frameworks of meaning conduct different investigations, with correspondingly different learning outcomes” (p. 28). The alternative conceptions literature contains many such examples and, thereby, constitutes a major argument in favour of a constructivist pedagogy that takes account of these different starting points. Recognizing that scientific observation is theory-laden and that students may sometimes have a different framework of reference from the teacher has another important consequence for science teachers: that the skills of scientific observation have to be taught and, moreover, taught and learned within particular theoretical contexts. It is just not possible to teach someone to observe in a way that is independent of the context in which the observation is to be made. In science lessons, we are not teaching students to observe per se. They can already do that; they have been making observations for many years, since long before they came to science classes. Our responsibility is to teach them to make scientific observations, and for that they need appropriate conceptual understanding.6 OBSERVATION AND INFERENCE

Before leaving this discussion of the relationship between observation and theory, there is one more matter that is worthy of discussion. In common with many other advocates of the traditional model of science, Zeitler and Barufaldi (1988) state that “observations are perceptual, while inferences are interpretive” (p. 97) and

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Abruscato (1988) asserts that “nothing is more fundamental to clear thinking than the ability to distinguish between an observation and an inference” (p. 33). Superficially, this distinction sounds fine and seems to accord with what we consider to be good practice in scientific inquiry: having respect for the evidence and not claiming more than the data can justify. However, closer examination in the light of earlier discussion about the theory-laden nature of scientific observation suggests that the supposed demarcation is not always as clear as Abruscato and others might claim. When a new theory appears, or when new scientific instruments are developed, our notion of what counts as an observation and what counts as an inference may change. As Feyerabend (1962) points out, observation statements are merely those statements about phenomena and events to which we can assent quickly, relatively reliably and without calculation or inference, because we all accept, without question, the theories on which they are based. Thus, where individuals draw the line between observation and inference reflects the sophistication of their scientific knowledge, their confidence in that knowledge, and their experience and familiarity with the phenomena or events being studied. When theories are not in dispute, when they are well understood and taken-for-granted, the theoretical language is the observation language, and we use theoretical terms in making and reporting observations. Terms like reflection and refraction, solution and suspension, conduction and non-conduction, all of which are used regularly in school science as observation terms, carry a substantial inferential component rooted in theoretical understanding. The key point is that unless some theories are taken for granted (and deemed to be no longer in dispute) and theory-loaded terms used for making observations we can never make progress. We would forever be trying to retreat to the ‘raw data’, to some position that we could regard as theory-free. Hanson (1972) refers to terms that “carry a conceptual pattern with them” (theoretical) and terms that are “less rich in theory, and hence less able to serve in explanations of causes” (p. 60). As an example of the former category he cites the word crater, which he says carries with it a cargo of astronomical theory that words like concavity and hole do not. [The moon] is pitted with holes and discontinuities; but to say of these that these are craters – to say that the lunar surface is craterous – is to infuse theoretical astronomy into one’s observations… To speak of a concavity as a crater is to commit oneself as to its origin, to say that its creation was quick, violent, explosive. (p. 56) He goes on to argue that theoretical terms may be employed to organize diffuse and seemingly unrelated aspects of a situation into a coherent, intelligible pattern, whereas ‘phenomenal’ terms cannot be so employed. However, Hanson later weakens this distinction by admitting that terms may be organizers in one situation and phenomenal in another. In other words, there is no sharp distinction: “It is not that certain words are absolutely theory-loaded, whilst others are absolutely sensedatum words. Which are the data-words and which are the theory-words is a contextual question” (Hanson, 1958, p. 59).

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Perhaps no-one would quibble with Gilbert Ryle’s (1956) comment that theoretical terms are such that knowing their meaning and using them appropriately necessitates a grasp of some theory. The special terms of a science are more or less heavy with the burthen of the theory of that science. The technical terms of genetics are theory-laden, laden, that is, not just with theoretical luggage of some sort or other but with the luggage of genetic theory. (p. 90) Non-theoretical terms, presumably, carry none of this “luggage of theory”. While this distinction sounds reasonable, it fails to account for the fact that many scientific concepts appear in more than one theory. In some cases a term can only be understood with respect to a particular theory; in other cases, the term is simply being ‘used’ by a theory and has its meaning anchored elsewhere - in some other theory. With respect to theory T1 a term may be ‘theory-laden’, whilst with respect to another (T2) it may be ‘theory-free’, but all terms are anchored in some theory, even if it is only the ‘theory’ of everyday commonsense. As Popper (1959) declares: Every description uses universal names (or symbols or ideas); every statement has the character of a theory, of a hypothesis. The statement, ‘here is a glass of water’ cannot be verified by observational experience. The reason is that the universals which appear in it cannot be correlated with any particular sense-experience… By the word ‘glass’, for example, we denote physical bodies which exhibit a certain law-like behaviour, and the same holds of the word ‘water’. Universals cannot be reduced to classes of experiences. (p. 94) When a new theory appears our notion of what is a theoretical term and what is an observation term may change: “Introducing a new theory involves changes of outlook both with respect to the observable and with respect to the unobservable features of the world, and corresponding changes in the meanings of even the most ‘fundamental’ terms of the language employed” (Feyerabend, 1962, p. 29). Only when we have good reason to doubt the theoretical grounding of a particular observational language do we retreat to relatively theory-free terms like ‘thin lines’ to describe the features of cloud chamber photographs; when we are confident, we use the much more powerful, theory-loaded terms such ‘track of an electron’. We approach a problem-situation with the strongest justified description, and only withdraw to less commital, more neutral ones when specific reason for doubt arises – and even then, we withdraw only as far as necessary with respect to the available reasonable alternatives (Shapere, 1982, p. 520) There can, of course, be no scientific language sufficiently free of theoretical assumptions that no doubt can arise, but the admission that (philosophically) doubt can arise does not mean that we have to be doubtful and to assume that our theories are unreliable. While we cannot claim scientific knowledge to be certain (we could be mistaken), this does not mean that it is uncertain (i.e., unreliable and arbitrary).

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As Shapere (1982) assures us, “the mere possibility of doubt arising is not itself a reason for doubt” (p. 515). While the ways in which we make sense of the world are, in principle, open to doubt and are subject to revision and change as science progresses, the truth is that we can take action in all kinds of ways, on the basis of our theoretical understanding, with entirely predictable outcomes. Confidence in scientific knowledge is a direct consequence of science being a social process: we collectively construct our view of the world and collectively validate it (characteristics of science to be discussed in subsequent chapters). The so-called ‘facts’ of science are simply those observation statements admitted to the corpus of scientific knowledge because the theories and procedures on which they depend have achieved consensus within the scientific community. As Churchland (1979) states, scientists learn from other scientists to perceive the world as the community of scientists perceives it. The exchange and criticism of ideas that leads to this consensus view is the basis of scientific rationality and the primary reason for our confidence in scientific observations.7 The acquisition and consolidation of new conceptual understanding carries with it the possibility of making more sophisticated observations. For example, once they have a theory of solubility, students see things dissolve, where previously they saw them disappear. Moreover, once they understand that there is an important conceptual difference between dissolving and melting, students see that it is important for them to be careful in their use of the terms. Younger children, without this knowledge, will continue to refer to sugar and salt ‘melting’ in water. They have no reason to do otherwise. Students can be made aware of the ways in which their observational skills change and develop as their theoretical understanding becomes more sophisticated by repeating an observational exercise from earlier in the course, or from a previous year. The new description employs observational language that encompasses previously unknown theoretical notions. Perhaps materials in the chemistry lab can now be observed to melt, sublime or decrepitate on heating, where previously they had just ‘changed’. All three of these new terms include theoretical inference. A thoughtful discussion of the theoretical assumptions underpinning the design and construction of common laboratory instruments – beginning with something simple, like thermometers, and progressing to ammeters, voltmeters, pH meters, and the like – can assist students to the realization that the supposed distinction between objective observation and theoretical inference is less clear than some science textbooks and some science teachers would assert, and is more a characteristic of their own stage of conceptual understanding, and their confidence in that knowledge, than a clear demarcation between two processes of science.8 By investing their observational language with additional theoretical assumptions, and thereby designing and conducting more sophisticated scientific investigations and experiments, scientists can construct more elaborate theories. By repeating the cycle at increasingly sophisticated levels, scientific understanding is propelled forward. In a sense, science ‘hauls itself up by its own boot straps’. The same argument applies to those learning science. However, both scientist and science learner need to be wary of assuming too much. There are occasions when inferences should be recognized as no more than tentative. There are occasions when it is unwise to 59

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invest too much confidence in what observations seem to tell us. This is my somewhat oblique way of returning to the traditional view of science and the centrality of induction in the so-called scientific method. MYTH 3: SCIENCE PROCEEDS BY INDUCTION

In the traditional view of the scientific method, observational data can be carefully organized and subjected to rational appraisal in order to ascertain patterns and formulate generalizations. These generalizations, and the predictions to which they give rise, can then be confirmed by further observation or experiment (see Figure 3.11). Hempel (1966) asks us to consider how a scientist who subscribes to an inductivist model of science would conduct an investigation… First, all facts would be observed and recorded, without selection or a priori guess as to their relative importance. Secondly, the observed and recorded facts would be analysed, compared, and classified, without hypothesis or postulates, other than those necessarily involved in the logic of thought. Third, from this analysis of the facts, generalizations would be inductively drawn as to the relations, classificatory or causal, between them. Fourth, further research would be deductive as well as inductive, employing inferences from previously established generalizations. (p. 11) Since earlier discussion has addressed the absurdity of the notion of innocent, unbiased observation embedded in this description, attention can now be focused on the inductive process itself – in particular, on the question of the validity of inductive inferences from observable ‘facts’. Those who advocate this approach argue that a generalization (an inductive inference) can be relied on if certain conditions are met. – The number of observations is large – The observations are made under a variety of conditions – No accepted observation statement conflicts with the derived generalization. Suppose, then, that you have observed that a metal bar expands when heated. First, you should repeat the test several times to ensure consistency of outcome. Second, you should vary the conditions: iron, copper, zinc and gold bars, at high temperature ranges and at low temperature ranges, under increased pressure and under reduced pressure, and so on. If any metal does not expand on heating, under any of the conditions, the generalization “all metals expand on heating” must be discarded. However, provided that all evidence is supportive, the generalization can be accepted. Moreover, according to the model, the generalization can subsequently be used to make predictions, as follows: 1. All metals expand on heating 2. This railroad track is made of metal 3. This railroad track will expand on heating (and, therefore, there needs to be a series of expansion joints to prevent buckling of the track). This simple, straightforward and logical model of how science functions seems fine until one starts to look carefully at the conditions for making an inductive 60

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inference. The first condition requires a large number of observations. How large is ‘large’? Will five observations suffice? Do we need to make 10, 100, 1000 or 10,000 observations? It isn’t clear. The second condition requires a wide variety of conditions. Testing iron, copper and zinc bars seems reasonable enough, but what about long bars versus short bars? How about fat bars and thin bars, or red ones and yellow ones? On Mondays, Tuesdays and holidays? Again, it isn’t clear. The third condition states that there should be no conflicting observation. How does one know whether it is a genuinely conflicting observation or just a ‘bad reading’ that should be repeated? How does one know when to accept the data, when to go back and check it, and when to reject it entirely? It isn’t clear. In each case, the answer to the uncertainty is located in theoretical understanding. Theory tells us how many observations are enough, what particular variables to consider and how to distinguish good observations from bad ones. However, theory is not permitted to intrude into the collection of data (see the Hempel quotation above). Observation is supposed to be objective, value-free and unguided – a notion that has already been dismissed as absurd earlier in the chapter. So far, I have argued that inductive generalizations are not reliable because they derive from observations, which are themselves unreliable – first, because of the limited range of human perception9; second, because the nature of the observations depend crucially on who makes them, as discussed at length earlier in the chapter. Inductive inferences are also vulnerable on grounds of logic. In passing from particular observations (even if considered ‘facts’) to the generalizations that comprehend them, something is added. A generalization is not simply a re-statement of the facts (or it would be valueless), but it cannot logically contain more information than the empirical content of the statements from which it is derived, as David Hume (1854) reminds us: There can be no demonstrative arguments to prove that those instances of which we have had no experience, resemble those of which we have had experience… even after the observation of the frequent or constant conjunction of objects, we have no reason to draw any inference concerning any object beyond those of which we have had experience. (p. 390) In other words, an inductive inference is not logically valid. A generalization derived from singular statements, no matter how numerous, may still turn out to be wrong. No matter how many white swans we see, we are never justified in asserting that “all swans are white”, because the next swan we see may well turn out to be black – as any student studying Philosophy 101 will eagerly point out. Bertrand Russell (1912) makes this point rather more humorously in his tale of the inductivist turkey, who was fed each day at 9.00 am. Not wishing to jump to conclusions, the turkey ensured that he made his observations under a wide variety of conditions (days of the week, variations in weather, holidays, etc.). Eventually he was satisfied and ventured the generalization “I am always fed at 9.00 am”. Sadly, at 9.00 am the following day, which happened to be Christmas Eve, he had his throat cut. An inductive inference based on true singular statements, however numerous, may still

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turn out to be false. The best one can say is that, so far, the observational evidence has not falsified the generalization.10 If inductivism is so fatally flawed, why do so many science teachers continue to tell students that science proceeds in this way? One explanation may be that it has the attraction of being simple and seemingly straightforward. Observations can be made by anyone, simply by careful and diligent use of the senses. Inductive inferences require nothing more than logical scrutiny of the data. My observations of twelve science teachers in New Zealand secondary schools show that many teachers adopt an inductivist stance with those students they consider to be less able, simply because they believe it is “easier” for them to understand (Hodson, 1993a).11 A second possible reason for the appeal of inductivism is that there is no personal, subjective element involved: the validity of observation statements, when observations are carefully and ‘correctly’ accumulated, are independent of the opinions and expectations of the observers. Thus, the model supports the belief that scientists are objective, dispassionate and disinterested (the ‘white coat’ image of the scientist) – a position that some find attractive and some find to be politically advantageous because it invests science with a spurious authority (as discussed in chapter 2). A third argument is that it has proved successful in the past. On many occasions, inductively produced generalizations (and the laws and theories derived from them) have proved perfectly satisfactory in providing explanations and making predictions. Therefore, it is argued, induction is justified by experience. Our Philosophy 101 students should immediately disallow this argument as circular: a universal statement asserting the validity of the principle of induction has been inferred from a series of singular statements (the individual instances of previous success) – that is, by induction. By using as justification the very argument it is trying to justify, it assumes what it is trying to prove. Those advocates of the inductivist method still anxious to salvage it may well turn to probability, arguing (for example) that if a large number of metals have been observed to expand on heating, under a wide variety of conditions, then it is probably true that all metals expand on heating. However, this is not a solution to the logical inadequacy of induction. Although the claim is weaker than before, it is still subject to the same criticism; while it seems reasonable to believe that increasing observational support increases the probability that a generalization is true, probability theory tells us that it is not the case. Regardless of the number of singular observations that a scientist makes, the ratio of ‘actual observations made’ divided by ‘number of situations to which the generalization is claimed to apply’ is zero. In other words, because universal generalizations claim to apply to all possible cases the probability that the generalization is true is zero. Faced with this reality, there are three possible courses of action. We could accept Bertrand Russell’s (1961) conclusion that “every attempt to arrive at general scientific laws from particular observations is fallacious… and without this principle science is impossible” (p. 647) or, if not impossible, not able to be rationally justified. Alternatively, we could simply take the view that it is ‘obvious’ that induction works because ‘we use it all the time’. In other words, it is just common sense.12 Unfortunately, ‘obvious’ things sometimes turn out to be untrue – for 62

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example, heavy objects do not fall faster than lighter ones unless there are air resistance factors in play. Nor is common sense or majority opinion always a reliable guide to the truth. The third option, and the one to be followed in chapter 4, is to seek an alternative explanation for how science functions, an alternative view of scientific method and an alternative view of the rationality of science. It is reasonable to demand that a theory of science does two things: (i) it describes the ways in which successful episodes in science have been conducted in the past; (ii) it provides practitioners with some advice on procedures to be adopted in the future – i.e., some guidelines for practice. It has been argued in this chapter that induction fares pretty poorly on the second requirement. It is unable to provide an initial focus for study (what observations to make, and how to make them); its alleged stance of objectivity is profoundly compromised by the theory-impregnated nature of observational evidence; it is logically invalid. Turning to the first criterion, we should ask how well inductivism stands up to historical scrutiny and/or testimony from contemporary practitioners on their methods of inquiry. Is there evidence that scientists proceed inductively? Have they done so in the past, with any degree of success? There is clear evidence that science does use inductive methods from time to time, despite its dubious logical status, as some of the scientists interviewed by Wong and Hodson. (2008a) confirm. For example, by examining a large number of individuals, geneticists have determined that all Down’s Syndrome sufferers have an extra chromosome (47 instead of 46). Seemingly, no prior theorizing was involved. Geneticists also make use of probability to explain inherited characteristics such as eye colour. Isaac Newton, in his master work Philosophiae Naturalis Principia Mathematica (1687) claimed that his law of universal gravitation had been inferred from the existing data – in particular, from Kepler’s laws. The problem with Newton’s claim for inductivism is that Kepler’s laws have the planets moving in perfect ellipses around the sun, whereas Newton’s law of gravitation predicts that planetary orbits cannot be perfect ellipses. Moreover, Kepler’s laws are expressed in terms of distances, time intervals, velocities and so on, while Newton’s laws use the concepts of mass and force. Clearly, there was more involved than simple induction from the data. Science does appear to use a form of non-deductive inference that philosophers call “inference to the best explanation’ (IBE), sometimes known as abduction: Given a particular set of observable events, what is the most likely explanation? For example, one can argue for the theory of ‘continental drift’ (later developed into plate tectonics) on the grounds that it provides a more plausible explanation than its competitors for common geological features in widely separated regions of the planet and the seeming overall correlations in the shapes of the major continents. Similarly, Darwinian theory can explain a very diverse range of facts about the living world, including anatomical similarities between species. Although each of these facts might be explainable in other ways, the theory of evolution accounts for all the facts in one coherent explanation. Of course, those wishing to use IBE still need a way of deciding which of the competing hypotheses represents the best explanation. In Darwin’s case, the criteria included elegance, simplicity and coherence.13 To take another 19th Century example, what criteria could be used to settle the dispute among rival explanations for Brownian motion?14 Options included 63

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electrical attraction between particles, convection currents and collisions between the suspended particles and the molecules in the surrounding fluid. From our 21st century theoretical perspective, IBE might incline us towards the third explanation. In fact, it was not until Einstein’s precise predictions from a mathematical treatment of Brownian motion, in 1905, that the kinetic theory explanation was finally established. In other words, in the absence of other considerations IBE is insufficient to establish the validity of a theory or settle a dispute. Indeed, it may lead scientists to choose the ‘wrong option’. ENDNOTES 1

2

3

4

5 6

7

8

9

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I have continued to use this example in my graduate classes because many students from nonWestern countries have no knowledge of Batman and so remain puzzled by the picture. Interestingly, these students find it easier to accept the Batman interpretation when presented with the colour version of yellow on black. A wonderful, though perhaps fanciful, example of previous experience impacting everyday observation is provided by Turnbull (1961) in his book The Forest People (cited by Riggs, 1992, p. 17). Turnbull reports that the pygmy inhabitants of the Ituri Forest (a region of Congo) live in an environment where visibility is highly restricted and, in consequence, they have not developed the capacity to gauge size and distance accurately. He describes, though one wonders with what seriousness, an episode in which he (Turnbull) and Kenge (a tribesman) ventured into an open area outside the tree line: “And then he saw the buffalo, still grazing several miles away, far down below. He turned to me and said, ‘What insects are those?’ At first, I hardly understood, then I realized that in the forest vision is so limited that there is no great need to make an automatic allowance for distance when judging size… When I told Kenge that the insects were buffalo, he roared with laughter and told me not to tell such stupid lies” (p. 227). Riggs comments: “the theoretical components of Kenge’s observation included the preconception that the perceived size of an object is its true size” (Riggs, 1992, p. 17). It’s a nice story and would illustrate my point perfectly if it were true. An alternative story for students is the Picasso joke found in Rose (1997): “A man troubled by Picasso’s portraits with eyes facing both frontwards and sideways asks the painter why he does not paint realist pictures. To make his point clear the man takes out a photograph of his wife and says: ‘Like this’. The artist looks at the photo and mildly observes: ‘Small, isn’t she?’” (p. 60). The hidden figure is a white cow with black ears and a black muzzle. Once the cow is detected, you will continue to see it. You can never return to the previous ‘innocent’ frame of mind. Try it! It will be argued later that critical scrutiny by the community of scientists is the key to scientific rationality. Whether these ‘different’ observations are also ‘better’ observations will be discussed in chapter 4. Knowing that children will find it easier to observe change than constancy, and differences rather than similarities, should serve to guide choice of observation exercises in the early years. The significance of consensus within the scientific community to the validity of scientific knowledge will be discussed in chapter 5. Some discussion of whether the so-called processes of science are as discrete and theory-independent as some science educators claim is included in chapter 4. Human beings are sensitive to only a very narrow range of electromagnetic radiation and only to a very narrow range of sound frequencies. Together with our senses of touch and smell, neither of which is particularly sensitive, this is the ‘perceptual apparatus’ with which we confront the world. These limited senses can be expanded through technology (microscopes, telescopes, infrared spectrometers, and the like) but we are still, in a very real sense, prisoners of these limited senses and our intellectual capacity to imagine how to extend them. The real world (whatever that means) may be suffused with entities we cannot detect and/or have not yet imagined. An added problem, as Heisenberg pointed out, is that the observer may substantially change the object being observed simply through the act of observation. This more tentative position, and its value in enabling progress to be made, is well illustrated in the Fable of a lost child keeping warm in the CHEM STUDY materials (1963a, pp. 3-4).

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11

12

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14

The teachers were also fairly consistent in presenting biology as predominantly inductivist and chemistry and physics as hypothetico-deductivist (see chapter 4 for a discussion of this latter model of science). However, the shift in philosophic stance between subjects was more a reflection of the learning opportunities presented by the particular topics being taught than a belief that different sciences proceed by different methods. Peter Strawson (1971) argues that induction is so fundamental to human reasoning that we don’t need to justify it. We can just use it! Induction, he says, is one of the standards we use in deciding whether claims to knowledge are justified – for example, whether a pharmaceutical company has sufficient evidence to substantiate its claim for the effectiveness of a particular drug – so it is absurd to question whether induction itself is justified. It is perfectly proper, he says, to inquire whether there is good reason to accept a particular inductive inference, but the demand for justification of induction itself is mistaken. He urges us to compare the situation with the question: “Is the law legal?” It makes perfectly good sense to inquire whether a particular action is legal or not, and the answer is provided by an appeal to the prevailing legal system and application of its set of rules. But, he says, “it makes no sense to inquire in general whether the law of the land, the legal system as a whole, is or is not legal. For to what legal standards are we appealing?” (p. 257) The deployment of these somewhat subjective criteria in science will be discussed at length in chapter 7. Brownian motion refers to the chaotic, zig-zag motion of microscopic particles suspended in a liquid or gas, first observed in 1827.

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EXPLORING ALTERNATIVE VIEWS OF SCIENCE The Ideas of Popper, Lakatos and Kuhn

If the traditional inductive method of science, as projected in many school science textbooks and curriculum documents, is as seriously flawed as I argued in chapter 3, and if there are so many absurdities and difficulties associated with it, why don’t teachers discard it? Why don’t we ‘come clean’ and tell students how science really proceeds? We should tell them that science starts from existing knowledge and understanding – from exploring it, thinking about it, using it, doubting it, testing it. Then you get an idea: “I wonder if there is a relationship between x and y.” “What would happen if I did a or b?” “If so and so is the case, it seems likely that a, b, c”. Once you have an idea, you refine it, develop it, and then test it. This, in essence, is what Karl Popper (1959) says in his hypothetico-deductive model of science when he claims that science proceeds by a 4-step cycle of imagination and criticism. – A hypothesis is generated from the existing theoretical background – by creative imagination or inspired guesswork. – From the hypothesis, certain observable/testable conclusions are deduced – i.e., predictions are made. – The conclusions (predictions) are tested by observation or experiment.1 – The proposition is accepted or rejected. To use Popper’s language, if the predictions are borne out by the observational tests, the hypothesis is corroborated, not proven. If the predictions are not borne out by the observational tests, the hypothesis has been refuted – that is, shown to be false – and must be discarded. It may then be modified and the cycle repeated. According to Popper, science is a constant interplay among hypotheses, the logical expectations to which they give rise, and observational/experimental test. It is a constant dialogue between what might be true (the hypothesis) and what is or is not corroborated by the experimentally determined ‘facts’. In Popper’s language, science proceeds by means of conjectures and refutations until scientists arrive at a proposition that satisfactorily accounts for the evidence – a proposition that is not refuted by the observational evidence. This is not a random, hit-or-miss affair. There is constant feedback for the modification and restructuring of hypotheses, with each new conjecture being made in the light of the previous cycle of conjecture and refutation. In other words, scientists learn from their mistakes. There are several important differences between Popper’s view of science and the traditional inductivist view. First, it should be noted that observation comes very late in the Popperian model of science; in the inductivist model, it comes first. More significantly, the first step in Popper’s model is formulation of an hypothesis. In other words, scientists begin their endeavours by thinking, speculating, generating a new idea. For Popper, imagination comes first. Science is a creative, 67

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imaginative activity, not a dull, objective, value-free and method-driven procedure. In philosophical terms, the most distinctive feature of Popper’s model is the centrality of falsification, rather than verification. Every test of a scientific proposition is an attempt to falsify it, not an attempt to prove it correct. Popper goes on to argue that there is an asymmetry between confirmation and refutation. Although a universal statement (a generalization) cannot be confirmed as true by singular observation statements, no matter how numerous, a universal statement can be refuted (shown to be false) by a singular observation statement, as the inductivist turkey found out to his/her cost (see chapter 3). The observation of just one black swan falsifies the generalization that “all swans are white”,2 while no finite number of observations of white swans will prove the proposition true. In other words, falsification is decisive. By exposing hypotheses to this fierce ‘struggle for survival’ scientists ensure that only the ‘fittest’ hypotheses are retained – where ‘fittest’ means best accords with the observational evidence (‘best fits the facts’). By rejecting hypotheses that fail to stand up to observational and/or experimental test, science makes progress towards a truer description of the world. The description is ‘truer’ because some possible explanations have been ruled out: we know that the world is ‘not like that!’ Falsificationists like myself much prefer an attempt to solve an interesting problem by a bold conjecture, even (and especially) if it soon turns out to be false, to any recital of a sequence of irrelevant truisms. We prefer this because we believe that this is the way in which we can learn from our mistakes; and that in finding that our conjecture was false we shall have learnt much about the truth, and shall have got nearer to the truth. (Popper, 1963, p. 231) Of course, scientists would never know if or when they had arrived at the ‘truth’. There is no access to absolute truth because all human beings are ‘prisoners’ in the sense that we are confined by our physical environment (which limits our perspective), constrained by our senses and our limited capacity to extend them, and restricted by the capabilities of our intellect. We can only imagine what we can imagine! Thus, ‘scientific truth’ – insofar as the term has any meaning – is no more than ‘our current best shot’. The theories we currently hold are simply provisional conjectures that we have not yet managed to falsify, though we may do so tomorrow on the basis of new evidence or a new way of looking at existing evidence. Thus, the best corroborated theory is the one we have least reason to think is false. We choose the theory which best holds its own in competition with other theories; the one which, by natural selection, proves itself the fittest to survive. This will be the one which not only has hitherto stood up to the severest tests, but the one which is also testable in the most rigorous way. A theory is a tool which we test by applying it, and which we judge as to its fitness by the results of its applications. (Popper, 1959, p. 108) Although science is cautious in that sense, it is very courageous and daring in another sense. By making predictions, new hypotheses expose themselves to the risk of falsification. They risk being wrong! The most searching tests of a 68

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hypothesis centre on those predictions that are not derivable from current theory or that contradict currently held beliefs. A hypothesis that survives such a test (i.e., is not falsified) constitutes a significant advance in scientific knowledge. By making daring predictions, and thereby running a greater risk of falsification, highly speculative theories that survive observational/experimental testing are, in a sense, ‘better’ theories than those that claim less about the world and take fewer risks of being wrong. Thus, boldness and risk taking are key elements in Popper’s philosophy of science. For the inductivist, the stimulus for scientific endeavour is the patient, systematic, meticulous and orderly collection of data, from which generalizations will be induced. For the falsificationist, the stimulus is the leap of imagination, the bold speculation about what might be true and the subsequent ruthless discarding of uncorroborated speculations. CLARITY AND PRECISION

The demand that hypotheses and theories should be falsifiable requires that they should be clearly stated and precise. If a theory is vague, such that it is not clear exactly what is being claimed, then attempts to falsify it can always be interpreted in a way that is consistent with the theory. Popper (1959) talks disparagingly about Freudian psychoanalysis as a classic example of vagueness being taken to the limit, so that everything is compatible with it and nothing can disprove it.3 Precision is valued because it increases the risk of falsification; lack of precision minimizes or even avoids altogether the risk of being proved wrong. For example, the proposition ‘planets move around the Sun in elliptical orbits’ is more at risk of falsification than ‘planets orbit the Sun’. Similarly, to borrow the example used by Chalmers (1999), asserting that the velocity of light is 299.8 × 10 6 m.s-1 is bolder than claiming the velocity of light is about 300 × 10 6 m.s-1. Both are infinitely better than saying “light travels very quickly” For Popper, theories that claim more, in a more general sense, are preferred to those that claim less. For example, the claim that ‘all planets move around the Sun in elliptical orbits’ is preferred to ‘Saturn moves around the Sun in an elliptical orbit’ because it claims much more and, therefore, is at greater risk of being wrong. Only observations of Saturn can refute the first proposition, whereas observations of any planet can disprove the second one. This, Popper (1959) argues, results in science having a quasi-inductive4 trend: it proceeds from theories of high specificity to more general theories. Theories of some level of universality are proposed, and deductively tested; after that, theories of a higher level of universality are proposed, and, in their turn tested with the help of those of the previous levels of universality, and so on. The methods of testing are invariably based on deductive inferences from the higher to the lower level; on the other hand, the levels of universality are reached, in the order of time, by proceeding from lower to higher levels. (Popper, 1959, p. 277)

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Thus, Newton proceeded from a theory that talked about planetary bodies in a solar system attracting each other with a force inversely proportional to the square of their distance apart to a law of universal gravitation – that is, all bodies attract each other with a force inversely proportional to the square of their distance apart. Similarly, Einstein proceeded from a theory of special relativity to a theory of general relativity. When theories are replaced, says Popper, the new theory has to explain all that the old one could explain and say something new – that is, it must explain additional things: “A theory which has been well corroborated can only be superseded by one of a higher level of universality; that is, by a theory which is better testable and which, in addition, contains the old, well corroborated theory – or at least a good approximation to it” (Popper, 1959, p. 276). Thus, Newton’s physics could explain all that Aristotle’s physics could explain, it was successful in dealing with the problematic aspects of Aristotelian physics, and it explained phenomena and events outside the scope of Aristotle’s physics. Similarly, Einstein’s physics was capable of explaining all that Newton’s physics explained, it accounted for the anomalies that struck at the heart of Newtonian theory, and it made several risky predictions, including the proposition that light waves bend when they approach an intense gravitational field. Surviving an observational test of such a risky prediction lends enormous support to a theory. The theories of Kepler and Galileo were unified and superseded by Newton’s logically stronger and better testable theory, and similarly Fresnel’s and Faraday’s by Maxwell’s. Newton’s theory, and Maxwell’s, in their turn, were unified and superseded by Einstein’s. In each such case the progress was towards a more informative and therefore logically less probable theory: towards a theory which was more severely testable because it made predictions which, in a purely logical sense, were more easily refutable. (Popper, 1963, p. 220) The demand that theories become more falsifiable (i.e., have more content) rules out theoretical modifications designed merely to protect the theory from the threat of falsification – what Popper calls ad hoc hypotheses. As regards auxiliary hypotheses we decide to lay down the rule that only those are acceptable whose introduction does not diminish the degree of falsifiability or testability of the system in question, but, on the contrary, increases it… If the degree of falsifiability is increased, then introducing the hypothesis has actually strengthened the theory: the system now rules out more than it did previously: it prohibits more. We can also put it like this. The introduction of an auxiliary hypothesis should always be regarded as an attempt to construct a new system; and this new system should then always be judged on the issue of whether it would, if adopted, constitute a real advance in our knowledge of the world. (Popper, 1959, p. 82) Thus, Popper (1974) explains that in accounting for an anomaly in the motion of Uranus, as predicted by Newton’s gravitational theory, a permitted auxiliary hypothesis was the existence of a previously unknown planet. This modification 70

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was independently testable: the position of the planet was calculated and the planet (Neptune) was discovered optically. Not permitted in these circumstances was the ad hoc hypothesis that Uranus is unique in the solar system in not behaving as Newtonian theory predicts. Events such as Galle’s discovery of Neptune, Hertz’s discovery of radio waves, Eddington’s confirmation that light bends in the vicinity of the Sun, and Powell’s observations of the first Yukawa mesons are significant in science because, in Popper’s terminology, they corroborate a bold hypothesis and so constitute powerful and persuasive evidence that the new theory is an improvement on the old: “All these discoveries represent corroborations by severe tests – by predictions which were highly improbable in the light of our previous knowledge (previous to the theory which was tested and corroborated)” (Popper, 1963, p. 220). The historical significance of such corroborative tests contrast sharply with the a-historical nature of confirmatory evidence in the inductivist approach, which would seem to lend increased support for a theory regardless of when the evidence is generated. Popper also regards the falsification of cautious hypotheses as significant. Because they enable us to reject well-established and seemingly unproblematic knowledge they are a major stimulus to creative theory building. THE PROBLEMS OF FALSIFICATIONISM

Elegant and appealing as Popper’s arguments may be, they are not free of difficulties. A major problem is his insistence that theory acceptance is tentative, while theory rejection is decisive. As argued in chapter 3, observation statements – the evidence on which theories are to be judged – are both unreliable (fallible) and theory-dependent. Because observation statements are theory-dependent, a theory may be protected from falsification until the appearance of a new theory capable of looking at the observational evidence in a new way, or able to produce entirely new evidence – a point to be discussed later in the chapter. Because observation statements are fallible, and their acceptance only tentative and open to revision, falsification is logically suspect. When theory and observation are in conflict, there is nothing in the logic of the situation that compels us to reject the theory. If a theory is falsified only when the observation statement that contradicts it is accepted, theories cannot be conclusively falsified because the observation statements that form the basis of the falsification may themselves prove to be false, mistaken or misleading in the light of later developments. In short, if we cannot rely on observations, we cannot use them in a decisive way to reject theories, just as we cannot use them as a certain basis for accepting a theory. While the observation of a single black swan does falsify the proposition that all swans are white, it would be a serious mistake to regard scientific theories as similar in scope and form to this simple generalization and, therefore, as equally vulnerable to decisive falsification. Scientific theories are not merely simple statements or generalizations; rather, they are complex explanatory systems comprising elaborate and complex conceptual relationships. In consequence, testing and disproving a theory is not quite as straightforward as Popperian falsificationism seems to imply. We should certainly not project a view in school science that theories 71

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stand or fall on the basis of a single and simple “Yes or No” test. It is precisely because theories are complex structures, supported by a complex array of other theories (for example, theories of perception and theories underpinning scientific instrumentation), that an apparently falsifying observation can be deflected away from what Imre Lakatos calls the hard core of the theory. Lakatos (1974) introduces the idea of a “protective belt” around a theory’s central principles (hard core) by means of a story about “an imaginary case of planetary misbehaviour”. Because of its insight and humour it is worth quoting at length. A physicist of the pre-Einsteinian era takes Newton’s mechanics and his law of gravitation… and calculates, with their help, the path of a newly discovered small planet, p. But the planet deviates from the calculated path. Does our Newtonian physicist consider that the deviation was forbidden by Newton’s theory and therefore that, once established, it refutes the theory? No. He suggests that there must be a hitherto unknown planet p’, which perturbs the path of p. He calculates the mass, orbit, etc. of this hypothetical planet and then asks an experimental astronomer to test his hypothesis. The planet p’ is so small that even the biggest available telescopes cannot possibly observe it: the experimental astronomer applies for a research grant to build yet a bigger one. In three years time, the new telescope is ready. Were the unknown planet p’ to be discovered, it would be hailed as a new victory of Newtonian science. But it is not. Does our scientist abandon Newton’s theory and his idea of a perturbing planet? No. He suggests that a cloud of cosmic dust hides the planet from us. He calculates the location and properties of this cloud and asks for a research grant to send up a satellite to test his calculations. Were the satellite’s instruments (possibly new ones, based on a littletested theory) to record the existence of the conjectural cloud, the result would be hailed as an outstanding victory for Newtonian science. But the cloud is not found. Does our scientist abandon Newton’s theory, together with the idea of the perturbing planet and the idea of the cloud which hides it? No. He suggests that there is some magnetic field in that region of the universe which disturbed the instruments of the satellite. A new satellite is sent up. Were the magnetic field to be found, Newtonians would celebrate a sensational victory. But it is not. Is this regarded as a refutation of Newtonian science? No. Either yet another ingenious auxiliary hypothesis is proposed or… (pp. 100-101) Embedded within this story are the key elements in the Lakatosian notion of science as a constellation of “research programmes”, complex conceptual and methodological structures which guide the work of scientists by indicating potentially fruitful lines of development (the “positive heuristic”) and specifying what cannot be done (the “negative heuristic”). The negative heuristic of a Lakatosian research programme involves the stipulation that the basic assumptions underlying the programme (the “hard core”) cannot be modified or rejected. Any mismatch between theory and and observation is dealt with by modification of the “protective belt” of auxiliary hypotheses surrounding the hard core, as in the story above. 72

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The positive heuristic of the programme comprises rough guidelines on future development. The positive heuristic consists of a partially articulated set of suggestions or hints on how to change, develop the ‘refutable variants’ of the researchprogramme, how to modify, sophisticate, the ‘refutable’ protective belt. (Lakatos, 1978, p. 50) Early work on a research programme often takes place in opposition to apparently falsifying observations. Time has to be allowed for development of the programme – a suitably robust and sophisticated protective belt must be constructed before the theory is subjected to rigorous testing. Concepts need to be refined and conceptual relationships clearly established before a theory can be subjected to critical experiment-based scrutiny. Once the programme is sufficiently well developed to permit testing, it is confirmations rather than falsifications that are considered significant. The basic unit of appraisal must not be an isolated theory or conjunction of theories but rather a ‘research programme’, with a conventionally accepted… ‘hard core’ and with a ‘positive heuristic’ which defines problems, outlines the construction of a belt of auxiliary hypotheses, foresees anomalies and turns them victoriously into examples, all according to a preconceived plan. (p. 99) A research programme is judged to be “progressive” or “degenerating”, depending on whether or not its theoretical growth anticipates its empirical growth – that is, whether or not it keeps generating new facts, leads to the discovery of new phenomena and predicts future events. Notable events of this kind were Newton’s prediction of the return of Halley’s comet in 1758 and the discovery of the two elements we now know as gallium and selenium on the basis of Mendeleev’s Periodic Table. A series of theories is theoretically progressive… if each new theory has some excess empirical content over its predecessor, that is, if it predicts some novel, hitherto unexpected fact. Let us say that a theoretically progressive series of theories is also empirically progressive… if some of this excess empirical content is also corroborated, that is, if each new theory leads to the actual discovery of some new fact… Progress is measured by the degree… to which the series of theories leads to the discovery of novel facts. We regard a theory in the series ‘falsified’ when it is superseded by a theory with higher corroborated content. (Lakatos, 1978, p. 33) Popper’s criterion for a satisfactory theory is agreement with the observed facts; the criterion for a satisfactory series of theories (research programme), according to Lakatos, is that it should generate new facts and provide clear guidance for research. A research programme is said to be ‘degenerating’ (and should be abandoned) when it loses its coherence and/or when it no longer leads to confirmed novel predictions.

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INSURMOUNTABLE PROBLEMS

The Lakatosian modifications of Popperian theory seem to accord better with historical evidence. If strict falsificationist methodology had been followed, some of our best theories would have been killed off very early in their history. Imagine the situation at the time of the Copernican revolution, for example. If the Earth revolves around the Sun, as Copernicus suggested, there should be a variation in the apparent size of the other planets during the year it takes to complete the orbit. Such a variation is not observed. Therefore, Copernican theory appears to be falsified. Galileo took a different view, arguing that the planets are much further away than we believe and, therefore, our eyes cannot detect the change in size. What is needed is a much better way of observing. Eventually, with telescopic observation, Galileo was proved correct: there is an apparent variation in the size of the other planets during the Earth’s rotation of the Sun. Galileo also had to deal with the observation that objects dropped from the top of a tower land at the base of the tower and not some distance away, as opponents of Copernican theory argued they would if the Earth was rotating. He did so by introducing the idea of relative motion, a move that challenged well-established Aristotelian views about human perception. What Galileo did was to defend the theory against the evidence. It was his insistence on adhering to Copernican theory in the face of apparently falsifying evidence that led to the development of new observational methods and new subsidiary theory (concerning the nature of human perception), and paved the way for the eventual universal acceptance of heliocentric theory.5 As Hall (1974) puts it: Galileo is above all aware that the senses must be educated and assisted to perceive realities. Thus one could know the true nature of the moon without the telescope: that instrument simply makes reality easier to discover. (p. 72) Similarly, early observations of the Moon’s orbit apparently falsified Newton’s law of gravitation and it took the best part of 50 years to explain away this anomaly. Later on, the theory survived even though it consistently failed to account fully for the observed orbit of Mercury. Einstein’s physics finally achieved that. The reality is that scientists don’t reject theories because of a few inconvenient facts; they know that, given time, the facts can sometimes be changed – by reinterpreting the observational data or obtaining better observational data. Even Popper (1974), the principal advocate of falsificationism, says that “if we give in to criticism too easily, we shall never find out where the real power of our theories lies” (p. 55). At the individual level, scientists are not immune to selecting data that supports their theoretical position and rejecting data that doesn’t, as Holton’s (1978) analysis of Millikan’s laboratory notebooks indicates. Holton posits the notion of suspension of disbelief to describe how Millikan withheld “final judgements concerning the validity of apparent falsifications of a promising hypothesis” (p. 71). Far from condemning such action, Holton regards it as an essential part of theory building: “The chief gain was the avoidance of costly interruptions and delays that would have been required to pin down the exact causes of discrepant observations” (Holton, 1986, p. 12). 74

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One question that Lakatos does not answer is: “How long do we wait before we label a research programme as degenerating?” It is always possible that some new modification of the protective belt will breathe new life into an old theory. If you are permitted to wait, asks Feyerabend (1975), why not wait a little longer? If it is unwise to reject faulty theories the moment they are born because they might grow and improve, then it is also unwise to reject research programmes on a downward trend because they might recover and might attain unforeseen splendour (the butterfly emerges when the caterpillar has reached the lowest stage of degeneration). Hence, one cannot rationally criticise a scientist who sticks to a degenerating programme and there is no rational way of showing that his actions are unreasonable. (p. 185) Feyerabend argues that Lakatos fails to provide any clear criteria for choosing or rejecting a particular programme and, therefore, that his model of science, whilst useful for retrospective evaluation of research programmes, offers practising scientists no guidance on how to proceed. It is, Feyerabend asserts, no more than a “verbal ornament… a memorial to happier times when it was still thought possible to run a complex and often catastrophic business like science by following a few simple and ‘rational’ rules” (Feyerabend, 1970, p. 215). Even the criterion of successful prediction is not always sufficient for a theory to be accepted by the community. As Brush (1990) has noted, the astrophysicist Hannes Alfven has a remarkable record of successful predictions concerning plasma phenomena (including magnetohydrodynamic waves, now known as Alfven waves, field aligned currents in the Earth’s upper atmosphere and critical ionization energy phenomena, including Uranian rings), yet his theoretical explanations of those predictions have not been widely accepted. As argued in the previous chapter, it is not unreasonable to insist that a satisfactory account of science should do two things. It should account for the actual course of science and it should provide guidance for aspiring scientists on how to proceed. The falsificationist view of science does not meet the first of these requirements: it is clearly not what scientists do, however elegant and appealing the model may seem. There is no choice but to abandon Popperian views about the nature of scientific method, despite its prominence in some science textbooks (those that don’t promote inductivism generally promote hypothetico-deductivism) and despite its exalted status as the so-called ‘scientific approach’ to educational research, with its emphasis on the null hypothesis. A REVOLUTIONARY VIEW

Despite my suggestion that Popper’s account of science should be rejected, it does represent a major step forward from the traditional inductivist view. For me, the most significant aspect of the Popperian model of science is that science is driven by people and their creative imaginations, not by some cold and clinical method to which people have to subordinate themselves. In Popper’s world of science, people have priority over method: people determine what science to do and how 75

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to do it, rather than science and its method requiring that people divest themselves of their essential humanity at the laboratory door and assume the role of the “depersonalized seeker after truth” (Cawthron & Rowell, 1978). Even more interesting in these respects is Thomas Kuhn’s model of science, as outlined in his 1962/1970 book The Structure of Scientific Revolutions. According to Kuhn, science does not proceed in an orderly, systematic and continuous way, but through a series of revolutions and periods of consolidation (what Kuhn calls normal science). In the beginning, in the early history of a science,6 there is no agreement on how best to proceed. Each individual is busy defining and re-defining the field, establishing priorities, making statements about correct procedures, deciding what should count as evidence, and so on. The disorganized and diverse activities that characterize pre-science, as Kuhn calls it, become structured and directed when the community of practitioners reaches agreement on certain theoretical and methodological issues – that is, when the disciplinary matrix (the framework of theory and method or paradigm, to use Kuhn’s term) becomes established and accepted. Kuhn illustrates his argument by reference to the situation prior to the publication of Isaac Newton’s Opticks, in 1704. No period between remote antiquity and the end of the seventeenth century exhibited a single generally accepted view about the nature of light. Instead there were a number of competing schools and sub-schools, most of them espousing one variant or another of Epicurean, Aristotelian, or Platonic theory… Being able to take no common body of belief for granted, each writer on physical opticks felt forced to build his field anew from its foundations. (Kuhn, 1970, p. 12) Once a particular paradigm has been established, scientists engage in normal science: they work within the paradigm, assuming that its basic premises are valid; they follow its rules and procedures; they use its concepts and theories to explore, develop and extend the paradigm, widen its scope, solve its internal puzzles and problems (both theoretical and procedural), formulate quantitative relationships among concepts, and so on. In Kuhn’s (1977) words, normal science “aims to elucidate the scientific tradition in which (the scientist) was raised rather than to change it… The puzzles on which he concentrates are just those which he believes can be both stated and solved within the existing scientific tradition” (p. 234). In engaging in the paradigm articulation of normal science scientists may encounter problems that the paradigm cannot solve or they may generate some seemingly falsifying evidence. Initially, this is not serious. Indeed, it is to be expected: the paradigm is a human creation and cannot be expected to be perfect, to be capable of explaining and accounting for everything within its domain (sphere of interest and concern). It needs time to develop: concepts need to be refined, conceptual relationships established and internal inconsistencies eliminated. Eventually the problems will be satisfactorily solved. What scientists look for, says Kuhn, is reasonable agreement between theory and observation, with ‘reasonable’ being judged in relation to the specific circumstances. This is a significantly different

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position from the extreme falsificationist position that contrary evidence instantly refutes a theory. However, if a large number of unsolved problems accumulates, if the problems are theoretically significant, in that they strike at the hard core of the theory and consistently resist solution, or if they are socially and/or economically significant,7 a crisis develops. When a paradigm cannot cope with its internal problems, scientists begin to lose confidence in it. When a paradigm is in crisis and dissatisfaction is widespread, the time is ripe for revolution. If an individual scientist, or a group of scientists, proffers a new set of concepts, a new theory or a new procedure that is able to solve some of the major problems, then others will be encouraged to try out the new ideas on their problems. If success is achieved again, still others will be encouraged to adopt the new thinking. Eventually, if the new approach provides a sufficiently plausible solution to the problems of the old paradigm, a revolution will have occurred and allegiance will have switched from the old paradigm to the new. This new paradigm now becomes the basis for a new round of normal science, until, in due time, a new crisis develops and further revolution occurs. While normal science is a somewhat conservative and rule-bound phase, it is the driving force for progress because it generates the problems and anomalies that precipitate the next revolution. Normal science does not aim at novelties of fact or theory and, when successful, finds none. New and unsuspected phenomena are, however, repeatedly uncovered by scientific research, and radical new theories have again and again been invented by scientists. History even suggests that the scientific enterprise has developed a uniquely powerful technique for producing surprises of this sort. (Kuhn, 1970, p. 52) After a scientific revolution there is much work to be done. All existing data not rendered irrelevant by the new paradigm have to be re-interpreted within the new theoretical framework. Moreover, scientific instruments and research procedures have to be reviewed and appropriately modified. And, of course, new textbooks need to be written to ensure that the next generation of scientists is ‘properly’ educated – that is, in the new way of thinking and acting. Sometimes this re-writing of science is so extensive and persuasive that all trace of preceding theoretical ideas are swept away – a phenomenon that Kuhn calls “the invisibility of revolutions”. [the textbooks] have to be rewritten in whole or in part whenever the language, problem-structure, or standards of normal science change. In short, they have to be rewritten in the aftermath of each scientific revolution, and, once rewritten, they inevitably disguise not only the role but the very existence of the revolutions that produced them. (p. 137) KEY FEATURES OF KUHN’S VIEW OF SCIENCE

There are four features of Kuhn’s view of science that are worthy of close attention. First, his point that scientific progress is discontinuous. For Kuhn, paradigms

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do not change in piecemeal fashion; rather, there is a wholesale shift to a new way of thinking, bringing with it a new set of procedures and a new set of ‘facts’ about the world. Kuhn is referring to the revolutionary nature of major theoretical breakthroughs by scientific giants like Newton, Einstein and Darwin. Of course, as argued in chapter 3, science is cumulative, and unless scientists assume the validity of science already done, further progress would be impossible. However, too uncritical an acceptance of science already done curtails further progress. Progress emanates from doubt. The second point of interest focuses on Kuhn’s tolerance of anomaly. Provided they are not too serious, and strike at the very core of the paradigm, anomalies are accepted, even expected. During the sixty years after Newton’s original computation, the predicted motion of the moon’s perigree remained only half of that observed. As Europe’s best mathematical physicists continued to wrestle unsuccessfully with the well-known discrepancy, there were occasional proposals for a modification of Newton’s inverse square law. But no one took these proposals very seriously, and in practice this patience with a major anomaly proved justified. Clairaut in 1750 was able to show that only the mathematics of the application had been wrong and that Newtonian theory could stand as before. (Kuhn, 1962, p. 81) Thus, refutation is much less significant for Kuhn than for Popper: “The scientist who pauses to examine every anomaly he notes will never get significant work done” (Kuhn, 1962, p. 82). Single discrepancies are not sufficient to falsify a theory and bring about a revolution. No one seriously questioned Newtonian physics because of discrepancies concerning the orbit of Mercury or the speed of sound. The fact that that there are lots of observations inconsistent with Einsteinian theory has not, so far, led to its overthrow. Paradigms are not discarded until there is an abundance of acceptable and significant falsifying evidence and, more importantly, an alternative theory.8 Once it has achieved the status of a paradigm, a scientific theory is declared invalid only if an alternative candidate is available to take its place. (Kuhn, 1970, p. 77) A paradigm is not usually rejected on the basis of a comparison of its predicted consequences with empirical evidence, as Popper insists. More often, it is rejected as a consequence of a 3-way comparison of the old theory, the new theory and observational evidence – though even this may be more difficult than it seems at first glance. Given the arguments of chapter 2, the nature of the evidence collected is determined by the theory, and so may be significantly different for the old and the new paradigm – a matter to be discussed below and in chapter 5. Kuhn’s views accord much better with historical evidence than do Popper’s.9 If a strict Popperian methodology was followed, many promising theories would have been ‘killed off’ very early in their history, thus depriving the scientific community of many potentially interesting and productive ideas. If theories were not remarkably resilient in the face of apparently falsifying data, scientists would be 78

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continually starting again and progress would be impossible. Theories are resilient because they can accommodate ‘counter observations’ in many ways, including: (i) challenging the reliability of the observations and/or the methods and instruments employed; (ii) deflecting criticism to a subsidiary (and, therefore, less important) part of the theory; (iii) postulating a ‘poorly understood’ complicating factor, to which ‘attention will be directed in due course’. Of course, this resilience sometimes works to the detriment of scientific progress, as in Alfred Wegener’s (1915) unsuccessful attempt to overthrow the reigning paradigm of ‘permanentism’ in geology in favour of his notion of ‘continential drift’ – a revolution that was delayed by more than half a century. (Frankel, 1979). A third significant element of Kuhn’s view of science is his assertion that rival paradigms look at the world in different ways. As argued in chapter 3, possession of new knowledge enables us to make new observations. In other words, what you see depends on what you know. Further, what there is to be seen depends on what you know. Because they involve different concepts and ideas, rival paradigms direct attention to different things, and in different ways. They have different priorities and focus on different issues, problems and questions. Consequently, comparison of rival paradigms is difficult, if not impossible. There is no paradigmindependent language and there are no paradigm independent concepts, so no paradigm-independent observations can be made or paradigm-independent experiments performed. Data, in the usual meaning of the term, cannot establish the superiority of one paradigm over another because data are perceived either through the lens of one paradigm or the other. In short, there is no common basis on which rival paradigms can be compared. In Kuhn’s terminology, rival paradigms are incommensurable. In retrospect, we see Lavoisier’s isolation of oxygen in the late 18th Century as a decisive event in the establishment of his theory of combustion. However, Priestley regarded this gas as ‘dephlogisticated air’ and its isolation as evidence in favour of phlogiston theory. In Priestley’s world, phlogiston is released into the air during combustion; in Lavoisier’s world, oxygen is taken out of the air during combustion. There is nothing in the oxygen theory that corresponds directly with phlogiston, nor is there anything in the phlogiston theory that corresponds directly to oxygen. Yet both theories explain the observational data.10 Even when a new paradigm utilizes concepts from an old one, it does so in a new way. Compare, for example, the concepts of mass, time, space and energy in the Newtonian and Einsteinian paradigms. In Einstein’s special theory of relativity, the mass of a body depends on the observer’s frame of reference and, moreover, mass can be converted into energy; in the Newtonian paradigm, the mass of a body is fixed and is constant for all observers, regardless of their frame of reference. Although the term mass is used in both paradigms, the respective concepts are incommensurable. Indeed, in the Newtonian paradigm, the concept ‘relative mass’ would be absurdly meaningless. Since new paradigms are born from old ones, they ordinarily incorporate much of the vocabulary and apparatus, both conceptual and manipulative, that the traditional paradigm had previously employed. But they seldom employ these borrowed elements in quite the traditional way. Within the new 79

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paradigm, old terms, concepts, and experiments fall into new relationships one with the other. (Kuhn, 1970, p. 149) In short, scientists before and after a paradigm change are not talking about the same theoretical entities, even when they are using the same words. The proponents of competing competing paradigms practice their trades in different worlds. One contains constrained bodies that fall slowly, the other pendulums that repeat their motions again and again. In one, solutions are compounds, in the other mixtures. One is embedded in a flat, the other in a curved, matrix of space. Practicing in different worlds, the two groups of scientists see different things when they look from the same point in the same direction… Both are looking at the world, and what they look at has not changed. But in some areas they see different things, and they see them in different relations one to the other. That is why a law that cannot even be demonstrated to one group of scientists may occasionally seem intuitively obvious to another (p. 150) Thus, the idea of incommensurability implies that after a revolution scientists have a new way of looking at things and new problems to work on (a new kind of normal science). Thus, old problems are not so much solved as simply forgotten or regarded as irrelevant. Since ancient times, theories in astronomy had struggled to account for planetary retrogression, but in the Copernican system it ceases to be a problem because the observed motions of the planets are a consequence of the Earth and other planets orbiting the Sun. If rival theories are incommensurable, there can be no crucial experiment to decide between them. Such an experiment would require the two theories to make mutually exclusive predictions about the same events. Because competing theories address the world in different ways, often using different concepts, they make different predictions about observable phenomena. Indeed, what is observable in terms of one theory may not be observable in terms of the other. Suppose, for example, that theory A says that light is a wave motion (electromagnetic radiation) and theory B says it is particulate (high energy photons). As a consequence of its behaviour as a wave motion, light will have particular observable properties, such as interference patterns, which scientists can seek to confirm or refute through observational evidence provided by experiment. Theory B also has particular observable consequences for the behaviour of light, such as the photoelectric effect, which experiments can seek to confirm or refute. Under one set of experimental circumstances, light will manifest particle-like properties; under another (experimentally incompatible) set of circumstances it will manifest wave-like properties. However, while experiments designed on the assumption that light is a wave motion may provide support for this theory, they will not falsify the theory that it is particulate. Nor will experiments designed on the assumption that light comprises high energy particles falsify the theory that it is a wave motion, though they may provide support for the particle theory. Experiments designed on the assumption that it is neither particulate nor wave-like are not possible unless there is a third theory that says something about the nature of light in terms other than 80

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particles and waves. But these experiments could not falsify either theory A or theory B; they could only lead to judgements about the third theory. In other words, experiments can only test theories within and against their own conceptual framework. They cannot tell us anything about theories that have a different conceptual structure. All that can be done in a situation of paradigm conflict is to evaluate a theory ‘in terms of its own terms’, supplemented by criteria additional to the criterion of simple empirical validity. Kuhn (1970) expresses this position as follows: The choice is not and cannot be determined merely by the evaluative procedures characteristic of normal science, for these depend in part upon a particular paradigm, and that paradigm is at issue. When paradigms enter, as they must, into a debate about paradigm choice, their role is necessarily circular. Each group uses its own paradigm to argue in that paradigm’s defence… the status of the circular argument is only that of persuasion. It cannot be made logically compelling for those who refuse to step into the circle. (p. 94) This is not what we tell students in school science, nor, I suspect, in university science courses. Chapter 5 discusses these matters at greater length. The fourth significant element in Kuhn’s account of science is its recognition of the importance of social factors at all stages of the scientific endeavour. Although Popper regards the generation of hypotheses as a creative act that is not susceptible to rational analysis, he asserts that hypotheses are tested and accepted/ rejected by orderly and logical procedures based on experiment and observation.11 In contrast, Kuhn insists that there is no purely logical argument to show the superiority of one paradigm over another. Individual scientists may be persuaded to adopt a particular theory for a variety of reasons, grounded in their particular interests, personal and professional goals, values, and day-to-day concerns and priorities. Thus, it is consensus within the community of practitioners that is the mechanism for acceptance. Of particular significance is Kuhn’s admission that consensus is influenced by all manner of psychological, social, political and economic considerations. In other words, science is not entirely logical and rational, in the sense usually employed in science textbooks. Rather, it is a value-laden and socioculturally located enterprise – a situation to be discussed at length in chapter 7. It is the consensus view of science embedded in Kuhn’s thesis that offends those critics who seek objective criteria for choosing between rival theories because, they argue, it leads to a relativist position – one theory is not superior to another, just different.12 If Kuhn’s arguments are taken at face value, facts about the world are paradigm-dependent and change when there is a scientific revolution. Thus, it makes no sense to ask whether a given theory corresponds to the facts ‘as they really are’ nor, therefore, to ask whether a theory is true. Truth itself is relative to a particular paradigm: what is true with respect to theory T1 is not true with respect to theory T2, and vice versa. In contrast, Popper (1972) asserts that one theory is closer to the truth than another, whether a particular individual or group of individuals thinks so or not. As science progresses theories approach the truth or, to use Popper’s (1972) language, their verisimilitude increases. Furthermore, Popper seems to regard this progress as guaranteed, provided that there is a sufficient 81

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number of individuals properly trained in scientific method and possessing the right attitude of “critical rationalism”. Paul Feyerabend (1975), on the other hand, denies that there is an objective scientific method. All attempts to characterize it have failed, he observes, and no one model of science stands up to historical scrutiny. The idea of a method that contains firm, unchanging and absolutely binding principles for conducting the business of science meets considerable difficulty when confronted with the results of historical research. We find then, that there is not a single rule, however plausible, and however firmly grounded in epistemology, that is not violated at some time or another. (p. 23) The idea of a fixed method of science rests on too naïve a view of what is a complex and uncertain enterprise, argues Feyerabend, and the only principle that is always applicable is the principle Anything Goes. The extent to which this view is appropriate for school science will form part of the discussion in chapter 5 and will be re-visited in chapter 9. ENDNOTES 1

2

3

4

5

Popper (1972) includes two additional steps in the procedure: (i) before the conclusions are tested, they are compared among themselves and appraised for internal consistency (there must be no inconsistencies or mutual contradictions); (ii) the logical form of the proposition is investigated for evidence of conceptual ambiguity, vagueness, circularity and lack of clarity. Falsification is achieved if we accept that it is a genuine black swan, rather than a white swan that appears black because it is living in a polluted environment. Disconfirming observations have to be acceptable – a point of importance in the earlier discussion of the conditions for inductive inferences (see chapter 3). In Popper’s (1959) words, “a few stray basic statements contradicting a theory will hardly induce us to reject it as falsified. We shall take it as falsified only if we discover a reproducible effect which refutes the theory” (p. 86, emphasis added). Chalmers (1999) remarks that “there are plenty of social, psychological and religious theories that give rise to the suspicion that in their concern to explain everything they explain nothing… Theorists operating in this way are guilty of the fortune-teller’s evasion and are subject to the falsificationist’s criticism. If a theory is to have informative content, it must run the risk of being falsified” (p. 64). Popper illustrates his argument with the following example: A man pushes a child into a river with the intention of murdering him/her, while another man jumps into the river and sacrifices his life in order to save the child. Freudians explain the first man’s behaviour by positing that he suffered from repression and the second man’s behaviour by saying that he achieved sublimation. Adlerians explain the episode by saying that both men suffered from feelings of inferiority; the first man needed to prove to himself that he could commit the crime and the second man needed to prove to himself that he was brave enough to rescue the child at whatever personal cost. By employing concepts such as repression, sublimation and unconscious desires, psychoanalysis is made compatible with all human behaviour. Because they are unfalsifiable, such theories are not science (according to Popper), though they may have value as something other than science. This is not induction, which Popper goes to considerable lengths to reject, but an inductive direction in theory building – a movement from the more particular to the more general. It was a long time before the heliocentric theory of the solar system could account for all the observational data. To do so, the theory had to adopt Keplerian elliptical orbits (rather than circular ones), planets of different masses in mutual attraction, rotating planets, planets with satellites (moons), and an additional planet (Neptune).

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6

7

8

9

10

11

12

Note that Kuhn discusses the development of sciences, not science as a whole. For Kuhn, there are significant differences among the sciences. The crisis that precipitated the Copernican revolution was the urgent need for an accurate calendar to predict the holy days of the Christian church. However, Copernicus presented his ideas in instrumental form (see chapter 6), lest he offend against the teachings of the established church (Dreyer, 1953). In science, there is rarely a period in which there is no prevailing paradigm, though there may be occasions when no consensus has been reached about which of the competing paradigms should be accepted. Indeed, it was Kuhn’s declared intent to provide a realistic and historically accurate account of how science develops, in contrast to previous accounts that, he says, are more like reading a tourist guidebook about a particular country than experiencing life there. It was also observed that when metals are heated to form what was then known as a calx, the resulting calx weighed more than the original metal. The combustion in oxygen theory explains this perfectly well: the metal combines with oxygen to form a metal oxide, which necessarily weighs more than the uncombined metal. Using phlogiston theory, the increase in weight can only be explained if phlogiston has negative weight – an absurdity that eventually proved the final nail in the coffin for phlogiston theory. Allchin (1997) makes a case for teaching about the ‘paradigm war’ between supporters of phlogiston theory and supporters of combustion in oxygen as a way of integrating philosophy of science, sociology of science and history of science into the science curriculum. In drawing what he considers to be a crucial distinction between the context of discovery and the context of justification, Popper says that theory evaluation should take no account of the personal, sociocultural and historical circumstances of its generation. Rather, all efforts should be concentrated on the chain of argument and the quality of the evidence: “The act of conceiving or inventing a theory seems to me neither to call for logical analysis nor to be susceptible to it… the question of how it happens that a new idea occurs… may be of interest to empirical psychology; but it is irrelevant to the logical analysis of scientific knowledge” (Popper, 1959, p. 27). Lakatos (1968) claimed that Kuhn’s views made theory change in science a consequence of what he disparagingly labelled mob psychology: “According to Kuhn scientific change – from one ‘paradigm’ to another – is a mysterious conversion which is not and cannot be governed by the rules of reason: it falls totally within the realm of (social) psychology of discovery” (p. 151).

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SCIENTIFIC INQUIRY, EXPERIMENT AND THEORY What Should We Tell Our Students?

Contemporary school science curricula are virtually unanimous in the views they promote about the relationship between scientific knowledge and scientific method – specifically, between theory and experiment. So, too, are school science textbooks, most of which assert that the validity of scientific knowledge is judged solely by its agreement with observable and experimentally acquired evidence. Indeed, the very rationality and objectivity of science are held to be guaranteed by insisting that theories are subjected to experimental testing by other scientists and by the assumption that this testing is decisive. Thus, almost all textbooks and curriculum documents invest enormous faith in the capacity of observation and experiment to provide reliable data for making unequivocal decisions about the validity of theories. There is no doubt that science is at its most powerful and most effective when it is able to control and manipulate phenomena and events, as in laboratory experiments. Interestingly, many of the events observed in experimental inquiries do not occur in the natural world, or they are so changed by the conditions of the experiment that they are, in essence, different events. In such circumstances, the experimental approach is able to obtain information that is much more detailed and precise than that arising from passive observation of uncontrived events. However, experiments may not always be sufficient, in themselves, to provide a reliable and valid basis for theory building about the natural world. Nor, it should be noted, are experiments always necessary or desirable. Many fields of scientific endeavour deal with events that are remote and inaccessible in time and space, and so make little or no use of experiments. In these cases, theoretical conjectures have to be confirmed or refuted by uncontrived observations. In some areas of science, experimentation may be possible but is ruled inadmissible on ethical grounds or for reasons of safety, difficulty or cost. In these cases, correlational studies in naturalistic settings may play a significant role.1 Moreover, there may be field settings that are unsuitable for experimental inquiry because they are too complex or too fragile and uncertain. For example, an experimental approach might so distort the natural setting that it no longer represents natural behaviour, as Bowen and Roth (2002) describe in their discussion of observational work with lizards. The power that results from close control is also the major weakness of the experimental approach and a potential trap for the unwary. The arguments developed in chapters 3 and 4 concerning the theory-laden nature of scientific observation and the incommensurability of rival paradigms lead to the conclusion that experiments can only be envisaged, designed and conducted within a particular theoretical matrix, which governs scientists’ perceptions of the problem, determines the experimental design, influences the interpretation of results, and so on. Theories determine which experiments are regarded as legitimate and how they are 85

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to be conducted. For example, in gathering data to test an hypothesis, the form of the hypothesis and the nature and method of data collection are dictated by the very theory that is under test. In other words, theory-independent experiments are impossible. If theories are incommensurable, as Kuhn (1970) claims, there can be no crucial experiment to decide between them (see discussion in chapter 4). In such circumstances, the best we can do is to evaluate each theory on its own terms. These points, made at length in Hodson (1988), serve to remind us that in seeking to give students an understanding of the nature of scientific inquiry we must be careful not to reinforce the many falsehoods about the role and status of experiments perpetrated by school science textbooks. Sometimes science teachers promote the belief that everything that falls within the province of science, and that students learn about in school science lessons, is susceptible to direct experimental study. They omit to mention that many theoretical advances in science did not result from experimentation, and that many theories were developed and substantiated by indirect means, such as consistency with other theoretical systems, use of ‘thought experiments’ and correlational studies, rather than by experimentally-based observation (Hacking, 1983). Misconceptions about the nature and purpose of experiments are also promoted by the popular media, especially prominent in the world of advertising with its insistence that washing powder X is “proven by experiment to wash whiter than any other product”. It is not uncommon for science textbooks to assert that an hypothesis can be rejected – and, by inference, another accepted – on the evidence provided by a single experimental test. Many suggest that this is the only role for experiments. It is also commonplace for teachers to insist on a clear demarcation between hypothesis generation and hypothesis testing. This kind of naïve interpretation of Popperian falsificationism carries with it the assumption that theory-independent evidence is obtainable and that unambiguous testing is possible. In practice, scientific experimentation is far from being a simple, straightforward matter, and science education that portrays it as such is grossly misleading. If ‘ordinary’, day-to-day and relatively passive observation of phenomena and events is theory dependent, as argued in chapter 3, how much more so is the active, interrogative observation of contrived events that constitutes experimentation? If observations are both unreliable (because of the frailty of our senses) and dependent on what the observer knows and assumes about the phenomenon being studied, and if experiments are predicated on the basis of particular assumptions about conceptual relationships, we cannot conclusively and confidently reject a theory on the basis of observations deriving from that experiment because the observations are impregnated with the very theory that is under test. It is important for students to realize that every experiment is set within a theoretical matrix (particular conceptual schemes and theories), a procedural matrix (a community approved ‘method’ or practice underpinned by theories and conventions about how to conduct, record and report experiments) and an instrumental matrix (theories underpinning the design and construction of all scientific instruments employed in the experiment, together with the theories of perception that underpin all observations). It is this complex of theoretical understanding and assumptions that gives both form and purpose to experiments. What counts as good research design, what kind of observations are 86 Derek Hodson - 978-90-8790-507-1 Downloaded from Brill.com11/09/2020 11:12:23AM via free access

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sought, what measurements are regarded as legitimate, what instruments may be utilized, and what sort of evidence is seen as crucial, are all determined by the theoretical matrix within which the scientist is working. It is the reason why experimental data are sometimes rejected on theoretical grounds and why there have been occasions when theory-based calculations have proved more acceptable than experimentally acquired data (Schaefer, 1986). Even when no error can be found in the experimental procedure, data may be rejected because it is insufficiently plausible in terms of current theory. Of course, this tendency to back theoretical judgement in the face of contrary observational evidence can sometimes work to the disadvantage of scientific development, as in the rejection of William Bray’s elegant experimental data because current theory disallowed the notion of oscillating chemical reactions, and continued to do so for almost 50 years (Epstein, 1987). Experiments form a critically important part of the scientist’s repertoire, so it is crucial that we don’t misrepresent that role in the school science curriculum. If Kuhn (1970) is correct, and historical evidence suggests that he is, theories are only abandoned when there is compelling evidence (long-standing and striking at the heart of the theory) and/or when an alternative and more promising theory becomes available. It is misleading to present students with the idea that theories are discarded because of a few negative results. In practice, all theories have to live with anomalous data; it is a natural feature of science. We seriously mislead students when we pretend that the kinds of experiments they perform in class constitute a straightforward and reliable means of choosing between rival theories. Experiments are enormously powerful for giving scientists precise information under highly contrived and highly controlled circumstances, but because experiments are conceived, designed and executed with a particular complex of theoretical understanding, considerable judgement is involved in appraising the significance of the evidence they furnish. Whether to accept the evidence, and in consequence to accept or reject the theory, reject the evidence, or conclude that some matters are still problematic and the experiment should be re-planned, is a decision that is not easily made. When scientists are working at the limits of secure knowledge there are sometimes uncertainties concerning the appropriateness of an experimental design, the robustness and reliability of the instruments (possibly new ones, designed for this particular inquiry) and even the ability of the technicians to achieve repeatable data. It is often the case that new craft expertise has to be acquired or a new laboratory technique developed, so it may be some considerable time before the eperiment ‘works properly’ in the sense of producing consistent data. Experimental testing of theories is not, therefore, an infallible single step procedure; rather, it is a multi-stage decision-making process monitored and validated by the scientific community. Unfortunately, as perusal of almost any school science textbook will confirm, we present students with a very different version of the nature and purpose of experiments. In particular, we neglect to make them aware that every experiment is set within a theoretical matrix that determines what can be done, how it can be done and how the data can be interpreted. The data does not speak for itself, as some textbooks suggest when they liken scientific investigation to detective work.2 87 Derek Hodson - 978-90-8790-507-1 Downloaded from Brill.com11/09/2020 11:12:23AM via free access

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Rather, the data means what the theory says it means. An important part of the misrepresentation of experiment in school science is that scientific claims are tested against reality. Not so! They are tested against our interpretation of reality, often using evidence collected by instruments that encode in material form a great deal of assumed theory that is subsequently implicit in the experimental conclusions (Latour, 1987). In addition, we seriously underestimate the complexity of the relationships among observation, experiment and theory. What we should be teaching students is that theory and experiment have an inter-dependent, interactive, reflexive relationship: experiments assist theory building (by giving feedback concerning theoretical speculation); theory, in turn, determines the kind of experiments that can and should be carried out, and determines how experimentallyacquired data are interpreted and used. Both experiment and theory, then, are tools for thinking in the quest for satisfactory and convincing explanations. Neither has absolute priority, though either may lead on a particular occasion. Newton et al. (1999) express this position particularly well when they say: “Observation and experiment are not the bedrock upon which science is built; rather, they are handmaidens to the rational activity of constituting knowledge claims through argument” (p. 555). The history of science provides many examples of developments during which theory was well ahead of experimental testing/corroboration and, equally, lots of instances of episodes during which there was an abundance of data but no satisfactory theory to account for it.3 LEARNING SCIENCE BY DOING SCIENCE

There is a long tradition in science education arguing that the most appropriate way to teach science is through activities designed to mimic the activities of scientists. This notion was particularly prominent in the penchant for discovery learning in the 1960s. In the United Kingdom, the major impetus for the promotion of discovery learning was the ‘progressive’ child-centred notion that inquiry-oriented teaching is close to children’s ‘natural forms of learning’. Long-standing beliefs that children are well-motivated by direct, inquiry-oriented experiences and learn primarily through unstructured, play-like activities were reinforced by Piaget’s descriptions of how the unstructured and self-directed observations and experimentation of children develop via a series of stages into sophisticated formal reasoning processes. Such was the frequency with which purely abstract reasoning seemed to be preceded by an operational stage in which understanding was rooted in the action itself, that there appeared to be an almost incontrovertible case for learning science through student-driven, hands-on inquiry methods. The assertion that the stage of independent thinking is achieved only by the “use of active methods which give broad scope to the spontaneous research of the child or adolescent and require that every new truth to be learnt be rediscovered” (Piaget, 1973, p. 15) was taken by the authors of the Nuffield science projects as theoretical justification for a revival of the heuristic approach first developed in the early 20th century by Henry Armstrong (Jenkins, 1979). Indeed, Piaget was quoted in support of the claim that adoption of other approaches would seriously prejudice student understanding: 88 Derek Hodson - 978-90-8790-507-1 Downloaded from Brill.com11/09/2020 11:12:23AM via free access

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Each time we prematurely teach a child something he would have discovered for himself, the child is kept from inventing it and consequently from understanding it completely. (Piaget, 1970, p. 715) In the United States, the major impetus for discovery learning came from the writings of Jerome Bruner and Joseph Schwab. In his influential essay ‘The Teaching of Science as Enquiry’, Schwab (1962) set out an agenda for a science curriculum emphasizing scientific inquiry as both content and method as the solution to what he perceived as a crisis in US science education. He argued that laboratory experiences should precede classroom instruction and that the laboratory manual should “cease to be a volume which tells the student what to do and what to expect”; it should be “replaced by permissive and open materials which point to areas in which problems can be found” (p. 55). According to Novak (1978) and Kirschner (1992), these assumptions were then compounded, on both sides of the Atlantic, by thinking based on a misinterpretation of Ausubel’s (1968) work on ‘meaningful’ versus ‘rote’ learning. Rote learning was falsely equated with transmission/reception methods and meaningful learning with discovery methods. A further confusion arose from the failure to distinguish considerations of how existing scientific knowledge is learned by students (what I have termed learning science) from considerations of how new scientific knowledge is generated and validated within the scientific community (learning about science), and from experiences in which students themselves might engage in authentic scientific inquiry (doing science) (see chapter 1, footnote 8). Because scientists achieve their goals largely through observation and experiment, it was assumed that the best way of learning of science is through activities based on a model of scientific inquiry. Unfortunately, the Nuffield courses in the UK and the BSCS, PSSC and ChemStudy projects in the US compounded these problematic assumptions by fusing progressive child-centred views emphasizing direct experience and learning by inquiry and discovery with inductivist ideas about the nature of scientific inquiry: A learning-by-discovery sequence involves induction. This is the procedure of giving exemplars of a more general case which permits the student to induce the proposition involved… General understanding is induced from a wealth of experience with specific cases. (Glaser, 1966, pp. 15 & 18) In promoting the value of direct experience and an inquiry-oriented curriculum, in stressing the motivational value of ‘finding out for oneself ’, and in their use of terms such as observation, experiment and investigation, the curriculum developers of the 1960s produced a model of learning which seemed to fit perfectly the traditional inductivist views of scientific method. As Cawthron and Rowell (1978) say: It all seemed to fit; the logic of knowledge and the psychology of knowledge had coalesced under the mesmeric umbrella term ‘discovery’ and there was no very obvious reason for educators to look further than the traditional inductivist-empiricist explanation of the process. (p. 38)

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What had started out as a psychological justification of learning by discovery had slipped over into an epistemological argument. Not only was discovery learning philosophically unsound (see chapter 3), it was pedagogically unworkable. For example, early in the original Nuffield Physics course, students are provided with a lever, a fulcrum and some weights (in the form of uniform metal squares) and are invited to explore and “find out what you can”. No particular problem is stated; no procedure is recommended: “Find out what you can about a balancing see-saw, with different arrangements of squares (weights) on it… See if you can find out some pattern about balancing that you could tell to other people” (Nuffield Physics, 1967, p. 186). It was assumed that the law of moments would simply emerge from undirected, open-ended exploration. Nothing could be further from the truth. First, because the pivot is below the centre of gravity the system doesn’t balance in the way the students expect. If the weights are suspended below the pivot, as in a set of scales, the beam will balance, but there is little chance that the students will discover this for themselves. Second, children tend to spread the weights irregularly along the entire length of the beam. The complexity of this arrangement obscures the simple relationship the teacher is seeking. Consequently, advice is proffered on how to make the problem simpler and instructions are issued about the best way to proceed. Similar things happen whenever students are presented with this kind of openended situation. For example, in another Nuffield Physics activity, students are given a bar magnet, a card and a shaker of iron filings, with the aid of which they are supposed to discover magnetic lines of force. Even teachers, who know that these lines of force can be detected with iron filings, sometimes have great difficulty revealing them. What chance is there for students, who do not know what they looking for? They cannot discover something for which they are conceptually unprepared. Without the relevant conceptual framework, they don’t know where to look, how to look or how to recognize the lines as significant, even if they find them. Additionally, there are many more entertaining things that young students can find to do with a magnet and a batch of iron filings, as many harassed teachers can testify. There is also the problem that many so-called ‘experiments’ fail to give the results that are required to meet the curriculum goals relating to content. Students may make errors in observing, measuring or recording data, have accidents, lose interest or just fail to finish. They may be distracted by all the clutter and ‘noise’ of hands-on activity; they may become so immersed in the practical details of what they are doing that they miss the conceptual significance of it (Hodson, 1993c). Even if they ‘do everything right’, the waywardness of shoddy and sometimes poorly maintained school apparatus may still lead them astray. As Dearden (1967) reminds us, “a teaching method which genuinely leaves things open for discovery also necessarily leaves open the opportunity for not discovering them” (p. 153, emphasis added). Many teachers responded to the pedagogical problems of discovery learning by engaging in what came to be known as ‘directed’ or ‘guided’ discovery. It follows this general form: the teacher guides the initial class discussion of the ‘experiment’ that is to be carried out; orchestrates the design of the ‘experiment’ – using the 90 Derek Hodson - 978-90-8790-507-1 Downloaded from Brill.com11/09/2020 11:12:23AM via free access

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apparatus that has been previously laid out on the teacher’s bench; wanders around the classroom/laboratory advising the ‘experimenters’ on matters of technique and giving advice on recognizing and recording the significant observations (and ignoring or re-making others); and guides the subsequent class discussion towards the ‘discovery’ of the underlying theoretical principles to be used in the explanation of the results. Throughout all these activities the teacher pretends that the class is engaged in open-ended inquiry and deliberately suppresses (for the moment) the very knowledge that was used in setting up the so-called inquiry. What purports to be student-driven inquiry finishes up as a subtle but very powerful form of teacher direction and control. To set up a situation that claims to be student-driven and open-ended but which, in practice, demands a particular outcome is to confuse learning science (which has a definite ‘result’ in mind) with doing science (which hasn’t). Not only is this confusing for teachers, because they are sometimes left in the situation where they are unable to respond properly to unexpected results, it can be very disorienting for students. The confusion that can arise is neatly encapsulated in an extract from some classroom observation work reported by Atkinson and Delamont (1976). It concerns a series of lessons on photosynthesis in which the class had covered growing leaves with metal foil, leaving several uncovered areas on each leaf. After a few days the students tested for starch in various parts of the leaf. The teacher tells the class that if starch is present only in the uncovered parts of the leaf it can be concluded that light is necessary for starch production. Delamont reports how one girl (Michelle) protests that such evidence constitutes proof; she suggests that there could be other explanations. Upon which, another student (Sharon) says: “Of course it’ll prove it. We wouldn’t be wasting our time doing it if it. didn’t”. This episode highlights the crucial distinction between learning science and doing science. Sharon has recognized the sham of the teacher’s supposed discovery approach. She sees that the teacher has set up the activity in a particular way in order to ensure a particular outcome, and thereby lead the class towards particular knowledge and understanding. For her, the class is learning science. Michelle, meanwhile, believes that the class is engaged in a real scientific inquiry – a genuine experimental study of the phenomenon of starch production in leaves. For her, the class is doing science. The teacher’s problem is that she believes she can, and should, be doing both. Of more significance in the context of this book, discovery learning projects all manner of undesirable images of science. First, that it proceeds via induction; second, that experiments are unplanned and discovery is largely accidental; third, though it seems contradictory to the others, that scientists know what the results of an experiment should be – hence the teacher’s impatience when activities in the school laboratory do not turn out as the curriculum guidelines require. While it is relatively easy to see how and why the curriculum developers of the 1960s, without the benefit of those views in the philosophy of science outlined in chapter 44 and lacking research knowledge concerning children’s learning in science only generated since the mid-1980s, were attracted to inductively-oriented discovery learning, it is much more difficult to see why some science educators continue to advocate this approach (see, for example, Sherman, 2000). One possibility is that the inductivist view of science encapsulated in discovery learning is perceived by teachers as more straightforward than other models of science and, 91 Derek Hodson - 978-90-8790-507-1 Downloaded from Brill.com11/09/2020 11:12:23AM via free access

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therefore, easier for students to follow. Indeed, there is evidence to suggest that teachers who adopt alternative models of science with high ability groups may still revert to inductivist views with those classes perceived as less able (Hodson, 1993a). A second reason is the high respect that primary school teachers have for childcentred methods, which, because of common linguistic features (inquiry, investigation, open-ended, unstructured, observation, discovery, etc.) appear to favour an inductivist model of science (Harris & Taylor, 1983). A third reason is located in teachers’ own inadequate views about the nature of science, which are largely derived from their own learning experiences in school and university, reinforced by the mythology of school science textbooks and curriculum documents. A fourth reason is, perhaps, an emotional one: a temptation to cling to the notion that there is a distinctive scientific method, even a precise algorithm for conducting scientific investigations. This particular emotional need is, in part, responsible for the absurdities of the approach to science teaching outlined in the next section. SCIENCE AS DISCRETE, GENERIC PROCESSES

Another major distortion of the nature of scientific inquiry is perpetrated by those curricula that adopt the so-called ‘Process Approach’ to science education. Since this movement in science education is addressed in some detail by Wellington (1989), Hodson (1996) and Osborne and Simon (1996), little needs to be said here about its history and development, beyond noting that Buchan and Jenkins (1992) attribute its prominence in the UK during the 1980s and early 1990s to the merger of hands-on pedagogy with the drive for rigorous and systematic assessment. Hodson (1996) identifies an equally curious coalition underpinning process-oriented science in the United States: “an uneasy amalgam resulting from the application of the logical-analytical approach to curriculum planning to child-centred pedagogy” (p. 121) – in effect, a technology of active learning. Prominent British examples of process-oriented science include Warwick Process Science (Screen 1986, 1988), Science in Process (Inner London Education Authority, 1987) and Active Science (Coles et al., 1988). In the United States, the most notable example is Science – A Process Approach (S-APA) (American Association for the Advancement of Science, 1967), a course based largely on the work of Robert Gagne (1963, 1965). Although S-APA is no longer in print its influence persists in an approach to elementary science education that Cain and Evans (1990) refer to as Sciencing (see also, Sherman (2000) and Abruscato (2004)). Underpinning all process-oriented approaches, no matter what their origin, are several basic assumptions, each of which deserves close critical scrutiny. – Scientific inquiry can be described in terms of a series of discrete processes: observing, inferring, measuring, predicting, classifying, collecting data, recording data, formulating hypotheses, controlling variables, and so on. – The processes are generic – that is, they are context-independent (i.e., theoryfree) and, therefore, transferable. – Scientific knowledge results from engagement in these processes. – Performance of these skills can be readily observed and accurately and reliably measured. 92 Derek Hodson - 978-90-8790-507-1 Downloaded from Brill.com11/09/2020 11:12:23AM via free access

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– By practising and developing these skills, students acquire the capability to conduct scientific investigations. Considerable space was devoted in chapter 3 to the argument that observation is theory-impregnated and, therefore, that the notion of theory-free observation is absurd. Also in chapter 3, a great deal of attention was devoted to the relationship between observation and inference – in particular, to the spurious claim of many science curricula that there is a simple and clear demarcation between them. Similar arguments extend to all the other processes of science (Millar & Driver, 1987). To be engaged in any of the processes of scientific inquiry one needs a focus of attention: one has to classify or measure something, rather than something else, one has to hypothesize about particular entities or events, and so on. It is not possible to engage in these activities independently of content. Moreover, the way one classifies, measures and hypothesizes, and one’s level of sophistication in doing so, depend crucially on one’s theoretical understanding. Science education is not about teaching students to observe, classify, measure and hypothesize per se. They can already do these things perfectly well, and have been doing so for many years, since long before they came to science class, and they will carry on doing these things after they leave the school science laboratory. What school science is concerned with is scientific classification, scientific measurement, scientific hypothesizing. What makes these processes scientific is the utilization of relevant and appropriate science concepts in pursuit of scientific purposes. In other words, all these processes are theory-laden and theory-driven. Put simply, doing science is a theory-driven activity. Scientific classification, for example, is not just a matter of noting similarities and differences, or it would be sufficient in science lessons to classify banknotes and postage stamps using criteria such as country of origin, colour, size and design characteristics. Rather, it involves the utilization of scientifically significant and appropriate categories, suited to the purpose for which the classification is being carried out. Different purposes demand different criteria, and may involve different theoretical understanding. It follows that success in classifying depends on appropriate matching of theory-based categories to purpose. It depends crucially on the knowledge, experience, assumptions and expectations about purpose that the wouldbe classifier brings to the task. A particular classification is not necessarily ‘right’ or ‘wrong’; rather, it reflects the sophistication of our knowledge and the nature of our intent. The decision to classify an animal as mammal/reptile/fish or lives on land/lives in water or carnivore/herbivore depends on why we wish to classify. Is the classification intended to inform the study of evolutionary processes? Is it part of preparation for ecological work? Or is it to help us find our way around the local zoo? Any classroom activity involving classification or ‘looking for patterns’ (as curriculum documents sometimes describe it) is, therefore, inextricably linked with teaching theory (appropriate concepts for classification) and identifying a legitimate scientific purpose for the classification. As students acquire more theory they are able to adopt increasingly abstract criteria. Thus, in chemistry, for example, classification shifts from simple observational properties such as flammability and solubility towards bond type and polarity. 93 Derek Hodson - 978-90-8790-507-1 Downloaded from Brill.com11/09/2020 11:12:23AM via free access

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At the risk of beating the argument to death with a stick, the same can be said for all the other processes of science: measuring, predicting, collecting and recording data, and the like. None of them can be carried out in a theory-free way. For example, the notion that hypotheses can be formulated or predictions made independently of content is just too absurd to be seriously contemplated. What can possibly constitute the basis of an hypothesis or a prediction other than good understanding of the phenomenon or event under consideration? Without theoretical understanding, a hypothesis or prediction is no more than a shot-in-the-dark, a blind guess – an activity with little or no educational value, and certainly no scientific value. McNairy (1985), a strong advocate of the process approach, argues that whether the student makes a ‘correct’ or ‘incorrect’ prediction does not matter. I agree wholeheartedly, but with major and critical caveats. What does matter is that the student has good reasons for making the prediction. What does matter is that the student can establish a sound line of argument from her/his current understanding as the basis for the prediction. What does matter is that the student knows enough about scientific inquiry to know what would constitute an appropriate and rigorous test of the prediction. To make the argument one last time, the control of variables (the basis of experimental testing) cannot be achieved without substantial theoretical understanding of the phenomenon or event under study. How would a scientist adopting a theory-free approach know what the important variables are likely to be? In a state of ignorance, the experimenter cannot control any variables, except fortuitously. Clearly, the planning of any experiment in which variables are carefully and systematically varied is a theory-driven and theory-impregnated activity. TRANSFERABILITY

The theory-impregnated nature of scientific processes creates enormous problems for the notion of transferability, which is, of course, a central principle of the process approach to science education. [Process skills] can be taught in a specific content area and subsequently used to solve problems from other areas within science, or from subjects such as social science or mathematics. The potential generalizability of the process skills represents an important reason for emphasizing their development and use. (Tobin & Capie, 1980, p. 590) A consequence of accepting the view that experience of scientific processes in any context is as significant as experience in any other is a commitment to the following notions. i. No particular conceptual understanding is significant – it doesn’t matter what scientific content we teach. ii. Ability to observe, classify and measure in one context can be taken as indicative of a student’s capacity to do so in an entirely different context. These arguments have been taken to an absurd degree by those who advocate rigorous and systematic skills-based testing in science – a movement which I have described elsewhere (Hodson, 1993b) as educationally worthless (because it 94 Derek Hodson - 978-90-8790-507-1 Downloaded from Brill.com11/09/2020 11:12:23AM via free access

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trivializes learning), pedagogically dangerous (because it encourages bad teaching), professionally debasing (because it de-skills teachers) and socially undesirable (because of powerful hidden messages concerning control and compliance). My concern here is that this approach to assessment and evaluation is philosophically unsound in its claim that competence in a skill such as observing or measuring can be learned in a particular context (any context) and subsequently transferred to an entirely different one with no apparent loss of capability.5 One is tempted to ask in what sense the skills learned in observing the behaviour in an ant colony can be successfully utilized in qualitative inorganic analysis or in making astronomical observations? In what sense does learning to dissect a dogfish help a student to use an oscilloscope or to synthesize a complex organic molecule? If we applied this principle of transferability between unlike contexts to the world outside school we would happily submit to a brain operation carried out by a specialist in obstetrics. In the real world, including the world of scientific practice, the context in which skills are acquired is crucial to the proper performance of that skill and to our confidence in the practitioner. In the words of Finley and Pocovi (2000), “a high energy physicist dropped in the middle of a human genome project and asked to collect the relevant observations would probably be clueless as to what observations were even possible, let alone which ones would be relevant to the problem of unraveling the human genome” (p. 58). SCIENTIFIC INQUIRY AS A SIMPLE ALGORITHMIC PROCEDURE

The final absurdity of the Process Approach to which I wish to draw attention is the assumption that once students have acquired the separate skills of observing, classifying, measuring, and so on, they can put them together into a procedure for doing science. In other words, it is assumed that doing science consists in the sum of its parts and is no more than the sum of its parts. In short, scientific inquiry comprises an algorithm to be applied in all circumstances. There are two principle arguments against this proposition. The first is that there is no empirical evidence from educational research to support it. Success in carrying out a series of decontextualized tasks focusing on observation, classification or measurement says very little about a student’s capacity to conduct a scientific investigation, much less about her or his ability to design such an inquiry. It is sometimes the case that students who perform adequately on these sanitized tasks are unable to integrate the skills into a coherent and effective strategy for investigation. Conversely, many who perform poorly in the tests can engage in interesting and successful scientific inquiry when they are suitably encouraged and given the freedom and support to follow their interests. The second counter argument relates to Paul Feyerabend’s (1975) assertion that the idea of a fixed method of science rests on too naïve a view of what is involved in conducting investigations and building theories. As noted at the end of chapter 4, Feyerabend states that the only principle that is always applicable in conducting the complex and sometimes chaotic business of science is the principle Anything Goes. In similar vein, Percy Bridgman (1950) remarked that “scientific method, as far as 95 Derek Hodson - 978-90-8790-507-1 Downloaded from Brill.com11/09/2020 11:12:23AM via free access

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it is a method, is nothing more than doing one’s damnedest with one’s mind, no holds barred” (p. 278). Much of Feyerabend’s writing – ‘epistemological anarchy’, as his critics have labelled it – casts doubt on the view of science projected in most school science curricula and on the public image of science and scientists. For example, he questions one of the cornerstones of school science: respect for the ‘facts’. Regardless of whether the curriculum projects an inductivist or a falsificationist model of science, correspondence with the facts (the observational aspects of a theory) is taken as a measure of a theory’s ‘truth’, or verisimilitude as Popper (1972) calls it. More particularly, lack of correspondence is taken as grounds for theory rejection. Feyerabend (1975) takes a somewhat different view: The suspicion arises that the absence of major difficulties is a result of the decrease of empirical content brought about by the elimination of alternatives, and of facts that can be discovered with their help. (p. 43) A theory’s success in accounting for observational evidence is a consequence of the way in which the theory is constructed – that is, in building a theory, scientists ensure that it explains the observational data in its domain and excludes the possibility of generating the evidence that would or could refute it. Moreover, Feyerabend argues, “empirical ‘evidence’ may be created by a procedure which quotes as its justification the very same evidence it has produced” (p. 44). In a sense, theories are like computer simulations: the ‘facts’ follow from the initial assumptions; the theory is designed in such a way that it creates the factual evidence that is subsequently used to justify the theory.6 The theory will explain the facts because it was designed to do so; there are no ‘counter facts’ because the theory was designed to exclude them, or to ensure that they cannot be revealed. For how can we possibly test, or improve upon, the truth of a theory if it is built in such a manner that any conceivable event can be described, and explained, in terms of its principles? (p. 45) The theory may well be false, but it appears valid because it creates its own confirmatory evidence in consequence of what it allows and disallows. Scientists who subscribe to a particular theory may find it difficult, if not impossible, to recognize deficiencies in that structure because their theoretical biases and expectations blind them to the theory’s shortcomings and prevent them from obtaining, or even from seeking, appropriate counter evidence. How can we possibly examine something we are using all the time? How can we analyse the terms in which we habitually express our most simple and straightforward observations and reveal their presuppositions? (p. 32) The only way of casting doubt on a theory is by creating a new theory, capable of looking at the world in a different way. Often, the evidence that might refute a theory can only be unearthed with the help of an incompatible alternative. When new theories are employed, they often reveal new ‘facts’ of a kind very different from those uncovered by the old theory. Thus, a new theory may be supported by an obser96 Derek Hodson - 978-90-8790-507-1 Downloaded from Brill.com11/09/2020 11:12:23AM via free access

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vational test that was not possible within the context of the old theory; the earlier theory may be rejected on the basis of a test that would have been quite inconceivable within the conceptual framework of the old theory. Therefore, says Feyerabend (1975), we should proceed counter inductively: introduce and elaborate hypotheses that are inconsistent with existing theories and/or with the facts that derive from them, even if those theories are “highly confirmed and generally accepted” (p. 105). As the new theory is elaborated it will generate its own confirmatory evidence. If the new theory is satisfying, for whatever reasons, allegiance will shift to it and the old theory will simply wither away. The old theory is not falsified; it is abandoned. The new theory does not necessarily solve the problems of the old, it dissolves them. Old problems are removed because the new theory declares non-existent the things that constituted the problems. Whether one accepts Feyerabend’s principle of counter induction or not, it is clear that correspondence with the observable facts does not afford any increased truth status on a theory, it simply means that it may be true. However, there may be an alternative theory that also agrees with the facts. Theory can still vary though all possible observations be fixed. Physical theories can be at odds with each other and yet compatible with all possible data even in the broadest sense. In a word, they can be logically incompatible and empirically equivalent. (Quine, 1970, p. 179) In such circumstances, there cannot be any justification for accepting (or rejecting) one of the statements that is not a justification for accepting (or rejecting) the other. Put differently, if observations provide equally good evidence for each of the generalizations, then they provide no significant evidence for either of them. THEORY ACCEPTANCE AND REJECTION

Posner et al. (1982) argue that a new conceptual scheme will be accepted only if learners are dissatisfied with their current belief/understanding and have access to a new or better idea with which to replace it. To gain acceptance the new idea should be intelligible, plausible and fruitful. Feyerabend seems to argue that in science itself (rather than in learning science) it may be the other way around. Ideas become clear and reasonable only after parts of them have been used for a long time and have been refined through use. Nor does science necessarily begin with a problem, as Popper alleges. Often it starts with ‘idle play’, which develops into a solution to a problem that only becomes apparent after the event. We do not think and then act, Feyerabend says, we act and then think – much as children do. We work with our ideas, by whatever means we can, until the theory has solved its own problems – that is, succeeded in creating the evidence that subsequently justifies it. In Feyerabend’s words, “Such unreasonable, nonsensical, unmethodical foreplay thus turns out to be an unavoidable precondition of clarity and of empirical success” (1975, p. 27). In consequence, science is much more sloppy and irrational than the conventional image would suggest: “Without chaos, no knowledge… Without a frequent dismissal of reason, no progress. Ideas which today form the very basis of science exist only because there were such things as prejudice, conceit, passion; 97 Derek Hodson - 978-90-8790-507-1 Downloaded from Brill.com11/09/2020 11:12:23AM via free access

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because these things opposed reason and because they were permitted to have their way” (1975, p. 179). The rationality of the chosen method is only seen afterwards, when satisfactory conclusions have emerged. Indeed, it could be argued that rationality is created retrospectively, as part of the case scientists build to persuade others of the validity of the findings, as Max Born (1934) remarked: I believe there is is no philosophical highroad in science, with epistemological signposts. No, we are in a jungle and find our way by trial and error, building our road behind us as we proceed. We do not find signposts at crossroads, but our own scouts erect them, to help the rest. (p. 44) The crux of Feyerabend’s argument is that in order to make progress, scientists should do whatever suits the particular circumstances in which they find themselves – the nature of the problem, the range of theoretical perspectives available, the opportunities and facilities for observation and experiment, and so on. Sometimes one kind of move may assist progress, sometimes another. Sometimes the most outrageous move pays off, and sometimes it proves to be just another crazy idea that got nowhere. As Albert Einstein is reputed to have said, the scientist needs to be “an unscrupulous opportunist” (Schilpp, 1951, p. 683), at least from the point of view of those who advocate a strict method of science. Given the complexity of the scientific enterprise, the myriad of different starting points for an investigation, the major differences in knowledge, experience and personality among scientists, and the likelihood of substantial variations in the range of facilities and resources on which individual scientists can draw, it would be surprising if all scientists proceeded in the same way (White, 1983). Interestingly, young children consider diversity of approach inevitable; they have no expectations of a particular method for doing science (Hodson, 1990). Teachers and science textbooks create the expectation of a single method through their continual reference to the scientific method, perhaps in an effort to simplify the teaching of integrated or combined science. However, the assertion that ‘anything goes’ should not be interpreted as a statement that science has no methods. It implies the absence of a prescribed method – an algorithm – rather than the absence of methods. It should not be taken too literally. Scientists wishing to make progress cannot just do anything. As Newton-Smith (1981) observes, “Lazing in the sun reading astrology is highly unlikely to lead to the invention of a predictively powerful theory about the constituents of the quark” (p. 269). Nor, despite Feyerabend’s advocacy of ‘rule breaking’, can every rule be broken. Moreover, while any particular rule may (and perhaps should) be violated in a particular set of circumstances, it is not rational to violate all rules simultaneously.7 Particular rules are violated to solve particular theoretical problems, but other rules governing the ways in which the new idea is appraised (concern for explanatory adequacy, simplicity, clarity, accuracy, insistence on testing, and so on) continue to exercise control over what new ideas can be generated. Science has many methods, including widely varying techniques and procedures for conducting experiments, analysing data and presenting results. Not to follow these procedures carefully and systematically is, in some important sense, to be unscientific. At 98 Derek Hodson - 978-90-8790-507-1 Downloaded from Brill.com11/09/2020 11:12:23AM via free access

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the very least, it is to be sloppy and unsystematic to an extent that prejudices the scientific quality of the work being conducted. Implying that the world of the scientist is totally anarchic does students (and the public image of science) as gross a disservice as implying that science has a single, all-powerful algorithmic method that is applicable in all circumstances. Indeed, in his later work, Feyerabend substantially modified his position on methodological rules, arguing that there are methodological rules but they are highly sensitive to their context of use and have no applicability outside that context.. A naïve anarchist says (a) that both absolute rules and context dependent rules have their limits and infers (b) that all rules and standards are worthless and should be given up… I agree with (a) but I do not agree with (b). I argue that all rules have their limits and that there is no comprehensive ‘rationality’, I do not argue that we should proceed without rules and standards. (Feyerabend, 1978, p. 32) It is also important to note that while the new idea may lead to the rejection of some existing theoretical constructs, all is not discarded. Some elements of the previous framework must remain, in the light of which the new structure makes sense and proves fruitful: “The fact remains that no one can depart from too much of the preselection at once and expect to make progress… What we perceive as revolutionary innovation in a field always challenges only a little of the preselection. Only because we focus on the contrast rather than the continuity does innovation seem so much of a departure” (Perkins, 1981, p. 279). Claims to scientific knowledge have to be publicly argued and publicly justified; the data from which conclusions are drawn and theories built have to be reproducible and the chain of argument from premise to conclusion has to be clear. In other words, science does have methods (the things that scientists routinely do8) and it does have criteria for judging the validity of knowledge claims, but their particular form depends on the particular circumstances: the matter under consideration, the conceptual structure (‘research programme’, as Lakatos calls it) within which the investigator frames the problem(s), the investigative techniques and instrumentation devices available, the scientists’ familiarity with them, and so on. Over time, new methods are introduced and old ones are refined or discarded. By making a selection of processes and procedures from the range of those currently available and approved by the community of practitioners, scientists choose a ‘method’ or cluster of methods that they consider contextually appropriate. There are no universal decision criteria for what to do and how to do it. All decisions are ‘local’ – determined by the particular circumstances of individual investigations – and, therefore, idiosyncratic.9 Oakeshott (1962) expresses this view as follows: The coherence of scientific activity (does not) lie in a body of principles or rules to be observed by the scientist, a ‘scientific method’; such rules and principles no doubt exist, but they also are only abridgements of the activity which at all points goes beyond them, in particular, in the connoisseurship of knowing how and when to apply them. Its coherence lies nowhere but in the way the scientist goes about his investigation, in the traditions of scientific 99 Derek Hodson - 978-90-8790-507-1 Downloaded from Brill.com11/09/2020 11:12:23AM via free access

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inquiry. These traditions are not fixed and finished, and they are not to be identified with merely current scientific opinion, or with an identifiable ‘method’; they are the guide in every piece of scientific investigation and at the same time they are being extended and enlarged wherever scientists are at work. (p. 103) Particularly intriguing are the differences in approach adopted by practitioners in the different sciences – something on which school science is strangely quiet. Bauer (1992) comments as follows: “The differences among adepts of the various sciences go beyond matters of theory, method, and vocabulary to subtler habits of thought and even to customs of behavior, to such an extent that the differences… can aptly be described as cultural” (p. 25). Ernst Mayr (1988) claims that many famous controversies in biology are a direct consequence of these kinds of ‘cultural differences’. The differences between the sciences, particularly the extent to which the discipline tends to be theory-driven or data-driven and whether it seeks to establish a simple linear cause and effect relationship or a complex web of interrelating causal factors, speaks to the issue of alternative sciences and whether, for example, there is any meaning to expressions such as ethnoscience and feminist or gynocentric science (see chapter 7). When the community comes to appraise a piece of scientific research, one of its criteria of judgement is a consideration of the methods employed. Were they well chosen? Were they satisfactorily performed? Could/should the investigation have been conducted differently? How was the evidence acquired? What instruments were used, and why? What errors are likely and how, if at all, were they estimated? Under test, too, is the craft expertise of the experimenter and the sometimes complex ‘know how’ necessary to ensure that the experimental procedures ‘work properly’. Sometimes other scientists are convinced by the quality of the data, the elegance of the method or the persuasiveness of the argument; the particular criteria deployed will vary with the circumstances. A claim to knowledge deriving from experiment is likely to be accepted as valid if the various ways in which the claim could be invalid have been thoroughly investigated and, as a result of the investigation, have been discounted. This is what Mayo (1996) calls “severe experimental testing”: an experiment constitutes support for a claim only when possible sources of error have been eliminated and, in consequence, the claim would be unlikely to “pass the series of tests” unless it were true.10 For example, Eddington could not have observed the effect of light bending in the vicinity of the Sun unless there is a fairly good possibility that Einstein’s theories about gravity are correct. It is important to emphasize to students just how difficult it is to assemble the mass of evidence necessary to install a new theory (and, thereby, overthrow an existing one) and to present it in such a way that enables the claim to achieve consensus within the community of practitioners. It is the demand for consensus within the community of scientists about what should be accepted as legitimate knowledge and the requirement that all claims to knowledge meet community-based criteria of validity, reliability and methodological appropriateness that invests scientific knowledge with its particular kind of authority. Unlike everyday knowledge, which needs little beyond simple consensus 100 Derek Hodson - 978-90-8790-507-1 Downloaded from Brill.com11/09/2020 11:12:23AM via free access

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or the personal authority of the knower for justification, scientific knowledge has to survive rigorous critical scrutiny by members of the scientific community, who achieve consensus by employing well-characterized methods and clearly stated criteria of judgement. Longino (1994) identifies four conditions that a community of practitioners must meet if consensus is to count as knowledge rather than mere opinion. – There must be publicly recognized forums for criticism – There must be publicly recognized standards for evaluation of theory and practice – There must be uptake of criticism – the community needs to do more than merely tolerate dissent; it must act on it. – There must be equality of intellectual authority – what is included or excluded must result from critical dialogue rather than the exercise of political or economic power. If it survives critical scrutiny by the community, using these public methods of evaluation and judgement, the knowledge item (model, theory, experimental procedure, instrumental technique, or whatever) becomes part of the written record of the scientific community and is made available to others.11 Because of this mechanism and the confidence that practitioners have in it, science is cumulative; current researchers utilize the knowledge generated by previous scientists and, in doing so, may develop it or discard it. In other words, science has a history, and although a theory may be displaced by one judged to be ‘better’, it retains its historically-located validity. STUDENTS’ VIEWS

As noted in chapter 2, most school age students and many undergraduates hold the view that scientific knowledge can be proven by means of careful appraisal of experimentally acquired data, though primary (elementary) school students sometimes see experiments as unplanned or highly speculative activities that often give rise to unexpected outcomes (Duveen et al., 1993). Understandably, as they progress through the school system, students begin to reject the ‘cartoon image’ of scientific inquiry in favour of the ‘school curriculum image’ (Solomon, et al., 1996). Whether this results in an authentic view of experiment and the relationship between evidence and theory depends, of course, on the nature of the curriculum and the priorities of the teacher. In recent years there has been widespread adoption of the so-called ‘fair testing’ approach to investigative work in school science, especially in the United Kingdom (Watson et al., 1999; Watson, 2000). It is an approach that reinforces the view that scientific inquiry consists in the isolation and systematic manipulation of variables. This ‘standardization’ of scientific inquiry contributes little to students’ understanding of the methods employed in ecology, geology, astronomy and meteorology – what Mayer and Kumano (1999) call the “systems sciences”, in which it is field work (rather than lab work) and the monitoring of changes over time (rather than regarding time as a variable to be controlled) that are important, and where emphasis shifts from analysis to wholism and quantitative relationships are replaced by 101 Derek Hodson - 978-90-8790-507-1 Downloaded from Brill.com11/09/2020 11:12:23AM via free access

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‘thick description’ in qualitative terms. Discussion in chapters 7, 8 and 9 will raise questions about whether these elements of the ‘systems sciences’ should be regarded as impregnating all sciences in the 21st Century. Perhaps this would be the way in which scientific knowledge could be transformed into scientific wisdom and attention focused on the kinds of social and environmental problems discussed in chapters 1 and 2. The ubiquity of the ‘fair testing’ approach may also be partly responsible for the major findings of studies by Millar et al. (1994), Leach (1999), Robertson (1999) and Ryder and Leach (2000) that students at all academic levels have little awareness of the significance of theory in the interpretation of data and, conversely, often fail to recognize the role of evidence in the appraisal of theory. Hogan (2000) has pointed out that many students have difficulty relating their experiences in school science lessons during hands-on, investigative work to their ‘formal’ knowledge of the protocols, practices and procedures of the scientific community. One way of attending to this shortcoming is to provide more metatalk about purposes and procedures during laboratory work and field work. Another way is to provide more explicit instruction about the relationships between models and theories in science – an issue that is addressed in chapter 6. ENDNOTES 1

2

3 4

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6

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8 9

10 11

Bencze (1996) provides a detailed argument for the promotion of correlational studies in school science and a critical discussion of their distinctive features, including systematic inquiry via statistical control. Gallagher and Ingram (1984) are typical of those textbook authors who adopt this position when they say that “science is about asking questions… you ask scientific questions when you are reasonably sure that the answers you get can be trusted” (p. 6). In other words, there is a true and certain explanation located in the facts revealed by observation and experiment. A detailed case for including the history of science in the school curriculum is provided in chapter 8. The deliberations that led to the discovery learning movement preceded the publication of key works by Kuhn, Lakatos and Feyerabend. Also, given the lengthy time lag between the publication of major works in philosophy and psychology and their appearance in the consciousness of teachers, it is safe to say that even Popper’s work was not well known among science educators until well into the 1960s. A much more detailed analysis of the philosophical problems associated with this approach can be found in Hodson (1992b). This situation is evident in school science when ‘experiments’ are conducted to ‘prove Ohm’s law’ using equipment calibrated on the assumption that Ohm’s law is valid. It should be emphasized that it is not irrational, as some of Feyerabend’s critics assert, to violate a rule, any more than it is necessarily rational to follow a set of rules. The nature of the rules and the context of action determine the rationality of the conduct. The notion that science is simply ‘what scientists do’ will be discussed in chapter 7. The implications of this position for teaching students about science and providing opportunities for them to conduct their own scientific investigations are addressed in Hodson (1992b; 1993b,c). Questions about the ‘truth’ of scientific knowledge are examined in chapter 6. The extent to which the community-approved procedures for appraising and validating scientific knowledge are able to guarantee the integrity of the scientific enterprise will be discussed further in chapters 6 and 7.

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REALISM OR INSTRUMENTALISM What Position for School Science?

Closely linked with arguments about how scientists generate new scientific knowledge (see chapter 5) is consideration of the role and status of that knowledge. Some years ago, in the early days of the Nuffield science teaching projects in the UK, Ernest Coulson (then Director of the Nuffield Chemistry project) said that it was important for students to develop “a proper view of theory”. At the time, I was teaching in a Nuffield ‘pilot school’, where curriculum materials and new approaches to teaching and learning science were being trialled, and my problem was that I didn’t know what “a proper view of theory” is supposed to be. For example, it was fairly common for science textbooks, teachers and curriculum documents to draw an analogy between science and detective work, thus implying that there is a correct version of events and phenomena, and that the application of good scientific procedures and the adoption of appropriate attitudes will enable scientists to arrive at the truth about the world. Philosophers of science refer to this position as naïve realism. It is a view that is still promoted in some science textbooks. At the other extreme of the ‘philosophical spectrum’ is instrumentalism (one of several variants of ‘anti-realism’1) – the notion that theories are simply convenient devices (‘fictions’) that enable us to predict, manipulate and control. Created entities like atoms, electrons, genes, gravitational fields and black holes are built into theoretical structures designed to account for ‘the world beneath surface appearances’ and give scientists a means of interacting with the real world in predictable ways.2 Provided that we solve our problems quickly and accurately (e.g., predicting the time of the next solar eclipse), it really doesn’t matter whether the theory employed to solve the problem or make the calculation is true or not, or whether the theoretical constructs really exist. Moreover, because it has no other value, the ‘predictive device’ can be discarded once it has ‘done the job’. Truth is irrelevant. Utility is the significant criterion. Thus, the kinetic theory of gases enables us to state precise relationships among volume, temperature and pressure and to predict the behaviour of gases on heating, but whether the molecules postulated in the theory actually exist, or not, is irrelevant. The position is neatly encapsulated in this quotation form the work of Ernst Mach (1911) In the investigation of nature, we have to deal only with knowledge of the connexion of appearances with one another. What we represent to ourselves behind the appearances exists only in our understanding, and has for us the value of a memoria technica or formula, whose form, because it is arbitrary and irrelevant, varies very easily with the standpoint of our culture. (p. 49)

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Toulmin (1963) adopts a less extreme form of instrumentalism, arguing that we cannot claim that electrons and protons exist but we can act as though they exist – that is, we can rely on them, and their postulated entities, as useful guides for dealing with whatever practical and theoretical problems may arise. Theories are not assertions about the world; rather, they are “techniques of explanation” – maps to enable us to find our way around the phenomena we wish to study, just as ordnance survey maps enable us to get around the British countryside and the famous map of the London Underground helps us to negotiate the city. Hence, theories are regarded as ‘holding’ rather than true, as ‘not holding’ rather than ‘false’. They are adopted or neglected, rather than believed or denied. Both realism and instrumentalism are beset with enormous difficulties. Naïve realism sets standards for the acceptability of knowledge claims that simply cannot be met. We cannot have direct access to truth about the world via our senses (which are fallible) and our created conceptual systems (which may be wrong for any or all of the reasons discussed in chapters 3 and 4). We may wish to compare our theory of the world with the real world, but we have no means of doing so. We can investigate nature and develop theoretical understanding of the world, but we cannot compare what we think we know with the truth to see how well we are doing. (Ellis, 1985, p. 69) As I argued earlier, we are ‘prisoners’ of our woefully inadequate senses (our physical frailty) and our capacity to theorize (our intellectual frailty). Moreover, whatever we interact with in order to build our conception of it could be changed in some possibly unknowable way by the interaction. In short we risk contamination and distortion through interference, so that all we can find out is information/ knowledge about “interacted-with-things”. Again, there is no guarantee of direct access to the real world. We have no way of stepping outside our minds and bodies to see the world in a theory-free way, assisted by perfect senses. Our success in building a model or theory about the world cannot be checked against the reality we are theorizing about. Even the instruments we build to give us greater access to information about the world are ‘contaminated’ by the theoretical assumptions make in their design and construction. In consequence, agreement with the ‘facts’ (observable evidence) does not mean that a theory is true. Firstly, the facts may be wrong – after all, they are interpreted responses to sense data collected with severely limited ‘tools’ (our senses or our instrumental extensions of them). Secondly, there may be other theories that also agree with the facts. The observational evidence may be susceptible to interpretation in more than one way, to suit more than one theory. Duhem (1962) argues as follows: Suppose that the hypotheses of a particular theory are able to explain all known appearances. What can be concluded is that they may be true, not that they are necessarily true. In order to make legitimate this last conclusion it would have to be proved that no other system of hypotheses could possibly be imagined which could explain the appearances just as well. If two theories can provide contradictory accounts for the same observable phenomena, yet make similar predictions about observable events, they are equally 104

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well corroborated by the available evidence. However, they cannot both be true in the sense that the theoretical entities they utilize in explanation and the interactions they postulate about those entities exist independently of our theorizing about them. We may wish to choose between these two theories on grounds of simplicity, elegance or similarity with other theories, as Kuhn (1970) describes (see also chapter 7), but these criteria say nothing about the truth of the chosen theory. We cannot assume truth from explanatory power. These problems lead some theorists and some science teachers and textbooks to embrace instrumentalism. Interestingly, this tendency seems to be greater in textbooks for the physical sciences than the biological sciences. Perhaps the exotic language of contemporary physics, with its leptons, quarks (and their traits of colour, flavour, strangeness, taste and charm), gluons and black holes lends strength to the notion that physics is an elaborate fiction. Perhaps the complexities of general relativity theory and quantum mechanics are such that the task of trying to imagine the real world described by the equations is just too daunting. Much easier to regard them simply as organizing tools. In school science, talk of ‘frictionless planes’, ‘ideal gases’ and ‘point masses’ seems to point clearly to an instrumentalist position. Nothing in the real world matches these conceptualizations and descriptions. Another argument for anti-realism is that the methods by which scientists investigate knowledge claims are so extensively theory-dependent and theorydriven (see chapters 4 and 5) that they are not so much a means of discovery as a means of constructing and re-constructing knowledge, and so cannot tell us anything about the world outside those constructions.3 In other words, if the ideas and procedures that scientists use to investigate the world are social constructs then what they tell us about the world is also a social construct, unless they ‘hit on the truth’ by accident. Therefore, it makes sense to admit that theories are simply fabrications of the human mind, invented to give us a measure of control and predictive capability. Indeed, Laudan (1984) argues that because the realist goal is unattainable, and because there is no means to measure how close a theory is to the truth, then scientists who pursue realist goals are acting irrationally. Thus, his position is that kinetic theory uses created entities such as atoms and molecules as devices to account for the behaviour of real gases such as oxygen and nitrogen, but makes no claim that such entities really exist. The behaviour of real objects like bar magnets and iron filings is explained by means of theoretical devices such as magnetic fields without any suggestion that magnetic fields are real. Some would respond that moral perfection is also beyond our reach but that doesn’t mean we shouldn’t strive for it or that it is irrational to do so. Indeed, it is generally held to make one a better person. So with science, perhaps: striving for truth makes you a better scientist and serves as a ‘corrective thrust’ by demanding explanatory breadth rather than mere computational efficiency. THE LANGUAGE OF OBSERVATION AND THE LANGUAGE OF THEORY

Many of those inclined to favour anti-realist views of scientific knowledge draw a sharp distinction between terms like dog, tree, yellow and hot, which refer to 105

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observable objects, properties, relations and events, and terms such as electron, gene and magnetic field, which refer to unobservable (i.e., theoretical) entities and can only be understood within the context of the theoretical system in which they are located. The position is clearly stated by Carnap (1956). It is customary and useful to divide the language of science into two parts, the observation language and the theoretical language. The observation language uses terms designating observable properties and relations for the description of observable things or events. The theoretical language, on the other hand, contains terms which may refer to unobservable events, unobservable aspects or features of events. (p. 38) The position seems to be that what we can observe, and describe via the observational language is real, while what we cannot observe – and have to infer, as the explanation of the observation – is theoretical and can be regarded as ‘fiction’. In other words, what is plainly observable to persons of normal perceptual ability is real and what is unobservable is not real. It is worth noting that both the Ontario Ministry of Education (1987) and the Alberta Ministry of Education (1993) urge teachers to draw a distinction between the descriptive language of science and the theoretical language of science, perhaps indicating a strongly instrumentalist view of scientific knowledge. My position, as outlined in chapters 3, 4 and 5, is that all scientific language is impregnated with theory. All terms used in designing, conducting and reporting scientific investigations are theory-laden, though in many cases we don’t recognize that we are using a theory-loaded term because the theory that underpins it is no longer problematic. The theory has become part of everyday language, and is now accepted without question. The point at which an individual begins to regard scientific terms as ‘theoretical’ is determined by her or his particular level of theoretical sophistication. Children, science teachers and research scientists will draw that line in different places. One of the reasons why many people find scientists difficult to understand, and accuse them of using esoteric jargon, is that they don’t have the conceptual understanding that has been built into that particular everyday language of scientific reporting. Problems can be considerable when faced with statements such as “Our eyes are sensitive to electromagnetic waves in the frequency range 4 × 1014 to 7.5 × 1014 Hz (wavelength between 4 × 10–7 and 7 × 10–7)” and “Once transcription has been successfully initiated, the RNA polymerase continues along the DNA molecule until it encounters terminator sequences on the non-transcribed DNA strand”. Even simple observation statements can be problematic: “the pH was found to be 4.73” or “the resistance of this coil is 2.5 ohms”. Given the arguments concerning the theory-laden nature of observation outlined in chapter 3, we could conclude that ‘we see what we choose to see’ simply by opting to use a particular theory, rather than some other theory. Does it follow, therefore, as the anti-realist position on the distinction between observational and theoretical language would seem to imply, that we can decide for ourselves what is real and what is fictional? Like Maxwell (1962), I take this as an absurd position to hold. 106

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Our drawing of the observational-theoretical line at any given point is an accident and a function of our psychological make-up, our current state of knowledge, and the instruments we happen to have available and, therefore, it has no ontological significance whatever. (p. 14) Hempel (1958) draws a distinction between directly observable and indirectly observable: “In regard to an observable term it is possible, under suitable circumstances, to decide by means of direct observation whether the term does or does not apply to a given situation… Theoretical terms, on the other hand, usually purport to refer to not directly observable entities and their characteristics. They function… in scientific theories intended to explain empirical generalizations” (p. 42). This elaboration of the language doesn’t seem to help at all. It isn’t entirely clear what directly observable and indirectly observable mean. And so it is not entirely clear what is supposed to be real and what is simply created/fictional. It is easy to observe a dog or a fish in a direct way, so dogs and fish must be real. So far, so good. What about an amoeba? It can’t be observed with the unaided senses, but it can be observed through a microscope (which can be regarded as a simple extension of our senses). Is an amoeba directly observable, and therefore to be classed as real, or is it indirectly unobservable, and therefore fictional? Does it mean that the amoeba was at one time a mere fiction (because it could not be observed by direct use of the senses) but became real once the microscope had been invented? Jupiter’s moons are not visible with the naked eye. Did they only become real at the time telescopic observations became available? Or did they only become real when, in 2006, a NASA spacecraft landed on Titan? Viruses and protein molecules are not visible through a microscope but can be ‘observed’ using an electron microscope. Does the use of an electron microscope, which utilizes senses that humans do not possess, count as direct observation, and therefore qualify a protein molecule for real rather than fictional status? What can we claim to ‘see’ in the ultrasound imaging of a developing foetus? It is indirect observation, of course, but we know that the foetus is real enough! As an aside, viruses represent an excellent example of those numerous occasions in the history of science when scientists, having postulated unobservable entities and incorporated them into theoretical structures which they have subsequently confirmed, via procedures deemed satisfactory to the scientific community, use those theories to devise and build instruments that detect and measure the very entities they had earlier postulated.4 To return to the main question, what can we say about electrons? They can’t be ‘seen’ at all, though we can observe their effects – in a cloud chamber, for example. Does that make them real or fictional? Neutrons do not produce tracks in a cloud chamber, so their presence has to be inferred. Is this the point at which we draw the line between direct and indirect observation, and by implication between real and fictional? Or is the line to be drawn at photons, which are in principle unobservable? If the demarcation between directly observable and indirectly observable (and unobservable, for that matter), is not clear, are instrumentalists also unclear about what is real and what is fictional? In practice, there is a continuum between observable and unobservable, via various degrees of indirect observation, 107

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as increasingly sophisticated instrumentation intervenes between the observer and the observed. Does this mean that there is a gradual transition from real to fictional status? Is a protein molecule or a virus ‘seen’ with an electron microscope less real than a synthetic polymer molecule or a bacterium ‘seen’ through an optical microscope? One more point is worth making. If human faculties had been different, the boundary between what is unobservable and observable, or unperceivable/ perceivable using other senses, would have been different. Would this entail a different set of realities? For a realist, it is unreasonable to draw the line between real and fictional at a point that is an accidental consequence of our particular physiological make-up. It also raises questions about species with radically different sense organs from our own. What for us is a fiction may be real for them. The endpoint of this kind of speculation is that our inability to observe is no guarantee that an entity doesn’t exist. Even if we do reduce theoretical entities to mere devices for prediction the fact still remains that something causes things to behave as they do. There is ‘something out there’. Some things are real: you and I, for instance; this book; that table. It is also true that some things are heavier than others, or yellower, hotter, further away and moving faster than others. It is not all a matter of how we choose to describe the world, how we elect to see it. The real world plays some part in that decision about how to describe it. So we may as well try to figure out what it is. I am arguing that science is one of the ways in which we attempt to find out what that ‘something’ is. Scientists are not concerned with mere prediction, they are concerned with what is. In a sense, instrumentalists have the cart before the horse: the capacity to make successful predictions is not the driving force for doing science, it is the consequence of successful attempts to build explanatory systems. Theories work as well as they do, in terms of predictions, not because we act as if theoretical entities exist, but because they really do exist – or close approximations to them exist. It is hard to believe that regularities that appear on the macroscopic level (what we see) should be just as if they were due to things on the theoretical level. Smart (1968, p. 152) asks why sense data such as “a cat’s tail on the left of a sofa” should be followed by sense data of “a cat’s head and whiskers on the right of a sofa” unless there is a cat walking behind the sofa. It isn’t just as if there is a cat walking behind the sofa, there really is a cat walking behind it. This is, in essence, the same inference to best explanation IBE) discussed in chapter 3. As Newton-Smith (1990) argues: I may never see a mouse in my house. But I may infer the existence of the mouse on the grounds that if there were a mouse that would provide the best explanation I can think of for the disappearance of bits of food in the night, the occurrence of scrabbling noises and the appearance of droppings. In the scientific context, a theory, such as Thomson’s theory of the electron, is argued to be more likely to be true than any rival theory on the grounds that it provides the best available explanation. (p. 184)

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A more interesting and compelling argument against instrumentalism and other forms of anti-realism, and perhaps an easier one for school age students to follow, is that it offers no incentive for the scientific endeavour. Once in possession of a satisfactory explanation that adequately accounts for the data, and enables accurate predictions to be made, there is no reason for an instrumentalist to seek alternatives. Why bother to do more? Only a realist, someone whose drive is to find out what the universe is really like, will continue the effort. In common with Newton (1997), I would argue that most (if not all) scientists are realists5 and, not with standing the technological benefits that sometimes accrue from advances in science, I would argue that realism is the major driving force for science. Indeed, it was precisely because Galileo took a realist stance towards Copernican theory, and set about solving its problems, that progress was made. He would not have persisted with his work unless he believed that by doing so he was getting closer to the truth. Science is driven by a realist position. We need a realist interpretation of phenomena if we are to make sense of the world, and making sense of the world is the main reason why we engage in theory building. If we have nothing but instrumental laws, they may explain in the sense of enabling us to predict, but they don’t explain in the sense of reducing the brutishness of brute facts. (Smart, 1968, p. 152 ) The realist goal also underlies the drive for theory unification. Two theories may be very successful in their own domains but in conflict from a realist perspective – for example, quantum mechanics and general relativity. The strenuous effort to produce a single unified theory signals very clearly that the scientific community (or, at least, the sub-group of theoretical physicists) has a realist outlook. If the goal of science was merely predictive there would be no reason to proceed beyond existing theories that work perfectly well in an instrumental capacity. WHY BELIEVE IN MIRACLES?

Instrumentalism cannot easily explain why theories are successful and, in particular, why they have predictive capability, nor how an idea introduced expressly to solve a particular problem can lead to the solution of quite different problems. If scientific theories are not (approximately) true, how is it possible for them to solve diverse problems and to yield such accurate (and sometimes very surprising) observational predictions? Surely, the argument goes, the continuing success of a particular theory in solving both theoretical and practical problems, its ability to provide common explanations for diverse phenomena, and its capacity to grow, develop and extend its domain, are good grounds for adopting a realist position. In other words, its success can be taken as evidence that its ‘hard core’ is approximately true. How can a theory be no more than a fictional calculating device if it can predict real and surprising phenomena such as the bending of light in the vicinity of an intense gravitational field, and with surprising regularity? How can instrumentalist theories, which are supposed to be mere calculating devices, lead to the discovery of new phenomena, using concepts that are supposedly no more than 109

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theoretical fictions? In Putnam’s (1975) words, “the positive argument for realism is that it is the only philosophy that doesn’t make the success of science a miracle” (p. 73), a view echoed by Karl Popper (1974): “it would be a highly improbable coincidence if a theory like Einstein’s could correctly predict very precise measurements not predicted by its predecessors unless there is ‘some truth’ in it” (p. 1193). Van Fraassen’s counter-argument is that predictive success is simply a consequence of the theory having been designed to account for observable phenomena and events. It doesn’t mean that the theory is true. As the history of science shows, we should be very careful about assuming our theories are true just because they fit the data; many people have assumed that in the past, only to be proved wrong. The success of current scientific theories is no miracle. It is not even surprising to the scientific (Darwinist) mind. For any scientific theory is born into a life of fierce competition, a jungle red in tooth and claw. Only successful theories survive – the ones which in fact latched on to actual regularities in nature. (van Fraassen, 1980, p. 40) Van Fraassen proceeds to argue that the success of a theory in providing explanations, making predictions and enhancing our ability to manipulate objects in the real world is a good reason for accepting and using a theory, but not a good reason for believing it (accepting it as true), on the grounds that “credibility varies inversely with informativeness” (p. 280). The more informative the theory, the more opportunities there are for it to be false. In other words, the more a theory claims, the less likely it is to be true. He concludes, “I assume that no one can coherently call one hypothesis less likely to be true than another while professing greater credence in it” (p. 294). It is much more difficult for instrumentalism to account for the embarrassing occasions when, as a consequence of improved instrumentation, a once purely theoretical entity (a fiction) becomes an observable one (and, therefore, real). It cannot readily account for those occasions when science creates phenomena and events that do not exist in the natural world, especially when they go on to form the basis of significant technological artifacts that give us the ability to interact with the real world in powerful new ways. Arguing this line, Hacking (1983, 1991) regards engineering success as the strongest case for realism. Perhaps electrons were once merely theoretical fictions, but now that we can manipulate them in a controlled way and use them to bring about effects in something else we are justified in believing that they are real. The best kinds of evidence for the reality of a postulated or inferred entity is that we can begin to measure it or otherwise understand its causal powers. The best evidence, in turn, that we have this kind of understanding is that we can set out, from scratch, to build machines that will work fairly reliably, taking advantage of this or that causal nexus. Hence, engineering, not theorizing, is the best proof of scientific realism about entities. (Hacking, 1991, p. 258) However, Fine (1986) argues that this instrumental success is hard-earned and less convincing of the realist status of theories than supporters would claim. 110

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Even when success appears at the end of the road, it generally crowns a long history of frustration and failure… an enormous amount of plain old trial and error… I think a reasonable historical picture would be to draw each success as sitting on top of a great mountain of failures. In inviting us to explain the instrumental success of science, the realist performs a sort of conjuring trick, and directs our line of sight only along the successful tips of the mountains of failures. (p. 152) Nevertheless, if scientists act as if theoretical entities exist, and that supposition proves robust (i.e., things behave as scientists had supposed), there must be something real about that entity. While knowledge of their behaviour is some evidence of their existence, it is the power to use unobservable entities that justifies our belief in the reality of what we manipulate. To paraphrase Ogborn (1995), electromagnetic waves were once a theoretical construction of Maxwell’s, now they are used to broadcast television programmes; genes were once a speculation of Mendel’s, now they are a tool for producing genetically engineered organisms. Hacking (1983) sums up this realist argument with the simple, down-to-earth statement that if there are “standard emitters with which we can spray positrons and electrons… then they are real” (p. 24). For Giere (1988), engineering is the driving force for science: “The development of science depends at least as much on new machines as it does on new ideas” (p. 138). He argues that entities like protons and electrons, once regarded as highly theoretical and problematic, have been ‘tamed’ and ‘harnessed’ by technology and are now research tools for investigating entities that are still problematic, such as gluons. George Thomson (1965) claims that the discovery of new effects and new phenomena is one of the aims (perhaps the major aim) of theory-building. It is difficult to see how an instrumentalist view of science can meet this aim. A ‘theoretical fiction’ is acceptable if it accounts for the phenomenon it is designed to explain, it need not go further. Indeed, it cannot go further unless it was designed to do so. As Popper (1963) says, “If theories are instruments for prediction, then we must assume that their purpose must be determined in advance, as with other instruments” (p. 118). CHOOSING BETWEEN REALISM AND INSTRUMENTALISM

It is necessary to ask whether there a major problem for realists in accounting for theory change. Not only are theories sometimes refuted, but also the very entities that comprise them (phlogiston and the notion of the aether, for example) are discarded. Anti-realists argue that empirical success and predictive capability is no guarantee that the particular entities comprising a theory actually exist. Indeed, Laudan (1981) points to a long list of now abandoned theories that once had predictive power, including the crystalline spheres of ancient and medieval astronomy, the phlogiston theory of burning, the caloric theory of heat and various theories of spontaneous generation. Clearly, we no longer believe that the entities in these theoretical structures exist. Therefore, he argues, we have good reason to believe that the entities we currently accept as real will “go the same way” as phlogiston and caloric – that is, into the dustbin of bad or discarded scientific ideas. However, 111

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theory replacement is not a problem for realists if these events are regarded as occasions when our theoretical understanding is brought closer into conformity with the real world, as occasions when science is learning from its mistakes and getting closer to the truth by using both observable and unobservable (theoretical) entities as tools for thinking. The fact that theories have anomalies, and that from time to time we abandon entire theories (and even the entities that comprise them), tells us that there is ‘something out there’ that is different from out current conception of it. Our view of the precise nature of that ‘something’ is always subject to change and revision. This is the impetus for further study, further investigation, further theory building. Insofar as they are prepared to conjecture that their theoretical entities exist in the physical world, realists are speculative and bold, whilst instrumentalists are cautious and defensive. While it is fair to say that knowledge of the mechanisms of real events is produced by scientific practice, it is not true to say that the actual mechanisms are so produced. The world behaves in particular ways, independently of us and our thoughts about it. While instrumentalism is content to allow scientific concepts and theories to be regarded as artificial constructs that enable us to impose order on the physical world, realism asserts that it is because the physical world is ordered that science becomes possible, and order can be perceived. Science attempts to ascertain the mechanisms underlying events in the real world. The nature of the physical world can only be known from a study of science, but its nature is not determined by science (as social constructivists would have us believe). There is a reality, which is largely unknown, but this reality is, at least in part, knowable. This view of science can accommodate the changing nature of scientific theory with the ‘unchanging’ nature of the physical world it attempts to explain.6 It is well described by Bhaskar (1975). The causal structures and generative mechanisms of nature must exist and act independently of the conditions that allow men access to them, so that they must be assumed to be structured and intransitive, i.e., relatively independent of the patterns of events and the actions of men alike… Structure and mechanisms then are real and distinct from the patterns of events that they generate; just as events are real and distinct from the experiences in which they are apprehended… The ultimate objects of scientific understanding are neither patterns of events nor models but the things that produce and the mechanisms that generate the flux of the phenomena of the world. Scientists attempt to discover the way things act, a knowledge typically expressed in laws; and what things are, a knowledge… typically expressed in real definitions. (pp. 56 & 66) This scientific knowledge is not constructed ‘from scratch’ each time; rather, new knowledge is built from and by means of existing knowledge. The more science speculates and investigates, the more it knows and the more it is able to know. But science has to start somewhere, even though we cannot be certain of the ‘reality’ of the starting point (i.e., the validity of our initial knowledge). Nash (1963) coins an interesting phrase when he talks about the principle of corrigible fallibility. 112

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However we conceive science, we cannot begin our work without some facts and some ideas provisionally accepted as unchallengeable. But the ideas may be quite wrong; the facts ill-observed or laden with ‘credulity’. Obsessed by such fears we don’t do science! From such obsession scientists are freed by what I call the principle of corrigible fallibility. It is a principle of action. Beginning with the best available facts and ideas, we proceed vigorously in the faith that any errors in them will be revealed by the interaction of facts and ideas – by the interaction of rational and empirical elements, in neither of which we have, or can have, absolute confidence. We amend out hypotheses in the light of our experiments; but we also reject (as errors), ‘correct’, and explain away some of our data when they conflict with ‘indubitable principles’. In such unquestioning acceptance of principles to which all experience is made to conform… science may seem at one with divination, or magic. Yet science progresses, as magic does not, and not simply because science had the good fortune to hit on the ‘right’ principles at the outset. It did not! But it learned better principles. (p. 83) It could be argued that the objections to a realist interpretation of Copernican theory were twofold. First, the theory lacked sufficient factual support of its own, while Ptolemaic theory could account for all that Copernican theory claimed to explain. Second, it was inconsistent with certain observations and with wellconfirmed physical theory (Aristotle’s). The conservative response would have been to retain Ptolemy’s epicycles; they were superior in the instrumentalist sense of making better predictions. However, the history of science shows us that inconsistency with other existing theory is not sufficient grounds for a realist to dismiss a new theory. Indeed, it was precisely because a realist interpretation of Copernican theory was adopted that a new and better dynamics was developed. Without a realist drive there would have been no point in seeking to improve on the predictive capability of Ptolemaic epicycles. Realism provides the incentive for the development of better articulated theories, new theories and better instruments for observation. Before Copernican theory could fully account for the observational data a number of refinements were necessary: Keplerian elliptical orbits (rather than circular ones), planets of significantly different masses in mutual attraction, planetary satellites, spinning planets. Eventually, the theory was capable of explaining the ‘facts’, but the imperfect theory was retained throughout - despite the poor supporting evidence. Why? Because scientists really believed they were in pursuit of the truth and retained the theory despite its shortcomings. In Feyerabend’s (1964) words, “the realistic position encourages research and stimulates progress, whereas instrumentalism is more conservative and therefore liable to lead to dogmatic petrifaction” (p. 302). Of course, because scientific knowledge is produced in a social context, the goal of ascertaining ‘how the world is’ (the realist goal) is bound to be impacted to some extent, and in varying degrees from theory to theory, by the personal and professional goals of scientists, the interests and priorities of funding agencies, and the cluster of economic, political and moral-ethical influences that impregnate the

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sociocultural context in which scientific practice is located. These matters will be addressed in chapters 7 and 8. MODELS, THEORIES AND CRITICAL REALISM

Speculating further on why we accumulate scientific knowledge may throw up a number of responses. – To overcome fear – the pursuit of rational explanations is preferable to superstition. – To reduce uncertainty – making the world (or our perception of it) more stable, more predictable and less disconcerting. – To understand – to satisfy our curiosity by gaining a sense of ‘what lies behind things’. – To solve problems – especially problems relating to food, shelter, health, transport, and the like. – To create artifacts – tools to make life easier, toys to make life more pleasurable. – To create ‘a better life’ – a somewhat vague but still powerful motivator for many people. Perhaps the status of scientific knowledge is related to our purpose in seeking it, to the role it plays once it has been acquired. Science is, of course, highly valued for its practical achievements and for its material benefits. In other words, it has instrumental value. But, according to Popper (1963), it is valued more for its ability “to free our minds from old beliefs, old prejudices, and old certainties, and to offer us in their stead new conjectures and daring hypotheses. Science is valued for its liberalizing influence – as one of the greatest of the forces that make for human freedom” (p. 102). Science liberates because scientists dare to create theories in contradiction to everyday experience, dare to go beyond the world of the senses. Indeed, much of scientific theory is counter-intuitive and counter to everyday commonsense. Eddington (1928) provides a wonderful example in his description of two tables. One of them has been familiar to me from earliest years. It is a commonplace object of that environment which I call the world. How shall I describe it? It has extension; it is comparatively permanent; it is coloured; above all it is substantial… Table No. 2 is my scientific table. It is a more recent acquaintance and I do not feel so familiar with it. It does not belong to the world previously mentioned – that world which spontaneously appears around me when I open my eyes, though how much of it is objective and how much subjective I do not here consider. It is part of a world which in more devious ways has forced itself on my attention. My scientific table is mostly emptiness. Sparsely scattered in that emptiness are numerous electric charges rushing about with great speed; but their combined bulk amounts to less than a billionth of the table itself. (pp. ix & x) Science liberates because scientists dare to challenge common sense appearances, received knowledge and the dictates of the state and organized religion. By trying 114

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to explain the regularities deduced from their theoretical speculations, scientists explain the known by the unknown. Sometimes scientists aim at a true description of the world and a true explanation of observable facts (a description of these facts must be deducible from the theory).7 On other occasions they are not seeking a ‘true’ description of the world; rather, a convenient predictive instrument is all that is required. When they wish to explain ‘how things are’ in the universe, when they are trying to make sense of it, scientists develop theories – our current ‘best shot’ at the truth. Each theoretical development takes us a little nearer to the truth about the universe, though we recognize that we are unlikely ever to achieve that goal and wouldn’t know if we had. When we simply want ‘to get the job done’ (make a prediction, achieve a measure of control, etc.) we invent theoretical models. Sidney Morgenbesser (1969) asserts that “a scientist is justified in using a theory T to accomplish a given end, if he has good reasons for believing that his theoryguided act will accomplish his end” (p. 213). I take this to mean that when scientists wish to predict an event they may employ an instrumental model, but when they wish to explain they must use a realist theory, and that the choice depends solely on their particular purpose at the time. Thus, the view I wish to promote for school science is that scientists play both a realist game and an instrumentalist game, as determined by their immediate purpose: they develop theories when they aim to explain and describe the real world; they use convenient models when they wish for no more than a quick and accurate calculation or prediction. This position, which some have termed critical realism (Jacoby & Spargo, 1992), enables scientists to be realist about some theories (those they consider to be genuine attempts to uncover the truth) and instrumentalist about others (those they find useful but do not accept as true descriptions). I believe there is enormous value in referring to the former as theories and the latter as models. In contrast, instrumentalists are always instrumentalist and blur the distinction between theory and model. It is interesting that a model originally designed simply to achieve a short-term instrumentalist goal may sometimes be developed, over time, into a realist theory. Sometimes entities that we ‘invent’ to gain a measure of control turn out to have a real existence. Smart (1968) argues that while many contemporary theories are instrumental, they are moving towards realism. Modern physics is instrumentalist, but may nevertheless constitute an approximation to, or a hint at, a realist theory. That is, a realist theory, even though it is unknown to us as yet, is ‘in the offing’. For if this were not so, how could the success of an instrumentalist theory be explained? Otherwise the success of the instrumentalist theory would have to depend on too many mere coincidences at the macroscopic level. (p. 163) It seems that models often function as the means of building progressively more complex (and realist) theories. They function as ‘scaffolding devices’, by means of which scientists make interim sense of observational data as they develop and extend their thinking. They play a key role in thought experiments and in the design and conduct of real experiments. Like scaffolding, models may be discarded once they have served their function. Indeed, it may be that some models used early in a 115

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theory’s developmental history prove incompatible with the premises of the final, refined theory despite their pivotal role in its construction. As observational support for the once tentative theoretical model increases, and it resists continued criticism and efforts to falsify it, it becomes accepted as the new theory (the new paradigm) and enters what Kuhn (1970) calls the phase of normal science, during which it is developed and refined (see chapter 4). Within normal science activities scientists may use a range of models in problem solving, prediction and further theory articulation – e.g., the so-called ‘billiard ball model’ to represent collisions of gas molecules. Indeed, within all significant theoretical frameworks there is a “family of models” (Giere, 1988, 1999) that scientists may deploy for solving short-term, practical problems, making calculations and predictions. The full theoretical force of the theory does not have to be engaged if instrumental models within it can suffice. Eventually, when scientists encounter insurmountable problems with the theory, find severe limitations to it, or construct a theory that is more satisfying, the old theory is rejected and reverts to the status of a model. It may still be useful for making predictions, but we no longer believe that it explains matters. From the critical realist position, it is not illogical to retain a falsified or superseded theory in an instrumental capacity, provided that its status is recognized and acknowledged. It may be that within a restricted domain of application, a falsified theory (in its new status as model) is more useful than the currently accepted theory because it is easier to use. For example, in many instances calculations using Newtonian physics give the same numerical results as would relativity or quantum mechanics if applied to the same problem, but the calculations are much easier! In a sense, school science does this all the time, and certainly in physics, where most of what is taught is pre-20th Century physics and a long way from the ‘cutting edge’ of contemporary research. Within the critical realist position it is not illogical to utilize alternative instrumental models, even incompatible or contradictory ones, to deal with different aspects of the same phenomenon. As Morgenbesser (1969) comments, “a scientist may be justified in using T1 for predictive or calculating purposes and using T2 for related ones though their conjunction is self-contradictory” (p. 213). For example, we can use a wave model of light to solve problems relating to interference patterns and a particle model of light to solve a problems relating to photoelectric effects. The use of diverse and sometimes mutually contradictory models is fairly common practice in engineering, along with the use of models that function only within a narrow range of conditions. According to Cartwright (1983), we design models according to the specific features of the situation we are interested in, without worrying too much about whether the model is compatible with another model we might use for other purposes. In exemplification, she cites a text on quantum optics in which various and mutually incompatible models are deployed to explain the various properties of lasers. She also notes that the need for idealized (fictional) models is greatest when scientists wish to use sophisticated mathematics. In general, nature does not prepare situations to fit the kinds of mathematical theories we hanker for. We construct both the theories and the objects to which they apply, then match them piecemeal onto real situations, deriving – 116

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sometimes with great precision – a bit of what happens, but generally not getting all the facts straight at once. The fundamental laws do not govern reality. What they govern has only the appearance of reality and the appearance is far tidier and more readily regimented than reality itself. (p. 162) My concern is that we often confuse students by not distinguishing sufficiently between different kinds of theoretical structures. Indeed, most curricula are silent on this matter. We leave students to form their own views about whether science has a realist or an instrumentalist thrust. Little wonder that many students are confused about the status of scientific knowledge. Some may come to believe that some of the strange calculating and predicting devices, that I would urge teachers to call models, are intended to explain - i.e., that they represent what scientists believe about real events and phenomena. Others may simply conclude that all scientific explanations are as fanciful as these models, and for them, science will lose its credibility. It is worth remembering the constructivist mantra: ‘new ideas will only be accepted by students if they perceive them to be intelligible, plausible and fruitful’ (Posner et al., 1982). Theories needs to be intelligible and plausible, and fruitful in the sense of being able to explain; models need to be intelligible and fruitful, though not necessarily plausible. In other words, models may fail the plausibility test even though they are excellent in terms of fruitfulness. There is, of course, an important link between the use of models in science for theory building and problem solving and the use of models by students and teachers in learning scientific concepts and acquiring new theoretical knowledge. Although these matters fall outside the scope of this book, it is important to note that the nature of mental models has long been an area of research in cognitive psychology, dating back to the seminal work of Johnson-Laird (1983) and Gentner and Stevens (1983). In recent years, the topic of models and modelling has generated considerable interest among science educators (Gilbert et al., 1998a,b; Franco et al., 1999; van Driel & Verloop, 1999; Gilbert & Boulter, 2000; Greca & Moreira, 2000, 2002; Coll & Treagust, 2002, 2003a,b; Justi & Gilbert, 2002a,b,c, 2003; Treagust et al., 2002; Davies & Gilbert, 2003; Taber, 2003; Gilbert, 2004; Kowasaki et al., 2004; Coll & Taylor, 2005; Coll et al., 2005; Justi & van Driel, 2005), an interest that can be categorized into three principal areas of concern: – The particular models and theories produced by scientists as explanatory systems, including the history of their development. – The ways in which scientists utilize models as cognitive tools in their day-today problem solving, theory articulation and theory revision. – The role of models and modelling in science pedagogy. Of particular interest to the substance of this book is the diversity among scientists in terms of how they utilize models as tools for thinking (Hesse, 1970; Gilbert & Mulkay, 1984; Giere, 1988; Stavy, 1991; Nersessian, 1995; Ogborn & Martins, 1996; Penner et al., 1997; Ault, 1998).

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WHAT IS REAL?

While I am content that the critical realist perspective is a productive one for school science, and a considerable improvement on simply leaving students to work it out for themselves, there remains a problem. Which theoretical entities should be accepted as real and which are to be regarded as fictional? Sometimes it is easy to decide, but in the ‘cutting edge’ physics to which Smart refers in the passage quoted earlier it may be more problematic. As discussed earlier in the chapter, Hacking (1983, 1991) adopts the position that theoretical entities are real if we can use them to bring about significant changes in a predictable way. He also states that the confidence we have in the existence of particular entities (because of our ability to manipulate them) does not necessarily extend to the complex theoretical structures that use these entities in explanation of the processes underpinning observable phenomena – a position also taken by Cartwright (1983) and Giere (1988). Thus, we can be realist about some of the entities in a theory even if the theory is not yet regarded as a true explanation of events. For example, we can believe in the existence of atoms but regard the accounts of crystallographers about how the atoms are arranged within particular structures as uncertain. Moreover, we can continue to believe in the existence of entities even when a theory that employs them is known to be false or has been superseded. Furthermore, as argued previously, scientists may simplify and idealize a realist theory into a range of instrumental models in order to utilize it more effectively in solving a range of problems or disposing of an anomaly. In other words, a theory may be regarded as comprising a family of models. In Kuhn’s (1970) account of science, models are constantly evaluated for their effectiveness in dealing with the paradigm’s problems (and those which prove ineffective are discarded), but theories are only evaluated in times of crisis, and only against a competing theory. One way of dealing with the dilemma about precisely what should be regarded as real is to draw a distinction between the statements ‘theoretical entities are real’ and ‘theoretical entities exist’. There is a distinction between our conceptual systems, which are human constructs and are susceptible to change, and the actual world, to which our conceptual systems bear some relation. The physical world is real and scientific theories are real, but they are not identical (there is an ontological distinction between them). Dragons and phlogiston are both real – they have properties and particular relationships with other concepts that are also well understood (such as fair maidens and burning) – but they do not exist. Other nonexisting but real entities include unicorns, hobbits, leprechauns and taniwha.8 Similarly, electrons and magnetic fields are real concepts, having an existence independent of individuals and having relationships with other concepts whether or not anyone is aware of that relationship. But in these cases we do not know whether they exist or not. We believe that they do, and act as if they do, but a change in theory may lead us to change our view in the same way that a change in theory led us to change of views regarding the existence of dragons and phlogiston. In a sense, all knowledge is real and has an existence independent of the opinions and feelings of individuals, though individuals are, of course, necessary for the initial generation and development of knowledge. Particular relationships among 118

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the ideas that comprise a complex matrix of scientific knowledge exist, and the entities within the theory relate to the available evidence in particular ways, whether or not any individual accepts the theory as a true account of events or believes the entities contained in the theory actually exist in the real physical world. In other words, they have an objective existence. ‘Objective’ is used here in contrast to ‘subjective’ and does not necessarily mean ‘true’. A theory can be objective and false – for example, phlogiston theory is not a true account of combustion, but its concepts and principles have an objective existence and can be critically addressed. The most complete description of this view of scientific knowledge is Karl Popper’s Objective Knowledge, published in 1972, in which he postulates the existence of three distinct ‘worlds’: the actual physical world (world 1), the world of human thought processes (world 2) and the world of objective knowledge (world 3). In this pluralistic philosophy the world consists of at least three ontologically distinct sub-worlds; or, as I shall say, there are three worlds: the first is the physical world or the world of physical states; the second is the mental world or the world of mental states; and the third is the world of intelligibles, or of ideas in the objective sense; it is the world of possible objects of thought; the world of theories in themselves, and their logical relations; of arguments in themselves; and of problem situations in themselves. (p. 154) The third world (the product of human activity) is separate from but related to the second world (the subjective act of thinking) which produced it in just the same way as a spider’s web is separate from but related to the spider’s act of spinning it. Scientific knowledge is created by people, but once it has been created it is independent of its creator and has properties which can be studied without regard to its origin. It may even have consequences unforeseen by those who created it; there may be both internal relationships and external relationships (to knowledge in other theories) that remain undiscovered for some time. Interaction between the physical world and the theoretical world is via individual consciousness, which is firmly anchored to and influenced by relationships in the world of theories. The world of objective knowledge (World 3) is not an exact account of the actual physical world (World 1); rather, it is our current ‘best shot’ at describing it. These views will change as science improves the match between World 1 and World 3 through a combination of theorizing, speculating, experimenting and arguing. This position is well captured by Bohm (1957): The world as a whole is objectively real, and that as far as we know, it has a precisely describable and analyzable structure of unlimited complexity. This structure must be understood with the aid of a series of progressively more fundamental, more extensive, and more accurate concepts, which series will furnish, so to speak, a better and better set of views of the infinite structure of objective reality. We should, however, never expect to obtain a complete theory of this structure, because there are almost certainly more elements in it than we can possibly be aware of at any particular stage of scientific development. (p. 100)

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Figure 6.1. Popper’s ‘three worlds’ view

Popper’s position stands diametrically opposed to the views of radical constructivists such as Ernst von Glasersfeld (1987, 1989, 2007), who asserts that knowledge exists only in the minds of cognizing beings (it cannot reside in books, for example) and so will vary substantially from individual to individual, even when addressing the same phenomenon. Scientific knowledge, like any other knowledge, is simply that which individual ‘epistemic agents’, given their particular experiences and traditions of thought and language, consider ‘viable’ for them.9 Knowledge does not reflect an ‘objective’ ontological reality, but exclusively an ordering and organization of a world constituted by our experience (von Glasersfeld, 1987, p. 199) The basic elements out of which an individual’s conceptual structures are composed and the relations by means of which they are held together cannot be transferred from one language user to another… they must be abstracted from individual experience (von Glasersfeld, 1989, p. 132) Returning to Popper’s ‘three worlds view’, it follows that the terms in which individual scientists think (the way they ‘see’ the world) depend on the particular selection they make from the objective third world of theories. They make this selection in response to a complex interaction of personal beliefs and values, impregnated with social norms, pressures and influences. And, in turn, the particular selection made by an scientist exerts a powerful influence on the kind of science that is done and the way in which it is done, and strongly influences the kind of knowledge that is generated. It is the cluster of social influences on science – internally, with respect to the day-to-day practice of scientists; externally, in terms of the ways in which science impacts (and is impacted by) the sociocultural context in which it is located - that is the principal concern of chapter 7.

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ENDNOTES 1

2

3 4

5

6

7

8

9

The term ‘antirealist’ may be used to refer to advocates of a number of philosophical positions opposing realism, including instrumentalists, idealists, phenomenalists, empiricists, conventionalists, constructivists and pragmatists (Fine, 1991). Instrumentalism and constructivism are the two antirealist positions most relevant to the discussions in this chapter. While instrumentalists may regard these entities as fictions, they are fictions that are purposefully created; they are not mere flights of fancy. Hence, utilizing an invented concept like gene and building it into a complex explanatory structure, for example, is not to be regarded as merely an intellectually satisfying scientific fantasy. This position, adopted by most contemporary sociologists of science, will be elaborated in chapter 7. Of course, if the theoretical assumptions underpinning the design and construction of particular scientific instruments are wrong or merely incomplete, then the data are spurious and the existence of the entities that they appear to confirm is in serious doubt. Wong and Hodson (2008a,b) provide some compelling evidence for this claim from interviews with a number of leading scientists. ‘Unchanging’ is used here in a relative sense. Of course, the universe is constantly changing, although within the normal lifetime of human beings there is no substantial change at the gross level. ‘True’ is being used in the somewhat restricted sense of scientifically true: not yet falsified, even by the most rigorous tests. Taniwha: mythical water-living beast in Maori folklore. Taniwha stories are used to ‘persuade’ young children to avoid dangerous places such as river estuaries and tidal caves. A detailed critique of von Glasersfeld’s views can be found in Suchting (1992), Matthews (1993, 1998a) and Kelly (1997), with a response in von Glasersfeld (1992). A special issue of Science & Education (1997, 6(1-2)) includes ten articles and a lengthy bibliography dealing with philosophical aspects of constructivism.

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INSIGHT FROM THE SOCIOLOGY OF SCIENCE Science is What Scientists Do

It has been argued a number of times in previous chapters that empirical adequacy is insufficient, in itself, to establish the validity of a theory: consistency with the observable ‘facts’ does not mean that a theory is true,1 only that it might be true, along with other theories that may also correspond with the observational data. Moreover, empirical inadequacy (theories unable to account for all the ‘facts’ in their domain) is frequently ignored by individual scientists in their fight to establish a new theory or retain an existing one. It has also been argued that because experiments are conceived and conducted within a particular theoretical, procedural and instrumental framework, they cannot furnish the theory-free data needed to make empirically-based judgements about the superiority of one theory over another. What counts as relevant evidence is, in part, determined by the theoretical framework the evidence is intended to test. It follows that the rationality of science is rather different from the account we usually provide for students in school. Experiment and observation are not as decisive as we claim. Additional factors that may play a part in theory acceptance include the following: intuition, aesthetic considerations, similarity and consistency among theories, intellectual fashion, social and economic influences, status of the proposer(s), personal motives and opportunism. Although the evidence may be inconclusive, scientists’ intuitive feelings about the plausibility or aptness of particular ideas will make it appear convincing. The history of science includes many accounts of scientists ‘sticking to their guns’ concerning a well-loved theory in the teeth of evidence to the contrary, and sometimes in the absence of any evidence at all. Marton et al. (1994) surveyed eightythree Nobel laureates in physics, chemistry and medicine about the role of intuition in their research. Seventy-two were in no doubt about its importance. Michael Brown, joint winner with Joseph Goldstein of the 1985 Nobel Prize in medicine for their work on cholesterol metabolism, commented “As we did our work… we would go from one step to the next, and somehow we would know which was the right way to go. And I can’t really tell how we knew that” (Marton et al., 1994, p. 461). Rita Levi-Montalcini (1986 winner, with Stanley Cohen, for their discovery of growth factors) said: “Intuition… is something unconscious, which, all of a sudden, comes out of a clear sky to you and is absolutely a necessity, more than logic… You’ve been thinking about something… for a long time… then all of a sudden, the problem is opened to you in a flash, and you suddenly see the answer” (pp. 462 & 465) and Konrad Lorenz (joint winner in 1973, with Karl von Frisch and Nikolaas Tinbergen, for work on animal behaviour) remarked: “[You keep] all known facts afloat, waiting for them to fall into place, like a jigsaw puzzle… If you try to permutate your knowledge, nothing comes out of it. You 123

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must give a sort of mysterious pressure, and then rest, and suddenly BING… the solution comes” (p. 467). Perhaps, as so often, Albert Einstein (1918/1954) says it best: The supreme task of the physicist is to arrive at those universal elementary laws from which the cosmos can be built up… There is no logical path to these laws; only intuition, resting on sympathetic understanding of experience, can reach them (p. 221) Elegance, simplicity and parsimony can be significant factors in gaining support for a theory. As Martin Amis (1995) says, in his novel The Information, “In the mathematics of the universe beauty helps tell us whether things are false or true” (p. 8), while Richard Feynman (1965) remarked that “You can recognize truth by its beauty and simplicity… When you get it right, it is obvious that it is right. The truth always turns out to be simpler than you thought” (p. 171). Similarly, in a conversation with Einstein, Werner Heisenberg (1971) argued that the simplicity of good ideas is a strong indication of their truth: “I believe, just like you, that the simplicity of natural laws has an objective character, that is not just the result of thought economy. If nature leads us to mathematic forms of great simplicity and beauty… we cannot help thinking that they are ‘true’, that they reveal a genuine feature of nature” (p. 68). Max Born (1924) argues in similar vein when he says that relativity theory was accepted long before supporting experimental/ observational evidence became available because it made science “more beautiful and grander”. Also commenting on the elegance of Einstein’s work, Paul Dirac (1980) states – Anyone who appreciates the fundamental harmony connecting the way Nature runs and general mathematical principles must feel that a theory with the beauty and elegance of Einstein’s theory has to be substantially correct… One has a great confidence in the theory arising from its great beauty, quite independent of its detailed successes… One has an overpowering belief that its foundations must be correct quite independent of its agreement with observation”. (p. 44) In another essay, Dirac (1963) says, “It is more important to have beauty in equations than to have them fit experiments” (p. 47). Miller (2006) argues that it was Dirac’s insistence on beauty at the expense of ‘facts’ that led to the discovery of antiparticles. Referring to his and Francis Crick’s elucidation of the structure of DNA, Jim Watson (1980) reports that Rosalind Franklin accepted the fact that the structure was “too pretty not to be true” (p. 124). More extensive discussion of the role of aesthetic criteria in science can be found in McAllister (1996). A new theory is more likely to be accepted when it is consistent with other well-established theories and is less likely to be accepted when it is in conflict with them (Laudan, 1977). Thus, Copernican theory had some initial problems because it was inconsistent with Aristotelian physics- a problem that was solved by Galileo. Perhaps scientists have expectations of a grand unifying theory, so they look for common explanations or common kinds of explanations.2 Holton (1981, 1986, 124 Derek Hodson - 978-90-8790-507-1 Downloaded from Brill.com11/09/2020 11:12:23AM via free access

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1988) refers to a number of cross-disciplinary “themata”, usually in the forms of dyads or triads, that guide the work of scientists by presenting choices between, for example, theories based on constancy/equilbrium versus evolution versus catastrophic change, and between driving forces such as hierarchy and unity or reductionism and holism. Holton (1988) also notes the conscious or unconscious preoccupation with symmetry shown by many scientists. Trends in other disciplines (philosophy, psychology, sociology and politics, for example) can be influential. Some theories are clearly products of their time and the prevailing intellectual climate. For example, phrenology (Combe, 1825, 1828) was perfectly suited to the socio-political climate of Victorian England and Wilhelm Reich’s theorizing about orgonne energy and its impact on sexual behaviour was similarly well-suited to the late 1940s/early 1950s (Boadella, 1985). Matters of contemporary social and economic significance will, of course, influence research priorities; they may also have impact on what findings are published and, in turn, play a part in forming scientists’ views about acceptability and validity. Despite some severe theological problems, acceptance of Copernican theory was hastened because it solved a persistent problem associated with fixing the precise dates of Holy Days in the Christian calendar. Dirac (1980) comments that Einstein’s theory of relativity was largely unknown outside a small circle of scientists until the end of the First World War, when it had enormous impact. It came at a time when everyone was sick of the war…People wanted something new. Relativity provided just what was wanted and was seized upon by the general public and became the central topic of conversation. It allowed people to forget for a time the horrors of the war they had come through. Innumerable articles about relativity were written in newspapers, magazines and everywhere. Never before or since has a scientific idea aroused so much and such wide-spread interest. (p. 42) In the contemporary world, the interests of those who fund the research are seen to impact significantly on the findings that are given prominence, though those who are charitable may cite unconscious motivation at work, rather than vested interest. To be admitted to the corpus of approved scientific knowledge, theories have to be socially, culturally and politically acceptable. In the Stalinist Soviet Union, Darwinian ideas underpinning evolutionary biology were rejected in favour of Lysenko’s theorizing about Lamarckism because transmission of acquired characteristics was much more compatible with Marxist views about human nature, with disastrous impact on agriculture and widespread famine (Joravsky, 1970; Lewontin & Levins, 1976; Lecourt, 1977). Archaeologists in Nazi Germany were strongly encouraged by the state to publish ‘findings’ indicating that the great achievements of Classical Greece were actually the work of Germanic peoples who had migrated south to escape a series of natural disasters (Arnold, 1990, 1992). In explanation of these aberrations, Bloor (1974) asks us to consider “the sorts of things that people think about… They think about objects like computers or oracles, about substances like oxygen or phlogiston, and about states like being infected by a virus or being 125 Derek Hodson - 978-90-8790-507-1 Downloaded from Brill.com11/09/2020 11:12:23AM via free access

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ritually unclean. Clearly peoples’ habitual categories of thought vary from culture to culture. To these categories they apply socially-varying standards of efficiency, cogency and satisfactoriness. The ideas that are in people’s minds are in the currency of their time and place… The terms in which they think do not emanate from their subjective psyches. They come from the public domain into their heads during socialization” (p. 71). Issues of power, influence and prestige play a major part in determining the acceptability of theories. Who is proposing this view? Who else supports it or accepts it? Are they prominent and important members of the community of scientists? According to Latour and Woolgar (1979), the credibility of the proposal and the credibility of the proposer are virtually identical, and whether a knowledge claim is judged plausible or implausible is strongly influenced by who proposed it, where the work was done, and how it was accomplished. In other words, the context of the research is just as important as the content of the knowledge claim. In Knorr-Cetina’s (1981) words, “Scientists speak about the motives and interests which presumably gave rise to the ‘finding’, about the material resources available to those who did the research, and about ‘who stands behind’ the results. They virtually identify the results… with the circumstances of their generation” (p. 7).3 Evaluating the skills of researchers (their ‘track record’) proves to be a good strategy for assessing the quality of their work (whether in accepting it uncritically or scrutinizing it more thoroughly). No one can afford the time or resources to assess every detail or repeat every experiment, however ideal that may seem… Evidence may be more fundamental, but credibility is generally primary, in the sense of being applied first. (Allchin, 2004, pp. 942 & 943) With regard to personal motives, an individual scientist is likely to ask: “Is this theory likely to play a useful role in my own work?” “Will it help to solve my particular problems?” In the group environment of a research institution, particularly if it has commercial interests, junior scientists may be strongly influenced in their decisions by what colleagues believe (especially if there is a powerful pressure group) or by what the Head of Department advises. Pickering (1982) describes a situation, which he argues is not uncommon, in which the chosen alternative (the ‘charm’ model of the properties of hadrons in the 1970s) was the one most compatible with the research group’s existing practice and offering opportunity for its extension. In other words, groups have a vested interest in the continued use of approaches that have served them well in the past. Like other professionals, scientists have to earn a living and so will seek out research fields with potential for growth. Personal ambition and the desire for recognition and fame will prompt some scientists to ask: “Is there a career to be built in this area?” “Is this the kind of research that academic journals are publishing at the moment?” “Is there likely to be a book in it?” “Is there good conference potential here?” “Is espousing these views likely to be of value in an interview situation or a seminar?” “Is this the kind of research for which funding agencies are awarding substantial research grants?” 126 Derek Hodson - 978-90-8790-507-1 Downloaded from Brill.com11/09/2020 11:12:23AM via free access

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If one takes the view that scientists are members of a community of practice, and that the ideas of particular scientists will only become accepted as scientific knowledge when they achieve consensus within the community, it follows that all of the influences that impact on people in their day-to-day lives have to be considered as possible or likely influences on the conduct of the scientific community – that is, as influences on the science that is carried out and the scientific ideas that gain acceptance. Of course, the empirical under-determination of theories does not prove that social and affective factors play a part in theory acceptance and theory rejection, though it makes it much more likely. Acknowledging this likelihood constitutes a major challenge to the muchvaunted objectivity of science promulgated by school textbooks. By failing to address these influences, the simple-minded accounts of theory acceptance/rejection that we promote through the school science curriculum are insulting to students, and often flatly contradict what they read about real scientists like Galileo Galilei, Albert Einstein, Barbara McClintock, Rachel Carlson, Jane Goodall and Jim Watson. What textbooks often seem to omit from their accounts of theoretical development is the personal dimension – the ways in which the decisions and actions of scientists are influenced by their worldviews, feelings, attitudes and prejudices. Because of the theory-laden nature of observation (and theory-impregnated nature of all the other processes of science) and the empirical under-determination of theories, what one ‘sees’ as an observer, the proper conduct of experiments, the adequacy of a theoretical explanation, and so on, are all open to dispute, contestation and modification. Rather than attempting to reduce science to a cold, clinical, depersonalized method, and rather than presenting science as independent of the society in which it is located, we should be emphasizing the ways in which knowledge is negotiated within the scientific community by a complex interaction of imagination, experiment, theoretical argument and personal opinion. And we should be promoting the view that science is a theory-driven and creative endeavour, influenced throughout by social, economic, political and moral-ethical factors as they impact on the decision makers – the ‘gatekeepers’ or guardians of the community’s store of knowledge. As Robert Young (1987) says: Science is not something in the sky, not a set of eternal truths waiting for discovery. Science is practice. There is no other science than the science that gets done. The science that exists is the record of the questions that it has occurred to scientists to ask, the proposals that get funded, the paths that get pursued… Nature ‘answers’ only the questions that get asked and pursued long enough to lead to results that enter the public domain. Whether or not they get answered, how far they get pursued, are matters for a given society, its educational system, its patronage system and its funding bodies. (pp. 18 & 19). Not only is science a social activity in the sense that society (writ large) determines “the science that gets done”, but also in the sense that the rules of scientific procedure and the legitimacy of the ‘product’ are determined by a community of practitioners. As Bereiter et al. (1997) remark, “If there is anything distinctive about science, it is not to be found in the workings of individual minds, but in the 127 Derek Hodson - 978-90-8790-507-1 Downloaded from Brill.com11/09/2020 11:12:23AM via free access

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way scientists conduct themselves as a community” (p. 333). Again, there are two levels of community here. First, it is rare for scientists to work entirely alone. Most experimental scientists in universities, research institutes and industry, are members of a laboratory team working on closely related problems over a number of years. Beyond the specific laboratory team an individual is also a member of the institution’s team of scientists and of the ‘invisible team’ of scientists in all other institutions who conduct similar and related research. Even without this collaboration, scientists are still dependent on one another for the ‘conditions’ under which they work (including availability of ‘starting knowledge’, established techniques, scientific apparatus, etc.). Second, the wider community of scientists determines what counts as acceptable scientific practice and exercises strict control of what is admitted to the corpus of accepted knowledge through its system of peer review. This community also exercises strict control over the education of future scientists and initiation of newcomers into the community of practice. Consideration of the larger social context in which science is practiced, including the ways in which the sociopolitical, economic and military significance of science and technology lead to major concerns about control and accountability (Dickson, 1988; Callon, 1995; Cozzens & Gieryn, 1995; Gieryn, 1995), are outside the scope of this book, save to note that different societies, because they are located in different physical and social environments and have different values and aspirations, are likely to have different priorities for science and technology. It is interesting to speculate on the extent to which science is culturally determined – that is, to what extent are the questions we ask, the kind of problems we perceive and try to solve, the ways in which we conceptualize the world, the ways in which we think and proceed towards solution of our problems, the criteria we generate for judging ‘success’, and the nature of the knowledge produced, a reflection of the needs, interests, values and aspirations of society? These questions raise important issues concerning the demarcation criteria of science. What can be changed (aims, values, concepts, methods, criteria of validity, and so on) and the activity still be characterized as science? What distinguishes science from pseudoscience? Do terms such as Feminist or Gynocentric science and First Nations science or African science have any meaning? Is the adoption of a particular worldview a sine qua non of science or is it possible to operate within more than one worldview? These and related matters will be addressed, albeit briefly, later in the chapter. With regard to sociological considerations internal to the practice of science, Ziman (1968) comments as follows: “Far from being the sum of independent, individual researches, the continuous compilation of innumerable disconnected facts, observations and theories, scientific knowledge is the joint social product of the members of… ‘Invisible Colleges’” (p. 61). In other words, scientific knowledge is the product of a complex social activity in which the creative acts of individual scientists are embedded: knowledge claims have to be argued according to the ‘rules of the game’ laid down by the community of scientists and expressed in a language and form determined by the community. An individual scientist’s confidence in the significance of her/his work is insufficient to establish it as part of the body of knowledge; it must withstand critical scrutiny by the community by whatever means the community decides is appropriate. Experiments are repeated 128 Derek Hodson - 978-90-8790-507-1 Downloaded from Brill.com11/09/2020 11:12:23AM via free access

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(sometimes with variations) by other scientists; chains of evidence are audited; conclusions and explanations are critically examined; and sometimes the claim is amended, modified or reformulated. Kuhn (1970) encapsulates the social dimension of scientific practice in his description of normal science: problem solving and theory articulation within a ‘received tradition’. Individual scientists are deeply committed to the tradition and to the research practices it encompasses; they use the resources of conceptual and procedural knowledge already established (what Kuhn calls the current paradigm) to address some of the problems defined by the paradigm as legitimate; when successful, the solutions are incorporated into the tradition and made available as resources for use by others. According to Ziman (1978), it is the community-driven nature of the enterprise that makes science unique. Scientific knowledge, he argues, can be distinguished from other forms of knowledge because it is “consensible” (expressed in mutually intelligible and unambiguous language) and “consensual” (the ultimate criterion of validity is consensus). To gain acceptance, knowledge must meet the standards, expectations and needs of the community, which are both formidable and strictly enforced through peer review. What counts as authentic knowledge and proper procedure is jealously guarded, as witness the rapid closing of ranks whenever there is a claim to knowledge by an outsider. These standards are maintained by means of rigorous ‘rites of passage’ (education and research training), which individuals must complete successfully before they can gain admission to the community. Once admitted, scientists must conform to the community’s rules and conventions, including the adoption of a strict linguistic code. Otherwise, they risk expulsion. While this is a way for the community to exclude charlatans, it is also an essentially conservative, restrictive and elitist stance that may serve to exclude members of minority groups. Charges that, in consequence of these constraints, science is both sexist and racist will be addressed later in the chapter. THE NORMS OF SCIENTIFIC PRACTICE

Some sixty years ago, Robert Merton identified four “functional norms” or “institutional imperatives”, transmitted by precept and example, which govern the practice of science and the behaviour of individual scientists, whether or not they are aware of it (Merton, 1973).4 Not only do these norms constitute the most effective and efficient way of generating new scientific knowledge, they also provide a set of ‘moral imperatives’ that serves to ensure good and proper conduct. – Universalism – science is universal (i.e., its validity is independent of the context in which it is generated) because evaluation of knowledge claims in science uses objective, rational and impersonal criteria rather than criteria based on personal, national or political interests, and is independent of the reputation of the particular scientist or scientists involved. – Communality – science is a cooperative endeavour and the knowledge it generates is publicly owned. Scientists are required to act ‘in the common good’, avoid secrecy and publish their findings and conclusions so that all scientists may use and build upon the work of others. 129 Derek Hodson - 978-90-8790-507-1 Downloaded from Brill.com11/09/2020 11:12:23AM via free access

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– Disinterestedness – science is a search for truth simply for its own sake, free from political or economic motivation or strictures, and with no vested interest in the outcome. Because attempts to exploit the ignorance or credulity of nonscientists or to fabricate results in pursuit of commercial or personal gain are strictly outside the code of approved scientific conduct, scientists have traditionally enjoyed a good reputation for ethical behaviour. – Organized scepticism – all scientific knowledge, together with the methods by which it is produced, is subject to rigorous scrutiny by the community in conformity with clearly established procedures for judging such matters as methodological appropriateness, chain of argument from data to conclusions, and testability. The ‘emotional neutrality’ of these procedures ensures that all knowledge claims are treated similarly, regardless of their origin. Two additional norms have been proposed by Barber (1962). – Rationality – science uses rational methods to generate and validate its claims to knowledge. – Emotional neutrality – scientists are not so committed to an existing theory or procedure that they will decline to reject it or adopt an alternative when empirical evidence points to it. Similar ideas underpin Garfinkel’s (1967) “rules of interpretive procedure”, which he contrasts with everyday reasoning: the rule of unlimited doubt asserts that scientists will not limit their scepticism by the kind of ‘practical considerations’ that govern everyday life; the rule of knowing nothing allows scientists to suspend their own knowledge in order to see where it leads, while testing in everday life proceeds on the basis of what can be taken for granted; the rule of universalised others enables scientists to trust the findings of others; the rule of publicisability requires that all findings are made public, regardless of personal motives and interests. Many contemporary sociologists of science argue that the so-called ‘Mertonian norms’ of scientific conduct do not guide practice; rather, they are used retrospectively by scientists to dignify what they have done, and to impress non-scientists. Mitroff (1974), for example, suggests that the ‘emotional neutrality’ of organized scepticism is frequently over-ruled by the ‘emotional commitment’ of scientists struggling to overcome difficulties and setbacks. Indeed, he postulates a counternorm for each of the norms listed above.5 – Particularism – the personal or professional attributes of the researcher, and the status of the institution, are frequently taken into account in the evaluation of scientific contributions. – Solitariness – ownership and control of distribution of scientific knowledge reside with the individual scientist (or group) who produced it. On occasions results are withheld until a patent has been secured or delayed until their announcement will have greater impact. – Interestedness – many scientists have personal agendas for engaging in particular research and may have a vested interest in the outcomes – even more so when research is funded by commercial organizations. – Exercise of judgement – the expert opinion of experienced scientists plays a prominent role in the evaluation of knowledge claims. Moreover, the research 130 Derek Hodson - 978-90-8790-507-1 Downloaded from Brill.com11/09/2020 11:12:23AM via free access

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of newcomers is subject to much more rigorous checks than the work of established scientists. – Non-rationality – scientists do not always act in a fully functional manner and scientific advances can result from non-rational as well as rational actions. – Emotional commitment – commitment to a theory is essential for its advancement; disinterest leads to stagnation. On occasions, however, commitment in spite of substantial contrary evidence becomes unreasonable. In practice, it seems that scientists simply act as they see fit and attempt to rationalize it afterwards. Hence, rather than regarding science as a distinctive way of proceeding, to which all scientists have to conform, it makes more sense to regard science as (no more than) what scientists actually do. Conventions (such as Mertonian norms) do not direct the actions of scientists, they are simply what the collective actions of scientists amount to – at least, in their retrospective rationalizations. In Mulkay’s (1979) words, “it seems more appropriate to portray the ‘norms of science’, not as defining clear social obligations to which scientists conform, but as flexible vocabularies employed by participants in their attempts to negotiate suitable meanings for their own and others’ acts in various social contexts… What is clear is that it is highly misleading to regard the diffuse repertoire of standardized verbal formulations as the normative structure of science or to maintain that it contributes in any direct way to the advance of scientific knowledge” (p. 72). If convention is not a determinant of action, but its product, then the beliefs, practices and values of scientists are reduced to a set of phenomena to be observed (directly or indirectly), analyzed and rationalized. In approaching this description of the scientific endeavour, there are two possible approaches. One is to ask scientists about aspects of their practice, using questionnaires, surveys and interviews; the other is to observe them as they engage in their day-to-day practice in the laboratory, making detailed field notes of events and audiotaping conversations between scientists for subsequent discourse analysis. The former approach, well exemplified by the work of Hagstrom (1965), tends to focus on the large-scale characteristics of science, in particular its growth, organization and established mechanisms for admitting and enculturating newcomers. It also aims at generalizability: what scientists say about their practice is regarded as applying to each and every situation. In contrast, observational studies tend to be smaller scale studies in which researchers use an ethnographic approach to describe and interpret day-to-day events and interactions between scientists in particular situations. Those researchers who adopt this case study approach sometimes make little or no attempt to generalize, regarding it as the reader’s responsibility to determine what, if anything, can be transferred and used to inform and interpret other situations. What these studies reveal is that science is much less linear, much less certain and much more disordered than the conventional image suggests. They also reveal a noticeable mismatch between the rhetoric and the practice of scientists, thus giving good grounds for subscribing to Albert Einstein’s (1933) remark that “if you want to find out anything from [scientists] about the methodology they use… don’t listen to their words, fix your attention on their deeds” (p. 270). 131 Derek Hodson - 978-90-8790-507-1 Downloaded from Brill.com11/09/2020 11:12:23AM via free access

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An important element of this mismatch centres on the cluster of personal characteristics and attributes that have long been regarded in the rhetoric of science education as essential for the successful pursuit of science and, so the science curriculum rhetoric goes, are clearly exhibited in the day-to-day practice of successful scientists: superior intelligence, objectivity, rationality, emotional neutrality, open-mindedness, willingness to suspend judgement, intellectual integrity and communality. Like Mertonian norms, these so-called ‘scientific attitudes’ are said to guarantee proper scientific practice by ensuring that (i) all knowledge claims are treated sceptically until their validity can be judged according to the weight of evidence, (ii) all evidence is carefully considered before decisions about validity are made, and (iii) the idiosyncratic prejudices of individual scientists do not intrude into the decision making. Of course, in traditional science curricula ‘evidence’ is always taken to mean empirical evidence – that is, agreement with the observed ‘facts’. Thus, proper scientific practice is seen to comprise a dispassionate appraisal of that empirical evidence (the ‘facts’) before decisions are taken. It is now more than forty years since Roe (1961) suggested that scientists rarely possess these ‘scientific attitudes’, although (she says) they think that they do. They, too, subscribe to the myth of the emotionally-detached, disinterested and impartial scientist. Or they continue to promote this false image because they perceive it to be in their interests to imply a connection between the disinterested approach and the ‘truth’ of the findings in the battle to maintain high levels of public funding for scientific research.6 Roe concludes: “The creative scientist, whatever his field, is very deeply involved emotionally and personally in his work” (p. 456). Mahoney’s (1979) conclusions about the attitudes and characteristics of scientists, derived from writings by sociologists, historians and scientists, make particularly interesting reading. – Superior intelligence is neither a prerequisite nor a correlate of high scientific achievement. – Scientists are often illogical in their work, particularly when defending a preferred view or attacking a rival one. – Scientists’ perceptions of reality are dramatically influenced by their theoretical expectations. – Scientists are often selective, expedient and not immune to perceptual bias and distortion of the data. – Scientists are among the most passionate of professionals. Their theoretical and personal biases often colour their alleged openness to the data. – Scientists are often dogmatically tenacious and inflexible in their opinions, even when contradictory evidence is overwhelming. – Scientists are skilled in ‘expedient reasoning’ – that is, bending their arguments to fit their purposes. – Scientists are not paragons of humility and disinterest. Rather, they are often selfish, ambitious and petulant defenders of personal recognition and territoriality. Vitriolic episodes and bitter disputes over personal credit and priority are common. – Scientists often behave in ways that are diametrically opposite to communal sharing of knowledge. They are frequently secretive and suspicious of others, and will frequently suppress data until they have established priority of discovery. 132 Derek Hodson - 978-90-8790-507-1 Downloaded from Brill.com11/09/2020 11:12:23AM via free access

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– Far from being a ‘suspender of judgement’, the scientist is often an impetuous truth-spinner who rushes to hypotheses and theories long before the data warrants. Following their study of scientists and engineers involved in NASA’s Apollo Project, Mitroff and Mason (1974) concluded that scientists are arranged along a continuum from extreme speculative scientists, who “wouldn’t hesitate to build a whole theory of the solar system based on no data at all” (p. 1508), to data bound scientists, who “wouldn’t be able to save their own hide if a fire was burning next to them because they’d never have enough data to prove the fire was really there” (p. 1508). These conclusions echo Mahoney’s earlier description of a continuum of scientists: “At one extreme there are ‘speculophobics’ – scientists who devoutly avoid any ventures beyond the data. Their opposites are ‘hypothophiliacs’ – scientists who need less than a hint of evidence to draw sweeping generalizations and ambitious models” (Mahoney, 1979, p. 357). Contrary to the school textbook stereotype, the scientists who produce the most significant work are those who disregard the so-called ‘scientific attitudes’; those who conform may be excellent technicians, but they don’t make the theoretical breakthroughs and procedural innovations. This conclusion is a reminder that we need to be sure which ‘game’ we are playing in school science education, and that we should make it clear to students, too. Careful attention to detail and painstaking accumulation of data is crucial to good science, to the effective conduct of laboratory testing, to the maintenance of safety and to the sound operation of science-based industries, but theoretical breakthroughs are not made this way. As discussed below, creative, theory-building scientists are those who ‘break the rules’ (see discussion of Feyerabend’s principle “Anything Goes” in chapter 5). We need to provide our students with experiences capable of developing both sets of attributes. In contrast to the caricature of scientific inquiry portrayed in many school textbooks, real scientific inquiry is holistic, fluid, flexible, reflexive, context-dependent and idiosyncratic (see chapter 5). It is characterized by frequent false starts, blind alleys and improvised modifications; it can be, and often is, re-directed by unexpected events and by unanticipated technical problems; it can be profoundly influenced by the availability (or not) or particular laboratory equipment or its unexpected malfunctioning, by the publication of a research paper in the same field or chance conversation with another researcher. Among others, Collins (1985) and Latour and Woolgar (1986) describe scientific practice as a long and tedious process for creating order out of disorder, information out of ‘noise’ and organization out of chance events. First, there is the difficult business of extracting data from ‘background noise’ – that is, deciding what is significant and what is not, and imposing meaning frameworks to create a coherent data set. Traditional ‘scientific attitudes’ are of little value here; much more important are intuition and tenacity in the face of conflicting evidence and counter argument from other scientists. Of course, arguing for a particular view will usually involve arguing against another – that is, negating alternative interpretations or rendering them less plausible through argument and skilful presentation of data, with each side in the dispute seeking to ‘explain away’ inconvenient data. Critics will cite researchers’ negative results as 133 Derek Hodson - 978-90-8790-507-1 Downloaded from Brill.com11/09/2020 11:12:23AM via free access

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grounds to dismiss any controversial idea with which they disagree, with any residual positive results being explained away as incompetence, delusion or even fraud. The proponents of the new idea, on the other hand, account for competitors’ negative results from attempted replication in terms of failure to reproduce exactly the same conditions used by them to obtain positive results (Collins & Pinch, 1993). Replication of experimental results, long held to be a cornerstone of scientific method, is much less straightforward than the school science curriculum implies, and what is eventually admitted as satisfactory replication may be a consequence of careful negotiation that relies heavily on intuition and value judgements and takes account of the prestige of the research group (Collins & Pinch, 1993; Knorr-Cetina, 1995). There are a number of reasons why replication is not a simple matter: while scientists engaged in cutting edge research may agree on basic conceptual issues, they may profoundly disagree on proper design of experiments, specifications for instruments and interpretation of data. Complex scientific investigations cannot be reduced to a simple algorithm that can be checked at each stage (see discussion in chapter 5); a great deal of the ‘know how’ that goes into the design of incisive experiments is tacit and intuitive, while much of the expertise that goes into their effective conduct is located at the craft level and is acquired through lengthy onthe-job experience. Given these complexities, it isn’t always clear whether a second experiment really is a replication or just another (different) experiment. Moreover, as Collins (1975) points out, most research groups would not consider exact copies of experiments desirable. First, it would reflect no particular credit on the group, whereas a better experiment would do so, and would give them a competitive edge. Second, a new effect is more powerfully demonstrated or a new explanation more effectively made when more than one approach is used – what social scientists call triangulation. In consequence, attention shifts from replication to what counts as a ‘good experiment’. Of course, in one sense a ‘good experiment’ is one that provides evidence for one’s theoretical claim, a ‘bad experiment’ is one that doesn’t. In contrast to the traditional notion that scientists complete their investigations and theorizing prior to disseminating their findings and conclusions, laboratory studies reveal a much more fluid and interactive relationship in which scientists are engaged in a continuing struggle to persuade themselves and others that their data are important and their interpretations are valid. For some, the laboratory is no longer a site for the discovery and validation of knowledge but a site for the manufacture of knowledge (Knorr-Cetina, 1981, 1983). The study of scientific knowledge is primarily seen to involve an investigation of how scientific objects are produced in the laboratory rather than a study of how facts are preserved in scientific statements about nature. (Knorr-Cetina, 1983, p. 119) Latour and Woolgar (1979, 1986) regard scientific work as essentially a form of writing and the laboratory as an instrument of persuasion through which conjectural statements are transformed into statements of ‘fact’. In other words, meaning is selectively constructed and re-constructed until it is capable of convincing the group with power of decision on acceptability. Recognizing that scientific knowledge 134 Derek Hodson - 978-90-8790-507-1 Downloaded from Brill.com11/09/2020 11:12:23AM via free access

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is negotiated within the community of practitioners opens up the somewhat alarming prospect that the outcome of scientific disputes may ultimately depend on the argumentation skills, prestige and material resources that participants in a dispute can mobilize in making their case. If there exists an unavoidable indeterminacy in principle in relation to scientific decisions, then it may be that the rhetorical brilliance of those advocating a particular outcome, the political saliency of the findings, or the support proponents can draw on, etc., may tip the balance in favour of a specific choice. (Knorr-Cetina & Mulkay, 1983, p. 12) It almost goes without saying that if the skills of persuasion and dissuasion are an important element of scientific expertise, they are an important element of scientific literacy and should be fostered in the science curriculum (Osborne, 2001; Duschl & Osborne, 2002) – an idea that will be elaborated a little in chapter 9. SEARCHING FOR AUTHENTICITY

Laboratory studies go beyond concern with the nature and conduct of experiments to shed light on the laboratory as a ‘cultural space’ within which knowledge is constructed by the collective efforts of scientists. They give us some understanding of “the bricolage, tinkering, discourse, tacit knowledge and situated actions that build local understandings and agreements” (Fujimura, 1992, p. 170) and the subsequent debating, persuading and political manoeuvring involved in gaining the interest and support of scientists outside the immediate group – support that is essential if the research is to become part of accepted scientific knowledge. Scientific objects are not only ‘technically’ manufactured in laboratories but are also inextricably symbolically or politically construed, for example, through literary techniques of persuasion such as one finds embodied in scientific papers, through the political stratagems of scientists in forming alliances and mobilizing resources, or through the selections and decision translations which ‘build’ scientific findings from within. (Knorr-Cetina, 1992, p. 115) Scientists rarely study objects and phenomena as they occur in nature. Indeed, some of the power of experimentation lies in the capacity to control and contrive situations so that scientists do not need to deal with all the complexities of studying an object or phenomenon as it is (it can be simplified, idealized and stylized) or where it is in the real world (by re-locating it to the laboratory, all kinds of technological resources can be brought to bear). Nor do scientists need to accommodate to an event when it happens to occur (natural cycles can be replaced by more convenient ones – more frequent, more predictable). Thus, experiments are representations of reality – processed, manipulated and partial versions of it, rather than the ‘real thing’. Everything in the laboratory is, in some sense, a human construct: the knowledge from which scientists begin, the materials, the measuring devices and other technical tools are all ‘created entities’; laboratory animals are selectively bred; plants are specially grown; pure chemicals are manufactured; and even the 135 Derek Hodson - 978-90-8790-507-1 Downloaded from Brill.com11/09/2020 11:12:23AM via free access

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water supply is sterilized and deionized. Because of the complexity, fluidity and context-specific character of experimentation, scientists themselves could be regarded as a kind of ‘technical device’: repositories of experiential knowledge, tacit understanding, scientific intuition and capacity for critical judgement. Technicians, through their capacity to optimize experimental conditions, to build, maintain and use apparatus specially suited to the circumstances, and to ‘feel’ what is reasonable and acceptable as experimental results, can also be regarded as ‘instruments’ for experimentation (Knorr-Cetina, 1992). Within this socially constructed working environment, the business of doing science proceeds through a series of decisions and negotiations about problems, priorities, procedures, measurements, interpretations, arguments and conclusions. As argued in earlier chapters, there is no one way to proceed on all occasions; scientific method is not a pre-determined algorithmic procedure. Decisions about the most suitable way to proceed are local and context-specific, determined by what is already known about the objects, phenomena or event under investigation and strongly influenced by: (i) access to information (including library provision), (ii) who can be consulted, (iii) what materials, facilities, equipment and other resources are available, (iv) extent of technician support, (v) availability of service laboratories, and the characteristics of their practices, (vi) funding and conditions/ restrictions governing its specific deployment (equipment versus technician support versus research assistants, for example), and even (vii) seemingly trivial matters such as office and laboratory regulations and business hours. Moreover, because of the complexity and uncertainty of scientific investigation there is considerably more at issue than the execution of a pre-determined plan. Fluidity is the key: every decision about procedure is made in the light of a previous decision (and its outcome) and has consequences for future decisions – both within a particular inquiry and within a research programme as a whole. In other words, the products of a particular scientific investigation are not only decision-impregnated, they are also decision-impregnating in the sense that they point to new problems and (to an extent) direct their solution. In effect, the logic of scientific research is an opportunistic one: scientists do what they can in the circumstances and adjust their research goals and intentions to the changing circumstances, modifying their approach in the light of successes and difficulties encountered, exploiting unanticipated opportunities, and constantly monitoring the progress of competing research groups. Success depends on the ability of the scientist to think on several different levels simultaneously, maintaining an overview while analysing the individual elements, piecing together seemingly disparate bits of information, recognizing clues and sensing what moves are appropriate, and at every stage trying to anticipate and counter likely criticisms of the research. Given the messy, fluid and contingent nature of the process, it is not easy to predict the course of an investigation or the likelihood of eventual success. In consequence, it is not possible to devise a set of decisionmaking criteria for would-be researchers to study and apply. This is not to say that scientists are unsystematic or irrational, but it is to say that the openness of scientific inquiry, the context embedded and intuitive nature of the decision making, the craft element of bench expertise, and the tacit knowledge and understanding 136 Derek Hodson - 978-90-8790-507-1 Downloaded from Brill.com11/09/2020 11:12:23AM via free access

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involved in using laboratory instruments skilfully and effectively cannot be easily captured in words. Of course, there is a major mismatch between the way scientific inquiry is conducted and the way it is reported, and a similar mismatch between the private language of argument and negotiation within the laboratory (and embedded in laboratory notebooks) and the public language of scientific argument used in academic journals. The need to communicate one’s findings as precisely and efficiently as possible, and to make them convincing to others, determines the linguistic form of the research report and the scientific paper. Gone are the references to crises, compromises and intuition; replaced by an account in which references to human agency are reduced to a minimum, a text in which the physical world is made to ‘speak for itself’. Thus, the emergence of the ‘correct view’ is portrayed as arising unproblematically from the data (Mulkay et al., 1983). More than 40 years ago, Peter Medawar (1963) asked the provocative question: “Is the scientific paper a fraud?” In the sense that it is constructed to persuade readers of a particular point of view rather than to describe the day-by-day events of the investigation, it is a fraud. It frequently conceals the situationally contingent and opportunistic logic of the inquiry, renders the choice of method straightforward and unproblematic and misrepresents the motives for the work in an effort to provide a clear and logically compelling argument for the validity of the findings and the author’s particular interpretation and explanation. As Knorr-Cetina (1981) so disarmingly puts it: “The scientific paper hides more than it tells on its tame and civilised surface” (p. 94). Latour and Woolgar (1979, 1986) see the creation and deployment of text as the dominant feature of laboratory life and regard enculturation into the scientific community as being, in significant part, the learning of literary techniques for persuading, interesting and influencing others and the mastery of ‘inscription devices’ for enhancing the persuasive power of texts. It seems that whenever technicians are not actually handling complicated pieces of apparatus, they are filling in blank sheets with long lists of figures; when they are not writing on pieces of paper, they spend considerable time writing numbers on the sides of hundreds of tubes, or pencilling large numbers on the fur of rats… When the observer moves from the bench space to the office space, he is greeted with yet more writing. Xeroxed copies of articles, with words underlined and exclamation marks in the margins, are everywhere. Drafts of articles in preparation intermingle with diagrams scribbled on scrap paper, letters from colleagues and reams of paper spewed out by the computer in the next room; pages cut from articles are glued to other pages; excerpts from draft paragraphs change hands between colleagues while more advanced drafts pass from office to office being constantly altered, retyped, recorrected, and eventually crushed into the format of this or that journal. (1979, pp. 48 & 49) Ideas become established, both within the laboratory and beyond, not simply on the strength of the data but through repeated use of data and interpretive commentary in linguistic forms that take away doubt about the preferred view and 137 Derek Hodson - 978-90-8790-507-1 Downloaded from Brill.com11/09/2020 11:12:23AM via free access

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cast doubt on the rival. According to Latour (1987), avoiding ‘isolation’ is a key strategy in winning the argument, hence the heavy use of footnotes, quotations and references to supporting literature – all of which have to be separately addressed and countered by those intent on opposing the argument. Opposing views should be anticipated and dealt with in the text through careful and selective referencing of other research. Latour’s (1987) advice is to “do whatever you need to the former literature to render it as helpful as possible for the claims you are going to make” (p. 37). A convincing text is arranged in layers – in Latour’s words, “a folded array of successive defence lines” (p. 48) to deal with opponents- with each claim being supported by references to other work, cross referenced to other parts of the paper and bolstered by technical detail, diagrams, graphs, equations and the like. Within the laboratory, and the scientific community at large, particular significance is attached to the operation of apparatus capable of providing some kind of ‘written output’ in the form of charts, tables, graphs and figures. Judicious deployment of such ‘inscriptions’, as Latour and Woolgar (1979, 1986) and Latour (1987) call them, gives some increased persuasive power to scientific papers, while reference to expensive ‘inscription devices’ (the technologies that produce them) sends an important message to readers about the resources available to the research team, thereby enhancing the group’s credibility and the likelihood of its ‘products’ being regarded as important. Indeed, these authors ultimately made sense of the ‘laboratory life’ they were studying (their particular sense of it, that is) in terms of the relationships they perceived among the inscription capabilities of scientific apparatus, what they call the “manic passion for marking, coding and filing” and the skills of persuading others through construction of scientific text. Thus, the observer could even make sense of such obscure activities as a technician grinding the brains of rats, by realising that the eventual end product of such activity might be a highly valued diagram. (Latour & Woolgar, 1979, p. 52) Latour (1987) talks about what he calls “black boxes”, a means of encoding certain aspects of a perceived reality within an instrument, procedure or theoretical structure. Using particular black boxes is a useful tactic in mounting a scientific argument because their use signals the legitimacy of the embedded view of the world. With its previously problematic aspects effectively hidden from sight, a black box becomes a powerful tool of persuasion because the intellectual effort that would be involved in mounting an objection to the validity and reliability of the data it produces. As Latour remarks, controversies end when black boxes are successfully deployed. Black box is used by cyberneticians whenever a piece of machinery or a set of commands is too complex. In its place they draw a little box about which they had to know nothing but its input and output… no matter how controversial their history, how complex their inner workings, how large the commercial or academic networks that hold them in place, only their input and output count. (Latour, 1987, p. 2)

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Of course, to be an influential contribution to science, a paper has to be sufficiently convincing and sufficiently important to ensure that ‘significant others’ make use of it, preferably without modification or qualification of its key points. Thus, while scientists extend knowledge in ways that serve their particular interests, they also have to serve the needs and interests of (some) others – for example, by solving a problem that others have encountered, creating a problem that others cannot ignore, developing a powerful new technique for generating data, striking at the fundamental assumptions of the rival’s research programme, or some such provocative move. NORMS, INTERESTS AND VALUES

In the scientific world described by Merton (1973) the academic community is simultaneously a communication system and a reward system. The contributions of individuals are assessed by an audience of peers and if judged to be original and significant they are allowed to be published, and are made available for all to use. Hagstrom (1965) describes it as a ‘barter system’ in which the scientist gets recognition (which may subsequently translate into tangible rewards such as tenure, promotion, research grants, or even a Nobel Prize) in ‘payment’ for providing new intellectual resources (information, ideas, techniques, etc.) and, in turn, such recognition stimulates the kind of approved behaviour that leads to further recognition. There is implicit agreement among scientists to adhere to the institutional norms described by Merton and Barber because they provide the optimal way of producing certified knowledge which, in turn, can be exchanged for recognition and reward. If everyone ‘abides by the rules’ then everyone ‘gets a fair go!’ In Storer’s (1966) words: Scientists subscribe to the norms of science first of all because of their importance for the continued, adequate circulation of the commodity in which they are mutually interested… It is the occasional reinforcement given these norms by the scientist’s awareness of their relevance to his own interest in obtaining competent response to his work rather than the general goal of science, which I feel accounts for their continued moral potency… these norms are natural concomitants of the desire to be creative. (p. 84) It is noteworthy that Storer includes successful completion of creative acts in his description of rewards. As Wong and Hodson (2008a,b) report, many scientists cite this as a major driving force for their research, alongside curiosity, “finding out how things work”, “making a contribution”, improving the quality of human life and the sheer enjoyment of solving complex problems. A decade after Hagstrom’s influential work, Bourdieu (1975) introduced the notion of a capitalist market economy in which scientists are engaged in a competitive struggle for a monopoly on scientific credit – symbolic capital acquired by scientists through research and other technical achievements and capable of conversion into resources for further scientific production. Thus, the cooperative world of science envisaged by Merton and Hagstrom was replaced by an essentially 139 Derek Hodson - 978-90-8790-507-1 Downloaded from Brill.com11/09/2020 11:12:23AM via free access

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antagonistic world, in which scientists seek to dominate the field and to discredit competitors. The scientific field is the locus of a competitive struggle, in which the specific issue at stake is the monopoly of scientific authority, defined inseparably as technical capacity and social power. (Bourdieu, 1975, p. 19) Latour and Woolgar (1979, 1986) modify Bourdieu’s account quite radically by suggesting that scientists do not simply seek credits or rewards; rather, they are investors in credibility – a form of capital that is capable of ready conversion into research grants, equipment, and in due course, further knowledge production. Scientists ‘invest’ in fields and topics that promise the greatest return for their efforts, and the credibility they gain from producing new knowledge is converted into resources for ‘reinvestment’ in further research. Therefore, the goal is not the pursuit of truth, nor the gaining of recognition per se. Successful research groups are those capable of accelerating and expanding the credibility-investment cycle. In a sense, production (publication) for the sake of production is the hallmark of scientific capitalism. In the traditional forms of ‘basic’ or ‘fundamental’ research envisaged by Merton (1973), usually located in universities and/or government research institutes, ‘pure scientists’ constitute their own audience: they determine the research goals, recognize competence, reward originality and achievement, legitimate their own conduct and discourage attempts at outside interference. In the contemporary world, research is often dependent on expensive technology and so must meet the needs and serve the interests of those sponsors whose funds provide the resources. In consequence, scientists have lost a substantial measure of autonomy and are now seen, in some situations, as advocates for a particular point of view rather than disinterested arbiters of the ‘truth’. The vested interests of the military and commercial sponsors of research, particularly tobacco companies, the petroleum industry, the food processing industry, pharmaceutical companies and the nuclear power industry, can often be detected in research design – especially in terms of what and how data are collected, manipulated and presented. More subtly, in what data are not collected, what findings are omitted from reports and whose voices are silenced. Commercial interests may influence the way research findings are made public (e.g., press conferences rather than publication in academic journals) and the way the potential impact of adverse data is minimized – for example, in publicizing the value of oral contraceptives and hormone replacement therapy, the increased risks of cervical cancer, breast cancer and thromboembolism were given little attention. Science is no longer the disinterested search for truth and the free and open exchange of information portrayed in the school science textbook stereotype. Rather, it is a highly competitive enterprise in which scientists may be driven by self-interest and career building, financial inducements provided by business and commerce, or by the ‘political imperatives’ of military interests. The cynical interpretation of this state of affairs is that the science that ‘gets done’ is the science that is in the interests of the rich and powerful, the self-interest of particular scientists, and the companies that employ them. Chambers (1984c) deals with these matters 140 Derek Hodson - 978-90-8790-507-1 Downloaded from Brill.com11/09/2020 11:12:23AM via free access

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admirably, and appropriately for both school science and science teacher education, in his compelling account of the manufacture and use of pesticides, the DDT controversy and the work of Rachel Carson.7 One consequence of this struggle for recognition, credit and credibility is the creation of boundaries between different sub-disciplines of science and between ‘insiders’ and ‘outsiders’. Science is increasingly fragmented, diversified and specialized. The days when any one individual could command knowledge of all science are long gone. While subject disciplines retain some political significance at the university level in terms of teaching, most of the effective work at the research level goes on in sub-groups of scientists with common interests (but little in common with other sub-groups). Across institutions, these sub-groups form ‘invisible’ research networks (Mulkay, 1977), whose members differ from the members of other groups in terms of research interests (area of concern, phenomena studied, etc.), theoretical frameworks employed, procedures, instruments and technology deployed, to such an extent that Hacking (1992) regards their practices as incommensurable. The greatest difference between sub-disciplines is in terms of the scientists themselves – in particular, their experiences, skills and network of informants. Research groups seek to retain this expertise within the group because that is where their investment capital is primarily located. Because a substantial component of this expertise is tacit and not amenable to transfer in written form, even if it were desirable, it has to be learned on-the-job and through personal contact with experts. As Ravetz (1971) says: “In every one of its aspects, scientific inquiry is a craft activity depending on a body of knowledge which is informal and partly tacit” (p. 103). Of course, proliferation of research groups and sub-disciplines leads to even more intense competition for limited resources, with possible deleterious impact on the ways in which scientists conduct their affairs. Callon et al. (1986) see the efforts of scientists to rally resources, and their methods of doing so, as similar in kind to those of politicians and entrepreneurs: “Controlling resources, controlling the environment, and controlling the world that is being built, all of these are aspects of the entrepreneurial activity of scientists. In a sense then, they are not only practicing science – they are also practicing politics, economics, and sociology” (p. 10). While the Mertonian norm of ‘communality’ demands openness of communication, competition fosters secrecy and concealment of information. Both commercial and military interests lead to increasing secrecy and to privatization of knowledge. Removal of science from public scrutiny and all its attendant safeguards, and the tendency to ‘cut corners’ brought on by impatience to get quick results, strike at our ability to distinguish sound from unsound knowledge, and plausible from implausible chains of arguments, and the public is left with no real means of judging the ‘warrant for belief’. When secrecy replaces openness, and the pursuit of personal reward replaces the search for explanation, science is profoundly devalued and the public can no longer trust what scientists tell them. When Latour and Woolgar (1986) assert that “each text, laboratory, author and discipline strives to establish a world in which its own interpretation is made more likely by virtue of the increasing number of people from whom it extracts compliance” (p. 285) they seem to suggest that any way of playing the game is acceptable if it brings success. 141 Derek Hodson - 978-90-8790-507-1 Downloaded from Brill.com11/09/2020 11:12:23AM via free access

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Indeed, Pinch and Collins (1984) go so far as to endorse deception when they suggest that one of the research groups they studied would have been more successful if the members had suppressed ‘inconvenient’ evidence – a position which Slezak (1994) characterizes as “truth is what you can get away with”. Sadly, there are scientists, most notably the psychometrician Cyril Burt, who take this dictum at face value and fraudulently manufacture the ‘evidence’ on which they build their theories. Indeed, it seems that fraud, the most blatent form of selfinterest serving, is much more widespread than we might expect or that scientists will generally admit to, or that we tell students in school (Broad & Wade, 1982; Kohn, 1986; Bell, 1992; Wible, 1992; Judson, 2004).8 While they are a long way from fraud, Wong and Hodson (2008a,b) report several examples of what might be termed ‘sharp practice’: using institutional power to stifle dissent, publishing false data to mislead rivals, and using the peer review system to delay competitors. SCIENTIFIC KNOWLEDGE AS A SOCIAL CONSTRUCT

It has been asserted a number of times in this book that we do not and cannot know the world as it ‘really is’. Rather, we describe and explain the world in terms of the conceptual frameworks that scientists have developed. While material reality will closely limit or constrain the number of possible ways of knowing, reality alone is insufficient to determine the truth or what we believe about it. We have to supply much of it, through our imagination. In this chapter, it has been argued that science (including the processes of theory-building) is a socially-embedded activity. In other words, scientific knowledge is socially constructed through the practices of the scientific community, in response to the demands, needs and interests of the wider community that surrounds and supports it. Furthermore, the procedures of science (experiment, observation, etc.) are based on conventions that are, themselves, human constructs, subject to variation and the outcome of negotiation among scientists. Some sociologists of science (and, of course, some philosophers of science, historians of science and scientists) go further, claiming that the knowledge produced by scientists is no more than a social construct: “Scientific activity is not about ‘nature’, it is a fierce fight to construct reality” (Latour & Woolgar, 1979, p. 2, emphasis added). In short, science creates its own reality. There is a sense in which this is self-evidently true: the science and technology of the modern laboratory is sometimes capable of creating phenomena and objects that previously did not exist.9 The laser is a prime example of such a technology. So, too, is Dolly the cloned sheep. For the past 50 years or so the research of most chemists and materials scientists has been directed towards the synthesis of molecules and materials that do not exist in nature. However, the case made by social constructivists is that all scientific knowledge is simply a social construct, and no more than a social construct. Crucially, it could have been constructed differently. In other words, scientific knowledge is not just socially constructed, it is a social construct, a mere social convention. Moreover, if scientific knowledge and its means of production are social products, and so could be otherwise, it follows that the criteria of judgement in science must also be a social construct. Indeed, rationality itself is simply a human convention, and could be otherwise. 142 Derek Hodson - 978-90-8790-507-1 Downloaded from Brill.com11/09/2020 11:12:23AM via free access

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From Shapin’s (1979) classic study of phrenology it is fairly easy to see why and how a theory linking intellectual ability with social class was developed in Victorian England, but the author goes on to make the point that phrenology cannot be understood apart from the historical contexts of use and sociopolitical interests. This assertion has been taken by some scholars as a warrant to shift from the position that knowledge is influenced by the social context in which it is produced to the position that all knowledge is solely determined by the social context. The only reality is the social reality, and all knowledge is relative to the social context of its production. Truth becomes simply the beliefs and values that happen to prevail among members of influential communities of practice. Knowledge for the sociologist is whatever men take to be knowledge. It consists of those beliefs… which are taken for granted or instituionalised, or invested with authority by groups of men. (Bloor, 1976, p. 2) I argued in chapter 4 that all the so-called processes of science are theory impregnated and theory driven. The way in which entities are classified, for example, depends on one’s purpose and theoretical knowledge. Borges (1964, p. 103) reports that the ancient Chinese encyclopaedia, The Celestial Emporium of Benevolent Knowledge, divides the animal kingdom into the following categories: (a) those that belong to the Emperor; (b) embalmed ones; (c) those that are tamed or trained; (d) suckling pigs; (e) mermaids (or sirens); (f) fabulous ones; (g) stray dogs; (h) those that are included in this classification; (i) those that tremble as if they were frenzied or mad; (j) innumerable ones; (k) those drawn with a very fine camel’s hair brush; (l) others; (m) those that have just broken a flower vase; (n) those that from a distance look like flies.10 Why does it sound so odd, even ridiculous, like something from a Monty Python sketch? In part, it is because our own familiar classification system has pre-determined the way we think and we see no need to include imagined animals, such as “fabulous ones’ and mermaids, in our classification. In part, it is because the (a), (b), (c) style of presentation sets up an expectation that the categories are mutually exclusive, logical, purposeful and inclusive of all animals. We are then presented with the category “included in this classification”. The system clearly doesn’t fit any purpose we might have. Nor can we ascertain its underlying logic. But, as argued in chapter 5, the categories we employ in classification are simply those that we have decided are significant and logical. They don’t emerge from our observations; rather, we impose them on our observations. We choose to observe and classify in one way rather than in some other way because it suits us to do so, because we are comfortable with that classification, because it serves our needs, purposes and interests.11 In other words, the categories we employ are convenient, socially constructed ones. Learning to classify ‘properly’ is a matter of learning to employ the classification system sanctioned by the particular community we inhabit. History tells us that the ways in which we classify things have changed over time. They also vary quite substantially from culture to culture. But it takes an example like the one presented by Borges to remind us of the extent of social construction in familiar everyday language and in scientific terminology. In Foucault’s (1970) words, “the thing we apprehend in one great 143 Derek Hodson - 978-90-8790-507-1 Downloaded from Brill.com11/09/2020 11:12:23AM via free access

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leap, the thing that, by means of the fable, is demonstrated as the exotic charm of another system of thought, is the limitation of our own, the stark impossibility of thinking that” (p. xv) Chapter 6 included a brief discussion of the ways in which scientists use a range of analogies and metaphors in building theories to account for natural phenomena. In other words, scientists attempt to make sense of the unknown in terms of what is familiar – both to themselves and to others. Kepler used metaphors from music and geometry to formulate views about planetary orbits; Rutherford and Bohr used the analogy of planetary motion to think about atomic structure. The everyday language of science is rich in embedded metaphor, simile and analogy: electrical resistance, the flow of electrons, genetic code, messenger RNA, natural selection, computer virus, and even hormonal permissiveness and antagonism. Because the effectiveness of such imagery is rooted in its familiarity, metaphors and analogies do not easily cross cultural boundaries (Nashon, 2003). It is tempting to speculate on whether the various ‘thematic features’ of scientific thought identified by Holton (1986) are also culturally specific, particularly the tendency to use dichotomies and hierarchies. Similar questions arise with respect to what Jurgen Habermas (1971) calls the universal human interest in the ‘technical control of nature’ and the anthropocentric motivation identified by Smolicz and Nunan (1975) as one of four “ideological pivots” underpinning both science and science education (see chapter 2). One further point should serve to complete the case for science as a social construct. According to some sociologists of science, academic journals are not devices for disseminating truth; rather, they are the means by which the scientific community imposes meaning – that is, enforces the current paradigm. Firstly, the distinctive language is a social construct and could be different. It is an imposed convention that serves a particular purpose – ensuring conformity to imposed ways of seeing the world. Forcing people to use a particular language is an important first step in controlling the way they think. Throughout history language has been used as an instrument of control, especially in colonial conquest. Secondly, the whole enterprise of refereeing for publication via peer review is a tradition established by the community. It, too, is a social construct and part of the mechanism by which scientific knowledge is ‘manufactured’, and is intimately concerned with issues of power, prestige and reward (in the form of funded research contracts, for example). If the ways in which we classify and observe are ‘conventional’ (that is, social conventions that we choose, for whatever reasons we regard as important), if scientific theories are often metaphoric in origin and, therefore, socially and culturally dependent, if science is conceived, conducted and reported within a language that is constructed to serve the purposes of a particular group, and if knowledge is intimately bound up with human interests of various kinds, then it seems to follow that scientific knowledge is determined by the prevailing sociocultural climate (Barnes & Edge, 1982). In other words, it is a social construct – and possibly no more than a social construct. Scientific knowledge is ‘what scientists say it is’, for the reasons they choose. It could be otherwise. It has no special status. Science is ‘no better’ than any other knowledge about natural phenomena and events; it is just ‘different’. This position is used to underpin arguments for the legitimacy of ethnosciences and argue for the inclusion of traditional environmental 144 Derek Hodson - 978-90-8790-507-1 Downloaded from Brill.com11/09/2020 11:12:23AM via free access

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and technological knowledge in the school curriculum, and to substantiate the claim that science is inherently sexist and racist – in that it reflects the interests, ways of thinking and values of Western males.12 Although a reasoned consideration of these arguments and claims is outside the scope of this book,13 it is worthwhile rehearsing (very briefly) the basic ‘common sense’ argument, on the grounds that it informs the position we might take with respect to science education. Since most scientists, for whatever social reasons, have been male there is good reason to expect that the science produced will be androcentric (male centred and male biased) simply because it reflects the outlook, interests, priorities and experiences of those who produced it. If it is legitimate to refer to masculine ways of thinking, then science could be expected to reflect them, and some would argue that prominent features of science such as analysis, quantification and the use of hierarchies and dichotomies are, indeed, illustrations of such masculine bias. So, too, the underlying values of science relating to control and manipulation of the natural environment. Furthermore, the argument goes, because science plays such a powerful ideological role in our society it has functioned to legitimate social inequality between the sexes – in other words, to discriminate against women. For many years, women were denied access to science – presumably in order to retain power and influence in the hands of men. In more recent years, with the removal of formal barriers to access, the masculine face of science has functioned to dissuade, limit or restrict access by making women feel uncomfortable or ‘out of place’. It is a truism that a society14 in which one gender (or race) is dominant is likely to distribute resources disproportionately, with the greater share going to the dominant group and the inequity justified on the basis of presumed inherent differences between dominant and subordinate groups. Thus, allegations of gender bias come in a variety of forms: – Claims about the unequal composition of the profession and the unfair treatment of women in it/by it. – Claims about the failure of the profession to investigate matters of interest and importance to women. – Charges that scientific research victimizes women. – Charges that scientists have projected their culture’s gender stereotypes onto the natural world. – Assertions that the language of science is masculine. – Assertions that scientific thinking itself is essentially a masculine way of theorizing and arguing. – Assertions that the underlying values of science are masculine. To all these charges can be added all the evidence and argument that science education is biased in terms of gender and serves to disadvantage young women – another vast literature that is outside the scope of this book.15 In addition, these arguments and claims about gender bias are fairly easily extended to encompass ethnicity. The case is essentially the same: because most scientists are and have been Western scientific practice and the knowledge it generates has a Western bias. Furthermore, science has often been used to oppress and to discriminate against particular ethnic groups. 145 Derek Hodson - 978-90-8790-507-1 Downloaded from Brill.com11/09/2020 11:12:23AM via free access

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Acknowledging that science is a socially embedded practice, admitting to the possibility that some of our scientific knowledge may be no more than a social convention, and recognizing the potential for bias and distortion in the construction of science, raises questions about the demarcation criteria of science – in particular, whether the distinctiveness of science is located in its area of concern, concepts, methods, traditions, linguistic conventions, criteria of validity or underlying values. It prompts further questions about which of these elements could be changed and the activity still be characterized as science? If certain elements could be changed, should they be changed? Would science be improved (in some significant way) by such changes? If so, in what ways? If change is considered desirable, how can it be brought about? ENDNOTES 1

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‘True’ is being used here in the sense of ‘scientifically true’ (the theory has achieved consensus within the community of scientists) - as discussed in previous chapters. This may be a Western characteristic. The traditional environmental knowledge of Aboriginal Australians, for example, puts much more emphasis on usefulness in a specific context than on generalizability across contexts as a criterion of validity. Hence, there is no need to seek similar or consistent explanations (Christie, 1991). One particularly startling study of the peer review process suggests that papers are sometimes accepted more on the basis of institutional affiliation of the authors than on the academic merits of the paper (Peters & Ceci, 1982, 1985) – a view endorsed by several of the scientists interviewed by Wong and Hodson (2008a,b). Merton first outlined this theoretical framework in a 1942 essay titled “Science and technology in a democratic order”, published in the Journal of Legal and Political Sociology. The citations in this chapter refer to a subsequent work published in 1973 (see references). Only six of Mitroff’s list of eleven counter-norms are directly relevant to the discussion in this chapter. Science teachers may also feel some vested interest in sustaining this image of science as a means of enhancing their status in school (Gaskell, 1992). See Dillon (2005) for a commentary on the continuing significance of Silent Spring (Carson, 1962), written to commemorate the 40th anniversary of its original publication. O’Rafferty (1995) makes a clear and strong case for a study of fraud and scientific misconduct to be part of the science curriculum. Cartwright (1983) suggests that one of the primary purposes of experiments is to create phenomena and events as evidence for the validity of theoretical speculation. Similarly incomprehensible to contemporary science is the assertion by Parcelsus that good doctors should not have red beards and his belief that an infusion made from a plant with a leaf pattern resembling a snake will provide protection against poisons. Although it is an urban myth that Inuktitut and the five Yup’ik languages have more than a hundred words for classifying snow, these languages do have more than English because there is a need for them. There are probably between 15 and 18, depending on interpretation, compared with about 6 to 9 in English (including snowflakes, falling snow, snow ‘on the ground’, snowdrift, slush, blizzard, sleet, frost and ice). Not surprisingly, many scholars (especially scientists and philosophers) have little patience with this proposition. Mario Bunge’s (1992) response is characteristically forthright: “There are no such things as proletarian science or Aryan science, black mathematics, or feminine philosophy. These are just political or academic rackets. To be sure, learning prospers more in some groups or societies than others, but so does superstition” (p. 51). Useful starting points for teachers wishing to acquire some awareness of this literature are Shepherd (1993), Keller and Longino (1996), Etkowitz et al. (2000), Lederman and Bartsch (2001). ‘Society’ is used here in the several senses that ‘community’ has been utilized throughout the chapter – the laboratory group in which a scientist works, the group of scientists engaged in similar

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15

and related research, the various official governing bodies (including publishing mechanisms), and society as a whole. Part of the drive for universal critical scientific literacy necessarily includes establishment of a much more inclusive form of science education – with respect to gender, ethnicity, class and sexual orientation (Gaskell & Willinsky, 1995; Roychoudhury et al., 1995; Barton, 1998; Barton & Osborne, 1998). It is also important for students to be made aware of gender bias in science and science education.

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MAKING A CASE FOR HISTORY OF SCIENCE Going Beyond Dates and Anecdotes

Developing an argument for including history of science in the school science curriculum should entail more than strenuous efforts by those with a keen interest in history seeking a suitable role for it. The curriculum is already overloaded with content and little is to be served by further addition unless the additional (historical) perspectives can enhance the achievement of key learning goals or assist students in reaching understanding that is difficult or impossible to achieve in other ways. Of course, one could argue for history of science as an alternative to handson activities in situations where experiments are difficult to perform, expensive, dangerous, unacceptably time-consuming or ethically inadmissible, but that is no more an argument for deploying history of science than for using computer simulations or watching videos. What is needed is an argument that focuses specifically on what history of science offers in the way of a distinctive learning experience. Such arguments have a long history in school science education (Sherratt, 1982, 1983; Brock, 1989), though the nature of the argument, and the success of its advocates in convincing curriculum developers, has shifted substantially over the years. Not surprisingly somewhat different arguments are advanced by different ‘stakeholders’ – that is, by historians of science, philosophers of science, sociologists of science, scientists and science educators. Among the most prominent, persistent and successful arguments is that history of science promotes student learning of science – that is, it assists concept acquisition and concept development. In his splendid overview of these arguments, Matthews (1994) gives prominence to the views of Ernst Mayr (1982): I feel that the study of the history of a field is the best way of acquiring an understanding of its concepts. Only by going over the hard way by which these concepts were worked out – by learning all the earlier wrong assumptions that had to be refuted one by one, in other words by learning all past mistakes – can one hope to acquire a really thorough and sound understanding. In science one learns not only by one’s own mistakes but by the history of the mistakes of others. (p. 20). There are at least three important points here. First, one learns from recognizing, analyzing and correcting one’s own mistakes; second, one learns from descriptions of the mistakes of others; third, a thorough understanding of conceptual niceties can only be acquired by putting oneself in the position of the ‘pioneers’ of the discipline and appreciating the specific problems with which they grappled. A fourth, closely related argument, deriving from Piaget’s (1970b, 1972) writing on genetic epistemology, is that individual learning histories in science tend to mirror the historical development of scientific concepts (Driver & Easley, 1978; McCloskey, 149

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1983; Nussbaum, 1983, 1989; McDermott, 1984; Hashweh, 1986; Vosniadou & Brewer, 1987; Nersessian, 1989; Mintzes et al., 1991; Gil & Solbes, 1993; Tsaparlis, 1997; van Driel et al., 1998). If this is the case, it follows that knowledge of the historical development of a discipline can sometimes help teachers to anticipate, understand and deal with the conceptual difficulties that students are likely to encounter and the kind of misconceptions they are likely to hold (Wandersee, 1985; Steinberg et al., 1990; Barker, 1995). Studying episodes in the history of science will indicate the kind of questions teachers should ask, the observational evidence they should seek and the experiments they should conduct in order to enhance student learning. In that sense, history of science is just as much for teachers as it is for students. As Sequeira and Leite (1991) point out, history of science is particularly helpful in identifying parallels between the problems that accompany conceptual change strategies with students and the historical resistance to new ideas and the overthrow of existing ideas. An explicit comparison of historical misconceptions with current scientific explanations helps both teachers and students to understand the ways in which common sense everyday understanding frequently reinforces misconceptions and, thereby, lays a good foundation for challenging and changing students’ own misconceptions in a non-threatening way. It is both intriguing and comforting for students to discover that eminent scientists of the past had views similar to their own. They realize that it was a perfectly good and sensible view to hold, even though it later turned out to be incorrect, and so they are better placed, both cognitively and emotionally, to engage in critical confrontation of other ideas they hold. Campanario (2002) extends Sequeira and Leite’s (1991) argument to embrace a thorough study of the scientific community’s resistance to new ideas and episodes of ‘delayed recognition’ in order to shed light on the problems of conceptual change in students. Many ‘good ideas’ in science were initially rejected through simple errors of judgement and because of ‘conceptual conservatism’, metaphysical and religious objections, concerns about methods of data generation, intuition, persistent simplistic assumptions (e.g., that proteins, rather than DNA, must be the carrier of genetic information on grounds of their structural diversity) and professional rivalries. Studying such episodes can help students to reflect on, and perhaps gain greater control over, their own learning. Such metacognitive skills will, of course, enhance future learning, not least because students will have more confidence when facing the emotional demands of changing their own conceptions. Rudolph and Stewart (1998) advocate a similar approach: studying opposition to Charles Darwin’s The Origin of Species as a way of shedding light on the difficulties that some students (and some adults) experience in accommodating the notion of evolution by natural selection. Similarly, Gauld (1998) urges teachers to present original arguments by Newton and his contemporaries as a means of rendering Newton’s Third Law more plausible to students. A somewhat different version of a parallelism argument between the history of science and individual learning histories was made in a report, Science Teaching in Secondary Schools, by the British Association for the Advancement of Science (BAAS, 1917), cited by Sherratt (1982) and Jenkins (1989). Drawing on the ideas 150 Derek Hodson - 978-90-8790-507-1 Downloaded from Brill.com11/09/2020 11:12:23AM via free access

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of Percy Nunn, the report claimed that both proceed through three phases of interest in understanding the natural world: wonder, utility and systematizing knowledge for the purposes of intellectual satisfaction. At about 11 years old, children respond to “the direct appeal of striking and beautiful phenomena”; then, after discovering and appreciating the utility of scientific knowledge, they are ready (at age 17, or thereabouts) to accept and study the systematization of knowledge. Sherratt (1982) also cites a passage from the Spens Report (Board of Education, 1938) that clearly illustrates the application of Nunn’s views to the history of electricity. (It began) with a period of wonderment and delight in marvellous and bizarre phenomena for the first time brought to light… it passed to the exploitation of electricity in the service of man… and was completed by the contemporary phase – initiated by the great work of Clerk Maxwell – in which the physicist seeks to construct a picture of the whole material world in terms of electrical entities. (Spens Report, 1938, cited in Sherratt, 1982, p. 228) However, it is important not to make too much of these kinds of parallel. There are some very important differences between children’s naïve thinking in the 21st Century, as they struggle to learn existing science, and the earlier speculations of scientists as they struggled to create that science, largely due to very significant differences in social, cultural and intellectual contexts. As noted in chapter 7, how one thinks and the worldview that underpins beliefs and values are just as much a product of one’s time and place as what one thinks and what one thinks about (i.e., the theories to which one subscribes).1 Added to which there are, of course, major differences in experience and maturity of intellectual judgement that result in substantial differences in the way conclusions are reached and in the extent to which metacognitive awareness impacts the thinking processes (Vosniadou & Brewer, 1987; McCloskey & Kargon, 1988; Gauld, 1991). Moreover, to reiterate a point made earlier in this book, doing science and learning science are significantly different activities: scientists struggling to create new concepts and conceptual structures to solve the theoretical and empirical problems confronting them are engaged in a very different exercise from students struggling to use existing concepts, or variations of them, to solve problems set by teachers. While scientists’ past views were likely to have been embedded in a complex, wide ranging and coherent explanatory system, children’s views are just as likely to be part of an assembly of ‘minitheories’ (Claxton, 1991), each of which is generated to engage satisfactorily with particular phenomena and events. In pointing to other traps for the unwary, Duschl et al. (1992) remind us that teachers attempting to use an historical approach on the basis of parallelism are faced with a crucial decision about whether to present a theory in the ahistorical context of justification (without regard to predecessor theories) or in the historical context of discovery and development, arguing that the former is more appropriate to episodes of normal science and the latter to scientific revolutions. They also suggest using “the context of justification whenever new theory requires only weak restructuring on the part of the student and the context of development when it requires radical restructuring” (p. 28).

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Nevertheless, despite all these caveats and difficulties much is to be gained by leading students through part of that historical journey by means of carefully selected episodes and topics (‘historical vignettes’, as Wandersee (1990) calls them), using curriculum materials that pitch the level of cognitive demand at an appropriate level for the students. The legitimate, sure, and fruitful method of preparing a student to receive a physical hypothesis is the historical method. To retrace the transformations through which the empirical matter accrued while the theoretical form was first sketched; to describe the long collaboration by means of which common sense and deductive logic analyzed this matter and modelled that form until one was exactly adapted to the other: that is the best way, surely even the only way, to give to those studying physics a correct and clear view of the very complex and living organization of this science. (Duhem, 1962, p. 268) In developing their notion of Large Context Problems (LCPs), Stinner and Williams (1998) add a motivational element to claims for the educational benefits of including historical studies in the curriculum – the excitement of sharing “the frustrations and rewards of the intellectual struggles of those who have made important scientific discoveries” (p. 1029). LCPs are ‘science stories’ built around powerful unifying ideas chosen for their curriculum saliency. Stinner and Williams (1993) argue the value of LCPs on two grounds: first, well-designed LCPs make very effective curriculum resources; second, their construction can play an effective role in sensitizing student teachers to the value of historical studies and awakening awareness of students’ alternative frameworks of understanding. In the context of teacher education, they say, the approach works best when the stories are created collaboratively by instructor and students in conformity with the following guidelines: – Map out a context with one unifying central idea both important to science and likely to capture student interest. – Provide experiences that can be related to the students’ everyday world at a level and in a way that makes sense to them. – Create and develop a storyline that will dramatize and highlight the main idea, even though the story elements may not all be historically accurate. – Ensure that the main ideas, concepts and problems to be addressed arise ‘naturally’ from consideration of the context.2 – Ensure that the concepts are ‘diversely connected’ (i.e., within the storyline and with everyday experience) and that there is scope for individual extension and elaboration. These features of good LCP design reflect Kenealy’s (1989) assertion that telling a coherent story, with a beginning, a middle and an end, and in which the characters’ actions are seen to make sense in relation to the overall theme, may be the best way of conveying complex ideas: the key, he says, is “a careful construction, an understandable rationale, and minor and major closures, all told while paying attention to making this technical construction interesting and exciting” (p. 214).

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Similar pedagogic motives and design principles underlie the detailed case study of the controversy between creationism and evolution developed by Michael Ruse (1989), the teaching unit on atomic theory (Thales to Dalton) designed by Jutta Luhl (1992), the history of sickle cell anaemia used to teach population genetics (Howe, 2007), and the use of historically significant experiments by Seroglou et al. (1998) to clarify student thinking about electromagnetism. An interesting variation on this theme is Lochhead and Dufresne’s (1989) idea of using ‘dialogues’ between important scientists – for example, between Aristotle and Galileo – as a way of elucidating conceptual difficulties and illustrating the chain of argument connecting theory and observation. More recently, Hoadley and Linn (2000) have described an approach simulating ‘historical debate’ (between Kepler and Newton) using online asynchronous discussion. HUMANIZING SCIENCE AND BRIDGING THE GAP

A second well-used argument for the inclusion of history of science in the school science curriculum is that it humanizes science and science education. Jenkins (1989, p. 25) identifies two principal reasons why this claim was “pressed with particular vigour in the years immediately following the First World War and, more generally, during the inter-war period”, particularly in the United Kingdom. First, the rapid growth in the history of science as an academic discipline; second, the reaction to what many saw as the ‘prostitution’ of science, particularly German science, in pursuit of military goals. He cites the work of Richard Livingstone (1916) criticizing contemporary science education because it “tells us hardly anything about man. The man who is our friend, enemy, kinsman, partner, colleague, with whom we live and have our business, who governs or is governed by us, never comes within our view” (cited in Jenkins, 1989, p. 25). Close to a century later, this is still the case for the science education of many students; science is still presented in a way that is austere, depersonalized, authoritarian and remote from personal experience History of science can go some way towards changing this unattractive face of science education by showing students that scientists are people, too, with all the hopes and fears that drive the rest of us, and by showing them that science is conducted for and in the interests of people.3 As Matthews (1994) remarks, “the lives and times of the great and not-so-great scientists are usually full of interesting and appealing incidents and issues that students can read about, debate and reenact… History is a way of putting a face on Boyle’s Law, Ohm’s Law, Curie’s discoveries, Mach bands, Planck’s Constant and so on” (p. 52). History of science shows students that the concepts and theories of science were developed by particular people, at particular times, in response to particular problems, needs and interests. The ‘big ideas’ of science did not just appear, fully developed, sometime in the recent past. Shedding light on the motives, feelings, thoughts, commitments, apprehensions, triumphs, failures, mistakes, changes of plan and struggles of scientists is a way

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of making science more inviting and more accessible. For example, by exploiting their natural interest in people, students can be subtly led to an interest in what scientists do, and why and how they do it, thus countering some of the current disinclination to study science. As I intimated in the Preface to this book, my own interest in science was triggered by the historical vignettes and anecdotes included in school science textbooks written by E.J. Holmyard and F. Sherwood Taylor, though more systematic theoretical arguments and empirical research data on the ways in which history of science can impact favourably on attitudes to science, especially for girls, are provided by Russell (1981), Nielsen and Thomsen (1990), King (1991) and Thomsen (1998).4 By providing more authentic information about the realities of doing science and by helping them to recognize that scientists are not ‘super human geniuses’ but ordinary people, just like them, some students may come to realize that they can become scientists, too, provided they have sufficient determination and persistence. In fact, history of science as a kind of careers education was listed by two respondents in Galili and Hazan’s (2001a) study of Israeli teachers’ motives for including history and philosophy of science in the curriculum. A related argument is that history of science, especially historical accounts of 20th and 21st Century science, can be an effective way to bridge the ‘gap’ between the two cultures of arts and sciences so lamented by C.P. Snow (1962) – thus simultaneously broadening the perspectives of future scientists/engineers and ensuring that future politicians and business leaders have some basic understanding of science, scientists and scientific development.5 As Conant (1951) asserted, more than a half-century ago, all citizens should have a robust understanding of the relationships among government, industry and commerce, education, and issues of scientific research and development. In a sense, this is the argument advanced in chapter 1 that some basic knowledge of the history of science (and knowledge of the philosophy and sociology of science) is an essential component of scientific literacy for citizenship and assists the development of the necessary skills for addressing current policy and potential future developments in a more critical way – that is, serious and critical consideration of questions about environment, health, natural resources and the like, informed confrontation of ethical issues and realistic preparation for change brought about by technological innovation. Of course, providing common ground for Arts and Science specialists to study is not without its problems: a proper appreciation of the historical development of major ideas in science requires both substantial scientific understanding and substantial historical sensitivity, and questions must be asked about whether either party would be sufficiently well-equipped to engage in serious study. Added to which is the problem that many science specialists are depressingly narrow in their interests, and may be reluctant to engage seriously with material that does not contribute directly to their mastery of science content, while arts specialists may exhibit an initial aversion to studying anything relating to science because of previous unhappy and unsuccessful experiences with scientific content. In crude terms, science specialists may have little interest in history and non-science specialists may have no more interest in history of science than in science itself. Schwartz (1995) draws on thirty years of 154 Derek Hodson - 978-90-8790-507-1 Downloaded from Brill.com11/09/2020 11:12:23AM via free access

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experience with such courses to proffer some sage advice on course structure and content, and to remind us that developing and teaching successful inter-disciplinary courses requires “imagination, self-confidence, a willingness to learn and to take risks, a fairly thick skin, and some resiliency with which to respond to the inevitable failures” (p. 1040). For Kauffman (1989), the value of such an attempt is in achieving some balance between the scientist’s emphasis on abstractions and universals and the historian’s and sociologists’s emphasis on localized contextual details and particularistic meanings. “Seen in the unifying light of the Tai Chi”, he says, “apparent opposites disappear, and, paradoxically, disadvantages can be seen as advantages” (p. 87). THE NATURE OF SCIENCE

A fourth argument is that history of science provides rich insight into the nature of science and scientific inquiry, an argument that lay behind James Conant’s famous Harvard Case Histories in Experimental Science (1957), designed to give students a feel for “the tactics and strategies of science”, and the much lamented Harvard Project Physics course (HPPC) for US secondary schools (Rutherford et al., 1970). Essentially the same point was made by John Ziman (1980) in his argument for history as a means of dispelling myths about scientific inquiry and as an antidote to naïve scientism because it shows the scientist as “a real person, the child of his times, vainly seeking glory and all the rest of it. It can illustrate by example all that one might wish to say about the personal dimension of research” (p. 121). Of course, history of science and philosophy of science are mutually enriching: just as history of science informs, illuminates and exemplifies the philosophy of science, so the philosophy of science assists us to make better sense of the history of science. As Lakatos (1978) says: “Philosophy of science without history of science is empty; history of science without philosophy of science is blind” (p. 102). Case studies in the history of science can illustrate many of the points made in chapters 3 to 6, such as the relationship between observation and theory, the theory-dependence of experimentation, and the role and status of theories and models (Arons, 1983; Kauffman, 1989; Betts, 1992; Lin & Chen, 2002; Wang & Marsh, 2002). They show that scientific knowledge is, in principle, refutable and therefore constantly under development and subject to change. They show that science is not conducted in an intellectual, social and cultural vacuum; rather, it occurs in a climate of constant criticism and debate, it is subject to economic and political forces, and it is often dependent on (as well as productive of) technological innovation. Historical case studies reveal the part played in scientific inquiry by intuition, luck, competition, technological ingenuity and sheer hard work, and illustrate how scientists are often dogmatically tenacious in pursuit of their views, even in the face of contradictory evidence. Above all, they reinforce Feyerabend’s (1975) point that there is no one universally applicable, simple and straightforward method of conducting scientific investigations. By showing that at different times in history there have been significant differences in what counts as an appropriate research question, what constitutes a satisfactory investigation or experiment, what makes a 155 Derek Hodson - 978-90-8790-507-1 Downloaded from Brill.com11/09/2020 11:12:23AM via free access

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particular concept acceptable and what counts as a satisfactory explanation, historical studies contribute to a deeper understanding of the nature of science. By drawing attention to significant changes in the way observational evidence is collected, processed and analyzed, and in the way scientific work is reported and disseminated,6 they assist students in developing their understanding of and ability to use the discourse of science – arguably the most significant aspect of scientific literacy for citizenship (see chapter 1). By studying episodes in the history of science, especially through original papers, and by reading biographical and autobiographical material, students can gain insight into the ways in which particular scientists thought about conceptual and procedural issues, designed investigations and went about solving problems. They are given graphic illustration of the interplay of theory and experiment: scientists design new experiments to counter an opponent’s theoretical position and the opponent counters with a modified theory, a new experiment, or a technological innovation capable of making more accurate readings or gathering an entirely new kind of observational evidence. There may be value, once in a while, in students replicating experiments that were highly significant in those respects (Kreuzman, 1995; Heering, 2000; Hottecke, 2000) or engaging in role play (Allchin et al., 1999). History also shows us that there is a difference between the way science is done and the way science is reported. It shows us that the creative phase is rulebreaking (just as Feyerabend claims), while the validation phase has to conform to the strict standards of the community of practitioners.7 I must compare myself to a mountain climber, who without knowing the way climbs up slowly and laboriously, must often turn around because he can go no further, discovers new trails, sometimes through reflection, sometimes through accident, which again lead him forward a little, and finally, if he reaches his goal, finds to his shame a Royal Road on which he could have traveled up, if he would have been clever enough to find the right beginning. (Helmholtz (1892), cited in Stuewer (1998), p. 16) While these insights into the nature of scientific inquiry are valuable in their own right as a contribution to learning about science, they may also have transfer value and lead to improved capacity for doing science and for constructing meaning. This is what Seroglou and Koumaras (2001) mean when they argue that history of science has a major role in the science curriculum because it contributes to improved problem-solving. What they have in mind is an expanded notion of problem solving that includes generating new conceptual models or improving, revising and developing existing ones in order to ensure a better fit between theory and observational data, especially experimentally acquired data (see also, Stewart & Hafner, 1991). In studying how particular conceptual models and theories were developed and established, students quickly realize that the supposedly unambiguous facts recorded in textbooks have not always been so unambiguous, nor have our taken-for-granted explanations of phenomena and events always been so well-established. Facts are not individual pieces of data but interpretations of observations linked in meaningful ways into explanatory systems, and underlying and underpinning these complex 156 Derek Hodson - 978-90-8790-507-1 Downloaded from Brill.com11/09/2020 11:12:23AM via free access

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conceptual frameworks is a host of assumptions and a wealth of interpreted data, many of which are not apparent on first encountering them. Some models and theories are so familiar that their fundamental assumptions remain hidden, their inadequacies are glossed over, their layers of embedded meaning remain unexplored and their misleading aspects ignored. Historical studies enable theories to be ‘unpacked’ to reveal their components and the influences that led to their construction, thereby leading students to a deeper understanding of how theoretical systems are constructed and what criteria must be satisfied in order for them to be validated (Hagen & Kugler, 1990; Castro & Carvalho, 1995; Weck, 1995; Justi & Gilbert, 1999). Many important questions are raised: What constitutes a well-built theory? How are convincing arguments made? What factors are likely to influence acceptance and rejection by the community? It is evident that the simpler and more elegant the model, the more likely it is to be believed, and the more intuitive the model, the harder it will be to displace it or modify it in the light of new data, especially if it is reinforced through the shared understanding consequent upon membership of other sub-cultural groups. Kipnis (1996) argues that this approach becomes considerably more effective when reinforced by what she calls “investigative experimentation”. In a sense, she is promoting the view that students learn science by doing science or by imitating scientists, as she describes it.8 In fact, the scientific inquiry in which students participate is carefully reconstructed to reflect historical development and to highlight specific conceptual issues, so perhaps learning science (and learning about science) by imitating particular scientists, but using modern apparatus and simplified experimental design, is a more apt description of the approach. In some ways, it resembles teacher demonstrations and computer simulations rather more than the open-ended scientific inquiry suggested by the term doing science, despite claims by Kipnis that she is trying to get away from teacher demonstrations. Lawrenz and Kipnis (1990) make some bold claims for the success of the ‘historical-investigative’ approach, including enhanced conceptual understanding and thinking ability, increased enjoyment of learning and greater interest in experimenting. While these claims should be viewed cautiously, there are good grounds for regarding this cluster of approaches as well placed to generate interest by showing students that science is often controversial, thereby stimulating curiosity in contemporary scientific debates and encouraging students to scrutinize their own beliefs and the beliefs of others by challenging underlying assumptions and critiquing evidence for them. Allchin et al. (1999) have shown that attitudes to science are positively impacted by courses for non-science majors that include historically-contextualized and relatively open-ended investigations of science problems. It might also be expected that students will become more confident in their reasoning ability and better prepared for discussion of controversial issues in science – a crucial part of scientific literacy (see chapter 1). Furthermore, one might expect enhanced metacognitive skills and self-regulatory cognitive strategies that enable individuals to reflect on, construct meaning from, monitor and regulate their own learning (Duschl & Erduran, 1996). Ultimately, success will depend on the way in which teachers implement the approach and, in particular, on the sensitivity with which they deal with student debate of ideas. Monk and Osborne (1997) provide a wealth of invaluable advice 157 Derek Hodson - 978-90-8790-507-1 Downloaded from Brill.com11/09/2020 11:12:23AM via free access

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in their 6-step model combining historical material, detailed consideration of issues in philosophy of science and constructivist pedagogy. – Presentation of phenomena or events – carefully chosen for their historical significance, inherent interest and capacity to generate questions, problems and predictions. – Eliciting students’ views, ideas and explanations – using the usual range of constructivist strategies: skilful teacher questioning, use of concept maps, word association, art work, group discussion, writing activities of various kinds, etc. – Historical studies – presented orally by the teacher or via text, multimedia, student research, museum visits, and the like. – Devising suitable tests – designing experiments and other kinds of investigations to evaluate and judge the range of ideas collected. – Presenting the current scientific view – if it has not already arisen, the current view (or the school science curriculum version of it) should be introduced using whatever means is appropriate, with particular emphasis on the reasons why this view has been accepted. – Review and evaluation – reviewing learning progress (an essential element of constructivist pedagogy) and reiterating the basic thrust of the approach – that is, how to distinguish between justified and unjustified beliefs. The value of this approach is that it shifts emphasis from the mere acquisition of theoretical knowledge towards a concern with the ‘warrant for belief’: How do we know? What are the reasons for holding this belief? What is the evidence for this view? How was that evidence acquired? Interpreting theoretical disputes from the history of science requires students to adopt rival perspectives on the interpretation of data, and to enter discussion about what counts as relevant data and appropriate ways of collecting them. Thus, it is excellent preparation for appraising new theoretical propositions in relation to existing ideas. By studying and understanding the ways in which scientists construct knowledge, students are assisted in building metacognitive insight into their own knowledge construction. By utilizing historical material and emphasizing epistemological concerns, the approach meets several of the learning about science goals embedded in the notion of scientific literacy discussed in chapter 1, and simultaneously addresses one of the affective issues surrounding constructivist pedagogy – that is, the reluctance of some students to contribute their own ideas. Perhaps it is comforting to know that others, including some eminent scientists, have held erroneous beliefs; perhaps contributing ideas to class discussion can be seen not so much as a potential threat to self-esteem as an opportunity to enrich discussion. Perhaps it is not too extravagantly optimistic to speculate that successful experiences of this kind might lead to increased tolerance of and appreciation for the views of others – a matter central to the role of history of science in multicultural and antiracist education (see below). Support for these speculations can be found in Crawford’s (1993) description of how she has used Michael Faraday’s experimental diaries to create a classroom climate that encourages students to (i) articulate their anxieties and uncertainties, (ii) develop the emotional commitment to struggle with theoretical and practical problems and (iii) learn to think independently. 158 Derek Hodson - 978-90-8790-507-1 Downloaded from Brill.com11/09/2020 11:12:23AM via free access

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STS, CURRICULUM INTEGRATION AND CULTURAL ENLIGHTENMENT

Historical case studies are ideal vehicles for teaching about the complex interactions among science, technology, society and environment (STSE education). Clearly, such things as the role of market forces and military interests, patents and the need for secrecy, problems of scaling up from the research scale to the production scale, issues of safety and social responsibility, environmental impact, and the ever-present moral-ethical concerns, are all easier for students to comprehend when they are set in a real life context. Moreover, studying episodes from the past enables students to reflect on such issues with a sense of perspective that is not always possible with current events and controversies. By judicious choice of examples, teachers can demonstrate occasions when (i) science precedes technological application, (ii) technology precedes the science that eventually explains it, (iii) scientific development and technological development are entirely independent, and (iv) scientific and technological development are mutually dependent and interactive. Layton (1988) makes the point that even when technology is ‘just’ applied science (item (i) above), there is still a lot of hard work to be done. He gives the example of Perkin’s development of the synthetic dye Mauve, and says that its translation into a commercial product required “knowledge, skills and personal qualities very different from those needed for the test tube oxidation of aniline” (p. 371). At the outset, Mauve would not take evenly on large batches of cloth, there was no suitable mordant for cotton, raw materials were not readily available, handling concentrated nitric and sulphuric acids on a ‘factory scale’ presented all manner of engineering problems, there were problems of marketing associated with consumer reluctance, and so on. Notions such as optimization, feedback modelling, systems analysis, critical path planning and risk assessment have to be included whenever science is applied to ‘real world’ situations. Of course, real world problems are rarely the simple matters of cause and effect portrayed in traditional science curricula; rather, attempts at solution often reveal layers of increasing complexity and uncertainty that cannot be contained within a particular disciplinary framework. Problems in science and technology become inextricably linked with considerations in economics, politics, aesthetics and moral philosophy. In general, a scientific solution is valid/acceptable if it conforms to the rationality of science – i.e., if it has observational or experimental support, if it is internally consistent, if it is consistent with other accepted theory, and so on. It helps if it is elegant and parsimonious, though these criteria may not be considered essential (see earlier chapters and chapter 9). In technology a solution has to work, of course, but it also has to be efficient, cost-effective, durable, and perhaps aesthetically pleasing as well. There may also be critical considerations relating to social and environmental impact. Technologies are rarely ‘good’ in an absolute sense. Rather, they are good from some perspectives, less good (or even undesirable) from others. In that case, whose perspective is to count, whose interests are to be served, whose values are to be upheld? One person’s acceptable risk or cost is another person’s intolerable hazard, social disruption or cultural insensitivity. Technology is inescapably a social activity, determined by the prevailing distribution

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patterns of wealth and power. History of science and technology provides the means for the curriculum to acknowledge these realities. Of course, the extent to which the curriculum depiction of scientific practice should be politicized, are matters of continuing debate and considerable controversy (Solomon & Aikenhead, 1994; Yager, 1996). Somewhat surprisingly, given the caution with which American educators often approach sociopolitical matters, Heilbron (1987) has suggested that students should study, in historical context, the “institutions and apparatus of science and the relations among the sciences, government, universities, and the military” (p. 554).9 While only a few science teachers will be willing to follow this advice, many more may be willing to use historical case studies to show how and why scientists have often disagreed on fundamental issues, thus laying important groundwork for (i) making the point that controversy is a perfectly normal part of science, (ii) illustrating how the course of science has often been profoundly influenced by the sociocultural context in which it is located, and (iii) identifying and confronting some of the complex ethical issues generated by scientific developments (Dunn, 1993). Clearly, history of science has a key role to play in dispelling the all-too-prevalent myth that science is conducted in a sociopolitical and moral-ethical vacuum. By illustrating how science is produced within particular social, economic, historical and technological contexts, history of science makes a major contribution to critical scientific literacy, as defined in chapter 1 (Lemke, 2001; Allchin, 2004). This particular role for the history of science is encapsulated in a 19-year old statement from the Department of Education and Science (1989): Pupils should be given opportunities to develop their knowledge and understanding of how scientific ideas change through time and how their nature and the use to which they are put are affected by the social, moral, spiritual and cultural contexts in which they are developed. In doing so they should begin to recognize that while science is an important way of thinking about experience, it is not the only way. (p. 32) It is the flavour of this passage that underpins my sixth argument for the history of science: its role in multicultural and antiracist education (Hodson, 1993d, 1999; Hodson & Dennick, 1994). Studies in the history of medicine, astronomy, optics and technology are particularly rich in examples of the achievements of Chinese, Indian, Arab and African scientists. Sadly, much of that history is ignored or misrepresented in school science textbooks. In lamenting this distorted history, Dennick (1992a) comments that “throughout European history since the renaissance there has been a tendency to disparage and down grade the discoveries and achievements of other cultures and historians have been very prone to give credit where it is not due” (p. 81). In evidence, he cites the assertion by Joseph Needham (1954, 1969) that the three greatest inventions of the previous millennium (paper-making and printing, gunpowder, and the navigational compass) were each used in China several centuries before their supposed discovery by Westerners. Oddly, Chinese science is often dismissed as ‘mere technology’, thereby creating the impression that it was

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little more than haphazard trial and error (‘suck-it-and-see’, as my fellow Lancastrians would say) or, at best, a series of chance discoveries. Throughout ancient Chinese, Egyptian, and other cultures of the time, there was, in effect, no real attempt to understand or to generalize. If devices or explanations of the universe worked, they were accepted as best or true. (Loving, 1997, p. 440) Needham (1981) tells us that there is considerable evidence to the contrary: Chinese science was theoretically driven, though its philosophical basis was radically different from that of Western science; it involved systematic observation and careful experimentation. Indian, Arab and African scientific achievements have been similarly trivialized or falsely attributed to Westerners. For example, when the Arab contribution to the growth of science is mentioned at all (and that is only very rarely), it is not seen as extending beyond the role of custodian of ancient Greek knowledge, which was later passed back to European scholars. In reality, what was passed on was a substantial corpus of new scientific understanding and practice (Winter, 1952; Hill, 1993; Hobson, 2004; Saliba, 2007) and “a sophisticated culture uniting art, religion and science in a profound world view which is still very much alive today” (Dennick, 1992b, p. 6). Ignoring or falsely attributing the work of Muslim scientists to Europeans is a practice that, according to Sardar (1989), has been going on for centuries: “Piracy was so common that as early as the twelfth century a decree was issued in Seville forbidding the sale of scientific writings to Christians because the latter translated the writings and published them under another name” (p. 10). A similar fate befell much of Indian science (Machwe, 1979; Kumar & Kenealy, 1992). In addition, the agricultural theory and practice of the pre-Columbian peoples of the Americas were subsumed within European science without any acknowledgement (Weatherford, 1988). Even more serious in the context of arguments for multicultural and antiracist education is the systematic trivialization, distortion and suppression of African cultural history and its scientific and technological achievements – a key element, of course, in the racist ideology that was formerly used to legitimize slavery and colonial exploitation, and still serves to deny a strong sense of cultural identity to many people of African descent living outside Africa. Despite the spectacular achievements of the ancient civilizations of Ethiopia, Benin and Zimbabwe, for example, the myth is still propagated that significant African history only began with the Imperialist invasions. Moreover, the great civilization of Egypt (and its achievements in science and technology) is presented without any acknowledgement of its African roots. It almost goes without saying that the goals of multicultural/antiracist science education require that we develop more authentic historical studies for use in primary and secondary schools. A seventh argument is that history of science assists curriculum integration, always a powerful argument with primary school (elementary school) teachers. Science developed alongside and in tandem with mathematics, technology, theology, philosophy, psychology and commerce; it was (and continues to be) affected

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by and influenced by each of the fields, and by politics, religion, ethics, literature, art, music and all forms of mass culture. Thus, history of science can provide students with access to a deep understanding of cultural and intellectual interaction, the kind of interaction highlighted in James Burke’s superb and highly idiosyncratic television series Connections and Jacob Bronowski’s classic series The Ascent of Man.10 Matthews (1994) makes this particular argument at some length, and very persuasively, with respect to Galileo’s physics. He concludes: “A historical approach to science allows students to connect the learning of specific scientific topics with their learning of mathematics, literature, political history, theology, geography, philosophy and so on. When the richness of science’s history is appreciated, then collaboration between science, drama, mathematics, history and religious studies teachers in schools can fruitfully be encouraged” (p. 53). While crossdisciplinary themes have been relatively common in primary/elementary schools in the past, they are increasingly under threat from the ‘accountability movement’, with its emphasis on increasingly analytical forms of assessment.11 In secondary and tertiary education, cross-disciplinary approaches have always been rare, and whenever implemented have tended to be the province of particular enthusiastic, energetic and charismatic individuals willing to work tirelessly in pursuit of a ‘dream’ in order to assemble a suitable team of teachers. Particularly striking illustrations of what can be achieved can be found in Samson and Weininger’s (1995) description of their integration of history of science and art history, together with relevant social history, philosophy, literature and psychology, into a course for engineering students titled “Light, Vision and Understanding” and Schwartz’s (1995) account of a multidisciplinary course on the history of alchemy. The eighth and final argument to justify the inclusion of history of science in the school science curriculum rests on the simple assertion that knowing science has a history, that it didn’t just appear in sophisticated and developed form at some time in the 20th Century, is an essential component of scientific literacy and of a sound liberal education. Such puzzling concepts as force, energy, etc., are man-made and were evolved in an understandable sequence in response to acutely felt and very real problems. They were not handed down by some celestial textbook writer to whom they were immediately self-evident. (Cardwell, 1963/1964, p. 120, cited in Brush, 1974, p. 1163) Sometimes students are genuinely surprised that people ‘back then’ were conducting experiments and building theories. Perhaps the creation of a sense of scientific history is the only justification that we need – in a sense, history of science for its own sake. Science is an important part of our cultural heritage and knowing something of its history and development is an important part of what it means to be a cultured and educated citizen (Arons, 1983; Jenkins, 1989; Bybee et al., 1991; Millar, 1993, 1996; Wellington, 2001).12 As Monk and Osborne (1997) argue, teaching science and teaching about science in an ahistorical way makes as little sense as studying Shakespeare without discussing the sociocultural context of Elizabethan

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England. In short, science education is seriously deficient if it fails to provide satisfactory answers to the following series of questions in ways that are interesting and accessible to all students: – Where did science come from? – How did it get that way? – Who were the significant people in its development? – Why did they choose to study these issues and problems? In Ernst Mach’s (1960) view, those who know the history of science are much better positioned to evaluate current developments: “They that know the entire course of the development of science, will, as a matter of course, judge more freely and more correctly of the significance of any present scientific movement than they, who, limited in their views to the age in which their own lives have been spent, contemplate merely the momentary trend that the course of intellectual events takes at the present moment” (p. 8). WHAT KIND OF HISTORY OF SCIENCE?

Needless to say, there has been some strong opposition to the inclusion of history of science in the school science curriculum. First, from those historians who see history in science lessons as poor history or even as a fabrication of history in support of current scientific views. Second, from those scientists who see it as diverting attention (and time) from what they see as ‘proper science’. There is also concern that history of science can have an adverse impact on students by undermining the ‘certainties’ of the scientific world (Brush, 1974). There are strong echoes here of Thomas Kuhn’s (1977) point that education in science is primarily ‘indoctrination’ into the prevailing paradigm and his warning that the proper performance of ‘normal science’ and the subsequent capacity to challenge the prevailing paradigm is likely to be compromised by too early a questioning of its fundamentals. Thus, whether to include history of science in the curriculum, or not, is not the only question; it is also important to ask what kind of history of science we should include (if any). A basic distinction is that between internalist accounts and externalist accounts. The former concentrate solely on the development of scientific concepts and their role in theoretical explanations, excluding all but the most cursory consideration of the sociocultural context in which the ideas were developed and the socio-economic factors that might have motivated their development. Externalist accounts, on the other hand, seek to describe and explain the growth of science in terms of the personal circumstances of individual scientists and/or the social and cultural climate of the wider society in which the work was conducted. Clearly, the motives for including history of science will be a powerful influence on the kind of history included. Those concerned to assist conceptual understanding may be inclined to interpret scientific history from a 21st Century perspective, frequently ignoring superseded ideas or regarding them as seriously misguided – an approach that has been termed “Whiggish” history.13 Such accounts may seriously distort history by criticizing scientists of the past for failing to 163 Derek Hodson - 978-90-8790-507-1 Downloaded from Brill.com11/09/2020 11:12:23AM via free access

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meet modern standards of data collection and experimental design, and may ridicule those scientists for being unaware of some of our taken-for-granted modern knowledge. They portray scientific knowledge as emerging in simple and predictable fashion from scientists’ struggles to solve theoretical rather than practical problems, with one scientific development leading directly and inexorably to the next until the current position was reached. When current theories are taken as the yardstick, those who initially opposed the ideas that eventually led to those theories are regarded as incompetent or perverse, while those who accepted and developed them are credited with exceptional foresight – a kind of ‘villains and heroes’ approach to scientific history. Because it is assumed that there has been one universally applicable method in use since the outset of the scientific endeavour, theories that were once accepted but were subsequently falsified are regarded as the product of scientists’ errors. By evaluating early scientific investigations using modern criteria and standards, Whiggish historians of science ignore altogether any appraisals made at the time about whether an experiment was appropriate and reliable, whether a theory was intelligible and whether an argument was convincing. The fact that a belief doesn’t stand up to critical scrutiny now, in the 21st Century, does not mean that it was irrational to hold such a view at the time it was proposed. Unencumbered by modern notions of rationality, scientists of the past had to make decisions about the acceptability of contemporary theories by their criteria rather than by ours. We may have the hubris to imagine that our theories of rationality are better than theirs (and they may well be), but how does it help historical understanding to evaluate the cogency of past theories utilizing evaluative measures which we know were not operative (not even in approximate form) in the case at hand? (Laudan, 1977, p. 129) We can only understand the past in its own terms; the intellectual standards of the present sometimes have little relevance to a proper understanding of events in the distant past.14 Accounts that are more faithful to historical circumstances and sociocultural influences entail consideration of the various by-ways, diversions, false paths and dead ends of science, recognition that science is frequently complex and uncertain, and acknowledgement that not all inquiries are fruitful. A ‘proper’ history of science attends to the theoretical and practical problems that motivated new ideas and new procedures, and takes cognizance of the metaphysics and worldview prevailing at the time. In these respects, ‘time slices’ rather than ‘vertical history’ may be more appropriate for the curriculum – that is, consideration of the range of ideas current at any one time, how these ideas were generated and how they were received, interpreted, modified and utilized in further work. However, simply noting that an idea was widely accepted at a particular time does not necessarily imply that scientists were sound in their judgement. Taking theory appraisal and acceptance at face value and invoking social influences as the major causative factor leads to the kind of relativism discussed in chapter 7. It leaves no way of judging whether one theory was better than another, no way of judging whether, by the standards in force at the time, a judgement was well founded. Thus, there is a problem: How can we judge episodes in the past without imposing and invoking 164 Derek Hodson - 978-90-8790-507-1 Downloaded from Brill.com11/09/2020 11:12:23AM via free access

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present-day criteria and standards? Laudan’s (1977) response, which will be discussed at some length in chapter 9, is that scientists behave ‘correctly’ (i.e., rationally) when they choose in favour of those ideas effective in solving the most urgent practical problems and the most significant theoretical ones. This simple criterion, he argues, is both trans-temporal and trans-cultural, and to do other than invoke it is to act irrationally. The notion of progress is both a distinctive feature of science and a major driving force for scientific endeavour. Thus, a history of science is necessarily evaluative. “It cannot be merely descriptive but will be required to pass judgement, to evaluate some ideas negatively as epistemological obstacles which need to be overcome and rejected, and others positively as epistemological acts of scientific genius. What is negatively evaluated is… excluded from contemporary scientific thought… what is positively evaluated continues to play a role in science” (Tiles, 1984, p. 13). It follows that a history of science cannot be written once and for all; a change in current scientific thinking will precipitate a re-evaluation of past thought. Thus, there is what Gaston Bachelard (1951) referred to as a “recurrent history” of science, one that is continually re-told in the light of the present, one that tells how scientific thinking reached its present state. Recurrent history of science is the attempt to show “not merely how we came to the present views but also why… the reasons for rejecting previous theories, for modifying previous concepts, and thus the reason behind the acceptance of currently accepted views” (Tiles, 1984, p. 15). The reasons under scrutiny are not primarily the psychological, sociological, economic and political factors that influence science, but the justifications used by scientists in addressing and making decisions about conceptual and procedural issues. In that sense, this reasoning is also part of the present justification of our theoretical positions and must be understood and subjected to critical scrutiny if further progress is to be made. In order to evaluate the past properly the historian of science must know the present; to the best of his ability he must learn the science whose history he plans to write. And it is through this that, whether one likes it or not, the history of the sciences has a strong connection with the science of the moment. It is when the historian of science is initiated into the modernity of science that he is also able to uncover more, and more subtle, nuances in the historicity of science. (Bachelard, 1951, p. 9, cited in Kragh, 1987, p. 92) Chamizo (2007) describes recurrent history as a focus on “distinguishing the ‘sanctioned’ from the ‘lapsed’. The latter is the history of false paths, of errors and illusions, of prejudice and mystification, whereas the first… is the history of the thoughts that continue (in) the science of the present time… Recurrent history helps us to understand, first the context in which ‘wrong’ ideas were once considered ‘right’, and second how (and why) such context changed” (p. 207). Attention is focused on the kind of problems that a theory was designed to solve (and why those problems were considered important), the extent to which a particular theory was successful in solving them, and the reasons why previous attempts were not successful and had to be altered or abandoned. Because recurrent history addresses 165 Derek Hodson - 978-90-8790-507-1 Downloaded from Brill.com11/09/2020 11:12:23AM via free access

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scientific error and its correction it focuses on both the nature and the limitations of scientific justification. Perhaps what suits the purposes of science education best is a careful delineation of the key conceptual issues set within a rich and lively sociocultural context. But, as Klein (1972) comments, what the science teacher wants of historical examples is precisely what the history teacher would reject as poor history: the one delights in a “sharply defined single insight’, the other in “the rich complexity of fact’” (pp. 12 & 18). History of science in the curriculum is necessarily selective in terms of extent, scope and style. Sometimes consciously and sometimes unconsciously, selected history of science can easily become distorted history or distorted science. Great scientists are often portrayed as ‘super heroes’, possessed of almost superhuman intellectual capability, extraordinary determination and startling resilience in the face adversity, while scientists who made mistakes are sometimes seen as fools. More worryingly, history of science can be used (and has been used) to promote the view that science is the exclusive province of Western males and the belief that the science they produce is infallible, authoritative and not to be questioned by mere students (or even by citizens in general). In contrast, the focus on people, social circumstances, false trails and fierce competition between rivals can easily lead to a distorted and over-simplified version of the science, with little acknowledgement or recognition of the complexities of key conceptual, philosophical and mathematical issues, thus producing what we might call “historical noise”.15 A number of researchers report that despite the long tradition advocating history of science in the school science curriculum (at least in some countries), the historical development of key ideas in science is generally very poorly presented in science textbooks and other curriculum materials, rarely extending beyond a few names and dates, some pictures, and the odd colourful anecdote (Chiappetta et al., 1991; Niaz, 1998, 2000; Leite, 2002; Rodriguez & Niaz, 2002; Williams, 2002). Such accounts not only trivialize the sociocultural dimensions, they also misrepresent the nature of scientific inquiry and theory building (Bauer, 1992; Hodson, 1998b). In Schwab’s (1962) words, they present science as an “unmitigated rhetoric of conclusions in which current and temporary constructions of scientific knowledge are conveyed as empirical, literal, and irrevocable truths” (p. 24). Allchin (2003) argues that the use of narrative form, chosen specifically for its appeal to students, leads inevitably to distortion. All narratives, he says, risk drifting into myth because of common narrative elements. – Monumentality – not only are scientists larger-than-life heroic figures, often working single-handedly, but the situations they face and the problem they solve are of immense significance. – Idealization – all nuances are laid aside in pursuit of a straightforward, ‘blackand-white’ storyline. – Affective drama – stories are made more entertaining, persuasive and memorable by enhancing emotional and aesthetic elements. – Explanatory and justificatory narrative – the storyline is always structured to justify the authority and certainty of the scientific conclusion. 166 Derek Hodson - 978-90-8790-507-1 Downloaded from Brill.com11/09/2020 11:12:23AM via free access

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Leite (2002) provides a checklist (comprising eight major dimensions) for analyzing the historical content of science textbooks. Its value extends well beyond the simple comparison of rival textbooks (useful as that can be for teachers contemplating the first time introduction of history and philosophy of science into their courses) to opportunities for reflection on the diversity and relative priorities of issues to be included in a history-oriented course. However, despite the valuable guidance that such a checklist can provide, the development of new curriculum materials is a complex and difficult task. Achieving the appropriate balance is not easy. As Stuewer (1998) remarks: “A scholar cannot be constrained by logic and strive for simplicity and at the same time give full weight to illogicality and strive to portray complexity” (p. 17). The problem of selection for the curriculum is not just a matter of what counts as the ‘best history of science’, it is impacted by consideration of what is in students’ best interests. Is it necessarily in students’ best interests for them to be given an authentic version of the history of science? Introducing history into the science curriculum opens a Pandora’s box by telling students that scientists do not always behave as rational, open-minded investigators who pursue knowledge through carefully controlled experiments and dispassionate consideration of the evidence. Is a ‘warts and all’ account of science likely to make students more or less enthusiastic about science? Is there some risk associated with an approach that reveals how scientists sometimes steal ideas from others, distort data and cut corners in their determination to establish the primacy of their work? Is the picture of the scientist emerging from the history and sociology of science even more harmful than the stereotyped image described in chapter 2? When Stephen Brush (1974) asked this question, more than a quarter century ago, his answer was that the way scientists behave (according to historians) may not constitute a good role model for impressionable students.16 These writings do violence to the professional ideal and public image of scientists as rational, open-minded investigators, proceeding methodically, grounded incontrovertibly in the outcome of controlled experiments, and seeking objectively for the truth, let the chips fall where they may. (p. 1164) De-mythologizing science through historical and sociological studies may lower the esteem in which scientists are held, so such studies are unlikely to be in scientists’ interests. As Holton (1975) remarks, “the apparent contradiction between the often ‘illogical’ nature of actual discovery and the logical nature of well-developed physical concepts is perceived by some as a threat to the very foundations of science and rationality itself” (p. 329). Are there situations in which it makes sense to project a series of stylized and mythical stories about great scientists because they make science more memorable and more interesting? Are there other occasions when it is more sensible to ‘re-write’ historical accounts somewhat in order to reduce conceptual complexity and focus on sociocultural issues, or to focus attention more clearly on conceptual aspects without too much distracting social, political and economic detail (de Berg, 1997). Much depends, of course, on the age and stage of intellectual and emotional development of the students, and on the ways 167 Derek Hodson - 978-90-8790-507-1 Downloaded from Brill.com11/09/2020 11:12:23AM via free access

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in which different versions of ‘history’ contribute to the notion of critical scientific literacy discussed in chapter 1 and to the drive to re-orient nature of science teaching. It may be that the notion of ‘authentic history of science’ is illusory. Scientists rarely leave detailed accounts of how they came to make their discoveries. As noted earlier, published accounts are rationally reconstructed after the event, while laboratory notebooks are usually little more than pages of data augmented from time to time by cursory indications of procedures adopted and critical reflective comments. Histories created after the events (by historians and biographers) are necessarily conjectures about the influences, circumstances and chains of argument that led to particular decisions. Those conjectures are influenced by the author’s understanding of the science and by her/his beliefs about the nature of science, as well as by knowledge of the sociocultural and political context. In other words, all histories comprise interpreted evidence. In organizing and interpreting data, historians have to make decisions about which actions and episodes they regard as significant; different assumptions about significance lead to different histories. In common with scientific accounts, historical accounts are empirically under-determined; for any set of recorded historical data, there may be more than one plausible explanation. Furthermore, it is not always clear what would count as confirming or falsifying evidence, and it is not always clear what counts as reliable data. Just as the assumptions we make about other times and places influence the significance we attach to particular historical data and determine the way we interpret events, so the assumptions that our predecessors made influenced the data they thought it important to record. As discussed earlier, science educators are urged to avoid a Whiggish interpretation of history, though it is tempting to speculate on the extent to which it is possible to write an account of anything from a standpoint other than the present. Also, one wonders whether an account, if it could be written, would have any relevance for us unless it is based on the concerns of the present. It might serve merely to encourage students to worry about theoretical and social problems that have already been satisfactorily solved or rendered obsolete. Despite expressing these concerns, I incline to the view that criticizing science teachers for projecting bad history is to miss the point. The history need only be as complex and sophisticated as necessary to make particular points in pursuit of learning goals associated with enhancing conceptual understanding, humanizing science, illustrating sociocultural context, addressing methodological issues, or whatever. It is not necessary to tell everything known or conjectured about historical episodes to use them to humanize science and scientists, to rationalize past problem choices, to explode the myth of objectivity, to underline the aesthetics and pigheadedness of creativity, and to teach that the validation and refinement of new science is a social, not an individual, affair. (Heilbron, 1987, p. 558) The science curriculum is designed for students to learn science, learn about science and engage in science; its purpose is not to teach history, teach about history, or give experience of doing history. It is well known that practical work is 168 Derek Hodson - 978-90-8790-507-1 Downloaded from Brill.com11/09/2020 11:12:23AM via free access

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more successful in bringing about learning when it is designed with specific goals in mind and that activities successful in bringing about concept acquisition and development are not necessarily well suited to teaching about scientific inquiry or developing bench skills (Hodson, 1993c). By extension, history of science should be deployed differently for different purposes. Differences in purpose, leading to different questions and different interpretive frameworks, are evident in the different ways that Karl Popper, Imre Lakatos, Thomas Kuhn, and Gerald Holton describe the final overthrow of Newtonian physics by Albert Einstein. It is here that Allchin’s (1995) distinction between rational reconstructions (using modern scientific perspectives) and historical simulations is useful: the former being useful for dealing with conceptual and procedural issues, the latter being well suited to dealing with the humanitarian aspects and for addressing social, economic and moral-ethical issues.17 These differences in presentation reflect Latour’s (1987) distinction between “ready made science” and “science in the making” and speak to the distinction between studies that deal with the context of justification and those dealing with the context of discovery. Kragh (1992) suggests that teachers should ‘come clean’ and make students aware of those situations in which history has been distorted to enhance the conceptual or philosophical aspects, and when the science has been simplified in order to focus on the sociocultural dimensions of an episode in the history of science. As an example of what she has in mind, she cites the following passage, in which Wichmann (1971, p. 19) introduces an account of the development of quantum theory. The reader should realize that our discussion is extremely deficient as a historical account: we could not possibly hope to do justice to the very interesting development of quantum physics in a few pages. We are looking at the situation at the beginning of this century in retrospect, and it is then easy to see that these three problems [Planck’s law of blackbody radiation, the stability of atoms and the photoelectric effect] were key problems. However, if we examine the publications for the year 1900… we find that the majority of physicists were concerned with very different things. (Kragh, 1992, p. 360) Moreover, as Justi and Gilbert (1999) remind us, the conceptual models used by teachers are not always coincident with models deployed in the history of science. Often they are modified or hybridized in order to meet particular pedagogical purposes. PERSISTENT PROBLEMS

Although arguments for including the history of science in the school science curriculum were made as early as 1855 (Jenkins, 1989) and have continued to be made at regular intervals ever since, there has not been widespread uptake of the advice, and surprisingly little research into the impact of history of science on student learning has been published. As mentioned previously, there is strenuous opposition to history of science on the grounds that it ‘dilutes’ science courses, takes too long, and deflects attention away from content acquisition. Consequently, there is 169 Derek Hodson - 978-90-8790-507-1 Downloaded from Brill.com11/09/2020 11:12:23AM via free access

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widespread apprehension that science departments in universities will not afford such courses the same value as conventional science courses, and may not accept them as entry qualifications. There is concern about who would teach such courses. Do science teachers know enough history? Do history teachers know enough science? Is either group sufficiently confident to take on the responsibility? Although the discussion in this chapter places the responsibility firmly in the science teachers’ camp, many teachers already express grave concerns about time constraints – arguing that with courses already seriously overloaded it would be difficult to find the time and create the opportunity to adopt an historical perspective. It is inevitable that some teachers will be concerned about the additional demands on them, feeling that they lack expertise in the field and do not have access to good teaching resources. Many teachers lack confidence in dealing with historical matters, just as they lack confidence in dealing with philosophical and sociological matters. It is clear that curricula designed along the lines being argued in this book will not be successfully implemented unless serious attention is given to teachers’ concerns and steps taken to develop appropriate curriculum materials. Particularly promising in this respect are the continuing efforts of the Project 2061 team to develop an integrated collection of computer-based, Internet-accessible collection of HPS resources – to be known as System 61 (Rutherford, 2001). Above all, there is urgent need for research and professional development in the area of pedagogical content knowledge – how to translate history of science into teachable form. The same urgency clearly attends other aspects of the nature of science, particularly the philosophy and sociology of science. Looming over all debate about curriculum is the ever-present spectre of assessment. Given the increasing concern of education authorities with assessment, evaluation and accountability, and given the widespread belief that students will not regard anything seriously unless it is rigorously assessed, there is an urgent need for the development of good and robust assessment procedures and instruments that address the historical, philosophical and sociological dimensions of science and technology. One final point: there are teachers who believe that encouraging students to study ideas from the past, most of which are now regarded as false, serves merely to confuse them; there are teachers who are unconvinced that history will motivate students, believing that some (perhaps most) students will regard history as even more tedious to study than science; there are teachers who believe that school age students are insufficiently mature, both intellectually and emotionally, to deal with the complexity and subtlety of issues arising from historical studies. Short of Ministry of Education directives (or their local equivalent), nothing will convince these teachers to introduce history of science into their courses (or philosophy of science and sociology of science, either) except clear research evidence indicating its educational value. One of the paradoxes facing the curriculum developer is that teachers will not try a radical curriculum alternative unless there is good research evidence in its favour, but that evidence will not be forthcoming unless someone implements the programme. While there is some evidence that Harvard Project Physics attracted a much wider clientele than regular science courses (Brush, 1989) 170 Derek Hodson - 978-90-8790-507-1 Downloaded from Brill.com11/09/2020 11:12:23AM via free access

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and may have improved attitudes to science (Welch & Walberg, 1972), there is little or no evidence to suggest that it improved content knowledge (Ahlgren & Walberg, 1973). Unfortunately, both this course and that devised by Connelly et al. (1977) to focus on historically significant examples of scientific inquiry have long since been abandoned. However, some encouragement can be taken from the following research studies, selected for inclusion in this chapter because they show that the benefits of history of science seem to cross cultural boundaries, even when the science on which they focus is Western science. First, a study by Galili and Hazan (2001b), in Israel, shows that a history-oriented course on optics can have a positive effect on both conceptual and procedural understanding. Second, research by Lin et al. (2002) shows that the performance of Taiwanese students in solving conceptual problems on the properties of gases and on atomic theory improved when historical studies involving debates, role play and hands-on activities were used. Third, California-based research by Kafai and Gilliland-Swetland (2001) showed that even primary school age children can reach an appreciation that data collection methods can and should be different at different times in history and in different circumstances. Fourth, and particularly striking, Hazari (2006) demonstrates that the inclusion of history of science in secondary school science courses (in the United States) impacts significantly on the attainment of women in university physics courses. Interestingly, for men, history of science is not a predictor of success. ENDNOTES 1

2 3

4 5

6

7

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Just how different the intellectual contexts can be is graphically illustrated by Chalmers (1998) in his comparison of the ways in which Demokritos and Dalton regarded atoms. Of course, attention must also be paid to the requirements of the curriculum. In my view, the curriculum should also address the sociopolitical and economic forces that result in science and technology sometimes serving the interests of the rich and powerful at the expense of the poor and powerless (Hodson, 1994, 2003). The history of technology may be even more effective in achieving these goals (Nielsen, 1993). At a more mundane level, history of science may be one of the few ways of generating interest among those students who have no other interest in science but are required by matriculation regulations to take a science course (Galili & Hazan, 2001b). Even the conventions of scientific reporting and methods of establishing claims to originality have changed over time and are, themselves, products of history. Jenkins (1989) makes the intriguing argument that introducing history of science into the curriculum is an effective way of shifting curriculum emphases, and so can be regarded as a tool for curriculum reform – for example, using historical evidence about the use of experiments in theory building to change the way teachers design and implement practical work. In my opinion this is a seriously flawed view, as I argue at length in Hodson (1985, 1988, 1993c, 1996). It has led to the absurdities of discovery learning, the excessive emphasis on the so-called processes of scientific inquiry, a focus on sterile laboratory exercises and neglect of the sociocultural aspects of science. My own view is that we should orient the science curriculum towards preparing students to take sociopolitical action. The curriculum proposals outlined in Hodson (1994, 2003) are concerned to produce activists: people who will fight for what is right, good and just; people who will work to re-fashion society along more socially-just lines; people who will work vigorously in the best interests of the biosphere.

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Although they have less impact than the television versions, both these series are available in book form: Bronowski (1977) and Burke (1978). This is certainly the case in Ontario and in New Zealand - the educational systems with which I am most familiar. Teachers now find it virtually impossible to meet the demands of the plethora of learning outcomes specified for each individual subject through inter-disciplinary projects. Brockman (1995) argues that the great intellectual achievements of science constitute a ‘third culture’, of equal value to literacy and numeracy. The term “Whig history” was coined by Herbert Butterfeld (1931). It may be defined as an attempt to explain the past in terms of the present, to investigate the past in order to support conclusions in the present and to fit the past into an explanatory scheme applicable to the present, as distinct from the attempt to explain the past on its own merits. It is not too much of an exaggeration to say that Whiggish history sees the beliefs, practices and institutions of the present as the goals of previous efforts. Kragh (1987) uses the term anachronic to describe this approach to history and the term diachronic for attempts to interpret historical events in the light of views prevalent at the time: “In the diachronical perspective one imagines oneself to be an observer in the past, not just of the past” (p. 90). As Foucault (1970) remarks: “Historians want to write histories of biology in the eighteenth century; but they do not realize that biology did not exist then, and that the pattern of knowledge that has been familiar to us for a hundred and fifty years, is not valid for a previous period” (p. 15). The term noise has been used to describe the features of practical work that frequently distract students from attending to the key conceptual and procedural aspects (Hodson, 1993c, 1996). Similarly, mathematical noise refers to unnecessarily complex arithmetical and graphing tasks that may divert students’ attention away from the underlying science. Historical noise distracts students from the science embedded in historical case studies. In a more recent paper, Brush (2002) says that he now regards some scientists, notably James Clerk Maxwell, Max Planck and Edwin Hubble, as good role models. Historical simulations may still modify the history slightly, but solely in order to emphasize rather than eliminate the sociocultural and intellectual climate of the time.

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LOOKING FOR BALANCE IN THE CURRICULUM Essential Elements in a Curriculum for Critical Scientific Literacy

While there are still some contentious issues concerning precisely what scientific literacy entails and why we need it (see discussion in chapter 1), there is a measure of consensus on some of its basic components.1 − A general understanding of some of the fundamental ideas, principles and theories of science, and the ability to use them appropriately and effectively. − Some knowledge of the ways in which scientific knowledge is generated, validated and disseminated. − Familiarity with the form, structure and purpose of scientific language. − The capacity to read and interpret scientific data and, at a general level, to evaluate their validity and reliability. − The ability to evaluate a scientific argument or claim to knowledge. − Some awareness of the sociocultural and cognitive circumstances surrounding the history and development of some of the ‘big ideas’ of science, and the origin and development of important technologies. − An appreciation of the complexity of inter-relationships among science, technology, society and environment − A commitment to critical understanding of contemporary socioscientific issues at the local, regional, national and global levels, including their historical roots and underlying values, together with a willingness to take appropriate and responsible action, and encourage others to do so. − The capacity and willingness to address moral-ethical issues associated with scientific research and the deployment of scientific knowledge and technological innovations. − General interest in science, together with a willingness and capacity to update and acquire new scientific and technological knowledge in the future. It is immediately apparent that issues in the history, philosophy and sociology of science (hereafter, HPS) impact on all ten categories. This is true even of the first item if one takes the view that understanding and using an item of scientific knowledge entails knowledge of its role and status as well as its strengths, weaknesses and relationships to other knowledge items. My intention in the earlier chapters of this book was to cast doubt on the image of science and scientists that school science curricula and school science textbooks have traditionally promoted. Indeed, elsewhere (Hodson, 1998b) I have identified ten common myths and falsehoods promoted, sometimes explicitly and sometimes implicitly, by the science curriculum.2 They are reproduced in Table 9.1 alongside a broadly similar list of falsehoods generated by McComas (1998) from his critical reading of science textbooks. 173

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Table 9.1. Myths and falsehoods about science

Hodson (1998) Observation provides direct and reliable access to secure knowledge. Science always starts with observation. Science always proceeds via induction. Science comprises discrete, generic processes. Experiments are decisive. Scientific inquiry is a simple algorithmic procedure. Science is a value-free activity. Science is an exclusively Western, post-Renaissance activity. The so-called ‘scientific attitudes’ are essential to the effective practice of science. All scientists possess these attitudes.

McComas (1998) Hypotheses become theories that in turn become laws. Scientific laws and other such ideas are absolute. A hypothesis is an educated guess. A general and universal scientific method exists. Evidence accumulated carefully will result in sure knowledge. Science and its methods provide absolute proof. Science is procedural more than creative. Science and its methods can answer all questions. Scientists are particularly objective. Experiments are the principal route to scientific knowledge. Scientific conclusions are reviewed for accuracy. Acceptance of new scientific knowledge is straightforward. Science models represent reality. Science and technology are identical. Science is a solitary pursuit.

Sweeping away the old is one thing; finding an acceptable set of alternatives is somewhat different. Many science educators will share Israel Scheffler’s alarm at some of the alternatives that have been advanced. The extreme alternative that threatens is the view that theory is not controlled by data, but that data are manufactured by theory; that rival hypotheses cannot be rationally evaluated, there being no neutral court of observational appeal nor any shared stock of meanings; that scientific change is a product not of evidential appraisal and logical judgment, but of intuition, persuasion and conversion; that reality does not constrain the thought of the scientist but is rather itself a projection of that thought. (Scheffler, 1967, p. v) Longbottom and Butler (1999) express similar concerns when they state that “if we go along with those who deny that modern science provides a privileged view of the world… we fall into an abyss where skeptical postmodernists, who have lost faith in reason, dismiss all knowledge claims as equally arbitrary and assume the universe to be unreliable in its behavior and incapable of being understood” (p. 482).

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Stanley and Brickhouse (1995) regard such remarks as examples of what Bernstein (1983) called “Cartesian anxiety”: the fear that if we do not retain our belief in the traditional objective foundations of scientific method we have no rational basis for making any knowledge claims. In short, fear that belief in scientific progress will be replaced by scientific change consequent upon power struggles among competing groups, with ‘victory’ always going to the better resourced. Fear that scientific knowledge is no longer to be regarded as the product of a rigorous method or set of methods; instead, it is merely the way a particular influential group of scientists happens to think, and can persuade, cajole or coerce others into accepting. The purpose of this chapter is to identify aspects of HPS that are suitable for inclusion in the school science curriculum. In making our selection, do we face a simple but stark choice between the traditional and the post-modern? Are we required to choose between the image of the scientist as a cool, detached seekerafter-truth patiently collecting data from which conclusions will eventually be drawn, when all the evidence is in hand, and that of “an agile opportunist who will switch research tactics, and perhaps even her entire agenda, as the situation requires” (Fuller, 1992, p. 401)? Which view is the more authentic? Equally important, what should we tell students? What is in their interests? Some years ago, Stephen Brush (1974) asked: “should the history of science should be rated X?” The question is just as pertinent to the philosophy of science and the sociology of science. Should we expose students to the anarchistic epistemology of Paul Feyerabend? Should we lift the lid off the Pandora’s box that is the sociology of science? Would students be harmed by too early an exposure to these views? When we seek to question (and possibly reject) the certainties of the traditional view of science, are we left with no firm guidance, no standards and no shared meaning? Does recognition of the sociocultural baggage of science entail regarding science as just one cultural artifact among many others, with no particular claim on our allegiance? Is any kind of compromise possible between these extremes and among this diversity? Can we retain what is still ‘good’ and ‘useful’ about the old view of science (such as conceptual clarity and stringent testing) while embracing what is ‘good’ and ‘useful’ in the new (such as sensitivity to sociocultural dynamics and awareness of the possibility of error, bias, fraud and the misuse of science)? Can the curriculum achieve a balance that is acceptable to most stakeholders? In short, what particular items from all the argument and counter argument reviewed in earlier chapters would constitute an educationally appropriate and teachable selection? What nature of science (NOS) understanding can be taken-for-granted and regarded as no longer in dispute? Is there any consensus among scholars about an acceptable alternative to the traditional view that will allay the fears expressed by Scheffler and others? Responses to a 20-item Likert-type questionnaire on “15 tenets of NOS” led Alters (1997a) to conclude that there is no consensus – at least, not among the 210 philosophers of science he surveyed.3 In the words of Larry Laudan et al. (1986): The fact of the matter is that we have no well-confirmed general picture of how science works, no theory of science worthy of general assent. We did once have a well developed and historically influential philosophical position, that of

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positivism or logical empiricism, which has by now been effectively refuted. We have a number of recent theories of science which, while stimulating much interest, have hardly been tested at all. And we have specific hypotheses about various cognitive aspects of science, which are widely discussed but wholly undecided. If any extant position does provide a viable understanding of how science operates, we are far from being able to identify which it is. (p. 142) Interestingly, despite this categorical denial of consensus, it seems that the authors of several recent science curriculum reform documents (AAAS (1989, 1993) and NRC (1996), among others), with their increasing emphasis on NOS issues, are in fairly substantial agreement on the elements of NOS that should be included in the school science curriculum (McComas & Olson, 1998) – a view endorsed by Cleminson (1990), Abd-el-Khalick et al. (1998), McComas et al. (1998) and Cobern and Loving (2001).4 Indeed, Abd-El-Khalick and BouJaoude (1997), AbdEl-Khalick et al. (1998) and Lederman et al. (2002) state that while philosophers and sociologists might disagree on some aspects of NOS, these disagreements are irrelevant to K-12 students and their teachers. In an effort to shed further light on this matter, Osborne et al. (2003) conducted a Delphi study to ascertain the extent of agreement among 23 participants drawn from the ‘expert community’ on what ideas-about-science should be taught in school science. The participants included five scientists, five persons categorized as histo-rians, philosophers and/or sociologists of science, five science educators, four science teachers and four science communicators. Although there was some variation among individuals, there was broad agreement on nine major themes: scientific method and critical testing; scientific creativity; historical development of scientific knowledge; science and questioning; diversity of scientific thinking; analysis and interpretation of data; science and certainty; hypothesis and prediction; cooperation and collaboration. A comparison of these themes with those distilled from the science education standards documents in McComas and Olson’s (1998) study reveals many simila-rities (Table 9.2). Essentially the same list is found in Lederman et al (2002): science is tentative, empirically based, subjective (in the sense of being theory dependent and impacted by the scientists’ experiences and values), socioculturally embedded and, in part, the product of human imagination and creativity. These authors are also concerned that students draw a distinction between observation and inference (see my comments in Chapter 3) and understand the functions of and relationships between theories and laws.5 A number of questions immediately spring to mind. First, is this apparent consensus deliberately pitched at such a trivial level that nobody could possibly quibble with it? For example, statements such as “science is an attempt to explain natural phenomena’, “scientists are creative” and “science and technology impact each other” – all items in the consensus list developed by McComas et al. (1998) – don’t claim anything particularly insightful. Of course, some would argue that a list of relatively trivial items is better than no list at all. Second, we should ask whether the list includes the ‘big issues’ with which philosophers of science

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Table 9.2. Comparison of themes in Delphi study and McComas & Olson study (Osborne et al., 2003)

have traditionally grappled? And third, we should ask whether it is a consensus arrived at in retrospective justification of a previously agreed set of wider curriculum proposals? We should also ask about the people involved in reaching consensus on NOS items. Given their diverse concerns, we might expect substantial disagreements among philosophers of science, sociologists of science, scientists, historians of science and science educators (Pomeroy, 1993; Abd-El-Khalick et al., 1998).6 So how is consensus achieved within such a diverse group and can that information be helpful in achieving the curriculum balance being sought in this chapter? When disagreements arise, whose views of NOS are to count? Should we defer to the philosophers of science, on the grounds that they spend the whole of their professional lives grappling with the important questions? “No” say Smith et al. (1997) because their concerns are “esoteric, inaccessible, and probably inappropriate for most K-12 instruction” (p. 1102). Should we put our trust in scientists, on the grounds that those engaged on a day-to-day basis with the enterprise of science must know what it entails? Some readers will recall that Peter Medawar (1969) once famously remarked that if you ask a scientist about scientific method “he will adopt an expression that is at once solemn and shifty-eyed: solemn, because he feels he ought to declare an opinion; shifty-eyed, because he is wondering how to conceal the fact that he has no opinion to declare” (p. 11). Pitt (1990) has also observed that most scientists have poor understanding of NOS issues and “generally don’t even know the history of their own discipline” (p. 16). What is interesting is that it clearly doesn’t matter. While NOS knowledge is crucial to the deep and

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reflective understanding of science implied in the term critical scientific literacy, it seems to be irrelevant to the practice of science. Science, broadly considered, is incomparably the most successful enterprise human beings have ever engaged upon; yet the methodology that has presumably made it so, when propounded by learned laymen, is not attended to by scientists, and when propounded by scientists is a misrepresentation of what they do. Only a minority of scientists have received instruction in scientific methodology, and those that have done so seem no better off. (Medawar, 1982, p. 80) In Weinberg’s (1987) words, “philosophy of science is just about as useful to scientists as ornithology is to birds” (p. 433). Interestingly, many of the scientists interviewed by Schwartz and Lederman (2006) and Wong and Hodson (2008a,b) did have fairly sophisticated views about NOS, though they don’t realize it until they discuss issues in depth. Inevitably, their day-to-day concerns as researchers and theorybuilders leave little time for reflection on matter philosophical. Nonetheless, some of the scientists in these studies also expressed very narrow and naïve views of NOS, which reminds us that NOS-oriented teaching in school and university is just as important in courses aimed at the pre-professional education of future scientists as it is in more general courses. Scientists are citizens, too! They also need the kind of critical awareness that will equip them to address complex socioscientific issues. In returning to the question of whose views of NOS are to count, should we follow Albert Einstein’s (1933) advice and put our faith in sociologists and ethnographers? If you want to find out anything from the theoretical physicists about the methodology they use, I advise you to stick closely to one principle: don’t listen to their words, fix your attention on their deeds. (p. 270) Or should we rely on historians of science, on the grounds that a robust theory of science must stand up to close historical scrutiny? After all, what value is there in an account of science for which there is little or no historical support? Of course, historians of the philosophy of science (Losee (1993) and Heidelberger and Stadler (2002), for example) tell us that NOS knowledge has changed as science itself has changed, and so we can’t simply look to the past for guidance on the present concerns of NOS knowledge. No more than a casual browse in the library is necessary to show that philosophy of science is a dynamic, changing and increasingly specialized field of study. Within the discipline, philosophers of quantum mechanics may have few concerns in common with philosophers of biology. Some philosophers of science hold that there is no universal nature of science because the sciences themselves have no unity. The best that can be said is that there is a ‘family resemblance’, with common interests and some areas of methodological and conceptual agreement7 – what Loving (1997) calls a “loose configuration of critical processes and conceptual frameworks, including various methods, aims, and theories all designed to shed light on nature” (p. 437). Thus, Mayr (1988, 1997) has criticized NOS views on 178

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the grounds that they are nearly always derived from physics. Biology, he argues, is markedly different in many respects, not the least significant being that many biological ideas are not subject to the kind of falsificationist scrutiny advocated by Popper and given such prominence in school science textbooks: “It is particularly ill-suited for the testing of probabilistic theories, which include most theories in biology… And in fields such as evolutionary biology… it is often very difficult, if not impossible, to decisively falsify an individual theory” (Mayr, 1997, p. 49). It is more than 70 years since Bachelard (1934/1985) expressed broadly similar views about diversity among the sciences. When one looks at science what is immediately striking is that its oft-alleged unity has never been a stable condition, so that it is quite dangerous to assume a unitary epistemology. Not only does the history of science reveal a regular alternation between atomism and energetics, realism and positivism, continuity and discontinuity, rationalism and empiricism; and not only is the psychology of the scientist engaged in active research dominated one day by the unity of scientific laws and the next by the diversity of things; but even more, science is divided, in actuality as well as in principle, in all of its aspects. (p. 14) As a particular science progresses, and new theories and procedures are developed, the nature of scientific reasoning changes. Thus, any consideration of NOS must be “contextual, conditional, with an eye to open horizons: ‘closed’ answers must, for that reason alone, be suspect, indeed rejected” (Suchting, 1995, p. 20). In short, we should seriously question whether views in the philosophy of science that were arrived at some years ago can any longer reflect the nature of 21st Century science, especially in rapidly developing fields in the biological sciences. Similar arguments were developed in chapter 5 to address and subsequently reject the fundamental assertion of the so-called “Process Approach” to science education: that science comprises a set of discrete, generic processes, and that these processes can be acquired in any context and subsequently used with competence in any other context. I argued that scientific inquiry is perhaps better understood as situated practice, in which the particular conceptual schemes deployed and the specific procedures and instrumental techniques utilized play a crucial role. It is not too much of an exaggeration to state that the different sub-disciplines of science employ distinctive styles of argumentation, rules of evidence and criteria of judgement. In other words, the specifics of scientific rationality change between sub-disciplines, with each sub-discipline playing the game of science according to its own rules. It is not surprising, therefore, that students often experience great difficulty in generalizing even the simplest process skills from one context to another – an observation that has been given theoretical legitimacy by the situated cognition movement (Lave, 1988; Brown et al., 1989; Hennessy, 1993; McLellan, 1996). This argument has been eloquently and forcefully made by Rudolph (2000). Understanding of the operations of science has changed dramatically over the past 40 years. Educators need to begin to exploit the vast literature of the science studies community, not to develop some universalist picture of science, 179

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the value of which is questionable, but to begin to understand what the various practices of science look like in all their myriad forms, in order to provide some reasonably authentic context in which to situate the scientific knowledge claims of the curriculum. (p. 409) Elby and Hammer (2001) also argue that the current consensual list of NOS items is too general and broad, and that it is neither valid nor productive of good learning of science: “a sophisticated epistemology does not consist of blanket generalizations that apply to all knowledge in all disciplines and contexts; it incorporates contextual dependencies and judgments” (p. 565). Essentially the same point is made by Clough (2006) when he says that “while some characteristics [of NOS] are, to an acceptable degree, uncontroversial… most are contextual, with important and complex exceptions” (p. 463). Thus, instead of trying to find and promote broad generalizations about the nature of science, scientific inquiry and scientific knowledge, teachers should be building an understanding of NOS from examples of the daily practice of diverse groups of scientists engaged in diverse practices, and should be creating opportunities for students to experience, explore and discuss the differences in knowledge and its generation across multiple contexts. It is for this reason that NOS-oriented research needs to study the work of scientists active at the frontier of knowledge generation.. Lederman (1995) questions whether school age students could cope with diverse and sometimes conflicting views of how science is conducted, citing Perry’s (1970) conclusion that even adults often experience difficulty with relativistic thinking. If we were to attempt to promote student understanding of the multiplicity of conceptions of science an enormous dilemma would quickly arise. We would be expecting students to internalize a particular world view or paradigm so that they can understand subject matter derived from that particular paradigm. We would then be asking these same individuals to internalize yet another paradigm so that they can understand the subject matter perspectives derived from the alternative paradigm. (p. 374) I am not so pessimistic as Lederman. In my experience, when presented with appropriate examples, students have no difficulty in recognizing that different situations require different strategies, depending on the nature of the problems, the expertise of the research group, and the resources available. Indeed, students find this perfectly natural; it is teachers who create the expectation of one fixed approach to scientific inquiry through their constant references to “the scientific method” (Hodson, 1990). I do not accept the extreme interpretation of Kuhn’s incommensurability thesis on which Lederman’s anxieties are based (see below); nor do I equate recognition of a plurality of approaches to scientific inquiry with relativism. While scientists are free to choose whatever approach they consider best suited to the immediate situation, their choices will be subject to close critical scrutiny by the community of practitioners. Among other considerations, appraisal will focus on the methods employed: Were they appropriate? Were they satisfactorily performed? Could/should the investigation have been conducted differently? In short, some scientific investigations are better than others, and other scientists will make 180

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judgements to that effect, judgements that are not arbitrary or subject to personal whim. While I am arguing for a much more fluid and context-dependent view of what constitutes scientific practice, I also recognize that telling students, too early in their science education, that scientific inquiry is context-dependent and idiosyncratic could be puzzling, frustrating and even off-putting. This is a similar point to Brush’s (1974) concern that teaching history of science can have an adverse effect on students by undermining their confidence in science and scientists. Claxton (1997) expresses similar anxiety: “Perhaps the ‘truth’ about science would be too complex, or too destabilizing for most young people to handle. After all, we protect them, as a matter of principle, from many aspects of the adult world for which we judge them to be unready” (p. 76). One approach is to take our cue from secondary school chemistry curricula, where we often begin with some very simple representations, such as “elements are either metals or non-metals” or “bonding is either covalent or electrovalent”. We then proceed to qualify these assertions in all manner of ways: “there are varying degrees of metallic/non-metallic character, depending on atomic size and electron configuration”; “there is a range of intermediate bond types, including polarized covalent bonds and lattices involving highly distorted ions, as well as hydrogen bonding, van der Waal’s forces, and so on”. Similarly, in the early years, we may find it useful to characterize scientific inquiry as a fairly standard set of steps. Within this simple representation we can emphasize the importance of making careful observations (using whatever conceptual frameworks are available and appropriate to the students’ current stage of understanding), taking accurate measurements, systematically controlling variables, and so on. As students become more experienced they can be introduced to variations in approach that are necessary as contexts change – for example, the startlingly different approaches adopted by experimental particle physicists, synthetic organic chemists and evolutionary biologists. Eventually, students can experience for themselves the joys (and frustrations) of having to work out the procedures for themselves. With these experiences comes the realization that doing science successfully involves learning to ‘think on one’s feet’. In a sense, this progression is similar to those cases in science where scientists begin with a conceptual model (which they know is not ‘true’) and proceed through debate and experimentation to refine and develop it into a more complex theory (see chapter 6). The model is merely a devise to help them think more clearly and to gain a measure of predictive control, while the theory is believed to explain the reality they are studying. By analogy, the early childhood version of science can be regarded as a model of science and the more robust and sophisticated later version as a theory of science and scientific practice. WHAT DO STUDENTS REALLY NEED TO KNOW?

While I wholeheartedly endorse Rudolph’s (2000) view that we need to address the diversity of scientific practice, we still have to confront the question of what specific ideas about science to include in the school science curriculum. Science teachers and science curriculum developers are still faced with the task of making a selection 181

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capable of capturing (at least some of) the complexity of science. Answering the ‘what NOS items do we include?’ question presupposes a satisfactory answer to the ‘why learn about science?’ question posed in chapter 1. Like all aspects of curriculum decision-making, decisions about inclusion of particular NOS items will be informed, explicitly or implicitly, by the wider sociopolitical context in which the decisions are located. In other words, any representation of science and scientists will carry with it a powerful sub-text of sociopolitical meaning and will reveal the interests and biases of the decision makers. Rudolph (2002) argues that previous representations of science and its epistemology in US science education during the second half of the 20th Century, deriving from the work of Dewey and Schwab, were formulated to advance particular social and political interests. Both men emphasized process over content, but Dewey vested authority in the individual and the capacity of the individual to use a universally applicable scientific method in the solution of wider social problems, while Schwab emphasized the specialized expertise of the community of scientists and the capacity of scientists to use complex, context-specific methods guided by prior conceptual frameworks in ways that are not readily accessible to the lay public – thus engendering respect for scientists and support for the scientific enterprise. Whether or not one agrees with Rudolph’s analysis, the simple point remains that there are no socially neutral images of science and scientists. Each and every representation will carry implicit or explicit messages. It is incumbent on us, therefore, to make our wider intentions clear. We need to be clear about the wider goals of science education, and why we choose to include NOS issues in the curriculum, and we also need to give some thought to the consequence of how the implicit goals of science education are likely to be perceived by students. My own motives for advocating NOS teaching were discussed at length in chapters 1 and 2 (see also Hodson, 2006). It is unrealistic as well as inappropriate to expect students to become highly skilled philosophers and sociologists of science, just as it is fruitless to pursue sophisticated expertise in history of science. The science teacher’s responsibilities encompass education in science, education about science and opportunities for students to do science. In chapter 8, I argued that we should subordinate history of science to the major goals of science education. Similarly, we should select NOS items for the curriculum in relation to other educational goals: the need to motivate students and assist them in developing positive attitudes towards science; the need to pay close attention to the cognitive goals and emotional demand of specific learning contexts; the creation of opportunities for students to experience doing science for themselves; the capacity to address complex socioscientific issues with critical understanding; concern for multiculturalism and antiracism; and so on. The degree of sophistication of the NOS items we include should be appropriate to the stage of cognitive and emotional development of the students and compatible with other long and short-term educational goals. There are numerous goals for science education, and education in general, that can, will and should impact on decisions about the NOS content of lessons. Our concern is not just good philosophy of science, good sociology of science or good history of science, not just authenticity 182

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and preparation for sociopolitical action (my ultimate goal for science education), but the educational needs and interests of the students – all students. Selection of NOS items should consider the changing needs and interests of students at different stages of their science education, as well as taking cognizance of the views of ‘experts’ and promoting the wider goals of (i) authentic representation of science and (ii) politicization of students. In short, we need to ask what is in students’ best interests at any given time – a decision that is best made by the teacher, of course. It is considerations like these that prompted Matthews (1998b) to advocate the pursuit of “modest goals” concerning HPS in the school science curriculum. In his words, “there is no need to overwhelm students with cutting edge questions” (p. 169). I agree. But agreement only serves to raise the question of “What should these modest goals comprise?” At the very least, we should include the following: consideration of the relationship between observation and theory; the role and status of scientific explanations (including the processes of theory building and modelling); the nature of scientific inquiry (including experiments, correlational studies, blind and double blind trials, etc); the history and development of major ideas in science; the sociocultural embeddedness of science and the interactions among science, technology, society and environment; the distinctive language of science; the ways in which scientific knowledge is validated through criticism, argument and peer review; moral-ethical issues surrounding science and technology; error, bias, vested interest, fraud and the misuse of science for sociopolitical ends; the relationship between western science and indigenous knowledge. A number of these elements are present in some science curricula, but more often than not they are implicit, part of the “hidden curriculum”, embedded in language, textbook examples, laboratory activities and the like, and so dependent, ultimately, on teachers’ nature of science views – hence the need for teacher education to pay close attention to the nature of science. More controversially, Jenkins (1994c) argues that it is incumbent on science teachers to introduce students to some of the more radical views concerning nature of science: the ideas of Paul Feyerabend, for example, the autobiographical accounts provided by scientists such as James Watson and Richard Feynman, and the sociological writing of Bruno Latour and Steve Woolgar. While I am strongly sympathetic to Jenkins’ argument, I also recognize that we need to be circumspect, modest in our goals and wary of promoting extreme views. In chapter 5, for example, I warned that too literal an interpretation of Feyerabend’s (1975) dictum that “anything goes” would constitute a gross disservice to students. While his freewheeling approach certainly applies to the creative phase of scientific inquiry (what some have called the context of discovery) it is less applicable to the context of justification, for which there are strict procedures relating to judgements about reliability, validity and appropriateness. This more circumspect approach might also incline us to consider that Feyerabend’s anarchistic view is fine (maybe even necessary) for what Kuhn calls revolutionary science, but is entirely inappropriate for the effective conduct of normal science, where a more dispassionate and systematic approach is essential. Careful attention to detail and painstaking accumulation of data are crucial to many aspects of good science, to the effective conduct 183

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of laboratory testing, to the maintenance of safety and to the sound operation of science-based industries. But theoretical breakthroughs are not made this way. Science needs both technicians and creative theory-builders, and we need to provide students with knowledge, understanding and experiences that acknowledge this dual need and lay the groundwork for all manner of future careers. Kuhn himself wonders whether “flexibility and open-mindedness have not been too exclusively emphasized as the characteristic requisites for basic research” (Kuhn, 1963, p. 342). He continues, “almost none of the research undertaken by even the greatest scientists is designed to be revolutionary, and very little of it has such effect” (p. 343). Interestingly, one of the scientists interviewed by Wong and Hodson (2008a) reported that funding bodies often have clear expectations about the conduct of scientific investigations and are suspicious of open-ended approaches, which they regard as little more than “fishing expeditions”. Hence, he argued, it is sometimes necessary to pretend to be engaged in more systematic inquiries. Further support for adopting a more fluid view of scientific investigation is provided by scientists in fields such as molecular biology and materials science, where data collection that previously took months to complete is now achieved by high-speed computers in a matter of minutes, rendering prior hypothesizing and theorizing unnecessary (or certainly less important than in the past). Hence scientific investigations in which data are obtained first and then interesting problems are identified by “data mining” have become much more common in recent years. Despite the theoretical and procedural difficulties associated with inductive approaches outlined in chapter 3, such methods do have a long history; they have been successfully used in science and have led to significant advances in many fields (Kipnis, 1996). It behoves us to tell students this ‘truth’ about the history of science. We should also ‘tell the truth’ about anomalous data. It is certainly not the case that scientists immediately abandon a theory when conflicting data arise. As Chinn and Brewer (1993, 1998) report, scientists’ responses may include any of the following, depending on the particular circumstances: (i) ignore the data, (ii) reject the data, often claiming methodological error, (iii) express uncertainty about the validity of the data, (iv) exclude anomalous data because it is outside the sphere of concern of the theory, (v) hold data in abeyance for later attention, (vi) reinterpret the data, (vii) change some peripheral aspect of the theory, (viii) change the theory. From a study of undergraduates in science labs, Lin (2007) has added a ninth category: (ix) express uncertainty about interpretation of data. Thus, in moves (i) and (ii) the data are declared invalid, in moves (iv) to (viii) the data are accepted as valid, and in moves (iii) and (ix) the scientist is undecided on the validity of the data. Similarly, too literal an interpretation of statements about the tentative nature of science can be counter-productive, leading students to regard all science as no more than temporary (Harding & Hare, 2000).8 Scientific knowledge is tentative because it is based, ultimately, on empirical evidence that may be incomplete and because it is collected and interpreted in terms of current theory - theory that may eventually be changed as a consequence of the very evidence that is collected. In 184

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all these endeavours the creative imagination of individual scientists is impacted by all manner of personal experiences and values. Moreover, the ‘collective wisdom’ of the scientific community that supports the practice, scrutinizes the procedures and evaluates the products, is also subject to complex sociopolitical, economic and moral-ethical forces. In consequence, there can be no certainty about the knowledge produced. However, to admit that absolute truth is an impossible goal is not to admit that we are uncertain about everything. We know many things about the universe even though we recognize that many of our theoretical systems are still subject to revision, or even rejection. There are several closely related issues to consider. First, very specific claims about phenomena and events may be regarded as true even though the theories that account for the events are regarded as tentative. Because the whole necessarily extends beyond the parts of which it is comprised, the whole may be seen as tentative while the parts (or some of them) are regarded as certain. Most theories are tentative when first developed, but are accepted as ‘true’ (in a scientific sense) when they have been elaborated, refined and successfully used, when they are consistent with other theories and strongly supported by evidence. Teachers make a grave mistake when they encourage students to regard all science as tentative. Indeed, if scientists did not accept some knowledge as well established we would be unable to make progress. Cromer (1993) describes the situation particularly well: The experimental and theoretical basis of some of our fundamental knowledge is so extensive that there is little likelihood of its being changed to any significant degree. This is an astonishing assertion, given the breathtaking pace of discovery today. But the pace of discovery is possible precisely because our fundamental knowledge is so complete. (p. 6) Nevertheless, there is always the possibility that some new theory will challenge and possibly displace these taken-for-granted ideas. Open-mindedness is the key virtue of the scientist. Hence the seeming paradox that although scientists have good reason for accepting particular theories as true they do so with the proviso that they can subsequently change their minds if new evidence or new ways of looking at existing evidence (brought about by a new theoretical perspective) become available. When compelling evidence has accumulated, scientists will come to regard the theory as settled and established. The claim in question, however, continues to rest on available evidence, and one’s open-mindedness consists not in suspending judgment where there would seem to be compelling evidence, but in being willing to reconsider present conclusions in the light of whatever evidence or rival interpretation appears. (Harding & Hare, 2000, p. 230) An important element of science education concerns understanding and being able to make effective and appropriate use of the ideas that the community of scientists takes as well-established (what I have called learning science), provided of course that the warrant for such belief is well-argued. There is little value in encouraging students to doubt every scientific proposition they encounter (Norris, 185

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1995). As Elby and Hammer (2001) say, “it would be naïve to think that quantum theory is the long-sought Theory of Everything. At the same time, it would be unsophisticated to consider it tentative that the earth is round or that the heart circulates blood through the body” (p. 557). As Ravetz (1997) has written: “Science, as it is taught, even up to degree level, admits of uncertainty, doubt and debate only rarely if at all. It is facts all the way… In some ways this assumption of certainty is justified. So much of science is unproblematic, that the uncontested facts can more than fill any course; and young minds do not need to be perturbed by uncertainties while they are still mastering difficult concepts and techniques” (p. 7). Thus, the statement “scientific knowledge is tentative.. it has only temporary status” (see Cleminson, 1990, p. 437) is grossly misleading. Much of the scientific knowledge that students encounter in class is no longer tentative. Rather, it is well established, taken-for-granted and used in the production of further knowledge. It is categorycally not the case that it could be invalidated by a simple experiment in a science class, and we do students a gross disservice by suggesting that it could. This is not to say that students shouldn’t be given the opportunity to ‘disprove’ hypotheses or to challenge some existing ideas. What is sought is a judicious balance: not a blanket belief in the certainty of scientific knowledge or its uncertainty, but appropriate levels of confidence, skepticism and open-mindedness, depending on the particular knowledge item and the context of its consideration. Indeed, there are good grounds for believing that students who appreciate that, from time to time, scientific knowledge is discarded in favour of better alternatives are able to use their own scientific knowledge and understanding in more flexible and creative ways than those who are taught to regard all scientific knowledge as absolute truth. According to Langer et al. (1989), they seem also to be more emotionally and intellectually resilient, simply because they are better prepared for negative or unexpected outcomes. Perhaps we should also be a little circumspect in the way that we present the empirical underdetermination of scientific theory. It is certainly the case that observational evidence alone is insufficient to guarantee the truth of a theory, as discussed previously. It is also the case that, in principle, there can be more than one plausible explanation for any given set of data. In practice, however, it is only rarely that this situation arises, and in many situations scientists may struggle to find even one satisfactory explanation for the data. Nor should it be assumed that when alternative explanations of the same set of data are generated they are all equally likely, equally acceptable, equally believable. Underdetermination has, in general, not been a problem for science. Scientists are not in perpetual disagreement. As discussed earlier, for all kinds of reasons scientists do reach consensus, and often surprisingly quickly. Perhaps the aspects of HPS where the greatest degree of caution is required are those relating to Thomas Kuhn’s incommensurability thesis and to questions surrounding the extent to which we consider scientific knowledge, and the practices that produce it, to be social constructs.

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INCOMMENSURABILITY, REVOLUTIONS, NORMAL SCIENCE AND THEORY CHOICE

Kuhn (1970) argues that because of the theory-dependence of observations rival theories about a phenomenon give rise to observation statements that, in the extreme, are mutually unintelligible. Therefore, he claims, such theories are “incommensurable” and there is no rational method for choosing between them in a way that is acceptable or meaningful to the advocates of the competing theories.9 Not only is this situation logically possible, says Kuhn, it has been evident on more than one occasion in the history of science. He cites the transition from Ptolemaic to Copernican astronomy and the shift from Newtonian mechanics to special relativity. In consequence, Kuhn argues, judgements between theories are based on a clutch of non-empirical and non-objective criteria. There are at least two issues to consider. First, is incommensurability as extensive and fundamental as Kuhn argues? Second, does the empirical under-determination of theories necessarily mean that theory change is reduced to a purely social process? Are there any rational criteria to judge the value of competing theories? According to Kuhn’s account of scientific revolutions the key concepts of an existing theory are discarded in favour of entirely new ones. For example, in the late 18th Century the notion of phlogiston as the defining property of inflammable substances was discarded in favour of an explanation based on combustion in oxygen – an explanation involving concepts that were not part of previous explanations. Moreover, even when concepts are retained (or, at least, the terms are retained) their meaning is sometimes subtly or radically altered as they move from theory to theory – for example, the meaning of mass, time and space as they move from classical mechanics to relativity theory or acid and base as they move from the Lowry-Bronsted theory of acids as hydrogen ion donors to the Lewis theory of acid-base behaviour involving electron pair donation for covalent bond formation. But does this really mean that scientists advocating these different theories cannot understand each other? It seems unlikely. Is there no transfer of meaning across ‘paradigmic frontiers’? Again, it seems unlikely. Even when scientific knowledge changes radically and rapidly there is often a chain of developments connecting them, a chain through which a rational evolution can be traced, and although invested with different meanings in the rival theories, concepts like mass, space and acid constitute a “family of uses” in which “ an ancestry-descent relationship” can be discerned (Shapere, 1984). Theories are not simple statements about the world; rather, they are complex structures of inter-related ideas nested within a much wider array of supporting theories. Within this complex, different theories will have areas of intersection, areas of common interest and aspects of experience for which they may proffer exactly the same explanation. All of this is transferred across paradigms regardless of the key theoretical difference at issue. In a so-called Kuhnian scientific revolution, there are, of course, some radical conceptual innovations, but much of our science is retained unchanged and some is retained in only slightly modified form. Perhaps, then, scientific revolutions are not quite so revolutionary as Kuhn suggests. Nor are they so rare. The posing and solving of conceptual problems is a regular 187

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feature of scientific practice; it is not confined to the short-lived periods of paradigm crisis envisaged by Kuhn. There is little historical evidence to identify periods in science when there was no questioning of basic theoretical assumptions and no interest in identifying the conceptual problems that a paradigm generates.10 This is not to suggest that all scientists are constantly questioning the fundamentals of their discipline and can never agree on anything; at any one time, many scientists will be engaged in normal science – i.e., ‘taking the paradigm for granted’ and working within it to extend its applicability (‘puzzle solving” as Kuhn calls it). It is to suggest, however, that conceptual change and replacement is a relatively common feature of (modern) science and it is to suggest that normal science (with no questioning of basic principles ) is not quite so widespread nor so prosaic an activity as Kuhn implies. It is, perhaps, more realistic to regard science as occurring at many different and intermediate points on a continuum from major revolution to standard (algorithmic) puzzle solving, and to regard the goals of science, the methods of inquiry and the theoretical knowledge of science as being constantly modified (Laudan, 1984a). Kuhn (1963) states that “much of the work undertaken within a scientific tradition is an attempt to adjust existing theory or existing observation in order to bring the two into closer and closer agreement… (it) aims to elucidate the scientific tradition in which (the scientist) was raised rather than to change it” (pp. 348 & 349). Nevertheless, he says, this paradigmbased research has often produced a revolution. History also tells us that major scientific revolutions are usually the outcome of lengthy periods of concentrated work on persistent problems by groups of contributors (see the DNA double helix story, for example), and only rarely the outcome of the heroic efforts of a unique visionary like James Clerk Maxwell. Nor is the impact of a scientific revolution always immediate. Although we quite rightly credit Charles Lyell with bringing about a revolution in geology, most of his contemporaries did not accept his views, nor would Darwin’s theory of evolution have proved the ‘fittest theory’ without T.H. Huxley’s vigorous campaigning.11 Even the Copernican revolution was not a sudden and universal shift of opinion; despite Galileo’s heroic efforts, it was many years before physics was sufficiently advanced for the dispute to be finally settled beyond doubt. As discussed in chapter 7, Kuhn’s notion of incommensurability, the DuhemQuine thesis of the empirical under-determination of theories, and recognition of the theory-dependence of experiments, seem to require adoption of the position that theories are accepted for reasons other than empirical adequacy. For some, this is taken to mean that theory acceptance has as much to do with the social context as it has with the intrinsic merits of the idea under scrutiny. It almost goes without saying that a key issue in the debate about suitable NOS views for inclusion in the school science curriculum concerns the mechanism for theory appraisal. Why is a particular scientific paradigm or theory accepted? What are the principal criteria of scientific credibility? The curriculum should no more promote the view that science has infallible methods for adjudicating the claims of rival theories than it should promote the view that scientific knowledge is produced by arbitrary

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methods and has only subjective and socially contingent criteria for judging the worth of knowledge claims and for accepting or rejecting theories. While the theory-ladenness of observation is generally taken to rule out the possibility of using observations to judge the merits of rival theories, this is only the case if the theory with which the observation is laden is the theory that is under test. In other circumstances (i.e., when the observation is impregnated with a theory that is not under test), observational tests are perfectly legitimate. Furthermore, even though rival theories may employ different concepts and conceptual relationships, they address a common area of interest, otherwise they wouldn’t be rival theories. While there will be two unique sets of empirical problems, these sets may be relatively small. Moreover, there will also be some common problems that the theories must attempt to solve, so the rivals can be appraised in terms of how well they succeed in doing so. Even without common ground, there are many objective/rational ways of evaluating and appraising theories. Principal among them is the capacity to make accurate and interesting predictions, though it should be noted that there are many theories now known to be false that were good predictors. Laudan (1977) regards problem solving capability as the major criterion of a good theory: solved problems count in favour of a theory; anomalous problems (unsolved by the theory but solved by one or more of its competitors) count against it; unsolved problems (not yet solved by any theory) constitute the priorities for future research. Of course, the ability to solve problems is no more a guarantee of a theory’s truth than the ability to make predictions: Ptolemy’s epicycles solved the problem of the retrograde motion of the planets perfectly well. Consideration of observational evidence and the capacity to solve empirical problems does not exhaust the scope for rational appraisal. Laudan (1977) identifies “methodological well-foundedness” (p. 59) as a significant criterion. Certainly, a sloppy or careless approach, ill-considered methods of data collection, vague and inconsistent arguments, unwarranted conclusions and structural incoherence are good grounds for rejecting a theory. Even Thomas Kuhn (1977), regarded by some as an irrationalist (and certainly the inspiration for those who are irrationalists or social constructivists), identifies four objective factors additional to empirical accuracy: scope (a theory should be wide in scope and should extend beyond the facts it was designed to explain; it should also unite phenomena that would otherwise require separate explanation), fruitfulness (it should provide a framework for on-going research, perhaps revealing previously unrecognized relationships or leading to the discovery of new phenomena), consistency (it should be consistent, both internally and with respect to other accepted theories) and simplicity (when theories are empirically equivalent, the simplest is preferred). Following van Fraassen (1980), we might add precision, practical utility and the capacity to unify otherwise disparate fields to Kuhn’s list. For Kuhn, these criteria do not constitute a set of rules to dictate or determine theory choice, but a set of values to influence and inform it. Of course, they may point in different directions. For example, while simplicity favoured Copernican theory, consistency favoured Ptolemaic theory. Because competing but empirically equivalent theories will satisfy these four criteria to different degrees, and because the criteria will be weighted differently 189

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by different people and may be differently weighted at different times in the appraisal, “choice between competing theories depends on a mixture of objective and subjective factors, or of shared and individual criteria” (Kuhn, 1977, p. 325). So it seems that Kuhn is willing to admit that theories can be compared, although science does not have an infallible means of doing so. In Kuhn’s (1970) words, we have “no neutral algorithm for theory choice, no systematic decision procedure which, properly applied, must lead each individual… to the same decision” (p. 200). An element of subjective judgement, or what we might call “scientific common sense”, will often be needed to decide between competing theories. Seen in this light, Kuhn’s suggestion that the adoption of a new paradigm involves a certain act of faith does not seem quite so radical, nor so destructive of scientific rationality. In practice, the criteria are not so easy to apply. Even the criterion of simplicity is somewhat ambiguous. For some, simplicity might mean fewer variables; for others, it might mean less complex mathematics. Nor is there any compelling reason to assume that nature itself is simple. Attractive as simplicity is as a criterion of theoretical acceptability, it is a human preference and its appeal is no guarantee of its appropriateness (Bunge, 1963). SCIENTIFIC KNOWLEDGE AS A SOCIAL CONSTRUCT

It is important that the school science curriculum achieves a sensible balance between the view that science is absolute truth, ascertained by value-free disinterested individuals using entirely objective and reliable methods of inquiry, and the dangerously relativist view that ‘scientific truth’ is any view that happens to suit the prevailing cultural climate or reflects the interests of those in power. To paraphrase Helen Longino (1990), the first account is a logical analysis that is historically unsatisfactory and the second is an historical analysis that is logically unsatisfactory. There is no doubt that scientific practice is profoundly influenced by the social context in which it is located. The key point at issue is the extent of this social influence. As Giere (1988) puts it: “The real issue is the extent to which, and by what means, nature constrains scientific theorizing” (p. 55). For those at one extreme, social factors are acknowledged to influence research priorities, but little else; for those located at the other extreme, scientific knowledge is regarded as social in content as well as in origin. In other words, the second position is that scientific knowledge is no more than a social construct and, therefore, has no more legitimate a claim to describe reality than any other form of knowledge. One response to this extraordinary proposition (extraordinary to scientists and science educators, that is) is to point out that such theorists are hoist by their own petard: if all knowledge is merely a social construct (and has no particular claim to truth) then so is the proposition that all knowledge is merely a social construct, and has no particular claim to truth. Another response is to ask for a clear illustration of the ways in which social conditions determine scientific knowledge. It is unremarkable to state that science is produced in a social context, but where is the evidence that specific elements of the social context lead unerringly and inevitably to particular scientific knowledge? In pursuing this line of questioning, Slezak (1994) asks what 190

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elements in the social circumstances surrounding Isaac Newton led directly to the inverse square law? In different social circumstances, Slezak asks, would Newton have formulated the inverse cube law of universal gravitation? And, in turn, was Newtonian physics replaced by Einsteinian physics simply because the social climate changed or because the new theory explained more and solved some outstanding problems? Developing an interest in gravity and choosing to express that understanding in mathematical terms was, no doubt, a consequence of the immediate social context in which Newton found himself; so, too, his underlying assumption that the universe can be understood in mechanistic terms; but the precise relationship at which Newton arrived (the inverse square law) was determined by features, relationships and phenomena in the real world. Recognizing that ideas emerge and are accepted and utilized under particular intellectual circumstances, and that these circumstances are impacted by social and political factors, is not to admit that the knowledge produced is simply a product of the wider social circumstances. And certainly not without more convincing evidence than the sociology of science has so far been able to produce. How can social constructivists account for those situations in which very different theories emerged in the same social milieu? How can they explain why we continue to believe in theories that were produced in social circumstances very different from those of the present day? Boyle’s Law was a product of 17th Century England, Darwinian evolutionary theory a product of 19th Century England, and Heisenberg’s Uncertainty Principle a product of early 20th Century Germany – each very different from my social circumstances in early 21st century New Zealand. Yet I, like many others, continue to accept these propositions. The crucial point is that these ideas were adopted principally because of their capacity to address matters of urgency in science, not because of their sociopolitical appropriateness.12 Indeed, it is fair to say that, far from being socially determined, the profoundly innovative theoretical advances brought about by scientists like Copernicus, Galileo, Newton and Darwin flew in the face of social convention – particularly, religious convictions. In addition, there are notable examples of theories being neglected despite their conformity with the prevailing zeitgeist. The ultimate requirement is that theories have empirical support, regardless of their appropriateness to the prevailing sociopolitical climate. As O’Hear (1989) comments, “ Despite all his prestige and the full backing of an oppressive and dictatorial ideological state apparatus, Lysenko was not able to make his wheat grow” (p. 214). Slezak (1989) has argued that scientific knowledge can now be produced outside any social context by means of computers. He describes how the BACON software has enabled computers to use raw data to generate some of the accepted laws of chemistry and physics – laws that were originally developed in very different sociocultural circumstances. The success of BACON and AM programs provide empirical confirmation of the view that the specific historical circumstances which undoubtedly attend scientific reasoning do not play a decisive role… On the contrary, the programs demonstrate that the widely varying social factors attending the originnal discoveries played no part in determining their specific contents. (p. 571) 191

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I would argue that the interests, expectations and understanding of those who designed the BACON and AM programs are necessarily embedded in the software and in decisions about what data to input, and in what form. Stated baldly, the computer will only search for solutions in ways it is instructed to search. In that sense, there is a social context. Some sociologists go on to argue that it is not just facts and explanations that are socially determined, but criteria of truth and the nature of scientific rationality itself. In other words, decisions about the validity of arguments, the truth of knowledge claims, the correct application of principles, and so on, are all made in terms of criteria determined by the socially dominant group – in this case, by influential people within the community of scientists. The so-called “strong programme” in the sociology of knowledge begins the chain of argument with the perfectly reasonable proposition that we do not know the world as it really is, but only as mediated through our conceptual frameworks. This is no different from the arguments I have made in earlier chapters of this book. The argument continues as follows: this framework is a human construction – it could have been otherwise – and is relative to the social structure (i.e., it was agreed within the community of practitioners). Is it still a reasonable position? It is only a short step from the assertion that all knowledge is socially constructed to the claim that the criteria by which we decide on truth and falsehood are also socially constructed and could, therefore, be otherwise – that is, not only knowledge, but rationality itself is merely a convention among scientists. Eventually, the chain of argument arrives at the position that truth and falsity are simply ‘institutionalized conventions’. In other words, ‘truth is as you choose to see it’ or as important members of the community of scientists choose to see it; the real world imposes no constraints. Bhaskar (1975) responds as follows: Taken literally, it would imply that a chromosome count is irrelevant in determining the biological sex of an individual, that the class of the living is only conventionally divided from the class of the dead, that the chemical elements reveal a continuous gradation in their properties, that tulips merge into rhododendron bushes and solid objects fade gaseously away into empty space. (p. 213) Of course, some would say that this is how the world is constituted. There are sexually ambiguous persons, just as there are transsexuals and hermaphrodites, and many would argue that gender is a more socially appropriate category descriptor than sex simply because it is less categorical. Many people believe that the dead are accessible at certain times and in certain places, and that they constitute part of the ‘spiritual fabric’ of society. Despite spectacular advances in molecular biology it is still not always clear what ‘life’ consists in, or whether entities such as viruses should be classified as living or non-living. My understanding of chemistry is exactly what Bhaskar jokes about: categories such as acid and base, covalent and electrovalent, metal and non-metal impose distinctions that do not adequately describe the intermediate character of many substances. Moreover, solid objects have a vapour pressure and many can be detected by smell at quite a distance, as 192

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observation of canine behaviour quickly reveals. The notion of social determination is not so easily shrugged off when we remember that witches, dragons, mermaids, phlogiston and transmutation of the elements have all had their ‘day in the sun’. Arguments like these lead to the proposition that different groups could legitimate different standards of validity, truth and correctness, according to their own interests and their level of sociopolitical power. The reference to ‘power’ is key: reality is never likely to be determined by all of us; it is determined by some of us. Given the relationship between knowledge production and commercial, political and military power, “truth is what the powerful say it is” and those in positions of power and influence determine reality for the rest of us. It is these relationships between power and knowledge and between power and scientific practice that we should address through the politicization of the science curriculum (Hodson, 1994, 2003). For example, we should ask: Whose interests are being served by particular kinds of scientific research? Whose interests are being promoted by particular kinds of technological innovations? Whose interests support and determine the treatment of scientific and technological issues in the media? How is public opinion on scientific and technological matters formed and consent to particular policies manufactured by media manipulation? It is here that the sociology of science makes its unique and powerful contribution to the attainment of scientific literacy (see arguments in chapter 1). But just how influential is the dominant social group in determining scientific knowledge and, therefore, what counts as reality? To what extent is scientific knowledge determined by the nature of things, the nature of the method by which it is generated and the need to provide a coherent argument linking evidence and conclusions? To what extent is it independent of those who use the method? Clearly there is a sense in which reality is determined by those in power, just as much in science as in any other area of human concern.13 There is no doubt that particular aspects of reality are only available to the initiated. Only the privileged members of the ‘scientific club’ have the conceptual understanding and the necessary language resources to access and understand the data and its significance as support for a particular belief. Data have no meaning outside a particular interpretative framework; explanations have no meaning outside a particular linguistic framework, as the following example illustrates:. NH4NO3 dissolves in water endothermically because the lattice energy of anhydrous NH4NO3 is greater than the combined enthalpies of solvation of the ammonium ion and nitrate ion. By controlling access to the community of practitioners and to the discourse of science, we can determine reality differently for different people.14 Also, we can control what knowledge is admitted into the knowledge store of science by controlling the organs of publication (academic journals, the media, the Internet). Does this mean that the ‘powerful’ groups can authorize any knowledge they choose? Are there any constraints on this power? It would be grossly misleading to believe that there is only one conceivable representation of the world, or that we can know what the world is like independently of our conceptual structures. But 193

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this is not to say that the world is merely a construct of the human mind, that our knowledge is purely arbitrary or that individuals are free to make unique interpretations of sense data or to fabricate any world that happens to suit them. The admission that observation is theory-dependent and that theories are created by individuals does not mean that science loses all objectivity. The admission that theoretical explanations could be different does not reduce science to mere fashion, prejudice or social convention. Science cannot be anything that important scientists choose to say it is. The world does limit us in some ways. Others put it more starkly: whatever social constructivists say about knowledge being a human creation, wasps still sting and dogs still bite, sound takes time to travel across a pond, wood burns and soap bubbles cannot be nailed to the wall. Limits are set to the ways in which scientists’ interests determine knowledge by (i) the interests of others and (ii) the nature of the real world. As Longino (1990) argues, what constitutes the world of science is not a given, but nor is it entirely fabricated. It is a product of the interaction between the external real world and our intellectual needs and capabilities. Of course, what we (as scientists) contribute may change over time in response to sociocultural change, technological innovation and new theorizing. Moreover, there are always features of the real world that we ignore or that remain unapprehended. Social forces do not determine how the natural world is constituted and how it behaves, but they do ‘open scientists’ eyes’ in particular ways, direct their attention to particular phenomena and events, and impact on the ways in which they make sense of them using procedures devised and sanctioned by scientists and using technological artifacts designed in accordance with existing theory. REALISM AND INSTRUMENTALISM REVISITED

As the foregoing discussion makes clear, questions about the extent to which we should regard scientific knowledge as a social construct speak directly to the debate about the relative merits of realism and instrumentalism as appropriate positions for the school science curriculum (see chapter 6). Realists, whether they are philosophers, historians or sociologists of science, are concerned with what scientists do in order to elucidate the nature of reality – that is, how they go about the process of discovery and theory building. In contrast, social constructivists and instrumentalists argue that science is not involved in finding out about things that already exist (the realist position) but in creating entities can be used to construct reality – thus asserting that entities such as electrons, magnetic fields and genes do not exist in any meaningful way outside this social construction. If we accept Bloor’s (1976) argument that science should be regarded as creating the phenomena it describes, we should presumably treat viruses, volcanoes and nuclear fission as mere social constructs/conventions. Only a fool would do so! Richard Dawkins (1995) puts the absurdity of this position in a nutshell when he says: “Show me a relativist at thirty thousand feet and I will show you a hypocrite” (p. 32). As discussed in chapter 6, the standard case against antirealists of all kinds hinges on the fruitfulness of theories, as Putnam (1978) argues with respect to both Newtonian physics and relativity theory. 194

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If these objects don’t really exist at all, then it is a miracle that a theory which speaks of gravitational action at a distance successfully predicts phenomena; it is a miracle that a theory which speaks of curved space-time successfully predicts phenomena. (p. 19) When we use scientific theories to make technological interventions, the devices we make usually work, and often work very successfully: spacecraft with their inboard telescopes are capable of sending back close-up pictures of Mars, Jupiter or Saturn; laser surgery does enable some sight defects to be repaired; nuclear fission can be harnessed to produce electricity. At a theoretical level, it could be argued that disputes in science reach closure precisely because the ‘successful’ theory more closely corresponds to reality – that is, it has more realist features than its competitors. Of course, we do not always need sophisticated scientific theories in order to build successful technological artifacts. An approximate or simplified theory is often good enough for practical purposes. Spectacles, telescopes and microscopes, for example, can all be successfully manufactured using optical theories dating from the mid-17th Century. Rival theories are sometimes equivalent for technological purposes and even falsified theories can be used successfully in some practical contexts (Bunge, 1967). Sociologists have done a great service in illuminating aspects of the day-to-day lives of practising scientists and in ‘putting a human face’ on science. However, it seems that in their eagerness to give priority to the social dimensions of science they may be guilty of ignoring the most important facet of the scientific enterprise: the theories generated by scientists and the reasons why these theories are so successful. In drawing attention to this misplaced focus, Laudan (1990) asks us to consider an analogy. No one would entertain for a moment the idea that the central problem in the history of music was how symphonic performers organised themselves. They would reject out of hand the idea that the central problem in the history of painting should be the question of how painters’ patronage was arranged. Yet it is today seriously being proposed… that the central questions about science have to do, not with the master works which science has produced, but rather with the mundane minutiae of the life of a ‘normal’ scientist or with the ways in which scientists garner political support for their activities. (p. 52) So what position should we adopt in the school science curriculum regarding the realist-instrumentalist debate? Solomon (1999) asks: “Should we teach that electrons, the energy concept, and the colliding molecules in a gas, which we have such difficulty making real and believable to our students, are not real at all? And which should we teach first – their relativity or their unreality?” (p. 4). I share her conclusion that “science simply cannot be taught at all if the students are to be told that there is no point in believing what is being said” (p. 5). Millar (1997) makes the same argument: “Is it wise, from the perspective of effective teaching and learning, to portray demanding and difficult ideas as tentative conjectures? Is this likely to increase students’ motivation to undertake the challenging mental work of coming to terms with these ideas, so that they can use them as tools for their own thinking 195

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about new problems and situations?” (p. 91). Millar goes on to state that there is moral issue here. For example, he says, “the germ theory of disease is intended to provide students with understanding which can be practically useful in taking decisions about their own health, is it responsible to portray generally accepted core knowledge as tentative conjecture?” (p. 91). At the other extreme, Eflin et al. (1999) advocate naïve realism (belief in the absolute truth of scientific knowledge) on the grounds that anything else is too difficult for students. I profoundly disagree and, as argued in chapter 6, I am inclined to adopt a critical realist position on the grounds of authenticity, flexibility and pedagogical utility. I argue for the authenticity of critical realism on the grounds that most scientists are realists of a kind, for whom the principal goal of science is to obtain knowledge of maximum clarity, validity, reliability and predictive capability. Indeed, all the scientists in the study conducted by Wong and Hodson (2008a,b) subscribed to the view that the predictive power and technological applicability of current scientific theories can be taken as strong evidence that in many respects we are getting closer to knowing some of the truths about the universe. Although we cannot describe the world except through the conceptual frameworks we have devised, we can test the adequacy of those frameworks by interacting with the world. Science assumes that there is regularity in nature (regularity is not solely a creation of human imagination) and that whatever underpins this regularity can be ascertained. Thus, the prime thrust of science is to generate explanations of nature and to use them to control, manipulate and generate more knowledge. The authors of Science for All Americans (AAAS, 1993) express it as follows: “Scientists assume that even if there is no way to secure complete and absolute truth, increasingly accurate approximations can be made to account for the world and how it works” (p. 4). My claim for flexibility rests on the point made in chapter 6 that critical realists can be realist about those conceptual structures they regard as genuine attempts to uncover the truth and can be instrumentalist about those that have utilitarian value (for prediction, control, etc) but no claim to truth. I suggested that the former should be termed theories and the latter models. Matthews (1998b, p. 166) argues that this position also enables students to recognize that “science is a human creation, that it is bound by historical circumstances, that it changes over time, that its theories are underdetermined by empirical evidence, that its knowledge claims are not absolute, that its methods and methodology change over time, that it necessarily deals in abstractions and idealizations, that it involves certain metaphysical positions, that its research agendas are affected by social interests and ideology” and still claim that in many respects it describes the real world. My criterion of pedagogical utility is based on the assumption that realism is more likely to motivate students, just as it motivated scientists like Galileo and Einstein. Students who are critical realists are more likely to think that they have the ability to build understanding and explanations for themselves through careful and critical reflection on their experiences (especially those we present in science lessons). But if scientific knowledge is absolute truth, this knowledge has to be learned; and if scientific knowledge is nothing more than a human invention (i.e., a mere social convention), then learning science also reduces to learning what others 196

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prescribe. A critical realist position enables students to construct their own models to solve short-term problems, where initially the only criterion of acceptability is ‘what works’. By comparing and contrasting their model with models constructed by others, students see the importance of robustness, breadth and scope, and predictive capability. Later, they come to appreciate how further rounds of inquiry and reflection can result in these models being developed into realist theories. ENDNOTES 1

2

3

4

5

6

7

8

9

Although a discussion of technological literacy is outside the scope of this book, a combined notion of scientific and technological literacy would also include: (i) understanding of basic technological concepts, principles of design and criteria of evaluation, and (ii) possession of a range of basic hands-on skills, the capacity and confidence to tackle technological problems, and the willingness to develop new knowledge and skills. I am not claiming that all ten myths are promulgated by all science curricula. Rather, that most curricula promote one or more of them and, across the range of curricular provision, all ten are evident. Smith et al. (1997) accuse Alters of bias in designing the questionnaire and interpreting the responses to make the differences appear greater than they really are – charges that Alters (1997b) contemptuously dismisses. There is also some dispute over what the term nature of science (NOS) encompasses. In recent publications, Lederman et al. (2002) and Lederman (2006, 2007) seek to restrict its use to the characteristics of scientific knowledge (i.e., to epistemological considerations) and to exclude all activities related to the collection and interpretation of data and the derivation and publication of conclusions. The definition adopted in this book is considerably broader, and includes: the characteristics of scientific inquiry; the role and status of scientific knowledge; how scientists work as a social group; how science impacts, and is impacted by, the social context in which it is located; the language of science; its underlying values; and so on. Thus, my usage is closer to the notion of “ideas about science” used by Bartholomew et al (2004): nature of science, plus “the social influences on science and technology, the nature of causal links, risk and risk assessment, and the impact of science and technology on society” (p. 656). Good and Shymansky (2001), however, question whether there really is a consensus, arguing that there are major inconsistencies between and within the lists of NOS items in Benchmarks for Scientific Literacy (AAAS, 1993) and National Science Education Standards (NRC, 1996), depending on whether the reader adopts a philosophy of science perspective or a history of science perspective. Lederman (2007) is insistent that students and teachers recognize that “observations are descriptive statements about natural phenomena that are ‘directly’ accessible to the senses (or extensions of the senses) and about which several observers can reach consensus with relative ease… Inferences, on the other hand, go beyond the senses” (p. 835). He also states that “laws are statements or descriptions of the relationships among observable phenomena… Theories, by contrast, are inferred explanations for observable phenomena” (p. 835). Osborne et al. (2003) detected some differences between the views of scientists and the views of philosophers and sociologists, and some substantial differences among science teachers. Questions about the unity/disunity of the sciences raise important questions concerning our capacity to formulate robust criteria to demarcate science and non-science – a crucial element of scientific literacy. There is a certain irony here. Teachers often have to work very hard in the early years of science education to get students to appreciate that scientific knowledge is tentative. Youngsters are naturally inclined to take all knowledge (especially knowledge located in books or heard on television) as secure and certain. Of course, by making such an assumption the world can be rendered stable and predictable, and so much easier to cope with. There is a sense in which the situation envisaged by Kuhn is nonsensical. It theories really are incommensurable there is no way of deciding whether they address different phenomena or address the same phenomenon in ways that are incompatible and, therefore, requiring of resolution. There are no ways of judging compatibility and incompatibility, difference or sameness (Longino, 1990). 197

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10

11

12

13

14

Kuhn (1970) and Lakatos (1974) both argue that the central tenets of an established theory (paradigm or research programme) are immune from criticism – an assertion that does not correspond to the historical evidence. Although a distinguished scientist in his own right, Thomas Huxley (1825-1895) is often remembered as “Darwin’s Bulldog” for his vigorous advocacy of evolutionary theory. Of course, the observation that some scientific knowledge is unintelligible to those outside the particular social context of its production is clear evidence of a measure of social construction, though it shouldn’t be taken as evidence of a causal link between social circumstances and scientific knowledge. We should also turn the critical spotlight on ourselves, and ask to what extent are we, as science teachers, concerned to determine reality for those we teach? And, in doing so, whose interests are we serving? Essentially the same situation exists with any highly context-dependent and culturally specific knowledge – only those who gain admission to the sub-culture and its specialized language will have access to this knowledge.

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FURTHER THOUGHTS ON SOCIAL CONSTRUCTION AND SCIENTIFIC RATIONALITY A View for School Science Thirty years after Stephen Brush (1974) famously asked whether the history of science should be rated X, Douglas Allchin (2004) posed a similar question regarding the sociology of science. For Mario Bunge (1991), the answer is clear. In a savage attack that is worth quoting at length he says that the sociology of science is guilty of adopting seven misleading tenets that, taken together, constitute “a grotesque cartoon of scientific research” (p. 525). These are externalism, or the thesis that conceptual content is determined by social context; constructivism or subjectivism, the idea that the inquiring subject constructs not only his accounts of facts but also the facts themselves, and possibly the entire world; relativism, or the thesis that there are no objective and universal truths; pragmatism, or emphasis on action and interaction at the expense of ideas, and the equation of science with technology; ordinarism, or the thesis that scientific research is pure perspiration and no inspiration, and the refusal to accord science a special status and to distinguish it from ideology, pseudoscience, or even antiscience; adoption of obsolete psychological doctrines, such as behaviorism and psychoanlayis, and the substitution of a number of unscientific or even antiscientific philosophies – such as linguistic philosophy, phenomenology, existentialism, hermeneutics, ‘critical theory’, poststructuralism, deconstructivism, or the French school of semiotics, as the case may be – for positivism, rationalism, and other classical philosophies. (pp. 524-525) Equally deplorably, but at the opposite extreme, the accounts of scientific rationality presented in many science curricula fail to acknowledge that sociopolitical forces play any role at all in determining the direction of science and establishing research priorities. By neglecting to consider the day-to-day practices of scientists, they fail to distinguish between ‘science-in-the-making’ and ‘ready made science’ (the edited, sanitized, ahistorical and systematized account of science common to so many textbooks). They take no account of the daily struggle to extract meaningful data, develop robust techniques, establish credible interpretations and create convincing arguments. The question at issue here and in the previous chapter is: what would constitute a sensible balance between the view that scientific knowledge is entirely independent of the social context in which it is generated and the position that says all knowledge (including science) is no more than a social construct? While it would be absurd to claim that the products of scientific inquiry and theory-building cannot 199

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be understood outside the sociocultural context in which they were produced, as some sociologists argue, appreciation of the sociocultural milieu within which particular scientists work (or worked) provides a context for a better understanding of their priorities, working styles and criteria of judgement. This applies just as much to a full understanding of the elegant rationalist work of Isaac Newton as it does to understanding the principles of alchemy, the theory of phrenology or the practice of acupuncture. Perhaps there is value in drawing a distinction between epistemic relativism and judgemental relativism (Knorr-Cetina & Mulkay, 1983). Epistemic relativism asserts that knowledge is rooted in a particular time and place. Knowledge doesn’t just mimic nature, it also reflects the society that produces it (at least in some respects). Judgemental relativism makes the additional claim that all forms of knowledge are ‘equally valid’. In other words, any one human construction is as good as any other. We can acknowledge the first without accepting the second. Socially produced knowledge still has to meet its purpose, and for science that purpose is to explain the nature and behaviour of the natural world in reasonably comprehensible terms, and with predictive capability. And it has to gain consensus among other practitioners who have this same commitment to theory building. The appropriate question is not “Is science objective and rational?” but rather “What is the nature of scientific rationality and objectivity?” In much recent sociological writing scientific practice is portrayed as an exercise in literary persuasion, in which theory acceptance depends less on a rational appraisal of evidential adequacy than on shrewd manoeuvres, tactics and rhetoric. As Latour and Woolgar (1986) state, the worth of a theory is established and measured by the “increasing number of people from whom it extracts compliance” (p. 285) and “the degree of accuracy (or fiction) of an account depends on what is subsequently made of the story, not on the story itself” (p. 284). Although it is no more than common sense to state that a knowledge claim only becomes established when it is used (as it stands or in modified form) by other scientists, Latour and Woolgar seem to imply that whether this occurs or not is simply a consequence of the scientist’s skill with literary techniques and her/his capacity to use inscription devices to lend rhetorical power to the argument (see chapter 7). Drawing heavily on the work of Foucault (1970, 1972/1982) on the emergence of professional discourse within a network of social, political and economic relations, Latour and Woolgar conclude that science is simply a form of discourse that has acquired a particular form of organization and a set of historically and socially contingent rules to establish what is admissible and what is true/false. These characteristics could have been developed differently. In consequence, the knowledge that is accepted as science simply reflects the interests and ideology of those currently in positions of power. Using that rationale, Blondlot’s theories about N-rays were not so much discredited on intellectual grounds as out-manoeuvred on sociopolitical grounds (Klotz, 1980; Nye, 1980; Ashmore, 1993). Fuller (1992) argues that the opportunistic and frequently self-serving activities of scientists are rational in some broad understanding of the term because they often succeed in what they are trying to do (publish articles, persuade others, win research grants, and so on), or they fail “in ways that permit them to continue and 200 Derek Hodson - 978-90-8790-507-1 Downloaded from Brill.com11/09/2020 11:12:23AM via free access

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improve upon their efforts” (p. 401). Acknowledging that published accounts of science are sanitized and depersonalized by omitting all reference to dead ends and failed experiments, and by minimizing the role of intuition and maximizing the role of rational, systematic planning is not to say that scientific writing is a ‘confidence trick’ or an exercise in fiction building. The scientific paper is not autobiography or history, it is not a narrative account of what happened. Rather, it is a rational reconstruction of events into a chain of logical argument and evidence designed to persuade readers of the legitimacy of a particular point of view. There is more involved here than literary techniques. No matter how persuasive the rhetoric, argument is won or lost on grounds of rational criteria that extend beyond the immediate sociopolitical context of the various players. For most scientists there is a key role for observational and experimental support, successful predictions, logical argument, internal and external consistency, absence of decisive counterexamples, and so on. Isaac Newton’s views did not prevail because he was a better politician, and adept at out-manoevring his rivals; they prevailed because they were scientifically significant, rationally justified and cogently argued. I am inclined to follow Laudan’s (1977) advice that there is no need to invoke social causes, either internal to science or external to it, unless there are no rational reasons at all that can be invoked. It may well be, as Forman (1971) argues, that Heisenberg’s Uncertainty Principle was readily accepted by German physicists in the late 1920s because it enabled them to repudiate, to an extent, the charge that science was overly rationalistic, mechanical and deterministic and left no scope for human values. But arguing that the social context created the overall intellectual climate in which a particular idea was regarded as acceptable is not to establish social conditions as the primary cause of its acceptance.1 The Uncertainty Principle was accepted primarily because it was an exceptionally good idea, because it solved a number of long-standing problems, and because it enabled the discipline of physics to make progress. In Laudan’s words, “the chief way of being scientifically reasonable or rational is to do whatever we can to maximize the progress of scientific research traditions” (1977, p. 124). This can involve solving empirical problems or making conceptual changes and adjustments that increase the theory’s problem-solving effectiveness. It is this second rational move that is being invoked here. The consequence of regarding factors in the social-cultural context as the sole or principal reason for accepting an idea is the reduction of science to whim, caprice, social conditioning or powerful propaganda. If we cannot regard the knowledge base of science as reasonably secure and rationally justified we cannot regard its claims any more seriously than those of astrologers, religious prophets or crystal ball gazers. This is an unacceptable position for the science curriculum.2 SAVING SCIENTIFIC RATIONALITY

It is important to acknowledge that science is practised by people and that their knowledge, experience and interests will influence science in all kinds of ways – deciding priorities, influencing procedures, controlling access to the community, controlling publication, and so on. Clearly, scientific knowledge is created, sustained, transmitted and modified through social processes. Whether they are employed in 201 Derek Hodson - 978-90-8790-507-1 Downloaded from Brill.com11/09/2020 11:12:23AM via free access

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universities, research institutes or industry, most scientists work as members of a team. At the day-to-day level, an individual scientist is likely to be a member of a group engaged in a specific investigation or series of investigations. At the wider level, the scientist is a member of the institution’s team of scientists, with the collective responsibilities that follow from it, and a member of the ‘invisible team’ of scientists extending across all institutions who conduct similar and related research. Science is a social practice in the sense that scientists are dependent on one another for the intellectual and technical resources with which they work. Existing theoretical and procedural knowledge, investigative techniques, laboratory apparatus and instruments, and so on, collectively constitute the research context within and upon which further progress is based. Science is a social activity in the sense that the rules of scientific procedure and the legitimacy of the ‘product’ are determined by the community of practitioners. The wider community of scientists determines what counts as acceptable scientific practice and exercises strict control over what is admitted to the corpus of accepted knowledge through its system of peer review. This community also exercises control over the education of future scientists and the initiation of newcomers into the community of practice. Furthermore, scientific practice is sociohistorically situated. Scientific theories are human constructions; they depend for their existence on strongly motivated human agents building and developing them, exploring their adequacy and rationality, using them to address both theoretical and practical problems, and so on. Immersed in the prevailing sociocultural milieu, scientists cannot remain immune from other cultural and ideological influences. History tells us that scientific ideas come from many sources, many of them outside the sphere of science. The cultural context is likely to shape the questions that are asked, the topics that get pursued, the observations that are made and attended to, and what overall theoretical perspectives are likely to find favour within the community. Thus, Darwin’s theorizing on evolution in terms of ‘survival of the fittest’ was a consequence of his experiences in the ruthlessly competitive society of Victorian England and the 19th Century science of phrenology (or craniology) was promoted as a rational justification for a society that already believed that women and non-Europeans are intellectually inferior to Caucasian men (Fee, 1979; Gould, 1981; Hodson & Prophet, 1986). It almost goes without saying that because scientists draw ideas from their cultural location there is the ever-present danger of bias and distortion. Furthermore, sociocultural pressures can also function to resist or even exclude particular lines of research and explanation, while encouraging others. Although they may be reluctant to accept the findings of sociological and ethnographic studies of science laboratories, most practicing scientists would readily acknowledge the (often significant) role played by intuition, hunch, luck, greed, personal needs, publishing pressures, and the like. They might admit Knorr-Cetina’s (1995) assertion that scientists can, on occasions, be guilty of practices that are not “open and above board”, such as hoarding of information, implementing personal and group biases, engaging in plagiarism, showing blind trust in their own data or theory while dismissing those of rivals without sufficient consideration. Many would also acknowledge that competition plays a key role and, for some, may even be the major driving force. As David Hull (1988) observes, as long as there are 202 Derek Hodson - 978-90-8790-507-1 Downloaded from Brill.com11/09/2020 11:12:23AM via free access

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rewards for publishing papers, formulating new theoretical propositions and developing new techniques and instruments, there will be scientists ready and willing to produce them, and many who will strive to be the ‘first’ or the ‘best’. Of course, competition can also lead to wasteful duplication of research and, in the rush to publish, to the generation of substandard work and the publication of incomplete studies. Even worse, it can lead to attempts to mislead competitors, steal other scientists’ results, discredit other researchers by spreading false information about them, and the regrettably all-too-common tactic of releasing part of the research findings in support of an alternative explanation/theory in a deliberate attempt to mislead or distract competitors (Monhardt et al., 1999; Wong and Hodson, 2008b). The question for us, as curriculum builders and teachers, is whether these social, cultural and economic factors constitute the main driving force for science or whether they are influences that simply make science a human (and therefore imperfect) endeavour. Recognizing that science is a social activity, and that its methods and procedures were established by people and are sustained by authority and custom, is not to say that the scientific knowledge produced is empirically inadequate, socially expedient, irrationally believed or likely to be false. Rationality can be retained in our account of science as a guarantee that the methods of appraisal we choose to employ produce knowledge that is robust enough to solve empirical and conceptual problems, and has some direct relationship to the actual world. We choose particular methods because they have some objective value in helping us to reach our principal goal of ‘getting a handle on the nature of reality’. The rationality of science is located in (i) careful and critical experimentation, observation and argument and (ii) critical scrutiny of the procedures and products of the enterprise by other practitioners. It is a community-regulated and community-monitored rationality. Science is socially constructed through critical debate. And those involved in it have a commitment to maintain certain rigorous debating standards. Longino (1990) makes the point that “it is the social character of scientific knowledge that both protects it from and renders it vulnerable to social and political interests and values “ (p. 12). First, she says, there are public forums for the presentation and criticism of evidence, methods, assumptions and reasoning – in particular, conferences, academic journals and the system of peer review. Second, there are shared and publicly available standards that critics must invoke in appraising work, including but not restricted to empirical adequacy (as discussed earlier in this book). Third, the scientific community makes changes and adjustments in response to critical debate and is clearly seen by practitioners and members of the public to do so. Fourth, the right to submit work for peer appraisal and criticism is open to all practitioners; so, too, the right to publicly criticize the work of others. Of course, the way in which the community of scientists exercises this public scrutiny at any one time is subject to a whole range of social, cultural, political and economic factors and the inclination of individual scientists to be persuaded by a particular argument or to be swayed by particular evidence depends, in part, on their background knowledge, assumptions and values. In these respects, as Longino states, the procedures of scientific appraisal are vulnerable to charges of social relativism. The resilience of science in the face of such charges is a consequence of its 203 Derek Hodson - 978-90-8790-507-1 Downloaded from Brill.com11/09/2020 11:12:23AM via free access

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openness to criticism by individuals of diverse backgrounds, experiences, interests and underlying values. Questions will be asked about the appropriateness, extent and accuracy of the data, how it was collected and interpreted, and whether the conclusions follow directly from the data, and so on. The explanation will be scrutinized for internal consistency and for consistency with other accepted theories. Particular attention will be directed to the background theory and assumptions underpinning the research design, and to the deployment of auxiliary theories and choice of instrumentation and measurement methods. The possibility that these questions may be answered differently by different appraisers, and that different perspectives will be brought to bear in the appraisal process, is the reason for upholding the principle of academic equality and is one of the guarantees of scientific objectivity.3 In short, Longino (1990, 2002) argues that the critical scrutiny exerted on scientific ideas by peer review and public critique via conferences and journals is the centerpiece of scientific rationality and a guarantee of the objectivity and robustness of the knowledge developed. The formal requirement of demonstrable evidential relevance constitutes a standard of rationality and acceptability independent of and external to any particular research program or scientific theory. The satisfaction of this standard by any program or theory, secured, as has been argued, by inter-subjective criticism, is what constitutes its objectivity. (Longino, 1990, p. 75) Of course, one of the main concerns surrounding the increasing commercialization and militarization of science is that the demands of patent secrecy and military secrecy remove science from public scrutiny, and thereby compromise its objectivity. The privatization of science strikes directly and damagingly at our collective ability to distinguish sound from unsound work, plausible from implausible arguments, and even truth from falsehood. And, of course, science can be rational and still get it wrong, in the sense of accepting ideas that subsequently turn out to be false. The key point is that we improve our science because of constant critical scrutiny by people with wide and varied experience and reflecting a range of value positions. Over time, we identify wrong science and bad science (such as science with clear evidence of bias), we detect and expose fraud, and we discriminate science from non-science. The point at issue for the science curriculum is that all accepted scientific knowledge has a well-argued and well-supported warrant for belief. While acknowledging that verification of theories is not possible, this position does recognize that science makes progress. Progress arises from continual criticism and efforts to meet criticisms through modification and/or replacement of theoretical structures. As Rorty (1991) argues, what makes science ‘special’ is that scientists have done a better job than most other groups in implementing certain values – in particular, reliance on persuasion rather than coercion and willingness to consider alternative ideas. With the goal of recreating this community-based and criticism-based model of science in the classroom, Carl Bereiter (1994) identifies four basic requirements for the establishment of progressive discourse within the community of scientists/ students. First, a commitment to work towards a common understanding satisfactory 204 Derek Hodson - 978-90-8790-507-1 Downloaded from Brill.com11/09/2020 11:12:23AM via free access

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to all; second, a commitment to frame questions and propositions in ways that allow evidence to be brought to bear on them; third, a commitment to expand the body of collectively valid propositions (what Bereiter has in mind here is similar to the Lakatosian notion of a ‘hard core’, the propositions that participants will not deny, even though they may not actively endorse them); fourth, a commitment to allow any belief to be subjected to criticism if it will advance the discourse. Bereiter notes that item four is the most problematic commitment. To paraphrase Wittgenstein (1969), although you can doubt everything, you cannot doubt everything at once; and to paraphrase Shapere (1982), the possibility of doubt is not sufficient reason to doubt. We need to ask whether certain doubts should be taken seriously. We should not doubt unless there is good reason to do so, no more than we should believe unless there is good reason to do so. There comes a point when doubt must be put aside. Without an established and taken-for-granted set of theoretical propositions, significant further progress is impossible; but without doubt, the possibility of scientific revolution is ruled out. A MODEL FOR THE SCHOOL CURRICULUM

Popper’s ‘three worlds’ view of scientific knowledge, introduced towards the end of chapter 6, might usefully be modified to take account of some of the sociological perspectives developed in chapter 7. Replacing the second world of subjective thought processes (the ‘mental world’ in Figure 6.1) by the complex social activity of scientific practice (see Figure 10.1) provides a simple model for enableing teachers to raise important questions about authentic scientific practice and address a cluster of seemingly unconnected issues: equity and exclusion; values in science and science education; ethnosciences, pseudoscience and scientific fraud; the issue of realism versus instrumentalism or social constructivism.

Figure 10.1. Popper’s ‘three worlds’, adapted to include scientific practice

The model implies that scientific practice has the same kind of status as scientific knowledge: it exists independently of its practitioners, though it is created, monitored, sustained and validated by its practitioners and may, from time to time, be 205 Derek Hodson - 978-90-8790-507-1 Downloaded from Brill.com11/09/2020 11:12:23AM via free access

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changed or modified as practitioners see fit or the situation demands. Importantly, the world of scientific practice (World 2) is no longer a ‘secret garden’. It is open to public scrutiny, and thereby subject to criticism and change. Scientific knowledge (World 3) can be regarded as a ‘conceptual net’: concepts at differing levels of abstraction are linked by generalizations of varying degrees of certainty and linked to the natural world through ‘instances’ expressed in observable terms (Hesse, 1980). Scientific practice is the creative extension of this conceptual net to fit new circumstances. In principle, inquiry is open-ended; it could lead anywhere. Nothing in the ‘net’ fixes its future form, though clearly it influences the way in which research is designed and conducted and constitutes the background against which problems are defined and addressed. According to Popper (1972), scientific problems exist because scientific knowledge has an autonomous existence outside the minds of individuals or groups of scientists and, in consequence, some problems may remain unsolved or even unrecognized for some time. He compares this situation with a nesting box in a garden. Eventually a bird will utilize an opportunity for nesting that has been there, undetected by other birds, ever since it was installed. In the same way, problems concerning the adequacy of theories in accounting for observations, problems concerning conceptual relationships within or between theories, or whatever, are sensed by individuals who then use the approved procedures of existing scientific practice to attack them and solve them. In this undertaking scientists are driven by their individual perceptions, ideas and intuition, and are guided by fellow practitioners. Science has achieved its remarkable success not because the problems it tackles are simple or because nature is particularly easy to study, but because scientists have refined and regulated their activities into a particularly effective scientific practice: “a social endeavour, which over the centuries has developed an approach appropriate to its limited goals, and where the work of each individual is informed and controlled by that of his colleagues in this endeavour, of the past, the present and the future” (Ravetz, 1971, p. 180). Ravetz (1971) has likened the scientific enterprise to cathedral building, with many individuals working over a long period of time on different aspects of a complex structure. Scientific knowledge is achieved, he says, “by a complex social endeavour, and derives from the work of many craftsmen in their very special interaction with the world of nature” (p. 81). The production of scientific knowledge, like cathedral building, requires a community of practitioners with shared knowledge, standards and goals, and it requires individuals with diverse and wideranging skills and capabilities working under a measure of overall direction and supervision (the “positive heuristics” of various research programmes and the continuing critical scrutiny by the community’s senior practitioners). The scientific knowledge generated by individuals or teams of individuals, and subsequently validated and accepted by the community, has an objective existence – just as a cathedral built by individual artisans working to a community plan has an objective existence. Thus, the intensely personal activity of creative research (within a team or as an individual) produces objective, impersonal knowledge by means of procedures developed, validated and supervised by the community of practitioners, or the community’s nominated agents. Basing their speculation on existing knowledge, individual scientists sense a problem, formulate a strategy for investigating it, 206 Derek Hodson - 978-90-8790-507-1 Downloaded from Brill.com11/09/2020 11:12:23AM via free access

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collect evidence, and so on, using procedures, techniques and instrumental methods developed and authenticated by predecessors, and subsequently present an account of the work for critical evaluation by peers in the formal ‘public language’ of science. Students can be sensitized to the existence of these different stages, and to the crucial distinction between the free and open ‘private language’ of creative thought and the formal, objective and de-personalized ‘public language’ of scientific publication by incorporating what we might call ‘conference opportunities’ into open-ended project work. Laudan (1977) reminds us that contemporary scientific practice is largely an exercise in problem solving. He divides problems into two broad categories: empirical problems (any feature of the natural world that is need of explanation) and conceptual problems. Conceptual problems can be internal (logical inconsistencies, ambiguities, circularities, etc) or external (conflicts with other theories), while empirical problems can be categorized as solved problems (those satisfactorily explained by the theory), unsolved problems (those that fall outside the scope of the theory) and anomalous problems (those not solved by the theory, but solved by a rival theory). Solved problems are important because they constitute a substantial part of the warrant for belief in the theory’s central premises (what Lakatos would call the “hard core”) and are especially important if rival theories are unable to solve them. However, as history reminds us, solved problems are no guarantee of truth: false theories can work just as well as true ones, and there are many examples of discarded theories that were previously accepted as true because they ‘worked well’. The goal of the researcher is to maximize the number and scope of solved problems and minimize the number and scope of anomalies and conceptual problems (compare the Lakatosian notion of a ‘positive heuristic’). Of course, anomalies are potentially the most serious threat to a theory’s viability because they can encourage scientists to abandon a theory in favour of a rival. Closely related to empirical problems, though not mentioned by Laudan, are the technical problems associated with the collection of experimental data. In many fields of science progress is increasingly dependent on the design of new instrumentation techniques – not simply to speed up data collection but to provide the corroborative evidence for theory building that may not yet exist. The theories that best solve problems will contribute most to meeting the aims of science: making accurate and reliable predictions, establishing manipulative control, increasing the scope and precision of explanatory systems and, whenever possible, integrating and simplifying the various components of those explanatory systems.4 Laudan (1984a,b) makes the point that there is a constant and complex process of mutual adjustment and mutual justification among aims, methods and theories. Aims justify methods and must harmonize with theories; methods justify theories and are chosen to meet aims; theories constrain methods and must harmonize with aims (Figure 10.2). This view sits well with what we should be trying to teach students about the contextual contingency of scientific inquiry. As Abrams and Wandersee (1995) point out, contemporary science is highly dependent on research funding, and regardless of whether funds are provided by industry, the military, universities or government, there is increasing pressure for 207 Derek Hodson - 978-90-8790-507-1 Downloaded from Brill.com11/09/2020 11:12:23AM via free access

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Figure 10.2. Interactions among aims, methods & theories, after Laudan (see Duschl, 1990)

research to be directed towards the solving of practical problems, creating comercial opportunities, establishing military advantage and meeting public interest needs. These “societal aims”, as Abrams and Wandersee (1995) call them, prioritize research funding and, in turn, drive the development of new research methods. In many cases, concern with fundamental theoretical issues (sometimes known as “Blue Sky” research) is pushed to the sidelines, a concern expressed by several of the scientists interviewed by Wong and Hodson (2008b). In the pursuit of critical scientific literacy two key questions for students to consider focus on who determines the extent and direction of research funding and how research priorities are established. Other questions follow: Should our priorities be different? How can we intervene to re-prioritize? Asking such questions and subjecting the scientific enterprise to close critical scrutiny is an essential element in the politicization of students, which I take to be the ultimate purpose of achieving universal critical scientific literacy. TEACHING AND LEARNING METHODS

Research tells us that teaching students and student teachers about the nature of science is much more successful when it is both explicit and supportive of critical reflection (Abd-El-Khalick & Lederman, 2000). Teaching about science, like any other cognitive learning outcome, should embody a specific tangible content around which teachers can plan a systematic and coherent sequence of learning experiences and assessment/evaluation activities. Implicit approaches, in which students are expected to acquire understanding by ‘reading between the lines’ as they engage in classroom activities, particularly practical work, have been shown 208 Derek Hodson - 978-90-8790-507-1 Downloaded from Brill.com11/09/2020 11:12:23AM via free access

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to be, at best, only moderately successful in achieving their goals. Also, as with any other complex learning goal, adequate curriculum time is essential. Nature of science learning cannot be rushed. Making matters explicit does not entail a didactic approach. Rather, it suggests a carefully focused approach using a variety of teaching and learning methods, including hands-on activities, contemporary and historical case studies, reading and writing activities and, most importantly of all, opportunities for guided reflection and critical discussion. Figures 10.1 and 10.2 are useful in focusing teacher attention on key issues. For example, Figure 10.2 is useful for concentrating attention on the complex relationship between theory and scientific inquiry, how scientists utilize models as cognitive tools in their day-to-day problem solving, how theories are articulated and revised, and how scientific arguments are constructed. The notion of scientific practice in Figure 10.1 focuses attention on social dimensions within the community of science and on the relationships of the community of scientists with the wider society and its institutions. It reminds us that this community, like all other communities of practice, has its own distinctive language, beliefs, codes of behaviour and values, each of which is a focus for curriculum attention. Demarcation criteria loom large in such considerations: What is science? Is it characterized principally by its methods, explanatory systems, criteria of validity, underlying values, or some other criterion? How does science differ from other forms of knowledge? How much room is there for manoevre and change without the activity losing its designation as science? Demarcation is a crucial aspect of critical scientific literacy – in particular, being able to distinguish good science from bad science, detecting bias and distortion and differentiating among science, pseudoscience and non-science The emphasis on science as a practice reminds us that because science is conducted by people it is vulnerable, on occasions, to bias, influence of vested interest, distortion and misuse for sociopolitical, business and military ends. It is also subject to errors and may sometimes follow false trails. Pressures on scientists can be such that they engage in misconduct and even fraud. Teachers have important decisions to make about the extent to which they will raise these kinds of issues in the curriculum. This book is a plea to those teachers to afford learning about science a much higher profile than has been usual in the past. ENDNOTES 1

2

3

It is noteworthy that Forman neglects to mention that several major players in these events were not German. Bunge (1991) reminds us that Schrodinger was Austrian, de Broglie was French, Dirac was English, Bohr was Danish and Einstein is best described as a ‘citizen of the world’. Moreover, “the place to which all the quantum physicists at the time flocked in pilgrimage and called ‘the Mecca of the quantum theory’ was Copenhagen, not Gottingen, Berlin, Leipzig or Munich” (p. 541). Of course, it is important to ask whether the desire to promote science as more rationally based than these other knowledge claims, and therefore more valid and reliable, has any sound foundation. Or whether it is, itself, merely the outcome of social conditioning. Among several others, Harding (1998) has developed this into a generalized argument for the urgency of involving more women, more members of racial/ethnic minority groups and more people from non-industrialized cultures in the appraisal of scientific practice.

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4

Some would argue that creating artifacts to meet human wants and needs and the creation of a better life also constitute legitimate aims for science (see chapter 6), while others would argue that these aims are technological rather than scientific. In the complex world of 21st Century technoscience this distinction is increasingly irrelevant.

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INDEX

Doing science 2, 29, 32, 88, 91, 93, 95, 136, 151, 154, 156, 157, 182 Economy, neoliberalism & globalization 12–14, 16, 27, 34, 36–38 Elegance & simplicity 105, 124, 157, 189, 190 Ethics 11, 12, 16, 20, 39, 85, 129, 130, 142, 154, 159, 160, 173, 183, 196 Experiment 29, 30, 59, 67–69, 73, 79, 80, 81, 85–91, 94, 100, 101, 119, 127, 134–136, 155, 164, 183, 201, 203 Falsification & refutation 67–71, 73–75, 77, 78, 86, 96 Feyerabend, P.K. 57, 58, 75, 82, 95–99, 102n, 113, 155, 183 Fluidity, holism & idiosyncrasy 97–101, 131, 133, 135–137, 156, 164, 179–181, 184 Giere, R.N. 111, 116–118, 190 Hacking, I. 86, 110, 118, 141 Hodson, D. 2, 10, 14, 20–22n, 25, 28, 32, 39, 40n, 56, 62, 63, 86, 90, 92, 94, 98, 102n, 121n, 139, 142, 146, 160, 171n–174, 178, 180, 182, 184, 193, 196, 202, 203, 208 Holton, G. 33, 74, 124, 125, 144, 167, 169 Humanizing science 153–155, 168 Hypotheses & conjectures 67–69, 71, 81, 86, 93, 94, 97, 110 Implicit & explicit 3, 13, 23, 24, 35, 95, 138, 157, 173, 182, 183, 208 Incommensurability 79–81, 85, 86, 141, 180, 186–188, 203 Induction 53, 60–64, 67, 69, 71, 75, 89, 91, 92, 96, 184 Inference 56–60, 93, 107, 108, 176 Intellectual independence 16, 17, 158

Abd-El-Khalick, F. 25, 25, 26, 176, 177, 208 Aesthetics 11, 27, 123, 159 Agreement with facts 74, 76–79, 81, 85, 87, 96, 97, 104, 110, 113, 119, 123, 124, 132, 168, 184 Aikenhead, G. 8, 16, 17, 25, 26, 160 Allchin, D. 83, 126, 157, 160, 166, 199 American Association for the Advancement of Science (AAAS) 1, 4, 11, 14, 16, 17, 19, 34, 92, 196, 197n Anything goes 82, 95, 98, 133, 183 Argumentation 3, 9, 33, 35, 38, 99, 119, 130, 133–135, 137, 138, 141, 145, 153, 157, 173, 179, 183–185, 189, 200, 201, 203, 209 Bencze, J.L., 14, 36, 37, 102n Bias 19, 145, 175, 182, 183, 202, 204, 208 Brush, S. 75, 163, 167, 170, 172n, 175, 181, 199 Competition & collaboration 139, 140, 141, 202, 203 Consensus in science 59, 81, 99–101, 127–130, 135, 200, 202 Consensus in science education 33, 173–177, 186 Constructivism 26, 56, 97, 117, 150, 152, 158 Corroboration 67–71, 105 Creativity 67, 68, 75, 81, 97, 127, 139, 142, 156, 183, 185 Critical realism 114–118, 196 Critical scientific literacy 2, 10, 15, 17, 18, 20, 35, 38, 39, 160, 168, 178, 208 Désautels, J. 19, 31–34 Direct & indirect observation 107, 108 Discovery learning 88–91 Diversity in science 33, 204 239

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Intuition 123, 124, 133, 134, 136, 141, 155, 157, 201, 202 Jenkins, E.W. 1, 5, 7–9, 16, 88, 92, 150, 153, 162, 169, 171n, 183 Knorr-Cetina, K.D. 126, 134, 135, 136, 200, 202 Kuhn, T.S. 20, 76, 77, 79–81, 83n, 86, 87, 102n, 105, 116, 118, 129, 163, 169, 184, 186–190, 197n, 198n Lakatos, I. 72, 73, 83n, 102n, 155, 169, 198n, 205, 207 Language of science 2–4, 20, 35, 36, 79, 105, 106, 129, 137, 138, 144, 145, 156, 173, 183, 193, 207, 208 Latour, B. 88, 126, 133, 134, 137, 138–142, 169, 183, 200 Laudan, L. 105, 111, 164, 175, 188, 189, 195, 201, 207, 208 Lederman, N.G. 24–27, 33, 40n, 176, 178, 180, 197n, 208 Literacy 2–4, 7, 20, 137, 138 Longino, H. 101, 146n, 190, 194, 197n, 203, 204 Matthews, M.R. 121n, 149, 162, 183, 196 Medawar, P. 53, 137, 177, 178 Merton, R.K. 129, 130, 132, 139, 140 Metacognition 8, 150, 151, 157, 158 Millar, R. 1, 6, 21n, 33, 93, 102, 162, 195 Miracles 109, 110, 115, 195 Models 104, 114–118, 155, 157, 169, 181, 183, 196 Non-Western science 16, 100, 128, 144, 160, 161, 183 Normal science 76, 77, 80, 81, 116, 129, 151, 163, 183, 188 Norms, interests & values 139–145, 159, 182, 183, 193, 204, 208 Norms of scientific practice 129–135, 139 Nuffield 1, 88, 89, 103 Objectivity 9, 31, 62, 63, 81, 85, 119, 127, 129, 130, 175, 190, 194, 200, 203, 204, 206

Observation 41–60, 67–71, 73, 74, 76, 78–81, 85, 86, 88, 89, 91, 93–95, 97, 104, 106–108, 113, 127, 155, 156, 176, 183, 187, 189, 194, 201, 203 Osborne, J. 2, 6, 40n, 135, 157, 176, 177, 197n Paradigm 76–81, 85–87, 116, 118, 123, 129, 180, 187, 188, 190 Political issues 2, 10, 12, 14, 15, 18–20, 34, 35, 37, 38, 154, 159, 160, 173, 183, 193, 208 Popper, K.R. 20, 58, 67–71, 74, 81–83n, 110, 111, 114, 119, 120, 169, 205, 206 Prediction 68–71, 73, 75, 78, 80, 94, 104, 105, 108–111, 113, 189, 200, 201, 207 Proof & certainty 29, 30, 101, 103 Quasi-induction 69, 70 Recurrent history 165, 166 Rudolph, J.L. 1, 150, 179, 181, 182 Scientific method (algorithmic) 92–95, 98, 99, 101, 134, 136, 155, 179 Scientific method/investigation 30, 31, 32, 34, 60, 82, 92, 95, 97– 102, 105, 106, 112, 127, 133, 134, 136, 137, 140, 154–156, 164, 180, 183 Scientific revolutions 76–78, 80, 81, 97, 99, 116, 151, 163, 183, 184, 187, 205 Shapere, D. 58, 59, 187, 205 Social construction 81, 105, 112, 118, 119, 125, 127, 128, 134–136, 142–146, 153, 164, 188, 190–194, 199–209 Sociocultural & economic influences 81, 102, 113, 120, 123, 125–128, 135, 139–141, 144, 151, 153, 155, 159, 160, 162, 163, 173, 183, 185, 191, 202 Solomon, J. 1, 22n, 30, 33, 40n, 160, 195

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Technological success 110, 111, 118, 195 Tentative nature of science 17, 27, 35, 71, 78, 155, 184 Theories as complex structures 71–75, 79, 118, 119, 151, 156, 157, 187, 206 Values 10, 11, 14, 17, 31, 35, 81, 127, 128, 141–145, 185, 189, 204, 208

Vested interest 125, 126, 130, 140, 183 Wellington, J. 2, 6, 25, 31, 92, 162 Whiggish history 163, 164, 168, 169 Wong, S.L. 25, 40n, 63, 121n, 139, 142, 146n, 178, 184, 196, 203, 208

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