Constructing Worlds through Science Education

The Selected Works of John K. Gilbert

John K. Gilbert

• Publisher: Routledge
• Year: 2013
• ISBN:
  9781135177157
• Edition: 1
• Topic: Éducation
• Subtopic: Éducation générale

Internationally renowned and award-winning author John Gilbert has spent the last thirty years researching, thinking and writing about some of the central and enduring issues in science education. He has contributed over twenty books and 400 articles to the field and is Editor-in-Chief of the International Journal of Science Education. For the first time he brings together sixteen of his key writings in one volume.

This unique book highlights important shifts in emphasis in science education research, the influence of important individuals and matters of national and international concern. All this is interwoven in the following four themes:

• explanation, models and modeling in science education
• relating science education and technology education
• informal education in science and technology
• alternative conceptions and science education.

PART 1

EXPLANATION, MODELS, MODELLING IN SCIENCE EDUCATION

CHAPTER 1

MODELS IN EXPLANATIONS

Horses for courses?

Gilbert, J.K., Boulter, C. and Rutherford, M. ‘Models in explanations: horses for courses?’ International Journal of Science Education, 1998, 20(1): 83–97

This paper seeks to identify some of the issues associated with the role of models in scientific explanations. Starting from a broad definition, a typology of explanations is developed and the notion of ‘appropriateness’ in scientific explanations is explored. Some characteristics of explanations sought and provided for and by scientists, science curricula, teachers of science and students of science are identified. Finally, the nature of models and their contribution to explanations are explored.

What is an explanation?

Even if the most simple of definitions is adopted, that an explanation is the answer sought or provided to a specific question, it seems that no one explanation is appropriate in all circumstances and for all questioners. The notion of an appropriate explanation will vary as a function of relevant experience and the expectation perceived by those involved to underlie the question asked. When one of us (CB) was observing a class of 9-year olds, the teacher’s general question, ‘What is going to happen in the eclipse tonight?’, produced many different answers. When another of us (JG) asked a group of 14-year olds in a science class ‘What is a good explanation in science?’, the answer was ‘Good for what?’. When the third of us (MR) asked a number of science teacher educators ‘How would you explain colour?’, the first response was invariably ‘To whom?’.

It is the latter investigation (Rutherford 1995) which is used as the source of the examples and exemplars in this paper. For that reason, the content area running through the text is ‘light and colour’. Other areas could as appropriately have been used. The outcomes of this investigation, when combined with our previous work in the area of models (Boulter and Gilbert 1996), led us to conduct a broad enquiry into the role of models in scientific explanations. This study drew on a diverse literature, including that of the history and philosophy of science, as well as that of cognitive and social psychology. Thus, the references given for Newton and his work are only a few of the many available. The complexity of the inquiry was revealed by the fact that, when we showed interim versions of our ideas to other researchers in science education, their comments focused on many different aspects of them. The resulting papers are thus speculative, intended to raise issues rather than to arrive at definitive conclusions. This paper is an attempt to identify and explore some of the social-psychological issues involved in the relationship between questions and explanations.

An illustration of the complexity of the field is revealed by the range of types of relationships which are possible between a question asked and an explanation produced. One way of analysing these relationships is in terms of an implicitness–explicitness continuum. The most straightforward case is where the question is directly posed and the explanation provided is equally explicit. For example, where a chemistry teacher’s question ‘Why is chlorine gas green?’ is answered by a student with ‘Because the molecules are green’ [sic]. In some cases, an explicit question can receive an implicit explanation, i.e. one where the actions of those questioned indicates that they are acting in response to their unvoiced answer. Thus, a physics teacher’s question ‘How does white light behave?’ is followed by the students drawing a light ray being refracted by a prism in their notebooks, having decided that this is the explanation called for. Teachers’ explicit questions have been characterized as being ‘open’, where a wide range of answers would be acceptable, or ‘closed’, where one specific answer is expected (Barnes et al. 1969). The above-mentioned drawing of a ray of light, rather than describing its colour characteristics, is an example of a closed type of response. Whether the expectation implied in a teacher’s explicit question is either open or closed, it is very likely that the student will give a closed reply, having interpreted it in the narrow context of the topic being considered. Thus, the students mentioned above produced a ‘physics’ description of light in a physics class, rather than a ‘chemistry’ answer which should also have been known. The relationships can become more complex still when the question is implicit. For example, a teacher’s provision of information about interference phenomena in optics can lead students to volunteer an explicit explanation for the implied question ‘How does this come about?’. Although the observer could not perceive what is going on, there are cases where both the question and the explanation are implicit; for example, where a teacher provides tables of colour and wavelength, such that students seem to understand the patterns in their own data because they can predict data yet to be collected, having implicitly grasped the significance of wavelength. Alas, in many cases teachers provide explanations without students, or perhaps even also themselves, being aware of what the question is.

Martin (1972) has analysed the complexity of the field in another way, by identifying five meanings for the term ‘an explanation’ in science and science education, i.e.:

1 a clarification of what a phrase means in a scientific context. It is a description of how the phrase relates to a phenomenon;

2 a justification of some belief or action. It is the provision of reasons why a belief or action is reasonable;

3 a causal account of some state, event or process. It is a propositional statement stating why something is;

4 a citation of a theory from which a law may be deduced;

5 an attribution of function to an object.

The present paper is concerned with this genre of meanings, i.e. with the content of explanations. It is not concerned with that range of meanings for ‘an explanation’, which focuses on the activity of providing an explanation, or on the discourse involved in doing so.

One important pattern of relationships stems from the interactions between the nature of questions asked and the explanations which they elicit. A typology can be constructed from these relationships.

A typology of explanations

In a simple view, the conduct of science involves the posing of questions about phenomena in a natural world. This suggests that a typology of scientific explanations might be deduced from the expectations required by these questions. The empirical finding of Abrams and Wandersee (1995), that practising life scientists base their work on seeking answers to questions, rather than on trying to validate theory, supports this approach. A philosophically inclined person of scientific bent might ask the following range of questions.

Why is the inquiry to be carried out?

The first act of a scientific inquiry, often taken unconsciously, is to segregate out some aspect of nature from the continuum which constitutes the world in which we live. Some kind of boundary is drawn around it and the phenomenon is named. It is usual in so doing to give a reason for believing that the phenomenon chosen is capable of study in isolation (Lipton 1991). The making of a selection from the complexities of nature, the construction of that which is to be investigated, carries the assumed question of ‘For what purposes is the study of this aspect of nature, this phenomenon, of importance?’. The explanation provided as an answer to this question is the intention underlying the conduct of the subsequent scientific inquiry.

Thus, in Newton’s time, astronomy concentrated on the place and movement of the Earth amongst the planets as part of a general inquiry into ‘the place of humanity in God’s universe’. The lenses used in the telescopes were prone to chromatic aberration, so the images formed had coloured edges and were poorly focused. The intention of the work carried out by Hooke, Huygens and Newton at that time was to understand and eliminate this problem (Westfall 1994). Even though these three researchers had the same intention, their work differed in other respects, as will be noted later.

How does the phenomenon behave?

Most scientific inquiries, at least those into phenomena which have not hitherto been extensively investigated, always address the question ‘How does this phenomenon behave?’ at an early stage in their conduct. A description is an explanation which provides an account of its behaviour, initially as originally encountered and later under the effect of experimental manipulation. In both cases, behaviour often changes over a period of time. Newton, for example, collected together examples of many situations where the phenomenon of colour was found, e.g. glass, water droplets, paint and fabrics, and investigated their behaviour (Sabra 1981).

Of what is the phenomenon composed?

The naming of entities within the phenomenon, together with the identification of their relative spatial and temporal distributions, constitute an interpretation of its physical structure. This type of explanation often allows it to be ascribed to a group of similar phenomena and thus to be classified. Newton’s early work on colour, like that of many other natural philosophers at the time, involved a naming of the colours of the visible spectrum, as revealed by the refractions of white light, and a demonstration that the same colours, in the same spatial relationship, were produced in different situations, e.g. in glass, in a water droplet (Sabra 1981).

Why does the phenomenon behave as it does?

The explanation produced in response to this questions is based on causation. A mechanism is proposed by means of which the phenomenon produces the observed behaviour through the operation of cause and effect on the entities of which it is composed, either deterministically or probabilistically. Newton, for example, initially tested Hooke’s ‘theory of pulses’ as a way of explaining rainbows and chromatic aberration. He went on to conclude that white light is heterogeneous and may be split into the different colours because they are differently ‘refrangible’ (Finegold and Olson 1972: 31–35). Hooke had also provided a mechanism to explain colours (Westfall 1994). This mechanism used a scale of colours which related to how much ‘darkness’ had been added to white light. The ‘scale of strength’ took red (white light with the least addition of ‘darkness’) as the strongest colour, through dull blue, to black, which involved the total extinction of light by darkness. Hooke’s mechanism, however, provided no causal explanation to underpin the ‘scale of strength’.

Causality has, of course, been much studied. The deductive-nomoligical model takes a standard form for deterministic explanations (Hempel 1965):

• the statement of causal law;

• a statement about a phenomenon;

• a deducted causal explanation.

For example:

• Light is refracted by the boundary between two translucent media.

• Light is being refracted.

Therefore, there is a boundary between two translucent media.

The Statistical-Probabilistic model of causal explanation (Hempel 1965) is very similar in structure. The causal laws are statistical in nature, so that the causal explanation produced is probabilistic in form.

How might it behave under other conditions?

When quite a lot is known about the phenomenon, the way in which it may behave under different circumstances can be anticipated. The explanation provided is a prediction which, because it can be experimentally tested, is one of the most powerful, and indeed defining, tools of science.

Newton, having produced his causal explanation of the relationship between coloured light and white light, went on to predict and to subsequently test what would happen both qualitatively and quantitatively when light was passed through chains of prisms (Finegold and Olson 1972: 36–61). This led to his second proposition, second theory, that ‘the light of the sun consists of rays differently frangible’. He stated that:

sometimes I placed a third prism after the second, and sometimes also a fourth after the third, by all which the image might be often refracted sideways.

(Newton 1952: proposition II, theory II, experiment 5)

The production of a descriptive explanation is often an early, if not the first, step in the production of a series of explanations of the other types in a de novo inquiry. Thereafter, each such inquiry takes place by seeking the other types of explanation, and indeed revisiting particular questions, in a pattern which is probably unique to it. In that the development of these other types of explanation is often facilitated by its production, it seems appropriate to include descriptive explanation within the listing for any given inquiry. This is contrary to the view of Bateson (1979: 81–83) who argues that behaviour is not a part of explanation because it makes no statement about causation in respect of the phenomenon under study. We, on the...

Table of contents

• Cover
• Full Title
• Copyright
• Contents
• Acknowledgements
• Introduction
• PART 1. Explanation, Models, Modelling in Science Education
• PART 2. Relating science education and technology education
• PART 3. Informal Education in Science and Technology
• PART 4. Alternative Conceptions and Science Education
• Index