Abstract
The nature of science is a complex theme, and continues to be the subject of advanced and ongoing scholarship, drawing upon a range of disciplines. Therefore, whatever is presented in school science as being ‘the’ nature of science must at best be a simplification, and so there is a need to form judgements about which simplifications are most appropriate. Effective ‘curricular models’ of science concepts are designed simplifications of scientific models that guide teachers by indicating target knowledge that is deemed appropriate in terms of the prior learning and conceptual development of a group of learners, and which is both ‘intellectually honest’ and a suitable basis for further learning. A similar approach can guide teaching about the nature of science. A consideration of the English National Curriculum offers an example of how aims relating to the teaching of the nature of science may not be realised in the absence of a suitable explicit curricular model to guide teaching.
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Appendix. The Draft Cambridge Curricular Model of the Nature of Science
Appendix. The Draft Cambridge Curricular Model of the Nature of Science
Science is about understanding (making sense of) the world (i.e. the universe in which we exist, not just the earth).
We try to understand the world for three main reasons:
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Curiosity (people like to make sense of the world) [there is an ‚explanatory imperative’, we get intellectual satisfaction, also we can feel unease when something doesn’t make sense to us; some people like to feel at one with nature, or may even see this as a spiritual quest/practice].
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Prediction (to help us plan, to take advantage of opportunities, to avoid problems, etc.).
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Control (to help us make our lives healthy, comfortable etc.) [note, according to some scholars this aspect may typically appeal more to boys, and less to girls, so perhaps be sensitive about examples used, e.g. avoid electric chairs and atom bombs?].
We try to understand the world by developing theories that enable us to explain what happens, and what might happen in the future (under various conditions).
An explanation is an answer to a ‚why’ question. A scientific explanation uses scientific ideas (such as theories) to answer questions.
A theory is a way of explaining the relationship between different things [‚things’: there is an issue here of theoretical entities, and how they come into being].
Theories are developed by scientists in response to observations. There are many different types of scientific work, involving different sort of observations. Sometimes these are of natural phenomena (just watching, measuring what is there), and sometimes scientists set up the conditions for an observation — we call this an experiment.
Information collected during observations and experiments is called data.
When we observe a regular pattern in our data, we sometimes call this a ‚law of nature’.
Before scientists can carry out an experiment, they must already have an idea of what the relationship might be. An idea about a relationship that has not yet been tested is called a hypothesis. [The hypothesis is tentative — should we call this a guess, an intelligent guess, an informed guess?] Scientists use imagination to form hypotheses [— this is a creative process]. To test a hypothesis a scientist must design an experiment and predict the outcomes if the hypothesis is correct. There are always many possible hypotheses that could explain any observation, so an experiment can never prove a hypothesis is the correct one.
Experiments are subject to errors, because our measurements are not exact, sometimes equipment is not working perfectly, and sometimes we do not fully understand how our equipment will work (scientists also make mistakes sometimes when doing experiments!).
Nature is wonderful (literally) and so very complicated. Scientists often try to simplify what they are studying by making models. Models are things [ugh!] that represent part of what we are interested in. Models may be physical (scale models), mathematical (equations), graphical (drawings, graphs, schematics, flow-charts...), or even an analogy (saying how something is like something else). A model is simpler that the real thing [should we use the word phenomena?], but reflects some part of it. The scientist knows the model is not the real thing [phenomenon], but because it is simpler it can help her think about the real thing [phenomenon]. Because the model is simpler than, and different to, the real thing we have to remember that what we learn from the model may not always tell us about the real thing. However, sometimes models can lead to hypotheses that we can test in experiments with the real thing [phenomenon].
It is a matter of judgement when an idea can be called a theory. A theory needs to be able to explain observational evidence, using accepted scientific ideas [concepts?]. Usually a theory explains the results of many observations and/or experiments. To be useful a theory has to make (testable) predictions rather than just explain what is already known (cf.␣Popper, Lakatos). Usually we are not happy [?satisfied] when experimental results don’t fit the predictions of theories, and we look for better theories (different, or just developed).
When there are several theories that explain the same observations, scientists usually try to design experiments to help find which seems to explain the phenomena best. Scientific theories are expected to be consistent (not to contradict themselves), and to be as simple as possible. [A theory that is inconsistent is known to need some development; the requirement for simplification less rigorous — who is to say how simple or complex the world actually is! Occam’s razor is an epistemological preference, but nature may actually be quite hairy!] No matter how much evidence supports a theory, scientists always accept that other experiments/observations may later show the theory needs to be developed or replaced. For a theory to be useful it must be specific enough to provide useful predictions — predictions that could then be tested. [This is a major demarcation criterion for science cf. non-science. (cf. Popper)].
Scientists use logic to relate ideas — to make predictions, to design experiments, to interpret observations. A good scientific explanation will be logical, and will use ideas (concepts and theories) that are well-accepted in science.
What is science — the business of understanding the world/nature by making observations, forming hypothesis, designing and doing experiments, building models and developing theories.
Science is a social process. Some scientists work alone, but most work in research groups or teams, and often different groups share ideas and data to help each other (often in several countries). Even scientists who work alone (e.g. Lovelock?) use the ideas of other scientists in their work, and communicate their ideas to other scientists. Scientists can only build theories using the evidence available to them, and rely upon the science that they have learnt (the concepts and theories that they have been taught about and understand). Sometimes well accepted, but flawed ideas, can prevent scientific progress. No scientists can know the whole of science (which is massive), and even great scientists had have areas of ignorance (and made/make mistakes). Sometimes scientists become strongly attached to certain ideas, and find it hard to be fair in deciding whether the evidence supports their favourite theories. Sometimes scientists let friendship, rivalry, ego (big-headedness?) and even prejudice (e.g. against women — e.g. R. Franklin, L. Meitner) influence their judgement: they are human like the rest of us. Luckily, other scientists will check their work and ideas.
Scientific theories develop over time as more scientists develop new models and experiments. Scientific ideas are taken seriously once they are written-up and published in special publications (magazines?) called research journals. When lots of scientists publish work supporting particular theories, and other scientists are unable to develop experiments that contradict the theories, the theories may become so well accepted that they are almost treated as facts or truth. However, there are many examples of widely accepted theories that were later found to be inadequate when new evidence was found (e.g. phlogiston). Overall, though, science seems to be developing more effective theories and models of the world, and these have been used to produce a great many technological advancements (antibiotics, central heating, dyes for clothing, CD players...).
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Taber, K.S. Towards a Curricular Model of the Nature of Science. Sci & Educ 17, 179–218 (2008). https://doi.org/10.1007/s11191-006-9056-4
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DOI: https://doi.org/10.1007/s11191-006-9056-4