Fighting genericism and putting knowledge first: The nature of school science

What is the nature of school science? I ask this because I think we should know the nature of a subject before we design our teaching and models of assessment. I believe a subject is more than the sum of its parts, that it has a character, texture, structure, shape. If we wish to use the findings of cognitive science to help our pupils to learn better, then we need to understand this character. Any model of progress and assessment must not conflict with the nature of the subject. If we can identify similarities in character with other subjects, then we can see where we can fruitfully borrow from them. Where we find differences we can guard against the foisting of unhelpful techniques and models from other subjects, or inappropriate “genericism”.

I’m leaving aside “scientific enquiry” for the time being and focusing on “content”, for want of a better word. This is because cognitive science tells us that you need to know stuff before you can enquire about it. Also I feel there has been quite a lot of theorising about the nature of scientific enquiry but rather less about content, and this needs redressing. 

I’ve identified five characteristics of school science and some possible implications stemming from them. In future posts I hope to consider what cognitive science can offer us in relation to these aspects of the nature of school science, what we can learn from other subjects, and what we as science teachers can practically do in light of these considerations.

 1. School science is factual

Most of the knowledge in school science is describing, explaining, predicting, and calculating. It relates to the natural world rather than the actions of humans or the products of our minds. 

Implications: 

  • Bloom’s is the enemy! But we knew that already. Helpful to have a clear argument against it though. 
  • Find out if cognitive science can tell us how best to teach this sort of knowledge. 

2. School science is visual

There are a lot of visual elements to school science, often in relation to its abstract explanations of phenomena. I’ve come to realise this ubiquity and value while creating knowledge-first textbooks for physics. When scripting explanations I’ve spent as much time making the perfect diagram as I have writing explanations. I feel this is an important area that I have overlooked in the past and perhaps applies less in many other subjects.

Implications:

  • Look at how maths, design and technology, and art use and teach visual material. I suspect we may need to be critical about borrowing here, as none of these subjects use visuals to represent abstract phenomena in the way science does.
  • When planning curriculum and lessons, consider visuals as a priority.
  • Consider what software we can use to make visuals.
  • From cognitive science, find out the best ways to a) design and b) present visuals. Oliver Caviglioli springs to mind, plus I read a thing once that said it’s better to draw the visual in real time in front of the pupils… I need to do some reading!

 

 3. School science is cumulative AND hierarchical

I’ve been interested to read about cumulative versus hierarchical subjects in conversations on Twitter. I would argue that science is a bit of both. There are many different areas to be learned, for example photosynthesis, bonding, and momentum. Within each area is something of a hierarchy of difficulty of content, usually with a necessary route through from easiest to hardest. For example, below is a series of questions on momentum taken from the new AQA trilogy specimen paper:


 I would argue that these roughly ascend in difficulty, not because of the style of question or task, but the difficulty of the scientific understanding needed to answer them.

Implications:

  • Bear in mind the hierarchical and cumulative models when looking at curriculum design, lesson plans and questions
  • Look at threshold concepts – what they are and how best to teach them
  • Maybe look at maths and languages for how they develop hierarchy, and geography and history for how they build cumulative knowledge?
  •  

4. School science has short, right-or-wrong answers 

I think an important way to find the nature of a subject is to look at the way it tests its learners. I’m not advocating using exam papers as the starting point for lessons, and heaven knows individual exam boards and assessment systems have their faults, but I think patterns in assessment globally and historically can give us valuable insight into the nature of a subject. Science, for example, is never assessed through an essay, but through many questions with short and medium-length answers. Daisy Christodoulou describes this as the difficulty model versus the quality model. I feel this is a useful distinction, and that it highlights an important aspect of the nature of school science: there are only ever a very finite number of correct answers to the sort of questions science can ask, and there are a lot of short answers that pupils need to know or be able to work out.

Implications:

  • Look at maths for feedback and practice on these sorts of questions and answers.
  • Do any other subjects have a lot of questions with a small number of right-or-wrong answers? Maths questions are to do with processes, and we also have description- and explanation-type questions in science…maybe geography or technology? Find out and see if there’s anything we can learn!
  • Think about different types of question. One area I want to look at is the different ways questions can be difficult. I have a sense that they can be difficult because remembering the facts needed is hard, or because the explanation is hard to understand, or because recognising the application of a concept in a new situation is hard, or because there are many elements that need considering at once… Look at cognitive load theory and element interactivity, hopefully some other research as well.
  • Be vigilant against the blithe importation of ideas from other subjects, for example “success criteria” which are designed for a quality model such as a design or essay.

 

 

5. School science is schematic

When I think about schemata, I imagine being inside my mind and looking up to see a big domed frame, like being in a geodesic tent.It’s made of lots of different pieces of wood joined together, but forms a single unitary structure. It’s dark under this frame, but I can find my way around it because of the way the pieces of wood are arranged. When I learn a new piece of related knowledge I can reach up and hang it on the frame like a coathanger. When I encounter a situation where I need to apply some knowledge from the schema, I can reach up and follow the wood along with my hand until I reach the bit I need.Schemata are very important in school science. Most of the knowledge required fits into one schema or another, and so if the schema is well constructed then retrieval will be more successful. Many questions, and many of the most difficult ones, require pupils not only to apply what they know to new situations but also to recognise that the situation is an example of the knowledge they already have. Consider the example below, again from AQA Trilogy:

As schemata are a fundamental cognitive aspect of learning, I imagine they are important in all school subjects. I would suggest a couple of features of science schemata that distinguish them from others: they often contain counter-intuitive elements; and they often rely heavily on abstract theories that require visualisation and imagination.I feel that a strong schema allows pupils to recognise the relevance of a theory to a new situation, and to become intuitive in applying it.

Implications:

  • Consider schemata in curriculum design, lesson planning and questions
  • Look at how threshold concepts relate to schemata, identify them, and consider how we can best teach them
  • I can’t really think of a school subject where schemata function in the same way as in science… I’m thinking philosophy or perhaps RE in that there are fundamental principles with explanatory power, observable phenomena or familiar examples with unobservable explanations?
  • Think about how we can nurture an intuitive sense of science’s schemata in order to overcome the counter-intuitive elements and encourage application in new situations… look at the work of Michael Polanyi, Thomas Kuhn and Greg Jacobs.
  • I think it is here that demonstrations and practical experience are most relevant – read and think about this.

 

I hope that this list will allow me to make some informed decisions about what we can do to best help our pupils. I feel I’m still groping around under my own, partially-built schema-tent a bit in this, so I’d be especially grateful for any thoughts in the comments section. Thanks!

 

References:

Greg Ashman on difficulty and element interactivity: https://gregashman.wordpress.com/2017/01/

 

AQA Trilogy Science paper 6 specimen: http://filestore.aqa.org.uk/resources/science/AQA-84646P2H-SQP.PDF

 

Niki Kaiser on threshold concepts: https://ndhsblogspot.wordpress.com/2016/12/21/threshold-concepts-4-confidence-and-retrieval/

 

Christine Counsell also on the need for subject-specific considerations: https://thedignityofthethingblog.wordpress.com/

 

Daisy Christodoulou on difficulty versus quality model:

Christodoulou, D. (2016), Making Good Progress?, Oxford, Oxford University Press, p64.

Harry Fletcher-Wood on schemata: https://improvingteaching.co.uk/2017/02/12/why-formative-assessment-matters-the-power-of-prior-knowledge/

 

Michael Fordham made me think about the need to think about our own subjects and how they are different to others: https://clioetcetera.com/2016/06/18/genericism-and-the-crisis-of-curriculum/

 

Thanks also to @bennewmark for helping me think about history, I’ll be returning to this when I write in more detail about science schemata.

 

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5 thoughts on “Fighting genericism and putting knowledge first: The nature of school science

Add yours

  1. Great piece as always. I think the link you were looking for about drawing diagrams in real time is here http://www.learningscientists.org/blog/2017/1/24-1

    Also re point 2:I’m not sure I’m fully sold on the word “visual” you have gone with. I don’t think dual coding is unique to science in terms of helping memory+understanding, but I think the amount of “modelling” and “analogy” certainly is. There are many areas of many other subjects where the content to be understood is quite so abstract, our students cannot really touch and feel the worlds which we are exposing them to (sure sure, But practicals! you know my feelings on that though). So we use models and analogies and sometimes out right anthropopathisms (how many times have I said atoms “want” to have full outer shells?).

    So I think what you refer to as “visual” insofar as it is ” often in relation to its abstract explanations of phenomena” is putting the cart before the horse – the abstract, unobservable concept that explains the observable is the root of the matter. The “visuals,” models, analogies or diagrams are merely ways to convey that concept.

    1. I agree models, analogies, and anthropomorphisms are a key feature, so perhaps we should have a sixth characteristic such as “school science is abstract “. I think I’m going to treat it as part of the schematic section though, at least to start with, as I have an intuitive feeling that abstract theory is the supporting structure in science schemata- I may well change my mind though after further thought!
      I think “visual” may not deserve status equal to the other characteristics, but I do feel it deserves more status than has previously been accorded. Yes it is important for explicating abstract ideas as you say, but there are also many heuristic visuals we use to answer questions. For example, dot and cross diagrams, refraction diagrams, free-body diagrams, vectors… I think this is fairly unique to science. Also there are descriptive visuals such as leaf structure, and the graphs such as rate of reaction and distance-time. I’ve realised that neither I nor any textbook or scheme of work I’ve ever come across have given pupils sufficient practice with these visuals, a problem compounded, I believe, by the focus on “questioning” in the classroom as a verbal practice rather than “on-the-page”. I’m also interested in the role some visuals play as “exemplars” in schemata, both models and heuristics, which I think may be more significant in science than other subjects…lots to think about!

  2. I also think that the concept of “misconception” which you’ve put in with your section on “schema” to be really important. Geary’s biologically primary/secondary gig explains where they come from, but how do we actually go about unravelling them? On my PGCE I read a lot of constructivist stuff about this but I wonder if there is any decent CogSci based material on this.

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