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Computational Thinking as Metacognition

Metacognition and computational thinking 

Children do not easily see connections between the school subjects that they learn. Nearly everything can been viewed from an interdisciplinary perspective but in secondary schools knowledge is organised and delivered and partitioned into the subjects that we are familiar with: “Maths teachers teach maths, English teachers teach English, science teachers teach science and never the twain shall meet1. When complex knowledge and understanding is partitioned neatly into silos like this, it is little wonder that children cannot relate learning from one subject to another. Of course, knowledge and understanding are highly interrelated and getting children to see these complex connections will enrich their learning experience.

Metacognitive strategies that can be applied across the curriculum can help to break some of these artificial barriers that children see between subjects. Metacognition is concerned with “learning about learning”. Equipping students with a metacognitive toolbox has a high impact on student learning according to the Education Endowment Foundation2.  We know that a range of metacognitive strategies are already being used across the curriculum, but students and indeed teachers may not be aware that they are using them.  For instance, techniques using mnemonics to remember words and sequences, study and revision skills using flash cards and using point, evidence and explain to structure prose is modelled and used across multiple subjects and children will know how to apply these strategies in a range of different contexts.

Pupils need to learn about computing at KS4 as part of the national curriculum. We are mindful of developing a curriculum that is relevant to all pupils regardless of whether they are studying GCSE computer science, creative media or another IT qualification. We propose to equip pupils with computational thinking3 which is a specific metacognitive strategy that can also be applied across multiple subjects not only in computing.  Broadly, this includes abstraction, decomposition, sequencing and recognising patterns and generalisation. Many teachers across all subjects will be using these approaches whether they are aware of them or not. Let us have a look at each one of these in turn.

Abstraction

Abstraction is the removal superfluous detail from a problem.  In geography maps are abstractions containing only the relevant information for a particular purpose. Ordnance survey maps contain landmarks to help with navigation. On the other hand, developers might want maps on soil types, geology and land ownership.   In art, abstract cubism is about the representation of art in the simplest ways, using primitive shapes and colours.  In maths, abstraction is involved when pupils convert word problems into equations that can be solved.  In English and humanities subjects children might take notes in a piece of prose or film only noting the information that is relevant for their purposes.

Decomposition

Decomposition is the breaking down of complex problems into small more manageable problems.  Any project that has multiple components will fall under this category with the need to break the problem into analysing, design, implementation and evaluation.

Sequencing

Anywhere where students follow a sequence of instructions to solve some problem constitutes an algorithm. In food technology following a recipe accurately is important so the outcome is always delicious! In science the idea of reproducibility is a fundamental tenet of experimentation and this can only be achieved if experimental instructions are followed precisely.

Pattern recognition and generalisation

Humans are naturally very good a seeking out patterns and in fact we are so good we even make generalisations where there are none!4  In maths we can use patterns to help us to learn the times table. This is why the 2, 5 and 10 times tables which have a nice pattern are easier to learn that the 3, 7 and 8 times tables which do not.   In music there are patterns and repetitions in chord sequences and repetition of bars.  In French there is a general form for the past participle for verbs which makes things easier.  But also there are exceptions which you just need to learn and this makes them harder.

No doubt all teachers are modelling these strategies, but these approaches do need signposting so that we can facilitate those connections between computing and these subjects.  Ultimately these are only small tweaks that teachers need to make which is important given already exacting demands on teachers. In the long run this will facilitate learning in all subjects by leveraging the learning that is taking place in computing so that it can support learning in other subjects.  And if we can do this with all metacognitive strategies across all subjects imagine how powerful that could be.

Delivery of this school wide initiative will require teacher and student awareness.  Teacher awareness will come through school wide teacher training during September 2021. Posters will be placed around the school as a reminder of different examples of computational thinking.  Lesson observations and learning walks will also focus on metacognition and computational thinking strategies.

For student awareness we will make use of the October 2021 collapse days to train up the entire cohort of all 300 year 10 students with computational thinking strategies.  We will begin by explaining the different computational thinking strategies and get them to complete puzzles that make use of these skills.  Pupils with then apply their skills to problems from other areas of the curriculum.  These sessions will be delivered by 4 specialist computing teachers.  We will have staff and student surveys and lesson observations to look for evidence of impact. But ultimately, we will know if this strategy is effective when students start to apply metacognitive strategies independently.

References

1.      Ramirez, A. 2013, Smashing Silos!, Edutopia https://www.edutopia.org/blog/smashing-silos-ainissa-ramirez (last accessed 18/6/2021)

2.    Metacognition and self regulated learning Guidance Report, Education Endowment Foundation https://educationendowmentfoundation.org.uk/public/files/Publications/Metacognition/EEF_Metacognition_and_self-regulated_learning.pdf (last accessed 18/6/2021)

3.    Wing, JM. 2006, Computational Thinking, Communications of the ACM, https://www.csd.uoc.gr/~hy108/downloads/compthinking.pdf (last accessed 18/6/2021)

4.     Kahneman, D, 2012, Thinking Fast and Slow, Penguin

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