We all want our students to be financially
literate, don't we? So you might think we should simply add
financial literacy to the curriculum. Alas, even ignoring the question of what to squeeze out to make room for it, it's really not clear what to do here. Following the 2008 financial crisis, unlike some educational systems, Shanghai schools did not add this to the
curriculum but its students nevertheless achieved the best financial literacy
scores in the subsequent PISA round - without any teaching. So what’s
going on?
This example highlights a huge question we
face today - what should students learn? It might surprise non-educators to know that this is even a debate - but once you get beyond the basics, it turns out that there is no definitive answer, as we have to draw not just on conceptions about what’s
worth knowing, but also speculate on what the future will bring, and ultimately,
about what is valuable in education and about what is worth pursuing in life in general. These are profound questions that schools rarely ask, but that all schools answer even if only implicitly; you can look at a school’s curriculum to deduce what the school values.
One argument is that schools need to adapt to
the changing world of work and teach what’s needed for the future. It’s hard to argue with the notion that
school has to be for something, and
not just a passing bubble in students' lives; but that said, what we know about
predicting the future is that is is extremely difficult, and that the history of predictions gives us little reason for confidence.
The archetypal modern course of coding is a good case study. It might look like the new UK National Centre for Computing’s aim to train 8,000 new teachers addresses the future needs of industry (and indeed perhaps it will). On the other hand Andreas Schleicher, director of education and skills at the OECD has recently gone on record saying that coding is merely “a technique of our times” and will become irrelevant in the future. So should we teach coding?
The archetypal modern course of coding is a good case study. It might look like the new UK National Centre for Computing’s aim to train 8,000 new teachers addresses the future needs of industry (and indeed perhaps it will). On the other hand Andreas Schleicher, director of education and skills at the OECD has recently gone on record saying that coding is merely “a technique of our times” and will become irrelevant in the future. So should we teach coding?
The answer is it depends on how you do it. We can teach coding as a
self-contained technique that requires a lot of knowledge of coding grammar; or we can teach it as a means to achieve a
deep understanding of algorithmic thinking. So are looking for knowledge or understanding? Schleicher answers it himself - the trick is to teach fewer things in
greater depth. And by depth, he
means a focus on understanding, not just knowing. That may sound like an idle distinction, but
it is actually central to what schools need to be thinking about.
The difference between knowing and
understanding explains why the Shanghai students scored well, despite not
‘knowing’ much about financial literacy.
They had a deep mathematical understanding of probability, change and
risk, and so could apply this understanding intelligently to new situations – more
intelligently, in fact, than those students who simply knew about those situations. So you could say that the best way of teaching financial literacy is not to teach it at all! More seriously and precisely - the best way to teach financial literacy is to teach a deep understanding of certain underlying principles, which are much broader than just financial literacy, but which can be applied in that field very successfully.
The difference between knowing and
understanding also explains Schleicher’s rather shocking claim that coding
is a waste of time. What I take him to
mean there is that coding is a waste of time if it is just about the details of
computer language rules, rather than about computational thinking. But if coding is used as a concrete tool to teach computational thinking,
then it may have great value, even if the details of the particular coding language prove to be irrelevant in future years.
This knowledge / understanding distinction applies
right across the curriculum. Here are
some more examples.

This distinction between knowledge and understanding has many interesting applications.
For example, it explains to me the sentiment
behind the popular but mistaken meme of you
don't need to know anything these days as you can just Google it. This notion misses is the crucial point that
the best routes to understanding usually involve processing knowledge,
interrogating knowledge, transforming knowledge from one form to another, questioning knowledge and so on. So there is no escape from needing knowledge, even if that's not the goal (just as a top sprinter cannot escape from good diet, even though nutrition is not the goal).
A further interesting application is that often, teachers can ask students to write their own understandings at the end of a unit or lesson. It's an alternative to the more traditional practice of a teacher specifying learning outcomes to students at the start of the lesson; it is a wonderful way of getting students to (a) review the unit (b) abstract the really important things from the unit (c) deepen their thinking by putting ideas in their own words (d) develop agency in constructing their own meaning. Here are some examples - all these student-written conceptual understandings were written by my current grade 11 (DP1) class. You can see such rich thinking from students, and while there are a few understandings that need sharpening, having the lists provides me with exactly the information I need as a teacher to know how to help them with their next steps as we progress through the course.
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This may all sound rather esoteric, but in
truth, the notion of conceptual understanding based on knowledge is literally
child’s play. A toddler, after knowing the taste of peas and broccoli, may
reject spinach. The (admittedly flawed) understanding that green things taste bad comes all too readily! Similarly, the
notion that good will triumph over evil
quickly emerges from watching a few kids’ movies. Spotting number patterns, students naturally speculate, generalise and understand that an odd number plus an odd number gives an even number. Even grammar errors from youngsters such as he holded it and broked it and then he runned away! show an innate capacity to study instances of deriving the past tense from the present tense by following a generalisation (adding -ed)
As Stern et al write we naturally move between factual instances and the conceptual rules and patterns that make up the logic of our world. Young children do it all the time, and we we are seeking to make the most of this natural habit to support deep, powerful learning for all students, regardless of age. As long as we have got the right end goal of rich conceptual understandings in the area of computational thinking, surely there is a place for coding as a means to reach it.
As Stern et al write we naturally move between factual instances and the conceptual rules and patterns that make up the logic of our world. Young children do it all the time, and we we are seeking to make the most of this natural habit to support deep, powerful learning for all students, regardless of age. As long as we have got the right end goal of rich conceptual understandings in the area of computational thinking, surely there is a place for coding as a means to reach it.
References
Stern J, Ferraro, K and Monkhern J (2017)
Tools for Teaching Conceptual Understandings. Corwin Press.
An interesting read Nick and I must say that much of your thinking is aligned to what I have been exploring in this area. Media, parents and many educators have very muddled understandings of what 'coding' actually means.
ReplyDeleteAre we talking about typing lines of code with correct syntax, using visual blocks to represent concepts or learning about the underlying concepts? Computational Thinking or as you mention algorithmic thinking is more valid way to describe this emergent curriculum area, with actual coding being just one way of practicing and illustrating your understanding. Perhaps the most effective teaching I have seen in this area are non-digital activities where students use symbols, manipulatives or games to learn about underlying concepts e.g. conditional loops or if statements. Hopefully this kind of learning endures as technology continues to evolve and change.