It’s here! My new podcast…
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Every episode transcript will appear here on the blog too. Enjoy!
Episode 001: What’s All This About Then?
Episode Link: What’s All This About Then?
Transcript…
Alan: welcome to How to Teach Computer Science the podcast. This is episode one. What’s this all about then? Well, I’ve had a lot of people say to me, “Alan, your book has been recommended to me and it looks fantastic, but I just don’t have time to read it. Can you make an audio book version?” So I looked into that and it costs a lot of money for little reward. So instead I’m doing this cheap podcast. But before I ramble on, and trust me, there will be rambling for it’s just me today. Nobody to interrupt me or get me back on track. So I hope you can follow me. , as an aside, I saw Ross Noble in concert, the comedian last week, and my wife said, that’s you that is, and I pointed out that’s a line from David Baddiel
[00:01:00] <Crickets chirping>
Alan: anyway, my name is Alan Harrison, and I wrote the books How to Teach Computer Science and How to Learn Computer Science available in all good bookstores and some bad ones. And on Amazon and you can find more details at the companion website to the books httcs.online That’s the initials. of How to Teach Computer Science, httcs.online I’ve got 25 episodes planned
<cheering>
Alan: Which will take us up to the summer holidays. And some fab guests booked in. There will be parables practice and pedagogy and a lot of computer science subject knowledge and jokes, probably and anecdotes and fun stuff like competitions and prize draws, talking of jokes. What’s the problem with jokes about the punchline often comes too early race conditions. <crickets>
That’s a degree level, computer science joke right there. More where that came from you lucky people. If you want to give me feedback, not on my jokes, please. Or get involved, just go to [00:02:00] httcs.online or check the show notes on your podcast player.
I’m also on threads Mastodon and X as mraharrison That’s M R A Harrison, or you can email me at alan AT httcs.online. I’d love to hear what you think about this podcast. And if you want to be a guest, just send me an email. Or a message. And if you like the content, please subscribe and tell your friends and buy my books at httcs.online. Leave a review of my books on Amazon or at the very least buy me a coffee. I have a- tag on my Website and blogs so go to httcs.online and bung me a few quid. Because I’m not getting paid for this.
Okay. So. Every week, I will transcribe this recording as well and blog it at httcs.online/blog. So if you don’t like my voice, you can get your favorite text to speech engine to read out my words., You can even go to Speechify to have my words read by somebody else.
Snoop: [00:03:00] What up dog it’s big snoop d o double g, and I’m an English voice from the United States
Alan: so if you really must have my words, read by Snoop Dogg, go to Speechify.com. So let’s get into today’s podcast then, and let’s start with a fertile question.
Alan: What’s this all about then?
It’s the podcast version of the book, How to teach computer science. This book that I wrote is for new or aspiring computer science teachers, wishing to improve their subject knowledge and gain confidence in the classroom. And it’s for experienced computer science teachers who wish to hone their practice. Especially in the areas of explicit instruction, tackling misconceptions and exploring pedagogical content knowledge. So trainee teachers. And NQTs or ECTs. will find this book, invaluable, experienced teachers will find it inspiring and all would benefit from a fresh look at the hinterland and pedagogy that makes computer science a fascinating subject to teach. So go get the book. If I haven’t mentioned it, I wrote a book.
But [00:04:00] today let’s discuss pedagogy in more detail, a little bit about PCK, pedagogical content knowledge. Educational psychologist, Lee Shulman defined PCK as quote knowledge of the most regularly taught topics in one subject area, the most useful forms of representation of those ideas, the most powerful analogies, illustrations, examples, explanations, and demonstrations end quote. Thank you Mr. Schulman. It’s that intersection of content or subject knowledge and pedagogy. PCK for computer science will be different to that for maths, science, or history, but may share some common features. For example, the pedagogy of fertile questions can be used in any subject.
What are fertile questions? I’m glad you asked. So you may know them as big questions or inquiry questions. Fertile questions are intriguing questions the teaching tries to answer and they help to tie all the lessons in a topic together. As explained by Mark Enser in his TES article, “are you asking fertile questions? If not, you should be” TES.com July, 2020. And I quote this sense of intrigue sparks my pupils natural curiosity. The subject itself becomes engaging rather than an activity designed to hook them. By phrasing each topic as a fertile question to be answered. I’ve been able to think more carefully about the disciplinary knowledge that a geographer, because he’s a geography teacher would need in order to answer it. I find myself asking what propositional and procedural knowledge will they have to bring to the question. Rather than what can I teach to fill up the lessons this half term? That’s Mark Enser in TES.
And William Lau gives us some examples of fertile questions for the architecture chapter in his book, teaching computing in secondary schools copy here. Next to the microphone. And it’s a fab book. Inspired me to write mine. And William says. As an example, the architecture chapter could have a fertile question. How can we design the [00:06:00] fastest computer system in the world? Now you see. Phrasing a series of lessons as the inquiry that will answer that question will give structure to the unit and motivation to find out the answer to that question. Individual lessons within that topic could have fertile questions such as why does my phone get hot? And why does cooling speed it up? Why do my phone and tablet boot in seconds while my desktop takes a minute? Why are some manufacturers computers more expensive than others? Why did chip manufacturers stop increasing clock speeds and instead, add extra cores. Why does magnetic storage still exist if solid state drives are quicker. So those questions can set the tone and the objectives for the lesson.
Once you’ve got your lesson planned around your fertile questions, you can start to explain stuff. And I’m a big fan of explanations. One technique you might use is analogy, always use good analogies. Why? Because a bad analogy is like a, bad analogy. Those of a certain age may remember the comedy series Blackadder, famous for terrible analogies, such as Baldrick. There hasn’t been a war run this badly since Olaf the Hairy, King of all the Vikings, ordered 80,000 battle helmets with the horns on the inside.
Alan: But I digress. I told you there’d be rambling.
Analogies help explain abstract ideas, using a similar idea in a familiar concept. Concrete examples exist in the real world and put the learning in context, connecting new competing ideas to other subjects. Which helps pupils assimilate them into their existing understanding. Analogies can be used as part of a semantic wave. Also described as unplug, unpack repack.
So basically you might describe an algorithm as a sequence of steps to solve a problem. Then slide down the semantic wave to a lower semantic gravity and say algorithms are like a recipe. Then go back up, repacking into the algorithm concept. Semantic waves are [00:08:00] described in an NCCE quick read and the link is in the transcript on my blog at httcs.online/blog.
Other pedagogies, unique to computing include unplugged and physical computing. I have a whole episode of this podcast planned to cover those. So just for now, park your physical computing enthusiasm on the stack, and I’ll pop it off in a few weeks.
Misconceptions can seriously hinder learner’s progress. I love a good misconception me like assignment statements make two arguments equal, always, like in mathematical equations or peer to peer networks require a mesh topology. Studies have shown that teachers who are aware of common misconceptions and actively seek to address them. are more effective. That’s Sadler et al 2013.
So. You’ve got your misconceptions. You’ve got your pedagogies. What makes a good lesson? And I think we really need to beef up our explanations. I pride myself on my explanations. So I wrote the book to help you explain things better. My books clear descriptions of each topic and deep exploration of the hinterland should enable teachers to explain topics in great depth suitable for a direct instruction approach to teaching.
Now I wasn’t always a fan of direct instruction. I was very much a progressive teacher at the start of my career. And I thought inquiry learning was wonderful, and constructivism and Constructionism. That’s Papert and everything, but there’s a limit to how much time we can give them to discover things. They’re not really discovering. They’re just finding out stuff that we already know. They’re not small adults they’re children. True discovery. comes after you’ve learned all of the substantive knowledge that’s already out there to learn.
And then, you know how to perform the discipline, of computer science in our case, and then go out and discover new things. So discovery learning is a little overplayed. I think children can’t discover new facts like scientists until they’ve got that body of knowledge, so limit your inquiry learning and don’t get me started on Googling. Googling is not inquiry learning and inquiry learning is. Not always the best way to get new facts across. So. Hone your explanations and tell the pupils most of the stuff they need to know and let them practice using that knowledge in a practical way, applying that knowledge in the classroom.
I’m a big fan of pedagogical approaches such as talk 4 writing from Pie Corbett, children internalize the key terms and language structures needed to write knowledgeably about the subject when teachers talk the text confidently and model their thought processes, and explicitly teach the specialist language of the subject.
So. That’s what I try to do. I’ve always prided myself on my clear explanations and it’s made a great difference to my teaching. For example, I might say a protocol is the rules for communicating across a network. But I might follow up with the word protocol in several other [00:11:00] sentences, such as, two computers communicate using the same protocol. And without a protocol to describe the rules, two computers cannot communicate. These multiple examples help illuminate the key tier three vocabulary so the pupils can grasp and use it themselves.
that music means it’s competition time. So you can win a free copy of one of my books, how to teach computer science or how to learn computer science. Just for promoting this podcast. You’ll find a post from me promoting the show on Threads, Mastodon, LinkedIn and X. Please like and reshare that post to spread the word and I will choose one listener on each platform who has done so to receive a free book. The podcast is available on all major platforms and on the web at, pod.HTTCS.online.
Okay. Back to the serious stuff now. We’re talking about direct instruction. I used direct instruction and other techniques described in the book as part of a wider strategy of research informed teaching. I use an approach that follows Rosenshine’s principles of instruction. First published in 2012 and explained by Tom Sherrington in his book, Rosen shines principles in action, which I strongly recommend link on my blog at httcs.online. So much of the PCK advice in my book is aimed at increasing what teach like a champion author, Doug Lemov calls the ratios. The ratios are explained in a blog by Adam boxer. And I recommend his blog and he’s now got a podcast called they behave for me with Amy Forester, which is a great listen and inspired me to do this. So, what are the ratios? Well, There’s participation ratio. How many of your students are participating and how often? And the think ratio: when they are participating, how hard are they thinking? Increasing these ratios is important because memory is the residue of thought as Daniel Willingham explained in his excellent book why don’t students like school? That book changed my teaching practice entirely, it was my first introduction to cognitive load theory and the impact it has in the classroom.
Cognitive load theory is important for inclusion as well. You can only hold so many new things in your head at once while you’re thinking about them. Pupils who find learning more difficult will have perhaps a smaller working memory. So it’s even more important to make sure you understand cLT and working memory and adapt your lessons accordingly. adopting some or all of the PCK techniques in my book would inherently make your classroom more inclusive. The activities suggested have a low floor [00:14:00] wide walls and a high ceiling, a phrase coined by Seymour Papert that guided the development of scratch at MIT. So reducing cognitive load can support send learners as Catherine Elliott explains in her discussion of PRIMM in Hello World 12.
I’m going to talk about PRIMM in a later podcast. But as Catherine explains, a young person with SEND or special educational needs or disabilities can thus learn about the same computer science concepts as their peers, without the fear of failure or the demand on working memory and recall that writing a program from first principles involves.
So think about your programming pedagogy, things like PRIMM, Parsons problems and pair programming, all the P’s, they reduce cognitive load and I’ll be talking about them. In a later podcast, but they improve inclusion in the classroom. And I’ve got some tips in the book from Beverley Clarke. And she says, in HelloWorld 11, equitable computing would mean experiences that are high quality in terms of pedagogy and robust in terms of nature and scope of learning goals. Taking students beyond the curriculum. Unplugged activities, physical computing and project work offer multiple means of engagement, representation, action, and expression recommended in the universal design for learning, UDL framework. Which was discussed in Hello world 15. Hello world, of course, is a magazine published by the raspberry PI foundation. And it’s available for free PDF download. And if you are a teacher, you can subscribe to the print version and have it drop on your doormat.
Talking of wide walls and a high ceiling as we were, I wrote a blog recently called On banning ‘I’ve finished!’. And why did I do that? Well, surely you want pupils to finish their work in lesson time. And if they finish early, what’s the harm if they find something less stressful to do like going online to play chess with their mates as a teacher on Twitter told me recently that her pupils do when they’re finished. They were really into their chess games, online with peers. Oh they did do that. And she got cross when the IT technicians blocked Chess.com. So she then said, well, just go on YouTube when you’re finished your work.
Well, allowing free time at the end of the lesson, encourages poor performance. Many pupils rush the work to get it done in plenty of time to play games or watch videos. In my early career, I often responded positively to the plea, Sir, if we get finished early, can we go on cool math games? But I learned that dangling that carrot of free time just ensured poor concentration. A tendency to fill boxes on worksheets with the bare minimum and importantly ensured a poor ratio. Remember, that’s the proportion of pupil minutes, thinking hard about the topic instead of other things. Learning is its own reward in my classroom, isn’t that right, class?
Sir, yes, sir!
why would I deprive them of enjoyable learning about our wonderful subject? Why would I suggest that playing games is somehow more desirable than building logic, circuits or learning to code? Why would I do that? So I have a poster on my classroom wall you can see on my blog and it says. ask your self, is this my best work? Am I proud of this and then goes on to list some of the things that I expect my pupils to do when they think they’ve finished and they’ve checked that it’s their best work. So at key stage four, they could use Quizlet, Seneca, or smart revise from Craig and Dave, which is an absolute game changer. More on that story on my blog at the usual place. httcs.online/blog.
I want to talk about an [00:18:00] important topic, gender balance. And there’s now a whole wealth of information available from the NCCE under the I belong banner. So go and have a look at that. But the tips in the book were From CAS originally, which were: Tip 1: women can change the world, right throughout key stage three, make links to the big picture and real-world computing roles, which have an ethical remit. For example, designing assistive technologies to enable people to overcome a disability or highlight technology’s role in medicine, humanitarian work, science, fashion, communications, art, journalism, or sport.
Another tip would be to encourage and praise, and show that praise addresses all aspects of learning computing, including creative solutions, planning, and conceptual understanding as well as technical knowledge and skills. So make sure you’re praising the effort, the progress. You don’t just judge your pupils by, have they finished a program that works. Because all of the stages are important and encouraging resilience, particularly among young people who don’t believe they belong in that classroom is really, really important.
So. There’s an old adage about tech bros that people think Silicon valley is trying to make the world a better place, but really they’re always just trying to make better technology. And this could really change if we get more women into technology.
I’m going to start closing out this podcast now, not before another joke. I was asked, can you write a joke about abstraction? And I thought about it. And I thought, yeah, I can do that. Here’s a joke about abstraction setup(), setup(), setup() punch line().
So why did I write the book? That we’re talking about, how to teach computer science. Well, The germ of an idea for the book was planted by a blog called signposting the hinterland in which Tom Sherrington him again, explains that curriculum can be divided into core and [00:20:00] hinterland where the hinterland is as important as the core and serves the purpose of increasing depth niche details about a particular area of study that deepen, enrich the core and increasing breadth. wider surveys across the domain of any curriculum area that helps to locate any specific core element within a wider frame. Sherrington quotes from an earlier blog by Christine Counsell, which said the core is like a residue. The things that stay, the things that can be captured as proposition often such things need to be committed to memory.
But if in certain subjects for the purposes of teaching, We reduce it to those propositions. We may make it harder to teach and at worst we kill it. What are they saying there well, If you just teach. Sequence selection and iteration. But you don’t understand programming if you just teach the FOR loop syntax., but you don’t understand what a count controlled loop is and if you haven’t got a real grasp of what the low level instructions would do when you compile a for loop. If you’ve got a good grasp of that, then you can really teach FOR loops or iteration or programming much better. So don’t neglect the hinterland.
If you read my book, you will get much more sound grasp of the subject and then you will be able to teach it well. So the original aim of the book was to assist computer science teachers in sharing some of that hinterland with their students to enrich their studies and cement core knowledge in a wider context. .
And so I wrote the book because I don’t think the hinterland and the pedagogy of our subject is well appreciated in the classroom practitioner community. By teachers basically. So I decided to enhance the book, not just with hinterland, but insight into research, making the concepts accessible to teachers with concrete, practical [00:22:00] ideas. That’s why.
So. Go and buy the book. If you’ve bought it, please give me a review on Amazon. I have a learn book out as well, which is aimed at pupils so you could buy class sets for your classroom. And if you email me, alan AT httcs.online. I might give you a discount for a class set they’re literally dirt cheap, because I said to the publisher, I want these books to be really affordable by the classroom teacher it’s my sort of gift. If you like to. Computing teaching community, which really is under appreciated. So the. How to teach computer science book is priced at 15 pounds and is cheaper than that on Amazon. And the learn book is 12 pounds, but if you email me and you want a class set, I can get a discount off that. And you can give them to your learners.
[00:23:00] this has been how to teach computer science. The podcast. And. I hope we’ve answered the fertile question. What’s this all about then? So remember the competition, share the love, share the podcast. Next week I will be attempting. The GCSE specification in 30 minutes, I will talk through the entire content of a typical computer science GCSE in 30 minutes or less.
And I may have some more strange and interesting jokes about computer science. I’m Alan Harrison. I’m on threads Mastodon and X as mraharrison And if you wondering why I’m making that buzzer sound. When I say X , just go and read my blog I’ve quit X and you should too. So thanks for having me today. [00:24:00]
This has been how to teach computer science, the podcast. Please share the love and I’ll speak to you next week.
How to Teach Computer Science 