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What does ecology have to do with digital making?

• Raspberry Pi Foundation • Season 3 • Episode 6

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In our final episode for this season we ask the question "What does ecology have to do with digital making?". Are there parallels between ecology and computing systems, and how do we use the latter to help us understand, measure, and protect our natural environment?

Full show notes:
https://helloworld.raspberrypi.org/articles/what-does-ecology-have-to-do-with-digital-making

Dr. Pen Holland:

I saw something on day where someone was saying. Oh, well another day has passed without me using Pythagoras in my daily life. So if you want to be an ecologist care about triangles.

Dr. Sarah Wyse:

So you need to programming. If you want to be doing cool stuff in science.

James Robinson:

Welcome to Hello for educators, interested in Computing and digital making. I'm James Robinson, a content creator for the Raspberry Pi Foundation, specialising in Computing Pedagogy.

Sway Grantham:

And I'm Sway involved with content creation at the Raspberry Pi Foundation. And my passion is working with children under the age of 11 to show everyone else the amazing things that that age group can do with Computing. If you want to support our show, then please subscribe whenever you download a podcast and leave us a five-star review.

James Robinson:

Today, we're ecology have to do with digital making? How can Computing help us better understand the natural world and conversely, how can we learn more about Computing through its application in nature. Our Learners are surrounded by both nature and Computing. But how can they be combined? Let's start with you Sway. What are your thoughts? What's the relationship between Computing and nature.

Sway Grantham:

In primary, so the under 11 age group. We have lots of opportunities to get outside and because we have the children all day, we can dodge the beautiful UK weather that we often have to endure, but it makes sense that we can take some of those Computing lessons outside. And we have the ability to be able to do that a lot more easy than with some of the older Learners, where you've got a smaller time window. Technology outdoors, is something that I really enjoy doing and often it's something that scares teachers a little bit because we've got expensive equipment. I have to say it's never gone wrong and nothing's ever exploded whilst I was outside. So there's a little safety disclaimer for you, if you're sensible, it's perfectly doable. A few years ago. I was involved in a technology outdoors project. We worked. We went out to a forest school and we were looking at capturing the seasons and recognising what a season looked like and finding leaves and different parts of nature, that would show us what season we were in. And we collected those and we created digital artifacts that would allow us to show and present and share with other people what this looked like. This Season looked like for us and we then had the opportunity of going back out in the different seasons throughout the school year to be able to create and update that artifact to show an example, as we worked our way through. That was really exciting for the Learners, we were able to bring in a lot of different subject areas and we were able to take that Computing outside. Another thing that I find is really important is often young learners have this Association that you can only learn at a desk in a classroom and that's where learning happens. That's what school is for. I like to show them that actually learning is everywhere. Everyone can do it, it's not tied to an age group. It's not cha... tied to a location. So I think the more opportunities we have to take Learners away from their desks or outside of the traditional classroom environment, the more opportunities we have to show them that learning can be fun and exciting but can also happen in lots of different places. And that's one of the reasons I really like going outside with nature and showing them how much we can get from our environment. I'm not sure how closely that I would say that outdoor experiences are to ecology or the subject of becomes ecology as you get older, but I definitely enjoy that opportunity and to get out into your local environment. Whatever that local environment is and I think sometimes we imagine like when we talk about nature. We need a forest or we need Rolling Hills, but actually your environment is whatever is outside your school wherever your school is.

James Robinson:

You're right. I me of an early episode of the podcast we recorded with Alasdair Davies. He was, we talked about two different settings. You know taking photographs using technology in the wilds of Antarctica versus using the same kind of principles and Technology to observe hedgehogs in your back garden, and I think, you know, that, that that importance of understanding that the environment is both, you know, something that can be remote and far away and difficult to observe, but also very local and immediate. And Technology can be a great tool for helping us, observe and record in those locations. We're clearly quite passionate about Computing and ecology, but perhaps not the experts we need to do this topic Justice. Our first guest is Dr. Pen Holland. She's a quantitative ecologist, senior lecturer and Raspberry Pi Certified Educator. Based in the department of biology at the University of York, she's keen on teaching and disseminating research and engaging people in the biosciences. So Pen, Why is ecology a good fit for computing?

Dr. Pen Holland:

Well, for me about connections and interactions and nature is a complex system, that's doing incredible things and as scientists and humans, we're all trying to understand how nature happens. How ecology happens. As a series of small events and associations l ike, how do my seeds grow differently? If they've got different amounts of water or nitrogen? Why does temperature have that effect on crop growth? Computing is about putting together simple instructions, like, follow these steps. Repeat those steps right down to zeros and ones. If you want to go down to the bottom, so we're using simple instructions to build up complex behaviour that can do incredible things like the internet, or keeping people alive on the International Space Station. So nature, and Computing, are kind of two sides of the same coin. We can use Computing to understand nature. It makes perfect sense because it forces us to think about how the small bits of the puzzle interact to produce the world and it gives us a mechanism to monitor and analyse and predict what is going to happen? Very efficiently.

James Robinson:

That's a really I was actually just listening and whether this makes it in the podcast or not. I was just listening to June this morning on my way in. And I'm at the bit where the ecologist is. He's having a sort of had a dream or a or a, you know, a moment where his father is speaking to him from beyond the grave and he's describing the Ecology of the planet and the interaction of systems. So it's quite a timely kind of little bit of listening, but I think that's a really nice parallel that those systems built from simple elements that combine to form complex systems.

Sway Grantham:

So our second Sarah Wyse, who is a lecturer in Forest ecology in the University of Canterbury, New Zealand, whose research focuses on understanding Forest ecology and plant regeneration. I wonder if you could tell us a bit about like what problem or question, your research has been seeking answers to and how Computing has been important in helping you get some of those answers or future projects you're going to utilise.

Dr. Sarah Wyse:

Okay, so our our here is is focused on seed dispersal and understanding how far seeds are likely to travel from different species. Our particular interest is on is on Wilding Pines, which in New Zealand and around the southern hemisphere, are a big problem. These are species that we've brought into New Zealand, Australia, South Africa, Chile, Argentina. For the purposes of Forestry for amenity plantings for shelter belts and wind breaks and things but they don't want to stay where we've put them and they're and they're escaping. And we to understand the invasion of these plants. We need to be able to model where those seeds where their seeds are likely to travel to figure out how they're going to be marching across the landscape. So in order to model the seed dispersal, we first we need to understand the seeds themselves principally one one particular characteristic of the seeds, which is how fast or slow the seeds fall, when they're released from the tree and a seed that Falls slowly is a seed that's going to be in the air for a longer period of time that the wind will be blowing it further and it's going to travel a longer distance. So to be able to model seed dispersal and therefore the movement of these plants through the landscape. We need to be able to measure seed terminal velocity. This falling falling speed of the seeds, we used our Raspberry trusty Raspberry Pi to create a tool that will allow us to do this. We called him Pieter the Seed Eater. And he has historically measured 300,000. Sorry three thousand seeds for us and we've been able to build up a good picture of the traits of these of these Pines and what they're likely to be doing within our within our Landscapes.

James Robinson:

That's really because to begin with. I think I imagined you sort of standing out there on the edge of a forest waiting for some seeds to fall and, you know, kind of measuring it with stopwatches, but I guess that's impractical, right? So, so, how did how did Pieter help solve that problem? What is it that Pieter's doing? I'm describing Pieter like a real person here. It seems a bit weird. But but what is it that Pieter was doing, how's it work? In order to help you measure the terminal velocity?

Dr. Sarah Wyse:

Well, so you can stopwatch or taking video footage and methodically go through it by hand, but that's not gonna be very accurate. And that's not going to let you do very many seeds at all. Being good, scientists. We want to have lots of replication. We want our data to be accurate. So Pieter and yes, we are talking about Pieter as our old friend. He's done, some Sterling work for us. Pieter's allowing us to do some good science to do reproducible science, get get high numbers through. And, you know, when I first started doing my PhD, I was, I was told by a friend that if you're doing the same thing over and over again, you should be asking computer to do it for you and that was something which which stuck with me. So yes, we could be doing this manually, but in order to be able to do this well, we need to turn to computers for help. Pieter has enabled us to automate this process, get lots of seeds, get lots of measurements and get some really good data.

James Robinson:

And so, had you experience before building and programming Pieter of, that kind of what we would call digital making? Is that something that was part of your work prior to building Pieter or is that something you had to sort of learn along the way?

Dr. Sarah Wyse:

Pieter was my into this, you know, during my PhD. I learnt programming like most most ecologist I'd say who certainly who are interacting with lots of data and doing data analytics. We get Colleges generally program in the language R, which is very good for stats, data analysis in particular. Yeah, it had started with programming but hadn't hadn't been in the digital digital making realm at all. But I met with with Pen. Just before I left the UK. In a catch-up she was telling me what she was up to, and talking about these, these Raspberry Pi things. What is this Raspberry Pi that you're talking about? We had a good chat and I was like that's, that's pretty cool. Okay. Went to New Zealand started the started the work we need to do something. We need to make something that will help us do this job. So I called up Pen, and I said, you know, what can we do here? And so, yes, we we came up with with Pieter, which is Pen's just reminded me I should describe what Pieter actually looks like for the, the uninitiated and yes Pieter is a long tube which is about 2.5 meters meters tall, and you drop. You kind of have a little ladder and you drop the seed in the top and the seed, this is a we're working with conifers with pines, that have, that have a wing, a bit, like a Sycamore and so you drop the seed and it spins, and it falls down the tube. And at the bottom of this the seeds fall, we have some perspex Windows and we have our Raspberry Pi set up with a, with a Pi Cam pointing at where the seeds fall in. And it's taking video footage and able to tell us the speed at which the seed is falling at the end of its flight and calculating terminal velocity and printing out the data and all these good things.

Sway Grantham:

That's very cool. start to get an idea of this Pieter were talking about and what it actually it looks like. Pen I wonder if you could add some more information about like, how did it so you bought the Raspberry Pi skills. You had some idea of the Raspberry Pis we said earlier you were a Raspberry Pi Certified Educator. How did you do it. Was there a lot of prototyping involved? How did you go get to the final idea of the tube shape and what it's made out of or anything around how you designed and made and the role of the Raspberry Pi in the digital thing you made.

Dr. Pen Holland:

Sure I mean Sarah for the original design, absolutely. And and the original Pieter, who lives in New Zealand as Sarah said is, is quite a sophisticated looking beast. It's a tall tube it's all like, solid materials plywood at the bottom, nice foam bed for the seeds to land in. Because, as Sarah said, we want to be able to do reproducible science. So when we use Pieter, you know, we drop the seeds down more than once per seed because they don't always fly exactly the same every time. But, yeah, we had a lot of conversations about. You know, how long does the tube need to be? So the seed can reach terminal velocity. And of course, that depends on how fast it falls. So, we're getting into our maths and drawing equations on the back of envelopes and things like that. And basically the faster, the seed Falls, the taller the tube you need because it's got to have longer to get up to two full speed. So I like slow seeds because then you can have a short Seed eater. It doesn't really matter what shape the tube is as long as it's not so big that you're going to get lots of strange air, currents and things going around. The point of the tube is just to stop your experiment going wrong. When someone opens the office door, you know, otherwise you could be happily just dropping it in the middle of your office. And as long as the the air cons not on, it's all good. So I mean I have one in my office that's built out of Shreddies packets and and then it has a bit of perspex at the bottom and some old foam. I found lying around in the corner. But yeah, so it's a big tube that can drop the seed down. There's a window at the bottom and the the magic really is that there's a camera trained on that window. And we know how big the window is. We know that the seed is falling through that field of view, we can use, what we do is we use the Raspberry Pi to timestamp, the images that we're taking so that we know how long the seed is in View. And then we use trigonometry to basically figure out how fast it's falling. I saw something on Twitter the other day where someone were saying, oh, another day has passed without me using Pythagoras in my daily life. We use Pythagoras all the time. So if you want to be an ecologist care about triangles because they're actually really important for thinking about all of those things like you want to measure the height of a tree, you're going to be using a bit of Pythagoras bit of trigonometry. You want to work out how fast a seed is falling, you need your triangles. So that's Pieter. It's a big tube. It's a window at the bottom and it's a camera that is monitoring stuff that goes past.

James Robinson:

I love the fact people I think listening or maybe have preconceptions about science scientific work, you know, when they imagine a piece of apparatus, that's being used to measure something, they might imagine something that's very clinical and clean and plastic, or stainless steel. And it's you know, constructed to you know, High degrees of precision, but I think I love the fact that, you know, the original Pieter is, you know, perspex and was it MDF I think you said and it's, you know, it's fairly accessible materials. And then we've got one built out of cereal packets. Other other other cereals are available other than Shreddies. And so I think that's really nice. And it kind of, I think it lends itself to this this idea that we can make sort of computing and digital making and science very accessible to Learners. And I think that's a really interesting kind of idea and I know it's something that you're particularly interested in Pen. So how is, what have you, I know that you've done some work following up from this experiment, to try to make some of the this sort of ecology and sort of surfacing some of the sort of mathematical and other elements, we kind of alluded to more accessible to Learners. So what have you been doing other than the experiment with Pieter to in this space? That's a really badly phrased question.

Dr. Pen Holland:

I think when when having all of these conversations about how to make Pieter work and so Sarah did her first version. She sent the code over to me. I made my cereal packet version. We tested the code, we passed it through a few iterations around and figured out how to do it in slightly different ways. And it was just so much fun. And I thought this is too much fun to keep to ourselves. Other people should should have this opportunity as well. So, what we tried to do is put together a series of resources for teachers to take them through the whole process. So, not just the Computing bit where we're throwing seeds down a tube but actually thinking about looking at the world that is around you, and trying to understand what's there. And, and really where the Pieter story starts is looking out of your window or round your playground, or the street that you live on and noticing that there are some trees and then noticing that those trees are different. And then noticing that, even the trees that have the same leaves, have maybe different sized seeds on them. Then we get into, you know, all of those really little things about ecology, which is just about looking at what's around you and seeing the differences in the connections, how big are the trees? You know, are the big ones also wide? Do you see similar trees next to each other? Or are they far apart? And that's really the questions that you need to start asking as a kid which lead you all the way into population e cology, where you're thinking, Well, well, why are the same trees near each other? It's because the seeds fell near each other. Or why are they far apart? Because somehow the seeds got over there and the population spread and then that takes you into what Sarah is doing now, which is thinking about that on a landscape scale of how do we stop trees that we don't want advancing across Landscapes. How do we make sure that we have the trees that we do want in the right places? I'm a mathematician. So, I wander around going. Oh, well, how tall is that? How can I work out how tall that is? And, and so, you know, we put all of that resources together to tell the whole story, right from, just what trees are there. What are seeds? How do seeds travel?Variability is really important in ecology. Because even if you go and measure the same thing every year for 10 years, you'll get a different answer every time because the world hates you as an ecologist and it wants to make you think about variability and then, you know, you get all the way to the actual physical Computing of well, how might we measure these things and can we get some cameras and do some cool programming?

Sway Grantham:

Yeah. I was just it's great to hear all of the cross-curricular like links. Even, cross, curricular is often used in an education sense, but cross-discipline cross-subject, oh there's a bit of maths here. And there's a bit of this here and I just wanted to come back to Sarah saying, that like this was the first time she had moved into more of a digital making space and not just using data analysis programming for data analysis. What did you learn from your digital making experience, what did you take away from that? If someone is looking to get involved, has some some programming skills, but is trying to do something like you did. What did you learn from that?

Dr. Sarah Wyse:

Gosh? Well, it was Yes it's always. Well, you know what I did this but hang on, hang on I could do this one next and then but what about that? So things that I'm chatting to someone else about who's really interested in Ferns and New Zealand and how they're moving around. It's like well, they've got spores, spores are very, very tiny. How can we measure that? And that's going to be a whole different kettle of fish. We haven't quite got the answer to that one yet. But yeah, there's all sorts of different questions about sort of just, you know, completely opened up yeah all sorts of things you can ask. And by doing these you know, digital making kinds of projects, you're able to ask very different questions in ecology and other science. Than you might otherwise be able to do. If you just sitting there stoically measuring things by hand. You it's it opens up many opportunities both both personally in terms of just having having a lot of fun but also in terms of the type of science you can do. So just dive in.

James Robinson:

I liked that when reflection on the, On the on the work and also Pen's motivation for kind of taking this content to other to Learners. Was that fun aspect, right? You know. The learning is important, but actually learning is, is intrinsically fun in my opinion, right. Interesting just in following up on that Sarah. So if you've got if you were to talk to like a young person, now who was thinking about a career in ecology or sort of biological science in general, or you know. What are the skills that maybe they should be looking at? That maybe maybe wouldn't have occurred to them, if that makes sense. If you were like maybe talking to your younger self. What are the things that maybe you should diversify and be exploring now as you enter that kind of career pathway, again, really badly, formed question.

Dr. Sarah Wyse:

I think you definitely need to be thinking about programming and about computers and that no, you can't just do your stats and Excel. That you're going to have to make a leap. So start, start learning programming. If I did University undergrad again. I would have done some computer science. I didn't know what that was that they looked at looked like, you know, I had some friends doing some basic stuff and it was like, this is which button to press in Microsoft Word, computer science is cool. Computer science let's you do all sorts of stuff and yeah, I would I would say you need to start start programming if you want to be doing cool stuff in science. It really helps.

Dr. Pen Holland:

I think something is, is look at the world around you that you're interacting with and identify the things that use programming. There might be a lot of things that you haven't spotted. So I teach programming and digital making to our Master students and they're often students who have specialised into biology and they're going down, a biology route. And then we chuck 20 credits of data analysis and programming at them and we build the equipment that they use in the biology Labs out of cardboard and really rubbish sensors and they're really insensitive and they don't work nearly as well as the ones that cost half a million pounds, but it's that moment where they think. Oh, you know that wasn't a black box that I just put my samples in and it comes out with the results. Somebody programmed that and actually I can program that because now I understand how it works. And so as you thinking about, well, what do I want to specialise in, whether it's biology or physics, chemistry, Arts, the humanities, you know, look around you and and say, oh, you know, that, that TV that I'm watching TV on demand on somebody programmed that app that allows me to get to the bit of Netflix or whatever streaming service you want. And, and lets me see what I want to do. When I go on social media, somebody programmed that and there's stuff going on in the background. And actually, you know, all the games that you play, there are so much Computing and programming around you. It doesn't matter what field you want to go into. It will be useful. If you have an understanding of what is happening. Even if you don't want to be the one who makes it happen, yourself.

James Robinson:

Yeah, I really Yeah, take taking something that you've used like a, like a piece of equipment and re- re- remaking it like in low-fidelity, you know, like, you know, cardboard kind of solution because you understand how that operation works, you've then got like you then got a tool that it might not be as you say as good as a half million pound sensor, but it might be good enough for something else that you are doing. Kind of the, you know, out in a field maybe for example, and I really like going back to what one of something I can't remember who said it Sarah or Pen. But if you're doing something more than once, or you're repeating, something, you should be using a computer. Like that, I think that's a really that's a mantra that, you know, people can live by in, in almost any kind of field I think really. That's really interesting.

Sway Grantham:

You mentioned that you've been developing some resources to help teachers to go on some of the journey that you've gone on with Pieter and what you can learn from it. Do you want to tell us more about the resources you've got at the moment and the resources that you would like to develop further in the future?

Dr. Pen Holland:

Sure. So at the piece of the resources is a set of Google Slides, which teachers can download and then they can edit themselves. There's bit's that can be presented to classes. There are worksheets for people to go through activities. There's lots of tables for reproducing, lots and lots of seeds dropping or measurements, so that you can think about means and averages and statistics and variability. We've got curriculum links in their for key stage 3, and 4. So it's age 11 to 14 and 14 to 16 in the UK. There are hints and ideas for going beyond that. So for more advanced and older Learners, they can get their teeth into some more complex problems. And that, particularly at the Computing end of the resources. I'm interested in developing, that more for younger Learners to get into as well. So, if anybody's interested in doing that, with me, then do get in touch.

Sway Grantham:

Super and we'll those things are linked in the show notes below so that you can find the resources and find out how to get in touch if that's something that is interesting to you.

James Robinson:

We lost our with us their favourite experience of teaching Computing through a cross-curricular context. So, Claire Rawlinson shared an example of how she uses music and English with her upper Primary students. That's kind of up to the age of 11 and she was talking about how her children create soundscapes in Scratch to reflect the some stories that they've read in their class time.

Sway Grantham:

Neil Rickus got in about some climate Champions work that they've been doing with Learners in Key Stage 2. So that is ages 7 to 11, where they've used physical Computing projects, and made close links with DT and Science. And explored, how they all work together with cross-curricular projects.

James Robinson:

And finally Shashi regular contributer to our podcast conversations. Shared in their experience they've done two good examples this year with year, with grade 10. Where they built chat bots built with python and that's created awareness of various social topics, particularly Human Rights, lgbtq+ rights and the environment. And they've also built suitable VR experiences using Code code spaces and he's going to follow that up with a Blog, which I'm looking forward to reading.

Sway Grantham:

If you have a a comment about the discussion today, then you can email via podcast@h elloworld.cc or you can tweet us@HelloWorld_Edu.

James Robinson:

Thank you Sway. So and Sarah for joining us today and sharing their expertise and their experience. And we should also say, a thank you to Pieter who couldn't join us t oday on the call. You can read their articles, multiple articles in both issue 10 and 11 of Hello, of Hello World magazine. So Sway, what did we learn today?

Sway Grantham:

I think my biggest as teachers in the classroom how often do we talk about the breadth of opportunities there are to use computer science skills, programming skills in different subject areas? Like today we were talking a lot about science and maths, but how relevant they are across the curriculum and making sure that Learners have opportunities to see projects like this, and the application of the skills that they are learning.

James Robinson:

And I learnt that system just like a computer system, and I that was a really a really fantastic piece of learning for me. So, thank you very much. Bye. Bye.