(0:02 - 0:11) Good morning and welcome to Data Science in Primary. My name is Melinda Kalk, one of the founders of Tech for Learning. Excited to be here with you today.
(0:12 - 0:39) I wanted to talk about data science because our world has and our kids have access to so much information. It can be overwhelming, which is why data science is exploding as a career option because it's very hard to do what we need to do with all that data and to make decisions using it. But the access to that data is also gives us access to a whole lot more information to make better decisions and to begin to foment and change our action.
(0:39 - 1:03) So anyway, data science is not though out of reach of even our youngest learners. And I've kind of simplified the data science process here. And it's very much like the scientific method where we are noticing things and wondering about things and actually having questions and then we look to what sort of data can I find an access to that? I collect it and I visualize it.
(1:03 - 1:22) Then I try to make sense of it so that I can make a decision, communicate that information to other people and take action. We can do so by the following bits of information in this webinar deal with specific actions. We can take within each of those and then talking about the entire process as a whole.
(1:23 - 1:39) So we already do a lot. I mean, I remember when our young kids are so curious anyway and ask all sorts of questions, but we can, you know, promote that a little bit with maybe an ICI wonder. And yes, our young learners might not be able to type all this or write quite yet.
(1:39 - 2:16) So I could do that. I can just put this on the board and have my kids call it out in a morning circle time. I might share an image like the meerkats here, you know, where they're going to say, well, what do you see? I see meerkats.
If somebody knows what the answer is, or they're fuzzy, they're all looking at something. They seem to be in grass. I see a log.
And then what do we wonder? Well, what are they looking at? Where did they live? I wonder what they eat. How many are there other ones? As you see, kids come up with all sorts of wonderful questions. And then sort of naturally leads to, well, if we wanted to know more about meerkats, we would have to collect data about meerkats.
(2:16 - 2:35) And that might be in the form of research or other things. So we often consider data simply numbers, which I think is very common for it. So we're going to talk a lot about that piece, but it can really get us to ask just just asking those questions and formulating information so that we do take action to do that research or collect our data.
(2:36 - 2:44) You might also do this if you follow the Reggio Emilia approach. They have what's called the provocation. I don't know if I said that right.
(2:44 - 3:09) But where you create a situation where kids have experiences and start to wonder and play in sort of a free form environment and what we do as adults, rather than ask because we're trying to teach our kids to ask the questions, is give them an opportunity to discuss and ask questions and listen to what those are. Because next we need to sort of collect data. We can teach them how to do this in lots of different subjects in lots of different ways.
(3:09 - 3:34) Also, for example, if I went on a nature walk, if we're working on building literacy skills, I might ask them to draw and write for plants that they saw. I might ask them to collect pieces from that nature walk and then put them in some sort of organization because that's really the next step of this. What am I going to do to visualize this data? And so I could just put it all out and not mix it.
(3:34 - 3:50) But here they organized it by brown, white, green, colorful, et cetera. And that sort of sorting is another part about collecting data, is collecting pieces of data in the right place. Wixie has all sorts of sorting activities.
(3:51 - 4:12) This one comes in, I think, one of the math folders in the curriculum. There is a sort and count in every single month, sort of with a different theme based on the season or holidays in that month. So whenever it works for you, you can look in that month by month folder and you will find that collect and sort of activity.
(4:12 - 4:29) But we could also do it in science. And we're doing that comparing and contrasting. A lot of this is just getting kids ready to analyze and present and sort things so that when we visualize it, we're able to do that in a way that makes sense for our brains and helps us make decisions.
(4:30 - 4:43) We could do tally mark surveys. That's a common one in the younger grades because, again, we're learning how to sort and count. And this is we could do, again, something on our at our circle time in the morning or morning meeting.
(4:43 - 5:09) Put something up on my whiteboard. In this case, what is your favorite summer treat? They did tally marks. Then we count it all, total it.
We could do the same thing with a bar graph. I think three category bar graphs are a pretty typical kindergarten standard and moving to three and four and five in the upper grades or upper primary grades. The nice thing is about the bar graphs is it makes it really visually obvious what's happening.
(5:09 - 5:25) And, yes, tally marks, I can see the difference between a lot of different tally marks, but I can also visually really see that the ice cream cone is higher than the other ones. So, again, it just makes it easier to read information. That's part of what we're doing with this.
(5:25 - 6:43) Another fun way we might do this is with an art sort of project. Pete Mondrian has a lot of geometric paintings and artwork that a lot of us are familiar with. He did other things, too.
But this is one where we could ask students to take a coloring page and simply color it in a similar way to Pete Mondrian, where we maybe limit the colors that they do. And then if they're filling us in with a paint bucket, yeah, we're building mouth skills. We're talking about art.
We're talking about primary colors. We're building vocabulary. But we could also then ask them to talk about rectangles, squares, red boxes, yellow boxes, blue boxes.
They could tally all of those for their own artwork. We could then do a turn and talk or meet with a partner so that they compare that. And, again, if I look at that tally, our tallies for rectangles and squares should be the same because that's constant information.
But red, yellow, blue, black, those are variables. Oh, so now can you already start to see? I don't have to use those words with these students. But to get them to see that, somebody will notice that their numbers are always the same at the top, but they were different at the bottom.
So that's again, they're back to that noticing piece of it. Another step with analyzing our data is to be able to identify patterns. And, yes, in upper grades, we're looking at is this a linear function with a constant rate of change or exponential.
(6:44 - 7:02) But even in the early grades, patterning activities can help us look at those predictions. And patterning is a pre-algebra skill. Again, in Wixie's month by month folder, there are patterning activities where there's a couple like finish the pattern at the top and then make your own pattern again for every month, every holiday.
(7:03 - 7:27) Their math has a lot of these also because, again, it's a pre-algebra skill, creating patterns with necklaces, flowers, balloons, all sorts of things that way. And like we love in Wixie is creating really helps kids cement ideas and understanding. Dr. Henry Olds and Dr. Walter Drew had their students create sort of patterns and what they called a pattern play piece with physical materials.
(7:27 - 7:57) And then they took a digital photo of that and brought that photo onto a Wixie page as what they called a pattern play piece. And Lynn let students use Wixie's tools to duplicate, rotate, flip, and move all of those things around to create their own patterns on the computer. And I love this attention to possibility leaves intention for possibilities, which is which equals creativity, which is again a fun one there, but they're starting to see how they can create a pattern or make a pattern emerge.
(7:57 - 8:14) And again, powerful ways to think about data and predictions. Speaking of predictions, with our emerging readers, we use pattern stories to help them predict the next sentence in a book and start to see patterns with that. So they start to recognize that as they hear words and see words over and over again.
(8:14 - 8:28) So here's an example of a student-created book based on Charles G. Shaw's, It Looked Like Spilt Milk. Let's look at a few pages. Sometimes it looked like spilt milk, but it wasn't spilt milk.
(8:29 - 8:53) Sometimes it looked like a heart, but it wasn't a heart. Sometimes I think it looks like a fish, but it wasn't a fish. So again, you can see that pattern and her ability to predict what the story is going to be or the second half of that sentence allows her to practice fluency and intonation.
(8:54 - 9:08) And this is my daughter's project that she did in preschool and she worked with an older student, obviously, to put it all together. But she loved reading this over and over again because she could. And so it was that confidence builder and again, using that pattern to reinforce that.
(9:09 - 9:20) In similar ways, her preschool class used Mary Wore Her Red Dress. It was like a nursery rhyme or those songs that we sing with repetition with our younger students. And this one was focusing on color words and clothing.
(9:21 - 9:35) Asking why her pink dress, her pink dress, her pink dress. Asking why her pink dress all day long. And again, not every student wanted to be able to sing that, but they could still do it.
(9:35 - 9:52) Selena wore her green dress, green dress, green dress. Selena wore her green dress all night long. So again, using those patterns with our emerging readers and, you know, as you're reading that, asking students what the pattern is and to make that next prediction.
(9:52 - 10:07) Because that's sort of the next one that we want to do is we want to use data to be able to take action. Like read the second half of a sentence that we don't know because we know the pattern. Go back to that tally mark survey that we did at the beginning, which is asking students about their favorite summer treat.
(10:07 - 10:25) Again, it seems like I'm just practicing that data science, which is valuable in and of itself, but I want to be able to use that to make decisions. So if we are going to have an end of the year party, I would go back to that tally mark survey and say, hey, this is what everybody chose as their favorite summer treat. We're going to have an end of the year party.
(10:25 - 10:34) What food do you think we should have? I'm not telling them we should pick the top one. I'm asking them to tell me why. Because now I want them to do something with this data to make a decision.
(10:35 - 10:51) And again, we do this in other subjects, and we probably are doing a lot of this already. One of the other examples is we ask kids to capture the weather of the week. And again, put this on my whiteboard, and I could then ask my students to go through and make those changes each day.
(10:51 - 10:59) Oops, sorry. And ask the students to drag in the picture. So again, we're representing data with pictures and with words.
(10:59 - 11:20) And once they're capturing all of this weather data, ask them on a daily basis to, okay, now that we've collected the weather for today, how might we want to dress the bear? Oops, it's not coming up. What is it going to do? I'm losing my internet. You can see that in there, dragging the clothes to be able to share or to be able to dress the bear appropriately for the weather.
(11:20 - 11:44) That's great for, you know, say preschool or kindergarten. As we go through to, say, second grade and we're starting to learn a little bit more about seasons, we might want to, what clothing should I pack to go on a trip to grandma who lives in a different climate? Again, because I'm using the data that I know about something or the information I know about something to make decisions. We can even practice that decision-making skill again with something as fun as a would you rather.
(11:45 - 11:56) And it doesn't matter which one. Would you rather have to group projects or work alone? Okay, maybe that's a little hard for the younger set. But here, would you rather sneeze glitter or burp bubbles? And again, I could do a tally mark survey for this.
(11:56 - 12:08) I could ask them to choose that and say, hey, everyone in this room who wants to sneeze glitter go to that side and burp bubbles go to that side. And then we're going to, again, visually compare amounts. Then I'm going to have them talk to each other about why, based on experience.
(12:08 - 12:19) Experience is data. So we're going to do that experience and then we're going to explain and share that with the rest of the group. And then, again, sometimes these can lead to additional questions, which you think they might.
(12:20 - 12:43) But would you rather have a quoll or nudibranch as a pet? I could post that to my students. If you encourage this, because some of them might know what a quoll or a nudibranch is, but other ones are not going to know that. So then it prompts the question, what is that? What is a pet? What makes a good pet? Now I'm starting to ask all sorts of these questions because it's hard to know what data we're supposed to collect if we can't narrow down our question and know why we're asking that question.
(12:45 - 13:07) So, again, so many different ways that we can build skills in that noticing, wondering, questioning piece, collecting the data, sorting information, analyzing it, finding patterns, and then communicating and taking action. And doing it in a context. We saw all sorts of things that were already familiar to you working in your primary classroom.
(13:07 - 13:16) And hopefully you can apply those and articulate some of those specific things to build additional data science skills for even our youngest learners. Thank you so much for joining me.
