Place-based teaching and learning in SD61

Category: Coding

Computational Participation

Building on my last entry about Computational Thinking (CT), I want to dive deeper into what it means to actually engage in CT as an active participant. In Yasmin B. Kafai’s article “From Computational Thinking to Computational Participation in K–12 Education” the term computational thinking is reframed to computational participation (CP) (2016). According to Kafai, CP involves “solving problems, designing systems, and understanding human behavior in the context of computing.

What does that look like in today’s Elementary (K-5) schools?

Kafai speaks of the importance of relevant and authentic learning opportunities, where kids can engage in digital practices that are fun, interactive, and actually mean something to them in the context of their lives. According to Kafai, “programming is not an abstract discipline, but a way to “make” and “be” in the digital world.” In other words, programming can be the digital language of identity-making online.

As with all identity-making, this is not a solitary pursuit. This must happen in collaboration, interaction, and communication with others. We are social creatures and we thrive in learning situations that allow us to build upon and with the genius of others. From building from “scratch” or “remixing” an existing product, Kafai stresses that a key feature for 21st century learning is open knowledge sharing and innovation.

It might seem like CP is as simple as grouping kids together to work on a coding project, but Kafai cautions that CP comes with its own set of challenges. Kafai reminds that students aren’t “digital natives” and that, “to learn to code students must learn the technicalities of programming language and common algorithms, and the social practices of programming communities.

Some ideas to build the foundational skills, communication, and processes to become a CP?

  • Design “Exact Instruction Challenges” for your classroom: written or verbal. Focus on deconstructing a simple (or complex, if you’re brave and patient and have done this before!) task into its most basic steps. Build skills in communication.
  • Do round-robin designs: one student starts it off and then passes it on. Consider that this can be done on-paper (written or visual), physically (designing a dance or movement), verbally (a story or song), or with a hands-on creation like Lego or blocks. Your imagination is the limit, and the purpose is to foster open sharing, lessening attachment to ownership, and learning to work collaboratively. *Check out the full Google Design Sprint Kit.
  • Start your day with a WODB dialogue: Which one doesn’t belong? There are no answers provided with these, because multiple correct answers exist. This task builds skills in reasoning and explaining an answer, while encouraging out-of-the-box thinking and understanding that one-solution-fits-all is often a myth. I love this as a warm-up activity for math.

Granted, none of these ideas use tech. What they do is build the foundational skills for CT and CP.

Over to you:

How have you seen CP come alive in your school?

What have been some of the most successful (in terms of student participation, enjoyment, and learning) ways in which you have incorporated CP into your practice?

References:

Kafai, Yasmin B. “From Computational Thinking to Computational Participation in K-12 Education.” Communications of the ACM, vol. 59, no. 8, Aug. 2016, pp. 26–27. EBSCOhost, doi:10.1145/2955114.

Josh Darnit (2017). “Exact Instructions Challenge PB&J Classroom Friendly | Josh Darnit.” Retrieved on July 21, 2021 from: https://www.youtube.com/watch?v=FN2RM-CHkuI

LUMA Institute (ND). “Round Robin” from the Google Design Sprint Kit, last accessed July 21, 2021 from: https://designsprintkit.withgoogle.com/methodology/phase1-understand/round-robin

https://wodb.ca: a website dedicated to Which One Doesn’t Belong? With a nod to Christopher Danielson and his Which One Doesn’t Belong – A Shapes Book

Computational Thinking and Robotics

Apparently, according to the BC Curriculum, children in grades K-5 are too young to learn Computational Thinking and Robotics. Or at least, anything explicitly called that. When I enter those search terms into the Search Curriculum page, with parameters set to K-5, I’m given nothing! When I remove the parameters, I see that the terms begin showing up in Grade 6 and are most predominant in Secondary grades. What a disappointment!

But what is computational thinking (CT) and how does it link to robotics? Is it possible that these skills are, in fact, taught at the K-5 levels, though not explicitly called that?

According to the CodeBC Computational Thinking Illustrated, when we engage in CT what we are doing is “specifically looking at what happens when we collect, store, and process data…. we take note and measure how data is transformed. We look at how information is processed and what is accomplished by that processing.” Another big part of CT is actually getting our hands busy by building and producing computational artifacts – like machines or robots. In other words, when we engage in CT, we do things like ideate, build, tinker, observe, and reflect. Now this is starting to sound like familiar curriculum for K-5.

When engaging in CT, we are also building skills in abstraction. One of the ways this is done is by building models – separating out the qualities we care about and leaving the rest. According to CodeBC, “when we deliberately separate our system into parts that can be individually understood, tested, reused, and substituted, then we are creating new abstractions.” Models can be physical objects or something less tangible, like a computer program. It takes time to learn how to narrow the margins and scope of a model so that the variables are measurable – create something without boundaries and you’ll “end up simulating the whole world!

In CT, we are also guided to build skills in analysis, problem-solving, and communication (with machines, computers and humans). The answers we get after analyzing results may not always be obvious to others, and so it is our task as computational thinkers to figure out how to translate our findings into clear and accessible terms. Inversely, we may have an idea that we want to test out and we must also learn to translate our ideas into CT: coding, programming, machinery, etc.

In K-5, we are asked to build and analyze models, solve simple and complex problems, and learn how to communicate with ourselves and others. A great deal of this is done through play and scaffolding emerging scientific, mathematical, social, physical and creative thinking skills.

Team-work is another skill developed with CT. CodeBC reminds us that “building any complex system, software or hardware, requires more work be done in less time than any single person can accomplish.” Adding more people isn’t the magic recipe, however; “interpersonal and communication skills as well as knowledge of different team methodologies and processes” are vital to effective teamwork, as is good management as teams expand.

As it turns out, we are continuously developing CT skills at the K-5 level; it’s just not explicitly called CT. Being aware of the end-goal might be helpful for teachers who are introducing the skill-building exercises that will prepare children to become computational thinkers.

So, what are some explicit ways we can engage in CT?

Decomposition is one. Taking apart objects or breaking down a process into individual steps, like Josh Darnit does in his PB&J Exact Instructions Challenge:

Josh Darnit (2017) Exact Instructions Challenge PB&J Classroom Friendly

Primary teachers are very familiar with another exercise in CT: pattern recognition. According to CodeBC, “forming an idea of what you expect is one way to find patterns. The more you look, the more patterns you will find in nature, in computational artifacts, and in processes. When we recognize a pattern, we can use our other computational thinking skills to help us understand its importance.

Once we start to find and recognize the patterns that surround and are within us, we must learn to describe the patterns we see with precision. For this, we learn pattern generalization and abstraction. When generalizing, we look for similarities or commonalities in a group of patterns and we try to describe them in a way that is both clear and efficient. When we learn to describe a group of patterns, or a pattern of patterns, all at once, then we have an abstraction.

Finally, CT skills can be explored using algorithm design. While some algorithms are computer programs, it’s fair to say that an algorithm is more like an idea. In order to design an algorithm, you need to think about what you want to accomplish (your goal), and what tools and limitations you have (the constraints of the system). CodeBC says that designing an algorithm that “accomplishes specific goal within the constraints of the system is like creating an elegant dance that everyone else wants to learn.” Just like a dance, this is a process that can be explored, played with, and scaffolded in K-5.

So, what do CT and robotics have in common? CT is the framework we need in order to engage in robotics. It is the exploration and skill-building of language, patterning, process, and thinking that makes something like robotics possible. While “Computational Thinking” and “robotics” may not show up in the K-5 BC Curriculum, the foundational building blocks are there: analyzing, communicating, ideating, pattern-recognition, problem-solving. We just have to learn how to read the language of CT and remember to begin with the end in mind.

TPACK for Gr. 3 Math

TECHNOLOGICAL, PEDAGOGICAL , AND CONTENT KNOWLEDGE (TPACK) FOR GRADE 3 MATH.

Learning Outcome: Students will use comparative language to discuss the likelihood of simulated events.

Using the TPACK Model, I have developed connections to the BC Grade 3 Mathematics Curriculum. By focussing on Content and Pedagogical Knowledge first, I prioritized student learning and curricular goals. Once I knew what I wanted to teach, and how I wanted to teach it, I then moved on to figuring out which technologies would best support the learning objectives. I used the SAMR questions from my previous blog post to help vet my tech options and ensure they were adding value to the learning experience.

This image and the ideas within are Creative Commons (CC) and yours to use, duplicate, share, and borrow from.

References:

YouTube read-aloud: A Very Improbable Story by Edward Einhorn

Online games of chance: https://www.online-stopwatch.com/chance-games/

Lesson resources and materials for probability in math: https://wehavekids.com/education/Best-Kids-Books-to-Teach-Probability-in-Math

An idea for creating your own game of probability using Scratch: https://researchideas.ca/mathncode/scratch-probability.html

Some more Games of Chance on Scratch: https://scratch.mit.edu/search/projects?q=games%20of%20chance

TPACK Framework: http://matt-koehler.com/tpack2/tpack-explained/

YouTube TPACK explained (Common Sense Education): https://www.youtube.com/watch?v=yMQiHJsePOM

BC Curriculum for Grade 3 Math: https://curriculum.gov.bc.ca/curriculum/mathematics/3/core

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