Piecing Together the Puzzle of Computational Thinking

There was a gap along the edges of the puzzle. Just a small one, given the puzzle’s full size, but enough to be irritating.

I looked through puzzle pieces I’d already sorted into piles. One pile held pieces with a single straight edge along one side: border pieces. In that pile, all the pieces were a blue-green shade, so color alone wasn’t enough to find what I needed.

I sifted through the pile of border pieces, noting the patterns. Half of the pieces had subtle striping, while the other pieces looked daubed with paint, almost impressionistic. The painterly pieces matched the mottled look of the border, so I choose that group to look for the missing piece.

Sort, test, sort, test. This looping process continued until I found a piece that filled in the gap with a satisfying click.

Jigsaw puzzles and computational thinking have a lot in common.

Puzzling and Computational Thinking

Computational thinking isn’t coding, although being able to think computationally can help you learn programming languages. It’s a multipurpose tool. Still, just as computational thinking can be used for everyday tasks, so can everyday tasks help you learn computational thinking techniques.

Putting together jigsaw puzzles, or puzzling, is a fun way to engage in the types of thought processes that computational thinking encourages. It involves breaking down a problem into steps in order to find a solution.

If you’ve ever looked up guides on putting together puzzles, you might notice similar instructions each time. Find the edge pieces. Sort by color. Sort by shape. Work section by section.

Each of these tasks aligns with the main components of computational thinking. It’s no wonder, given that computational thinking is a problem-solving framework. Putting together a puzzle is an exercise in problem solving, in manipulating known variables and using different methodologies to reach a solution.

Decomposition, or Lots of Little Pieces

A puzzle itself is a decomposition. It takes something big — an image, or a 3D object — and decomposes it into smaller pieces. The whole point of a puzzle is to put things back together.

By looking closely at a puzzle’s pieces, you’ll start to notice the differences that set them apart. Depending on a puzzle’s difficulty, these differences may be small. A monochrome puzzle, for example, will not require sorting by color. But each piece is unique through its shape, and through the subsequent ways that it connects to the pieces around it.

Decomposition makes big problems less scary. Even if the solution to a problem isn’t known — as with a puzzle without a final image to guide the solver— breaking things down into smaller, manageable parts helps to forge a path toward what needs to be done to reach it.

Pattern Recognition, or Matching the Pieces

One of the ways to sort puzzle pieces is to look for patterns. This includes not just literal patterns, but also certain shapes or certain colors. Grouping these similar pieces together, even if you’re not sure how they’ll all fit, can be enough to lead to later breakthroughs in piecing parts of the puzzle together.

Puzzle pieces have unique qualities that allow them to be grouped, but those qualities must be determined through pattern matching. Sometimes actual patterns are matched — for example, stripes and solids, or differing textures. Sometimes the pattern is noticing how the line of an image continues from piece to piece.

Pattern recognition allows you to find commonalities in the parts of a problem. Can two similar parts be grouped together, or are there other ways they can be classified? Just as in code, where items can be added and arrays or variables reused, so can puzzle pieces be sorted and tried as possible answers.

Abstraction, or the Big Picture

Abstraction is looking at the big picture, rather than small details. How does this line up with puzzling, which is an innately decomposed activity?

For some people, part of the joy is putting together a puzzle without looking at the box, instead focusing on the smaller pieces and how they fit together. They use pattern matching and sorting as their means of solving the problem bit by bit.

Others, however, find they approach problems with a reasoning that’s deductive, rather than inductive. They see the whole, then extrapolate. For them, abstraction can be a way of looking at the front of the box — the final image — and seeing the solution, the picture itself, as a collection of shapes and colors.

In abstracting a solution, pieces can be sorted. Patterns can be seen. Abstraction allows you to view problems from a macro, rather than micro, view.

Algorithmic Thinking, or Puzzling Tasks

Algorithmic thinking is a way of using algorithms, or rule-based processes, to solve problems. Like recipes, algorithms result in something more or less consistent. As such, they’re especially good for completing reoccurring tasks.

With puzzles, the recommended puzzle-solving tasks of setting aside pieces and sorting pieces by color are based on algorithmic thinking. There’s a mental checklist involved: does this piece have a flat edge? Is it red? Does it have any special attributes?

It’s possible to put together a jigsaw puzzle without sorting pieces or building out sections and edges. Possible, but slow. The benefit of algorithmic thinking is to simplify problems where possible. Just as in coding, where a function can be written to resolve baseline tasks, algorithmic puzzling helps complete tasks in definable ways, revealing the biggest underlying issues.

Beyond the Puzzle

While being able to sort by color or match patterns won’t necessarily transfer to real-world usefulness, developing skills like spatial awareness and logical problem solving will. These are the types of skills that will serve you well whether you’re a student learning to break down math problems or an office worker looking to navigate a new building.

For teachers, jigsaw puzzles are especially good in that they provide a low-tech way to teach students computational thinking without complicated technical setups. Even young kids can do puzzles and begin to sharpen their problem-solving abilities. These abilities will bolster students as they begin learning to code or working on STEAM-centered projects.

If you’ve never tried to solve a jigsaw puzzle, give it a shot. Whether you approach it from a computational thinking angle or not, there are numerous benefits to piecing things together — and you might just have fun.

About the blogger:

Jesika Brooks

Jesika Brooks is an editor and bookworm with a Master of Library and Information Science degree. She works in the field of higher education as an educational technology librarian, assisting with everything from setting up Learning Management Systems to teaching students how to use edtech tools. A lifelong learner herself, she has always been fascinated by the intersection of education and technology. She edits the Tech-Based Teaching blog (and always wants to hear from new voices!).