Computational thinking is the problem-solving skill of the digital world. It’s powerful when integrated into the curriculum because students engage in experiential learning of content-related problems, such as how to identify the tone of a story or how to best address pollution in their local area.
Students sharpen their critical thinking skills by working through all the considerations that a problem presents. They practice inquiry-based thinking by imagining and molding problems to be solved. They sharpen their logical thinking by outlining specific rules to be followed to solve their problem. Practicing and combining these three types of thinking to solve problems is what students have to gain. Thinking first, computing second.
I find the most compelling reason for CT integration isn’t preparing students for the jobs of tomorrow, or even the emphasis on the computation, but rather the thinking. CT is not the future of education, it’s the now!
Despite the importance of CT in K-12, it can be intimidating for educators to implement. It certainly was for me. Initially, I thought, “Why would my students need to learn about computing in Spanish class?” I didn’t see its relevance to the content.
I decided that I wanted to try to create a Spanish lesson integrating CT to get a better understanding of what teachers face when first learning CT. This article attempts to answer all the questions I initially had in plain terms.
What even is CT?
While there are many different definitions, they all center on the following core idea:
Individuals and organizations use massive amounts of data to make decisions at every turn in life. That data can be internet searches, purchase histories, trip destinations — absolutely anything. To make sense of that data, they create algorithms, which are rules a computer (or a human) follows. This is powerful stuff.
As society plunges further into the Information Age, we use computing to solve our problems. This helps us understand how to best use computing to better solve problems as they arise. Computers need instructions, and this is where CT comes into play.
In other words, people create rules, based on data, which we give to a computer (or human) so that it can solve problems or reach decisions for us.
It’s problem solving and communication. These are skills students of all ages in all subjects need, from kinders deciding where to best put a school garden to high schoolers creating chatbots that answer questions about Macbeth.
[Click on the image below to open the computational thinking infographic.]
Why invest effort in CT?
Asking questions to logically organize and analyze data, creating detailed rules for others to follow, and engaging in trial and error deepens content learning. These skills teach tenacity, tolerance for ambiguity and complexity, and teamwork. If this sounds familiar, chances are you’re already promoting these in your classroom!
The “thinking” in CT is worth the investment of time and energy because thinking is a skill applicable to all subjects, which is why integrating CT into content across grade levels is vital.
According to Code.org’s 2021 report, State of Computer Science Education, just 51% of high schools offered computer science, up from 35% in 2018. It also states that 31 states had adopted 50 computer science education policies in the prior year. While that’s a start, it’s nowhere near enough.
The fact is, all students need an education that will prepare them for the world they’re walking into. Not only for the sake of jobs or furthering economic development, but also so they will know how to be good digital citizens, recognize misinformation, and create better lives for themselves and those around them.
Computational thinking is a literacy that is desperately needed in K-12 education.
Why should I integrate CT into my class?
It’s important on a societal scale, but also in your classroom with your students.
There’s the old saying that you don’t really understand something until you can teach it. That’s CT. I’ve always assumed it meant teaching people, but now I know it includes computers. Teaching computers what exactly? How to solve problems!
The connection between these various activities is that they all involve problem-solving and computing. Designing and implementing a plan to reduce food waste in your immediate environment is leagues more memorable than learning the theory of it. Experience is the best teacher.
Like with language, the earlier students learn a skill, the more proficient they’ll become. As students grow more comfortable with the skills and language of CT, they’ll be able to solve problems at larger scales. Today it might be how to reduce food waste in school; tomorrow it could be finding solutions to global food security issues.
Your students’ learning is deepened and made more memorable when integrating CT into your class.
How do I integrate CT into my class?
If you’re a teacher, your students already learn CT skills, just not packaged as the CT process. For example, middle school algebra students learn to move from solving specific math problems to deriving general formulas and equations. This is called abstraction and is a core element of CT.
Another example is students discussing Macbeth. They have to read, understand and analyze Macbeth. This is decomposition and pattern recognition, which are other core elements of CT.
Why not take it a step further? Students could create a chatbot to quiz their classmates by creating questions, crafting answers, and designing rules for the chatbot to follow. You need a deep understanding of Macbeth to do all of that!
I often found myself asking, if it’s called CT, won’t students need computers? The answer is not necessarily! There are plenty of unplugged CT activities where students can create algorithms. Another strength of CT is that it can be integrated into any subject area — plugged or unplugged!
Learning to think computationally is the start of a journey of seeing society’s relationship with technology more clearly, and it’s a skill that will help students change society for the better.
Nick Pinder is a project manager of computational thinking and higher education projects at ISTE. Nick is interested in the promotion of computational thinking and its intersection with language instruction specifically and the humanities in general.