Computational Thinking and Classroom Applications

Do you think computational thinking will positively affect the future of education?

Technology is rapidly growing, gaining dominance in the educational sector. And if we must embrace educational technology (EdTech) as the future of education, then it is important to teach students how to identify, question, manipulate, and program digital devices – Computational thinking. 

Computational thinking involves identifying a problem and generating different solutions in a way that can be understood by humans or computers. In the coming years, computational thinking will positively affect the future of education by helping students identify the concepts behind the application of technology. It will also become the prerequisite skill for understanding the technologies of the future. Computational thinking is often associated with computers and coding, but it can be taught without a device.

For that reason, computational thinking can be a part of any classroom. It is gradually becoming a necessary foundational skill for students. By explicitly encouraging computational thinking, teachers can ensure that young students learn to think in a way that will allow them to access and understand their digital world. Teaching computational thinking prepares students for future success, as it can be integrated into existing routines and curricula.

Components of Computational Thinking

There are four components of computational thinking. They include decomposition, pattern recognition, abstraction, and algorithms. Decomposition employs students to break down complex problems into simpler problems. Pattern recognition guides students to make connections or find similarities between problems. Abstraction invites students to identify important information while ignoring unrelated or irrelevant details. And algorithms involve finding solutions.

It may seem challenging to imagine young school children solving algorithms in the nearest future. However, each of these components fits into active learning. Computational thinking births curiosity, imagination, invention, creation, and encourages students to broaden their horizons, and prepares them for the future.

Coding in elementary school
Teaching children how to code

How to integrate computational thinking in the classroom

One of the ways CT can affect the future of education is when students have the opportunities to utilize their computational thinking skills outside their computer science or ICT lesson. One way of doing this is to revisit the curriculum of other subjects and identify opportunities to accommodate computational skills.

Computational thinking can be adopted in a wide range of subjects by:

  • Teaching Decomposition

Teaching decomposition to young learners involves creating problem-solving scenarios. More like problem-based learning, students are taught to identify a problem and break it down into smaller ones. For example, teachers can describe a scenario, such as planning a birthday party, that involves multiple steps. While students break down the task, the teacher can draw or write a visual representation of their thinking, giving them a mental map of how to solve similar problems in the future.

  • Teaching Pattern Recognition

Pattern recognition—as a component of computational thinking—encourages students to analyze the connection or similarities between objects or experiences. By finding what objects or experiences have in common, young students can begin to develop an understanding of trends and are therefore able to make predictions.

To teach students how to recognize patterns, you can ask them to analyze trees. Find their similarities and common parts. All trees have roots, trunks, and branches. While there are many differences between types of trees, these components are present in all trees. They can also analyze these commonalities and identify the differences in size, color, and shape.

Teaching students to recognize patterns increases their awareness of the world around them. This helps them use the patterns they have identified to solve future problems and make predictions about the world.

  • Teaching Abstraction

Abstraction is focusing on the information that is relevant and important. It involves separating core information from irrelevant details. With literature (while identifying the main character, main idea, and storyline), students can learn to sieve information, picking out the necessary details. 

  • Teaching Algorithms

Algorithmic thinking involves developing solutions to a problem. Specifically, it creates sequential rules to follow to solve a problem. For example, you may ask students to think about cooking a meal. What comes first? Second? Etc. Having conversations about sequence and order develops the foundations of algorithmic thinking and helps build students for the future. 

Linking Young Children to the Thinking of the Future

Teaching young students computational thinking strategies goes far beyond increasing their comfort level with computers. It is deeper and more profound. We live in a world with tech devices, and understanding how these devices work allows us to approach technology to help us solve problems. 

Computational thinking allows students to be active, rather than passive, users of technology. How we understand the technology that surrounds us, and the way we ask questions about these devices are significant factors for success in the future. 

Conclusion

Computational thinking is not the same as computer science. As described above, the two are very different. But some schools that are early adopters of computational thinking often associate it with computer Science or see it as a substitute for Computer Science. 

Computational thinking is an element of Computer Science — but it has applications in all subjects. And the main essence of integrating it into the classroom is to encourage students to think broadly about the challenges facing the universe, break it down into smaller parts; identify the core areas that require solutions, and then generate solutions in an organized and methodical manner.

Computational Thinking and Classroom Applications

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