Understanding Computational Thinking for More Effective Learning

The idea of bringing computational thinking into all areas of education is becoming increasingly important. Even though computational thinking has its roots in computer science (specifically, computer programming), this way of solving problems can help students in every subject, from math to art.

Many educators find computational thinking to be new or even a bit out of place in their core subjects, but its value to developing future-ready students is immense. The skills included in computational thinking are not just for coding or using computers; they’re essential for critical thinking and problem-solving in any field.

As the world becomes more connected and technology-driven, students need to be ready to think critically, solve complex problems and be creative. That’s why computational thinking is so crucial. It prepares students not just to use technology, but to understand and solve the challenges of tomorrow. This doesn’t mean turning every class into a computer science lesson; instead, it’s about adding a layer of problem-solving skills that can make learning more effective and relevant.

In this article, we explore the importance of computational thinking and how educators can better understand computational thinking so they may start to include these concepts in their teaching. Even if it seems challenging at first, integrating computational thinking can enrich students’ learning experiences and better prepare them for the future. 

Quick Links:

What is Computational Thinking & How is it Used?
What are the Components of Computational Thinking?
How Do You Become a Computational Thinker?
How Do You Explain Computational Thinking to a Child?
What are the Pros and Cons of Computational Thinking? 

Further Reading:

The Definition of Computational Thinking
Why is Computational Thinking Important for Students? 
What is Computational Thinking in Everyday Life?

What is Computational Thinking & How is it Used?

Computational thinking is a set of methodical problem-solving skills that help people solve complex problems more effectively. Computational thinking helps people break down complex issues into simpler ones, notice patterns, focus on the important details and devise clear, step-by-step plans to overcome challenges. It’s a practical approach that can be used in everyday situations, from organizing a to-do list to making sense of a recipe. It’s about thinking methodically and logically to find solutions.

While computational thinking has the disadvantage of having the word “computational” in it, it isn’t only used in the field of computer science. For example, it’s used in biology to understand gene sequences, in mathematics to solve complex problems, and in the social sciences to analyze large data sets. In everyday life, computational thinking can help with organizing and analyzing data, automating tasks and making decisions.

What are the Components of Computational Thinking? 

The four main components of computational thinking are:

Decomposition: Breaking down complex problems into more manageable parts.
Pattern Recognition: Looking for similarities among and within problems.
Abstraction: Focusing on the important information only and ignoring irrelevant detail.
Algorithm Design: Developing a step-by-step solution to the problem, or the rules to follow to solve the problem.

Each component of computational thinking is essential for tackling complex problems efficiently and effectively:

1. Decomposition: This is the process of breaking down a large, complex problem into smaller, more manageable parts. It is important because it makes the problem less overwhelming and easier to understand. Each smaller problem can be addressed individually, which is much more feasible than trying to solve the complex whole all at once.

2. Pattern Recognition: After decomposing problems, the problem solver will look for patterns among the parts. Recognizing patterns helps in identifying similarities or trends that can inform the solution. This is important because it can lead to solutions that solve not just one specific instance of a problem, but a whole class of problems.

3. Abstraction: This involves filtering out the unnecessary details and focusing on what’s important. Abstraction is important to the computational thinking process because it allows problem solvers to disregard the irrelevant and complex details that can clutter the thought process, thus simplifying the problem-solving steps. It helps define the problem without getting sidetracked by details that do not affect the outcome.

4. Algorithm Design: The final component of computational thinking is about creating a clear, ordered series of instructions to solve a problem. This is important because having a well-defined set of steps ensures that the problem can be solved systematically and that the solution is repeatable. It also allows for the solution to be communicated to others easily—or even be automated.

For a teacher to effectively teach students how to be computational thinkers, the teacher should be a computational thinker themselves. But what if this is a relatively new skill for the educator? Here are some tips for becoming a computational thinker:

How Do You Become a Computational Thinker?

To become a computational thinker, you first need to cultivate a mindset of computational problem solving. This means you’re going to intentionally slow down your problem-solving process (for now) to conscientiously take the steps of computational thinking. If you’re used to solving problems quickly or all at once, it will be a learning process, but the end result will be more thorough and effective solutions, as well as generalized solutions that can be applied in multiple situations.

1. Practice Breaking Down Problems

Immerse yourself in the basics of analyzing and breaking down problems into smaller parts. This means looking at a challenge as parts, instead of as a whole, which makes the overall problem less daunting and more manageable. For example, if you’re planning a party, instead of getting overwhelmed by everything at once, you could break it down into steps like creating a guest list, deciding on the menu and setting up the space.

Engaging with puzzles, logic games and even coding exercises can sharpen this skill. Regularly practicing decomposition helps you see larger problems as a series of smaller, solvable tasks. 

2. Start Identifying Patterns

Next, focus on recognizing patterns. This skill helps in making connections between similar problems and often leads to recognizing a solution that has worked before. Look for trends in the problems you solve every day. For instance, if you notice that you’re always late in the morning, you might spot a pattern in your routine that’s causing the delay.

To enhance this ability, you can analyze case studies, historical events, or even daily tasks to find recurring themes or outcomes. By doing so, you develop an intuition for pattern recognition that can be applied to new and unfamiliar situations. 

3. Engage in Using Abstraction & Algorithmic Design for Solutions

Finally, you’ll use abstraction and algorithmic skills to design a solution. First, filter out the “noise” or excess information/questions/complications to focus on what’s truly relevant. This can be achieved by engaging in activities that require critical thinking and prioritization. Then, create simple, step-by-step instructions for the solution. You can start small with everyday tasks and gradually progress to more complex scenarios.

4. Consider Learning Basic Coding Skills

Learning basic programming skills can also be immensely helpful in becoming a computational thinker, as it forces one to think in terms of clear, ordered steps. It’s not the act of programming that’s critical here but the habit of thinking about how to structure solutions to problems.

How Do You Explain Computational Thinking to a Child?

Computational thinking is like being a smart problem-solver. It’s about using your brain to figure things out in a cool, easy way.

Imagine your brain is like a superhero. It has different powers to solve problems. One power helps you take a big problem and split it into smaller parts. This is nice because it helps make the problem easier to solve since you have a few smaller problems instead of one giant one.

Another super power lets you spot things that are alike, which can help you guess what might happen next because it’s happened before.

Then you have a power that helps you see only the really important stuff, so you don’t get distracted by things that don’t help you solve the problem.

And the last superpower helps you make a great plan to solve a problem, but you don’t just follow the plan; you save the plan in case you need to use it again or if you find a new problem that is similar to a problem you already solved—then you can use your previous plan to solve the new problem faster. It’s like having a map that shows you where to go step by step until the problem is solved.

So, computational thinking is about using these superpowers to be really good at figuring things out, without getting stuck, even if it’s something you’ve never seen before.

What are the Pros and Cons of Computational Thinking?

Computational thinking has advantages and drawbacks. Here are some pros and cons to consider. These aren’t used to convince for or against the use of computational thinking in problem solving, but rather to identify areas where nuance may be used for more thoughtful use of this skill.

Pros of Computational Thinking 

1. Systematic Problem Solving: Computational thinking provides a structured approach to problem-solving that can be more efficient and effective than traditional problem solving. It helps break down complex problems into manageable parts, making them easier to understand and solve.

2. Transferable Skills: The skills used in computational thinking, such as decomposition and pattern recognition, are transferable to a wide range of disciplines beyond computer science, from engineering to economics and even to everyday life.

3. Enhances Creativity: By using abstraction to ignore irrelevant details, computational thinking allows individuals to focus on designing creative solutions for the core of a problem.

4. Improves Efficiency: Algorithm design helps in creating processes that save time and resources, which is beneficial in both programming and real-world scenarios.

5. Encourages Logical Thinking: Computational thinking fosters logical reasoning, which can improve decision-making and reasoning abilities in children and adults alike.

Cons of Computational Thinking

1. Oversimplification: Sometimes, by breaking down problems into smaller parts, the subtleties or complexities of the real world can be overlooked, leading to solutions that might not be as effective in practice.

2. Requires Training: Not everyone has innate computational thinking skills; it often requires education and practice to develop these abilities, which can be a barrier for some.

3. Potential Rigidity: An over-reliance on computational thinking can lead to rigid problem-solving methods that may not be suitable for problems that require more nuanced or empathetic approaches.

4. Not Always Intuitive: For people not used to algorithmic thinking, the step-by-step approach can sometimes be counterintuitive and stifle other types of intuitive or creative problem-solving techniques.

Overall, computational thinking is a powerful tool when applied correctly, but it’s also important to be aware of its limitations and to balance it with other problem-solving techniques.

Final Thoughts

The adoption of computational thinking across the curriculum is more than just an educational trend; it’s a necessary evolution to prepare students for a future that is increasingly influenced by technology and complex problem-solving needs. By embracing the principles of computational thinking, educators can unlock new dimensions of learning for their students, fostering a generation that is not only technologically proficient but also adept at critical thinking, creativity and innovation.

For educators, integrating computational thinking into their teaching practices offers an opportunity to enrich traditional subjects with new insights and problem-solving strategies. It encourages a learning environment where students are not passive recipients of knowledge but active participants in their learning journey, equipped to tackle real-world problems with confidence and creativity.

Computational thinking empowers students to navigate the complexities of the modern world, equipping them with the skills necessary to innovate, adapt and thrive in diverse fields. By fostering computational thinking, educators are not just teaching students to code or to solve mathematical problems efficiently; they are nurturing adaptable, analytical thinkers who are prepared for the challenges and opportunities of the future.

The journey to incorporate computational thinking into all areas of education may be challenging, but it is undeniably rewarding. As educators, embracing this shift is part of the commitment to developing future-ready students who are capable of transforming their understanding of the world through logical reasoning, creativity and a systematic approach to problem-solving. In doing so, you are not just preparing students for the jobs of the future; you are empowering them to become the innovative problem solvers and thoughtful leaders of tomorrow.

Further Reading