If you think computational thinking means you have to solve problems like a computer scientist, you’re not necessarily wrong. However, there’s much more to it than that, and let’s be honest, thinking like a computer scientist all day sounds a little bit exhausting.
In reality, computational thinking is a fairly simple and highly efficient approach to problem-solving, allowing one to discover a solution through the steps of decomposition, pattern recognition, abstraction, and algorithm design.
While that might sound highly complex and technical, it’s actually a process that children begin to develop naturally at an early age. In fact, the fundamental capacities for problem decomposition begin to emerge in preschool years and continue to develop throughout early childhood.
And that is just the beginning stage of computational thinking, as children develop these skills well into adulthood. Providing structure and guidance during early education can help nurture these emerging computational skills.
If you’re new to the concept of computational thinking, this blog will further break down exactly what it is, why it’s an important skill to start developing at an early age, and how educators can encourage it in the classroom and at home.
The Importance of Computational Thinking for Young Learners
Computational thinking is an important skill for children to hone, as it helps them know how to manage problems they encounter both in the classroom and in life beyond. Additionally, computational thinking is considered a basic skill that is necessary for job opportunities and success, as defined by President Obama’s 2016 Computer Science for All initiative.
If we can help young children learn to rely on computational thinking as a way to approach learning and see the world, then we can begin to focus less on how they acquire basic knowledge and more on how they apply it.
According to Seymour Papert, an early pioneer of computational thinking, the essence of computational thinking is “what we can do while interacting with computers, as extensions of our mind, to create and discover.” Papert reminds us that the focus of computational thinking should not be on the machine but on the mind. Ultimately, the goal of computational thinking is the ability to forge ideas.
How Computational Thinking is Applied
Computational thinking skills are applied all around us, and not just in the science, technology, engineering, and math (STEM) fields. The fundamentals of computational thinking—decomposition, pattern recognition, abstraction, and algorithmic thinking—are important to all learning.
Anytime we approach a problem by breaking it down or focusing on what we know we can tackle first, we are using computational thinking without realizing it. This type of thinking doesn’t require a worksheet or some sort of final presentation of your learning, either. It can be as simple as making a shopping list, organizing items on your desk, or doing the most important things on your to-do list first.
In fact, studies using Sphero robots have found that computational thinking doesn’t have to be practiced in front of a computer to be effective, and that it’s important for activities in various subjects to be designed to foster computational thinking. Moreover, Sphero’s newest programmable robot, Sphero indi, inspires computational thinking without the use of an app or electronic device if preferred. This allows the focus to be on the learning and less so on the computer itself.
Real-World Examples of Computational Thinking
When we start to pay attention to computational thinking, we will discover real-world examples of it being used everywhere. This exploratory process allows us to recognize ways in which we can further develop these skills in young learners.
1. Decomposition
Imagine your favorite food. Maybe it’s a slice of pizza, a cheeseburger, or a fresh salad. Are you able to sit down and eat it all at once, in one big bite? Probably not. Each time you take a bite of the food and chew it up, you are quite literally breaking down the problem of “how do I eat all of this?” into smaller pieces. Any time you simplify something or break a problem down into more manageable parts, you are demonstrating decomposition.
2. Pattern Recognition
Patterns are everywhere. Routines, habits, and traditions are all patterns that we can recall to help us understand or solve an unfamiliar problem. For example, most kids today would not know how to operate a payphone, but the pattern or habit of dialing a phone number on a smartphone would most likely assist them in figuring it out.
3. Abstraction
Abstraction is integral to just about everything we do. Being able to focus on what’s important and disregarding the irrelevant is a life skill that helps with time management and organization. Without abstraction, we would have a difficult time finding meaning in all the information we take in—meaning comes from filtering out the distractions and being left with what is most important.
4. Algorithm Design
Algorithm design applies the learnings from the previous stages to develop a set of rules that, when followed, will resolve the issue at hand. Algorithms exist all around us and often provide structure to learning and problem-solving. Rules for a board game are a great high-level example of algorithmic design and thinking, as they provide a set of steps to perform a given task. If the instructions aren’t followed correctly, then the game cannot be played.
Developing Computational Thinking Skills In the Classroom and Beyond
Although these are skills applied in our daily lives, many educators may feel out of their element when approaching computational thinking. Here’s what our Sphero Heroes recommend administrators can do to build teachers’ confidence in developing these skills in the classroom.
“Fostering relationships within the community allows thought-leaders outside of the school to share their expertise surrounding computational thinking with students,” says Nicholas Provenzano, Makerspace Director at University Liggett School in Michigan and Sphero Hero. “By fostering community engagement, administrators can support the work teachers are doing in the class by connecting them with people who solve problems outside of class.”
Brandy New, Instructional Technology Coordinator and Sphero Hero, suggests, “Look for opportunities for professional development for your staff on computational thinking. Many educators are not comfortable with this content and need to build their skillset and confidence. Then, celebrate them when you see them applying it in their classrooms!”
We also know that fostering environments for growth extends beyond the classroom, as education researchers predict that STEM will play a larger role in home life by 2030. This makes at-home STEM education and computational thinking important for enriching a child’s development.
Teach Young Learners Computational Thinking Skills
Computational thinking isn’t just beneficial for computer scientists or those going into STEM-related fields; it’s beneficial for all. By incorporating computational thinking into the everyday lives of young learners, we can ensure they are equipped with the best set of tools for solving life’s smallest and biggest problems.
Encouraging computational thinking in the classroom and in the personal lives of students is made simple with Sphero. Learn more about the Sphero indi and how it inspires computational thinking and STEM learning for young students in an approachable and affordable way.
Educators can also help develop these skills in K-12 students with Sphero’s programmable robots and STEM kits, designed to teach decomposition, pattern recognition, abstraction, and algorithm design through play.
