When you think of coding, you probably envision a person sitting at a computer and typing out lines of code – producing letters, numbers, and symbols that instruct the machine on what to do.
But how do they know what code to write, and how can a youngster learn to translate their thoughts into these lines of code? The solution is discovered through a process known as computational thinking.
In addition to being essential to the coding process, computational thinking is a key life and career skill. It is the driving force behind a number of the leading reasons why children should learn to code, particularly to encourage problem-solving and creativity.
What is the definition of Computational Thinking?
Computational thinking is merely a skill for addressing problems. Imagine that your hamper is filled with dirty clothes. The problem is that you require clean clothing. The obvious option is to clean the garments.
That sounds straightforward, correct? In reality, however, there are numerous complexities involved in the procedure. Initially, you may divide the process into three steps: washing, drying, and folding the clothes.
However, each of these processes includes substeps. When washing the garments, it would help if you properly loaded the washer, measured the detergent, added fabric softener, etc. You must also examine for specific stains that may require different treatments.
Imagine attempting to compose a set of cleaning instructions. Doesn’t it sound complicated? Computer science studies translating these complex procedures into lines of code in a programming language (e.g., Scratch coding, Python, JavaScript). Computational thinking facilitates this by providing a framework for doing so.
Four pillars comprise the computational thinking process.
Decomposition — Separating the issue into smaller, more manageable pieces
Pattern recognition — Identifying similarities between and within problems
Abstraction — Concentrating on only the essential components of a topic and discarding extraneous particulars
Algorithm Design — Developing a step-by-step solution to the problem is algorithm design.
Instructing Computational Reasoning
Educators typically teach computational thinking by focusing on the four pillars we described previously. In addition to its usage in computer programming, each of these building blocks has real-world applications that may be easily introduced to elementary school students.
Decomposition
Even day-to-day activities can be utilized to introduce young children to decomposition. You can help deconstruct any complex problem by identifying all the various tasks involved.
For instance, the routine of getting ready for school in the morning can be utilized. This will be broken down into steps, such as getting dressed and acquiring schoolbooks. Each of these processes can be further broken down into smaller steps. In doing so, they gain knowledge of decomposition.
Pattern recognition
Pattern recognition requires generalizations about things and processes. As with numerous computational thinking skills, children are already doing this; they only need to comprehend how they are doing it.
When children encounter a chair, they recognize it as such. Even if they have never seen the chair before, this is true. You can bring this procedure to their attention by asking the following inquiries. This can also be done with any other familiar object to the infant. How did you determine that to be a chair? What feature do all chairs share? What is the distinction between a chair and a sofa? What about a bed and a chair?
Abstraction
Abstraction is all about learning to disregard irrelevant particulars. Video games are a wonderful tool for teaching this ability. There are brilliant lights and intricately detailed items everywhere they look in the game, but they can locate the crucial elements for achieving their objective.
Teaching abstraction and pattern recognition can go hand in hand. Referring to the chair example, you can ask the child to describe a chair and help them determine which aspects are essential and which are not. Essentially, this is incorporating critical thinking into the procedure. Does a chair have to be made of wood? Do they require four legs?
Algorithm design
A child seated in front of a blackboard containing an algorithm.
In the first three pillars, students identify specific steps, recognize patterns, and eliminate excessive information. The final phase, algorithmic design, combines the preceding steps, patterns, and abstractions into a set of instructions.
The most effective way to instruct children about algorithm design is by using a basic example algorithm. Instead of preparing for school, you can concentrate on a specific step, such as getting dressed.
You can walk them through their actions, including any crucial aspects of sequencing and conditionals — for instance, if your shirt has buttons, then button them. Lastly, you can discover opportunities to develop additional problem-solving abilities, such as debugging, if, for instance, the student puts their shirt on backward.
With this final pillar in place, your learner has everything necessary to begin applying computational thinking abilities!
Final Reflections
Learning computational thinking is essential to becoming a programmer, but its application to problem-solving makes it an essential component of any lesson plan.
This skill applies to a 10-year-old playing with Legos, a high school student learning algebra, and a professional career building a new corporate marketing strategy. Even automation and artificial intelligence, two of the most prominent technological developments of the 21st century, are all about integrating computer thought into the actual world.
