# Computational thinking is set to change the way we work and the skills we will need in the future

Prateek Karkare

2 years ago | 4 min read

World is changing and it is changing at a blinding pace. Problem solving, analyzing the validity of solutions and spotting patterns in data — these are all essential skills for the workplace of the future and are now taught in schools grouped under the title of computational thinking. This term has been much discussed amongst educationalists as schools get to grips with a new computing curriculum designed to equip pupils with such skills, and to reduce the skills gap between education and the workplace. So what actually is computational thinking?

It is the thought processes involved in problem solving, so that the solutions are represented in a form that can be effectively carried out by an information-processing agent, such as a computer. Core concepts involved in computational thinking include but are not limited to

• Algorithmic thinking — developing a set of instructions or sequence of steps to solve a problem;
• Decomposition — breaking a problem down into its component parts;
• Abstraction — hiding detail or removing complexity without losing the important detail required to solve a problem;
• Pattern matching — looking at ways in which the objects and ideas are alike and different

I don’t want to suggest that computational thinking or its core tenets are only essential for tasks involving coding and things related to information technology or computer science. I would argue that these skills equip an individual to demonstrate high level of creativity and innovative thinking.

In this rapidly changing world it is often said that students today are training to work in jobs that don’t currently exist. For this reason, students need to learn how to grasp new ideas quickly. Computational thinking, helps to acclimatize learners to novel ideas — and the more exposure to working with and generating new ideas, the better it is for the student.

## Algorithmic Thinking — The Creative Process

Algorithmic thinking is taking something with a discernible sequence or pattern and breaking it down into steps or instructions. Algorithms are deeply embedded into today’s technology. Given that algorithms often have a known beginning and an end, creativity might seem to be an oxymoron to algorithm. But the steps of an algorithm don’t necessarily have a prescribed form. Determining the sequence of those steps, the building of the algorithm itself is part of the creative process.

Algorithmic thinking requires creativity. Take for example planning a vacation. Does it make sense to visit more places in a given time or less places with more time at each place? Is the journey more important than the destination? These questions aren’t entirely philosophical in nature. While the beginning and end of the vacation are fixed the different requirements create a whole new experience and a different set of steps. A lot of daily tasks and games can teach students to learn and imbibe algorithmic thinking. For example writing recipes step by step, arranging events in the correct order, finding patterns among different objects.

## Decomposition takes an object or an idea and breaks into parts. For example physicists continuously decompose the basic ideas to further answer more fundamental questions. Gravity is an old idea, Newton when saw the apple falling to the ground asked many questions about the event but while formulating gravity he must have decomposed his thoughts, what are the objects and events involved? Apple, earth, tree, direction of motion, air around and so on. The parts don’t need to be abstracted but abstraction pairs well with decomposition, so two are often used together. Abstraction is the ability to distill something to its essence, the process of abstraction is inherently creative.

Decomposition sometimes goes together with deconstructionism. A deconstructionist theater plays with tropes and ideas of a genre. In the physical world, deconstructed objects become collages. Chefs specializing in molecular gastronomy often deconstruct dishes providing new ways of exploring recognizable flavors. When students use decomposition to break down an idea, the resultant parts become seeds or raw materials for new ideas. If students use decomposition to determine the constituents of an object those parts could be rebuilt into something new or mixed and matched as an abstracted idea. Similarly a deconstructed sentence could become a template to create their own sonnets!

## Pattern Matching — Correlate, Contrast, Create

Pattern matching is about looking at ways in which the objects or ideas are similar or different. Sometimes there is a discernible way or method in which the ideas or objects are ordered other times they might have a logic to their grouping. Depending on the problem discovering a pattern or a common link can lead to a eureka moment!

Observing patterns can be very individualized. Students usually create their own devices, which draw upon their own interests, to see patterns though their own experiences and learning. There are lot of tools to nurture, encourage and teach pattern matching and recognition. Writing poems from poetic forms, grouping objects together, forming series etc. are great tools to encourage computational thinking and creativity.

## Creativity, Computational Thinking and Closing Remarks

While each of these thinking skills have their own specified purposes but combining these together equips an individual to generate novel ideas. The combining approach also aligns with the real world tasks. For example managing a project involves decomposing it into individual tasks, matching people with tasks, creating iterative tasks and so on.

I personally feel an important aspect of computational thinking and learning computational thinking which is often overlooked is active engagement of the student which involves interacting with rather passive materials like objects, physical games, cards and the environment. Learning computational thinking with passive objects sounds antithetical but it encourages active involvement of the brain. Videos, mobile applications and screen while open avenues to create innovative ways to teach computational thinking come with a downside. An animated and colorful active video and computer application takes a lot of cognitive load off the brain and stimulates the pleasure centers without much effort of the brain. This is an active research area and there are lot of arguments for and against but nevertheless computational thinking is an important skill for the upcoming generation to shape the future.

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Prateek Karkare

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