Home > Blog > Problem Solving and Computational Thinking Skills

  • By Seema Narang
  • December 24, 2016

Problem Solving and Computational Thinking Skills

This is a complex quote on the objectives of Education. To understand this objective, let’s break it further into smaller objectives:

  • Prepare young people for newer types of jobs
  • Prepare young people to use the technologies that are not yet invented
  • Prepare young people to solve problems

If you look at the first two objectives, these appear to be challenging objectives to achieve! If the technology is not invented yet, how can we train the younger generation to prepare for the newer jobs when we don’t know it ourselves? However, if you train students on problem-solving approach, you don’t need to prepare them for the rest. They would be able to meet any challenge in life.

So, what is problem-solving and how do we teach it to students?

Problem-solving is a higher order cognitive process that helps you understand the goal of the problem and what rules can you apply to solve the problem. It involves logical reasoning and interpretation. It can be applied to any situation, subject, or context. The problem-solving approach helps to develop Computational Thinking (CT) skills in students. These skills include the ability to:

  • think algorithmically;
  • think in terms of decomposition;
  • identify patterns and think in generalisations;
  • think in abstractions; and
  • think in terms of evaluation.

Algorithm thinking is the ability to break a task into a sequence of sub-tasks to reach the solution. For example, baking a cake involves doing some tasks in a sequence. It would also involve identifying what all is available and what are the constraints/ conditions for performing the sub-tasks.

Decomposition is the ability to break down a larger problem into smaller components and then solving each of them. For example, hosting a party would include booking the venue, inviting guests, identifying the menu etc.

Generalisation involves identifying patterns, similarities and connections, and figuring out how these can be used. It is a process of reaching a solution based on previous solutions to similar problems, and building on prior experience.

Abstraction is the process of making a problem more understandable through reducing the unnecessary detail. The skill in abstraction is in choosing the right detail to hide so that the problem becomes easier, without losing anything that is important. A key part of it is in choosing a good representation of a system. For example, to understand the working of a car, you need to focus on wheel and engine separately.

Evaluation is the process of ensuring that a solution is a good one and it meets the goal. The solution need to be evaluated in terms of parameters such as correctness, speed, economically viable, and easy to implement.

To conclude, computational thinking enables students to recognize when and how technology can boost their own critical-thinking, creative and problem-solving skills in order to find innovative solutions to real-world problems. To prepare students for a future that we can’t yet imagine, it’s important to empower them to become lifelong learners and equip them with the skills to face future challenges resourcefully and creatively.

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