Ways of Using Computational Thinking to Improve Students' Ability to Think Critically

Introduction

The prospect of thinking ability is observed from a critical viewpoint, given its usability in solving definite and indefinite problems. Based on the culture of thinking ability, students are often faced with the dilemma of appropriately gaining solutions to their issues that has an analytical pattern (Agbo et. Al., 2019). The correlation between computational thinking (CT) and a student's thinking ability is ascertained to be linked with cognitive processes [6]. In terms of this, the application of computational thinking is viable through extensive digging into the cognitive systems which are responsible to help humans utilise natural problem-solving qualities. Evidence from earlier studies has strongly focused on the usage of the outermost circle which is the cognitive process which becomes the core fundamental for developing adequate computational thinking skills (Abdullah et al., 2019).

Following the above-stated notion, the term computational thinking typically defines the activity of witnessing a problem and approaching it through a systematic pattern. This systematic approach to solving issues is noted to be detrimental to inducing higher thinking skills among the masses, especially students (Alam, A., 2022). With respect to problem-solving qualities, the majority of corporate and business sector runs upon informed decision-making, which is a residue of analytical problem-solving, thereby, it is of utmost vitality to train students in recognising problems and issues through a specific manner and thus upscale their existing skill sets (Avila et al., 2021) and broaden their knowledge horizon.

CT is a problem-solving technique that depicts on thoughts and procedures from computer science to implements complex problems in an organised and effective manner. It encompasses collapsing down problems into subproblems, convenient components, recognizing patterns and perceptions, and originating algorithms to resolve them. Employing CT to learning can help to enhance students' ability to think significantly. Here are some ways to achieve that is Problem Decomposition, Pattern Recognition, Abstraction, Algorithm Design, Data Analysis, Logical Thinking, Problem Formulation, Iterative Approach, Debugging and Troubleshooting, Collaboration, Real-World Context, Multidisciplinary Connections, Ethical Considerations, Creativity and Reflection (Agbo et. Al., 2019). The brief description of each approach is given here.

Problem Decomposition: In this approach, students must teach about to break down large or complex problems into small sub-problems, which is more manageable and easier to handle. This benefits the students to recognise the problem's construction and recognize possible explanations. In a scholastic framework, problem decomposition helps students’ approach to solve complex assignments, projects, or even exam questions more efficiently and effectively (Agbo et. Al., 2019, Abdullah et al., 2019). By demonstrating students to division of a problems, tutor can improve their fault-finding skills and thinking skills, as students learn to analyse, arrange, and disentangle each component one by one. This methodology also promotes coordinated thinking, organised planning, and better time administration. There are few advantages of problem decomposition like Clarity, Focus, Efficiency, Parallelism, Reusability and Debugging.

Steps involved in problem decomposition is given as:

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  Understanding of the problem: Ahead of breaking down the problem into sub-problems, confirm a clear understanding of the overall problem's range and situation.

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  Identification of sub-problems: Examine the problem and recognize different sections or portions that can be attended separately. Each sub-problem should be a self-contained, answerable problem, so that it would be helpful in solving the actual problem.

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  Arrangement of sub-problems into a hierarchical order: Arrange the sub-problems in such a manner, where higher-level sub-problems may be determined by on the resolutions of lower-level sub-problems.

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  Start solving subproblems: Start finding the solution of the sub-problems one by one and solve the entire sub-problems to get the solution of main problem. As students solved every sub-problem, so it contributed to solve the large problem.

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  Integration of results: Once the sub-problems are solved, integrate their results to reach the solution of a large problem.