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problems that are used in solving datasets using computational thinking

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problems that are used in solving datasets using computational thinking

Burcu Berikan and Selcuk Ozdemir (2020) outline various problems that are used in solving datasets using computational thinking. Computational thinking refers to the approach of solving concepts and methods which are used in the field of computing for advanced processes. The skills of computational thinking are imperative to comprehend when working with computer principles. Mostly, the CT groups offer attention to the people within the computational fields. CT is addressing abstractions that can be automated in various computers. Essentially, CT is a method of solving problems efficiently. Nowadays, CT skills are used in work disciplines of computation as well as the existence of computerized systems within areas of essential innovation within various fields. The importance of CT skills assists in different professional ranges. Again, the powers appear to be the future prerequisite in multiple professions. Augmenting automated systems may lead to the creation of massive data. Thus, CT skills are essential in using a more significant amount of data and solve problems within the computational globe. Currently, an increment in significant data interest has raised eyebrows within the computational field.

In teaching CT skills, it is essential to separate sub-skills as well as address such as the process of abstraction. The critical thing is the CT automation. Computation skills are pegged on level 4. To achieve automation of the ideas, it is imperative to take into consideration all the technical skills which are anchored on the computational capabilities. Algorithmic thinking, as well as abstraction, are essential when it comes to solving problems effectively. Typically, algorithmic skills of thinking are crucial when it comes to conducting a question related to the abstraction. Comparatively, abstraction is a form of algorithmic thinking.  This includes different sub-skills and critical results of reaching abstract solutions.

Visual programming is preferred in the study of CT skills since it is more compatible with the skills and knowledge of students. Programming activities cause meaningful career choices, as well as the self-esteem of learners, becomes fascinating. Programming improves CT skills and puts more emphasis on the problems through the use of automation techniques. Again block-environments are the assessed tools ‘which assist in enhancing CT skills as well as various programming techniques that are needed for learners. Measurement tests apply to learners who are taking programming units at the university levels. Mostly, the cognitive skills used in programming can be used in supporting various CT skills that are used in programming.










Work Cited

Berikan, Burcu, and Selçuk Özdemir. “Investigating “Problem-Solving With Datasets” as an Implementation of Computational Thinking: A Literature Review.” Journal of Educational Computing Research (2019): 0735633119845694.

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