In 1974, Aho, A.V | Hopcroft, J.E. and Ullman, J.D presented an article about the study of the algorithm saying that: the algorithm is the heart of the computer science.
In fact, this can be corroborated by the advancement of the high-level languages that was developed at now.
In addition, Computational thinking is like a process related to the expression of solutions such as the computational steps or algorithms that can be released by a computer. (Cuny, Snyder, & Wing, 2010; Aho, 2011; Lee, 2016).
Computational thinking demands the acknowledgment of computer faculty to formula issues to be managed by a machine and order algorithms that can be processed by a computer.
Learning Computer Science is so necessary because is the major area to develop computational thinking.
Why? They are inherently linked.
Paraphrasing Aro,
Computational thinking is at the heart of computer science
and its practices are traced by the routines below:
Practice 1. Identifying and Depicting Computational Problems
Practice 2. Evolving and Operating Abstractions
Practice 3. Building Computational Artifacts
Practice 4. Testing and Refining Computational Artifacts
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