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DOI: 10.14569/IJACSA.2022.0130571
PDF

Improving Computational Thinking in Nursing Students through Learning Computer Programming

Author 1: Leticia Laura-Ochoa
Author 2: Norka Bedregal-Alpaca
Author 3: Elizabeth Vidal

International Journal of Advanced Computer Science and Applications(IJACSA), Volume 13 Issue 5, 2022.

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Abstract: Computational thinking is a fundamental skill for problem-solving, it uses computational concepts and other types of thinking such as algorithmic. The experience of improving computational thinking in nursing students using block-based programming environments such as Code.org, Lightbot, and the Python textual programming language is described. The results obtained are analyzed by applying a pre-and post-test of computational thinking to the students. The methodological design is quasi-experimental since it did not work with a control group. The study group was made up of 30 students from the Professional School of Nursing of the National University of San Agustin de Arequipa. The results show that teaching programming allows the understanding of computational concepts and improves computational thinking. It is concluded that block-based programming environments and the Python language facilitate the development of algorithmic thinking and computational thinking.

Keywords: Computational thinking; computational thinking assessment; computational thinking test; programming; programming environments

Leticia Laura-Ochoa, Norka Bedregal-Alpaca and Elizabeth Vidal. “Improving Computational Thinking in Nursing Students through Learning Computer Programming”. International Journal of Advanced Computer Science and Applications (IJACSA) 13.5 (2022). http://dx.doi.org/10.14569/IJACSA.2022.0130571

@article{Laura-Ochoa2022,
title = {Improving Computational Thinking in Nursing Students through Learning Computer Programming},
journal = {International Journal of Advanced Computer Science and Applications},
doi = {10.14569/IJACSA.2022.0130571},
url = {http://dx.doi.org/10.14569/IJACSA.2022.0130571},
year = {2022},
publisher = {The Science and Information Organization},
volume = {13},
number = {5},
author = {Leticia Laura-Ochoa and Norka Bedregal-Alpaca and Elizabeth Vidal}
}



Copyright Statement: This is an open access article licensed under a Creative Commons Attribution 4.0 International License, which permits unrestricted use, distribution, and reproduction in any medium, even commercially as long as the original work is properly cited.

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