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Developing Algorithmic Thinking Through Computational Making

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Data Science: New Issues, Challenges and Applications

Part of the book series: Studies in Computational Intelligence ((SCI,volume 869))

Abstract

Programming needs algorithmic thinking—the main component of computational thinking. Computational thinking is overlapping with many digital age skills necessary for digital learners. However, it is still a challenge for educators to teach CT in an attractive way for learners, also to find support to CT teaching content design and assessment. To address this problem, the literature review on CT in education was conducted and the main ideas of CT implementation and assessment were identified. The results show that modern technologies are widely used for learning enhancement and algorithmic thinking improvement. The implications of these results is that modern technologies can facilitate effective learning, CT skills gaining and learning motivation.

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Acknowledgements

This project has received funding from European Social Fund (project No 09.3.3-LMT-K-712-02-0066) under grant agreement with the Research Council of Lithuania (LMTLT).

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Authors and Affiliations

  1. Institute of Data Science and Digital Technologies, Vilnius University, Vilnius, Lithuania

    Anita Juškevičienė

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  1. Anita Juškevičienė
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Correspondence to Anita Juškevičienė .

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Editors and Affiliations

  1. Institute of Data Science and Digital Technologies, Vilnius University, Vilnius, Lithuania

    Gintautas Dzemyda

  2. Institute of Data Science and Digital Technologies, Vilnius University, Vilnius, Lithuania

    Jolita Bernatavičienė

  3. Systems Research Institute, Polish Academy of Sciences, Warsaw, Poland

    Janusz Kacprzyk

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Juškevičienė, A. (2020). Developing Algorithmic Thinking Through Computational Making. In: Dzemyda, G., Bernatavičienė, J., Kacprzyk, J. (eds) Data Science: New Issues, Challenges and Applications. Studies in Computational Intelligence, vol 869. Springer, Cham. https://doi.org/10.1007/978-3-030-39250-5_10

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