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Developing Computational Thinking in Compulsory Education - Implications for policy and practice

Author

Listed:
  • STEFANIA BOCCONI

    () (Institute for Educational Technology, CNR (Italy))

  • AUGUSTO CHIOCCARIELLO

    () (Institute for Educational Technology, CNR (Italy))

  • GIULIANA DETTORI

    () (Institute for Educational Technology, CNR (Italy))

  • ANUSCA FERRARI

    () (European Schoolnet)

  • KATJA ENGELHARDT

    () (European Schoolnet)

Abstract

In the past decade, Computational Thinking (CT) and related concepts (e.g. coding, programing, algorithmic thinking) have received increasing attention in the educational field. This has given rise to a large amount of academic and grey literature, and also numerous public and private implementation initiatives. Despite this widespread interest, successful CT integration in compulsory education still faces unresolved issues and challenges. This report provides a comprehensive overview of CT skills for schoolchildren, encompassing recent research findings and initiatives at grassroots and policy levels. It also offers a better understanding of the core concepts and attributes of CT and its potential for compulsory education. The study adopts a mostly qualitative approach that comprises extensive desk research, a survey of Ministries of Education and semi-structured interviews, which provide insights from experts, practitioners and policy makers. The report discusses the most significant CT developments for compulsory education in Europe and provides a comprehensive synthesis of evidence, including implications for policy and practice.

Suggested Citation

  • Stefania Bocconi & Augusto Chioccariello & Giuliana Dettori & Anusca Ferrari & Katja Engelhardt, 2016. "Developing Computational Thinking in Compulsory Education - Implications for policy and practice," JRC Working Papers JRC104188, Joint Research Centre (Seville site).
  • Handle: RePEc:ipt:iptwpa:jrc104188
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    File URL: https://publications.jrc.ec.europa.eu/repository/handle/JRC104188
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    Citations

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    Cited by:

    1. World Bank, 2019. "Children Learning to Code," World Bank Other Operational Studies 31528, The World Bank.
    2. Margarida Rodrigues & Federico Biagi, 2017. "Digital technologies and learning outcomes of students from low socio-economic background: An Analysis of PISA 2015," JRC Working Papers JRC106999, Joint Research Centre (Seville site).
    3. Ramón García-Perales & Ascensión Palomares-Ruiz, 2020. "Education in Programming and Mathematical Learning: Functionality of a Programming Language in Educational Processes," Sustainability, MDPI, Open Access Journal, vol. 12(23), pages 1-15, December.

    More about this item

    Keywords

    Computational Thinking; Coding; Programming; Algorithmic Thinking; 21st century skills; Innovation in Education; education policy; compulsory education; learning innovation;
    All these keywords.

    JEL classification:

    • I20 - Health, Education, and Welfare - - Education - - - General
    • I21 - Health, Education, and Welfare - - Education - - - Analysis of Education
    • I23 - Health, Education, and Welfare - - Education - - - Higher Education; Research Institutions
    • I28 - Health, Education, and Welfare - - Education - - - Government Policy
    • I29 - Health, Education, and Welfare - - Education - - - Other

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