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On the Future of Computational Thinking Education: Moving beyond the Digital Agenda, a Discourse Analysis Perspective

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  • Vladimiras Dolgopolovas

    (Institute of Data Science and Digital Technologies, Vilnius University, LT-08412 Vilnius, Lithuania)

  • Valentina Dagiene

    (Institute of Data Science and Digital Technologies, Vilnius University, LT-08412 Vilnius, Lithuania)

Abstract

This article explores the development directions of the phenomenon of Computational Thinking (CT) from the perspectives of discourse analysis. The motivation is based on the understanding of CT as an advanced educational approach, methodology, and community, aimed at a set of learners’ digital and further competences having a huge impact on modern education and society. The novelty of this study lies in the attempt to look holistically at CT and its perspectives, considering it as an evolving phenomenon per se, leaving aside discussion on its internal characteristics or applications. The study utilizes a comprehensive analysis, applying discourse analysis and social semiotics methods. The results present the most trended storylines associated with CT and its context, providing a thorough introduction to the CT discursive landscape. The findings and discussion present a reflective insight into the discursive landscape directions, focusing on meaning-makers and their identities, the transformative and transductive potential of CT, observing the phenomenon’s development paths from a metaphorical perspective and positioning it towards the development of the socio-technical networks it mediates. In the conclusion, the options for development and possible trends in the reconstitution of the CT phenomenon are outlined.

Suggested Citation

  • Vladimiras Dolgopolovas & Valentina Dagiene, 2021. "On the Future of Computational Thinking Education: Moving beyond the Digital Agenda, a Discourse Analysis Perspective," Sustainability, MDPI, vol. 13(24), pages 1-21, December.
    • Handle: RePEc:gam:jsusta:v:13:y:2021:i:24:p:13848-:d:702777
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    Cited by:

    1. Ting-Chia Hsu & Ching Chang & Lung-Hsiang Wong & Guat Poh Aw, 2022. "Learning Performance of Different Genders’ Computational Thinking," Sustainability, MDPI, vol. 14(24), pages 1-16, December.
    2. Vladimiras Dolgopolovas & Valentina Dagiene, 2022. "On Semiotics Perspectives of Computational Thinking: Unravelling the “Pamphlet” Approach, a Case Study," Sustainability, MDPI, vol. 14(4), pages 1-22, February.
    3. Valentina Dagiene & Vladimiras Dolgopolovas, 2022. "Short Tasks for Scaffolding Computational Thinking by the Global Bebras Challenge," Mathematics, MDPI, vol. 10(17), pages 1-30, September.

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