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Computational Thinking & Artificial Intelligence in K-12 Education: Two Distinct but Still Complementary Worlds
Linnaeus University, Faculty of Technology, Department of computer science and media technology (CM).ORCID iD: 0009-0008-8564-9277
Linnaeus University, Faculty of Technology, Department of computer science and media technology (CM).ORCID iD: 0000-0002-6937-345X
2023 (English)In: Methodologies and Intelligent Systems for Technology Enhanced Learning, 13th International Conference. MIS4TEL 2023 / [ed] Marcelo Milrad, Nuno Otero, María Cruz Sánchez‑Gómez, Juan José Mena, Dalila Durães, Filippo Sciarrone, Claudio Alvarez-Gómez, Manuel Rodrigues, Pierpaolo Vittorini, Rosella Gennari, Tania Di Mascio, Marco Temperini, Fernando De la Prieta, Springer, 2023, p. 207-218Conference paper, Published paper (Refereed)
Abstract [en]

Computational thinking (CT) is an approach to problem-solving that has been introduced in the educational curriculum in K-12 in several countries around the world. This approach is based on a set of concepts and principles that are the foundation on which CT education is based. Artificial intelligence (AI) has recently started being incorporated in K-12 education and therefore some guidelines and frameworks are starting to be defined to allow teachers impart AI knowledge effectively. We conducted a limited scoped literature review aiming at finding some clues as for the interrelation that may exist between CT and AI. Our findings suggest that there are several CT concepts underlying AI techniques thus having CT education could contribute to a better understanding of AI. We also found some challenges of integrating CT and AI as there are some important differences between these two worlds that must be considered when teaching them as part of a whole.

Place, publisher, year, edition, pages
Springer, 2023. p. 207-218
Series
Lecture Notes in Networks and Systems, ISSN 2367-3370, E-ISSN 2367-3389 ; 764
National Category
Computer Sciences
Research subject
Computer and Information Sciences Computer Science, Computer Science
Identifiers
URN: urn:nbn:se:lnu:diva-126316DOI: 10.1007/978-3-031-41226-4_22Scopus ID: 2-s2.0-85172703050ISBN: 9783031412257 (print)ISBN: 9783031412264 (electronic)OAI: oai:DiVA.org:lnu-126316DiVA, id: diva2:1825871
Conference
International Conference in Methodologies and intelligent Systems for Techhnology Enhanced Learning, MIS4TEL 2023, 12-14 July, Guimaraes, Portugal
Available from: 2024-01-10 Created: 2024-01-10 Last updated: 2024-02-01Bibliographically approved

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Zerega, RafaelMilrad, Marcelo

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