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Computational Thinking Design Application for STEAM Education
Institute of Data Science and Digital Technologies, Vilnius University, Vilnius, Lithuania.
KTH, School of Industrial Engineering and Management (ITM), Learning.ORCID iD: 0000-0002-5184-4743
Institute of Data Science and Digital Technologies, Vilnius University, Vilnius, Lithuania.
Institute of Data Science and Digital Technologies, Vilnius University, Vilnius, Lithuania.
2023 (English)In: Studies in Computational Intelligence, Springer Nature , 2023, Vol. 1084, p. 1-26Chapter in book (Other academic)
Abstract [en]

Motivation: Integrating STEAM education and Computational Thinking (CT) provides the skills of analysis, problem-solving and creativity enhancement necessary to twenty-first century citizens. STEAM education can also be seen as a bridge, reinforcing the link between science, schools and industries. Teachers play an important role as mediators and mentors. The difficulties faced by teachers are not only a lack of knowledge of specific disciplinary terms but also the context in which they are applied, such as the computational context. Problem: In order to clarify the context for teachers, and extend their competence beyond knowledge of basic concepts and terminology, guidance on CT and STEAM education integration in schools has emerged as a pressing problem. Solution: A Design Thinking and CT practices taxonomy interaction framework is proposed, providing scaffolding to teachers as they struggle to understand the context of CT implementation in STEAM education. Results: The proposed framework provides concrete guidance to educators in planning class activities, and choosing suitable educational practices in order to engage students. Implication: The results support educators looking for guidance in the integration process and those seeking to incorporate integrated aspects of students’ STEAM learning into teaching practice.

Place, publisher, year, edition, pages
Springer Nature , 2023. Vol. 1084, p. 1-26
National Category
Pedagogy Educational Sciences
Identifiers
URN: urn:nbn:se:kth:diva-338439DOI: 10.1007/978-3-031-24453-7_1Scopus ID: 2-s2.0-85149933573OAI: oai:DiVA.org:kth-338439DiVA, id: diva2:1812685
Note

QC 20231116

Available from: 2023-11-16 Created: 2023-11-16 Last updated: 2025-02-18Bibliographically approved

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Pears, Arnold

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CiteExportLink to record
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