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A Systematic Literature Review of Computational Thinking in K-8 Education Setting Through the Lens of a Pedagogical Content Knowledge Analysis
KTH, School of Industrial Engineering and Management (ITM), Learning, Learning in Stem.
Nanyang Technological University, National Institute of Education, Singapore.
North Carolina State University, College of Education, United States.
State University of New York, The College at Brockport, United States.
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Number of Authors: 52022 (English)In: Proceedings - 2022 IEEE International Conference on Teaching, Assessment and Learning for Engineering, TALE 2022, Institute of Electrical and Electronics Engineers (IEEE) , 2022, p. 810-813Conference paper, Published paper (Refereed)
Abstract [en]

As Computational Thinking (CT) becomes an increasingly necessary skill, it is crucial to examine how CT can be taught in the classroom. Pedagogical Content Knowledge (PCK) is a practical concept to examine how CT education can be developed. This systematic literature review presents the discussion of K-8 teachers' PCK in the implementation of CT- related activities in the classroom. Studies were extracted from Google Scholar's database. Among these studies, 14 articles were deemed to be relevant for a more in-depth examination. Findings from this preliminary literature review suggest that teachers have clear purposes and goals for teaching CT and various instructional strategies for teaching CT. However, the existing studies lacked information about teachers' knowledge and beliefs regarding the methods for assessing students' CT. Practical implications and future directions to enhance K-8 teachers' PCK on CT are discussed in this study.

Place, publisher, year, edition, pages
Institute of Electrical and Electronics Engineers (IEEE) , 2022. p. 810-813
Keywords [en]
Computational thinking, K-8, Pedagogical content knowledge, Primary education, Systematic literature review
National Category
Didactics
Identifiers
URN: urn:nbn:se:kth:diva-334532DOI: 10.1109/TALE54877.2022.00150Scopus ID: 2-s2.0-85163884832OAI: oai:DiVA.org:kth-334532DiVA, id: diva2:1790600
Conference
11th IEEE International Conference on Teaching, Assessment and Learning for Engineering, TALE 2022, Virtual, Online, Hong Kong, Dec 4 2022 - Dec 7 2022
Note

Part of ISBN 9781665491174

QC 20230823

Available from: 2023-08-23 Created: 2023-08-23 Last updated: 2023-08-23Bibliographically approved

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Lin, Tingjun

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CiteExportLink to record
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Citation style
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
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More languages
Output format
  • html
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  • asciidoc
  • rtf