Characterizing Computational Thinking for Tertiary Education Learning

  • Salman Firdaus Sidek Faculty of Art, Computing and Creative Industry, Sultan Idris Education University, Malaysia
  • Maizatul Hayati Mohamad Yatim Faculty of Art, Computing and Creative Industry, Sultan Idris Education University, Malaysia
  • Che Soh Said Faculty of Art, Computing and Creative Industry, Sultan Idris Education University, Malaysia
Keywords: Abstraction, Algorithm, Computational thinking, Decomposition, Tertiary education

Abstract

As the term computational thinking was just introduced into Malaysian education landscape in early 2017, the knowledge about it is still limited. Therefore, a literature review mapping has been done in order to identify its features and global research pattern related to this skill. IEEEXplore, Science Direct, and Web of Science were selected as the main sources of the articles out of 13 other repositories. The total of 325 articles were found by using computational thinking with punctuation marks " " as keywords via selected repositories. Out of this total, 109 articles have met the criteria and only 86 articles were referred together with another 30 additional multi-type references. Finally, 66 features were generated from 29 referred articles related to the characterization of computational thinking skill. Among these features, three with the highest frequency were identified. It made up of two features that often assessed at tertiary education level namely algorithm and abstraction as well as two other features that are said as the true essence of the skill namely abstraction and decomposition with one of them is overlapped. Therefore, these three features are suggested to be in the list of variables of any research related to tertiary education learning.

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Published
2020-07-30
How to Cite
Sidek, S. F., Mohamad Yatim, M. H., & Said, C. S. (2020). Characterizing Computational Thinking for Tertiary Education Learning. Journal of Contemporary Issues and Thought, 10, 58-69. https://doi.org/10.37134/jcit.vol10.sp.6.2020