The effect of computer science unplugged on abstraction as a sub-component of computational thinking


Gün-Tosik E., GÜYER T.

Thinking Skills and Creativity, vol.53, 2024 (SSCI) identifier

  • Publication Type: Article / Article
  • Volume: 53
  • Publication Date: 2024
  • Doi Number: 10.1016/j.tsc.2024.101552
  • Journal Name: Thinking Skills and Creativity
  • Journal Indexes: Social Sciences Citation Index (SSCI), Scopus, EBSCO Education Source, Psycinfo
  • Keywords: Abstraction skill, Computational thinking skill, Computer science, Computer science unplugged
  • Gazi University Affiliated: Yes

Abstract

Since computational thinking is a high-level cognitive skill and its conceptual framework has not yet been clarified, the assessment of this skill is problematic. While there is no consensus in the literature about the components of computational thinking, the abstraction component is located at a point where opinions intersect. In addition, it is predicted that computer science unplugged activities will improve computational thinking, and there is limited research examining this effect. As a result, this research aims to demonstrate the alleged effects of computer science unplugged activities on abstraction skill which is considered the critical component of computational thinking. The study, which was planned with a mixed methods research design, lasted 8 weeks. Quantitative data were obtained from the abstraction skill test developed by the researchers, while qualitative data were obtained from observations and task- based interviews after each activity. Quantitative findings showed that computer science unplugged activities significantly improve abstraction skills and thus computational thinking. Qualitative findings not only revealed that developments in the six abstracting steps caused this significant difference but also identified abstracting steps where the effect of each activity was limited. Suggestions for organizing activities to improve these steps are given. Finally, suggestions are presented for the conceptual framework of computational thinking based on abstraction.