A bibliometric analysis of computational thinking skills: definition, components and assessment tools

This paper provides an in-depth analysis of computational thinking (CT) skills and their assessment. It discusses the definition and components of CT. Various assessment tools, such as surveys, exams, self-assessment instruments, and performance tests, are explored. A bibliometric analysis reveals a growing trend in publications related to CT skills since 1993. The study employs citation analysis, co-citation analysis, and co-keyword analysis, identifying clusters of related work and emphasizing the core ideas of CT skills, their components, and their assessment. The findings highlight the intellectual synergy between publications, particularly the strong conceptual and thematic links between works that often cite each other. The discussion underscores the importance of CT components like abstraction, decomposition, and algorithms, as foundational elements across disciplines, particularly in education and computer science. Additionally, the integration of CT into educational curricula, such as robotics, programming, and STEM, demonstrates its growing significance. The conclusion identifies several gaps in the current understanding of CT, particularly the need for a standardized, widely accepted definition that encompasses all aspects of CT. It also emphasizes the limited focus on the assessment of CT skills and calls for the development of validated and reliable assessment tools. Furthermore, the paper highlights the need for more research on the impact of teacher training programs on CT development, to ensure effective integration at the school level.

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Publication Details

Journal
Research and Practice in Technology Enhanced Learning
Published
2024-12-03
DOI
https://doi.org/10.58459/rptel.2025.20035
Citations
1
Primary Topic
Online Learning and Analytics
Type
article
Field-Weighted Citation Impact
0.41

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article

A bibliometric analysis of computational thinking skills: definition, components and assessment tools

Nur Aira Abd Rahim, Priscilla Moses, Su Luan Wong, Mas Nida Md. Khambari et al.
1 citations
Research and Practice in Technology Enhanced Learning
Online Learning and Analytics
0.41
article

A bibliometric analysis of computational thinking skills: definition, components and assessment tools

Nur Aira Abd Rahim, Priscilla Moses, Su Luan Wong, Mas Nida Md. Khambari, Fariza Khalid, A. Hamed
article en
1 citations

Abstract

This paper provides an in-depth analysis of computational thinking (CT) skills and their assessment. It discusses the definition and components of CT. Various assessment tools, such as surveys, exams, self-assessment instruments, and performance tests, are explored. A bibliometric analysis reveals a growing trend in publications related to CT skills since 1993. The study employs citation analysis, co-citation analysis, and co-keyword analysis, identifying clusters of related work and emphasizing the core ideas of CT skills, their components, and their assessment. The findings highlight the intellectual synergy between publications, particularly the strong conceptual and thematic links between works that often cite each other. The discussion underscores the importance of CT components like abstraction, decomposition, and algorithms, as foundational elements across disciplines, particularly in education and computer science. Additionally, the integration of CT into educational curricula, such as robotics, programming, and STEM, demonstrates its growing significance. The conclusion identifies several gaps in the current understanding of CT, particularly the need for a standardized, widely accepted definition that encompasses all aspects of CT. It also emphasizes the limited focus on the assessment of CT skills and calls for the development of validated and reliable assessment tools. Furthermore, the paper highlights the need for more research on the impact of teacher training programs on CT development, to ensure effective integration at the school level.

Research and Practice in Technology Enhanced LearningVol. 20
Universiti Putra Malaysia (MY), National University of Malaysia (MY), Universiti Tunku Abdul Rahman (MY)
Universiti Putra Malaysia
Quality Education
Openalex Percentile: Top 25%
Online Learning and Analytics
0.41
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