Research Trends Of Computational Thinking For Advancing Sustainable Development Goals (SDGs) In Science Learning: Bibliometric Analysis

Computational Thinking (CT) emerged as a crucial competency that bridges digital literacy and scientific problem solving in the context of achieving Sustainable Development Goal (SDG) 4 on quality education. However, the model of integrating CT in science learning is still poorly explored, hindering progress towards SDG Targets 4.4 (technical skills) and 4.7 (scientific literacy). This study is the first bibliometric analysis to map the trends of CT research in science learning (2021–2023) through Scopus. The novelty lies in the identification of global collaboration patterns, knowledge gaps, and research priorities that are aligned with the 2030 Agenda. Three research questions were guided: (1) Publication distribution, (2) Dominant journals and subject areas, (3) Keyword dynamics/co-occurrence networks. Data retrieved from Scopus using the strings TITLE-ABS-KEY("Computational Thinking" AND "Science Education/Learning") (47 articles, open access, 2021–2023). Analysis techniques include: Performance analysis (publication/citation metrics), Science mapping (author affiliation), Network analysis (keyword grouping via VOSviewer). Key findings show: (1) Peak publication in 2022 (19 articles), (2) Education Sciences (Q1) as the top journal (7 articles), (3) Dominance of Social Sciences (43 articles) and Computer Science (21), (4) Most cited articles: Lodi & Martini (2021; 43 citations), (5) Main keywords: Computational Thinking (27 appearances), Computer Science Education (15), (6) US-led geographic contributions (>20 publications), (7) Co-occurrence analysis reveals that Scratch (a block-based application) is a less researched CT tool (3 occurrences) than technical languages such as Python. CT integration improves science literacy but is constrained by teacher training gaps (SDG 4.c) and access to resources. The scarcity of research on gamified tools like Scratch signals a critical innovation gap. This study provides an evidence-based roadmap to prioritize teacher professional development, scale accessible CT tools (e.g., Scratch) for science education, and direct future research toward SDG-aligned classroom-based practices.

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Publication Details

Journal
Jurnal Pendidikan IPA Indonesia
Published
2025-06-30
DOI
https://doi.org/10.15294/jpii.v14i2.23645
Citations
1
Primary Topic
Engineering Education and Technology
Type
article
Field-Weighted Citation Impact
3.25
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article

Research Trends Of Computational Thinking For Advancing Sustainable Development Goals (SDGs) In Science Learning: Bibliometric Analysis

Lukman Abdul Rauf Laliyo, Frida Maryati Yusuf, Alfian Erwinsyah, Mursalin Mursalin et al.
1 citations
Jurnal Pendidikan IPA Indonesia
Engineering Education and Technology
3.25
article

Research Trends Of Computational Thinking For Advancing Sustainable Development Goals (SDGs) In Science Learning: Bibliometric Analysis

Lukman Abdul Rauf Laliyo, Frida Maryati Yusuf, Alfian Erwinsyah, Mursalin Mursalin, Inga Riumkina
article en
1 citations

Abstract

Computational Thinking (CT) emerged as a crucial competency that bridges digital literacy and scientific problem solving in the context of achieving Sustainable Development Goal (SDG) 4 on quality education. However, the model of integrating CT in science learning is still poorly explored, hindering progress towards SDG Targets 4.4 (technical skills) and 4.7 (scientific literacy). This study is the first bibliometric analysis to map the trends of CT research in science learning (2021–2023) through Scopus. The novelty lies in the identification of global collaboration patterns, knowledge gaps, and research priorities that are aligned with the 2030 Agenda. Three research questions were guided: (1) Publication distribution, (2) Dominant journals and subject areas, (3) Keyword dynamics/co-occurrence networks. Data retrieved from Scopus using the strings TITLE-ABS-KEY("Computational Thinking" AND "Science Education/Learning") (47 articles, open access, 2021–2023). Analysis techniques include: Performance analysis (publication/citation metrics), Science mapping (author affiliation), Network analysis (keyword grouping via VOSviewer). Key findings show: (1) Peak publication in 2022 (19 articles), (2) Education Sciences (Q1) as the top journal (7 articles), (3) Dominance of Social Sciences (43 articles) and Computer Science (21), (4) Most cited articles: Lodi & Martini (2021; 43 citations), (5) Main keywords: Computational Thinking (27 appearances), Computer Science Education (15), (6) US-led geographic contributions (>20 publications), (7) Co-occurrence analysis reveals that Scratch (a block-based application) is a less researched CT tool (3 occurrences) than technical languages such as Python. CT integration improves science literacy but is constrained by teacher training gaps (SDG 4.c) and access to resources. The scarcity of research on gamified tools like Scratch signals a critical innovation gap. This study provides an evidence-based roadmap to prioritize teacher professional development, scale accessible CT tools (e.g., Scratch) for science education, and direct future research toward SDG-aligned classroom-based practices.

Jurnal Pendidikan IPA IndonesiaVol. 14(2)
State University of Gorontalo (ID)
Openalex Percentile: Top 8%
Engineering Education and Technology
3.25
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