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<p>This study explores the integration of Computational Thinking (CT) into the Teaching Factory (TF) model within Asian Technical and Vocational Education and Training (TVET). Using a combined bibliometric and content analysis, this research evaluated 1,695 Scopus-indexed documents (2015–2025) via VOSviewer and RStudio. Quantitative findings indicate a steady annual growth rate of 8.66%, with Vocational Education (Total Link Strength [TLS] = 188) and Computational Thinking (TLS = 187) emerging as central research themes. However, bibliographic coupling reveals an empirical gap: the TF model remains largely disconnected from CT research clusters in the current literature. To address this, the study proposes a three-pillar conceptual framework to guide their integration: the contextual pillar (utilizing TF as a practical learning environment), the methodological pillar (incorporating problem-oriented learning and robotics), and the technological pillar (employing augmented reality and AIoT for simulation). Theoretically, this framework positions CT as a foundational element that enhances the TF model. The findings provide a basis for academics and policymakers to design experimental studies that validate this integration, ultimately aiming to improve complex problem-solving capabilities among TVET graduates.</p>

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Teaching factory and computational thinking in Asian vocational education: a bibliometric analysis of the scopus database 2015–2025

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2026年4月21日

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  • Tri Handito,
  • Herri Mulyono,
  • Ihsana El Khuluqo

摘要

This study explores the integration of Computational Thinking (CT) into the Teaching Factory (TF) model within Asian Technical and Vocational Education and Training (TVET). Using a combined bibliometric and content analysis, this research evaluated 1,695 Scopus-indexed documents (2015–2025) via VOSviewer and RStudio. Quantitative findings indicate a steady annual growth rate of 8.66%, with Vocational Education (Total Link Strength [TLS] = 188) and Computational Thinking (TLS = 187) emerging as central research themes. However, bibliographic coupling reveals an empirical gap: the TF model remains largely disconnected from CT research clusters in the current literature. To address this, the study proposes a three-pillar conceptual framework to guide their integration: the contextual pillar (utilizing TF as a practical learning environment), the methodological pillar (incorporating problem-oriented learning and robotics), and the technological pillar (employing augmented reality and AIoT for simulation). Theoretically, this framework positions CT as a foundational element that enhances the TF model. The findings provide a basis for academics and policymakers to design experimental studies that validate this integration, ultimately aiming to improve complex problem-solving capabilities among TVET graduates.