Computational Thinking and Learning Strategy in Technical Education: A Bibliometric Analysis of Global Trends, Knowledge Structure, and Future Research Directions
DOI:
https://doi.org/10.16920/jeet/2026/v40is1/26145Keywords:
Bibliometric Analysis, Computational Thinking, Learning Strategy, Technical Education, TVET.Abstract
This study analyzes global research on computational thinking (CT) and learning strategies in technical education using 3,899 Scopus-indexed documents published from 2008 to 2026 and mapped with Bibliometrix, BiblioShiny, and VOSviewer. The results show that the growth of publications since 2019 is fast, led by China, Indonesia, and the United States, and the dominant subject areas are Social Science, Computer Science, and Engineering. Keyword mapping revealed two major thematic clusters and eight recurring pedagogical approaches: inquiry-based learning, problem-based learning, creative pedagogy, flipped learning, gamification, online literacy integration, collaborative learning, and CT skill-oriented approaches. Nevertheless, CT research in Technical and Vocational Education and Training (TVET) is still fragmented, with gaps in contextual learning models, teacher readiness, assessment, and integration with practice-based approaches such as the Teaching Factory. The findings suggest that there is a need for more curriculum integration, teacher development, and industry-relevant learning to support students’ digital literacy skills, employability, and readiness for technical work
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