Bibliometric analysis on technical and vocational education and training (TVET) research

• 主要な著者: Fam, Soo Fen, Lan, Xin-Er, Wahjono, Sentot Imam, Sahlan, Mohd Khairulnizam
• フォーマット: 論文
• 言語: English
• 出版事項: Leadership Academy of Social Sciences 2024
• オンライン･アクセス: http://eprints.utem.edu.my/id/eprint/27791/2/02444190820241230201021.pdf; http://eprints.utem.edu.my/id/eprint/27791/; https://hrmars.com/papers_submitted/22260/bibliometric-analysis-on-technical-and-vocational-education-and-training-tvet-research.pdf

Purpose – This research aims to comprehensively analyse the area of Technical and Vocational Education and Training (TVET) research. The objectives of this study are to identify the current states and trends of publications in TVET research, analyse the most cited documents in TVET research, determine the most productive contributors, examine the most frequent keywords in TVET research, and explore the current states of knowledge structure in terms of cocitation, collaboration, and co-occurrence networks. This research uses bibliometric analysis to analyse the database of publications on TVET research. Bibliometric analysis was conducted using Biblioshiny, which is a shiny app for the R package. The researcher extracted the database from 1993 to 2023 via Scopus.Starting in 2016, the total publication was higher than the previous 23 years. The highest total publication in TVET research was achieved in 2022. The most cited paper identified is the research conducted by Oketch (2007), with a total of 79 citations. The most productive author is Ismail A. The most productive country in TVET research is Malaysia, while the most productive institution or affiliation is Universiti Tun Hussein Onn Malaysia. Three of these analyses are consistent, as all are in Malaysia context in terms of author, country, and university. The most frequent words used in TVET research are "technical and vocational education and trainings", followed by "students" and "vocational education" and "apprentices". The most prolific authors identified based on the result of co-citation analysis are Mcgrath S. and Oketch, who highlight the strategy for TVET. Moreover, the collaboration between Malaysia and Indonesia contributes the most to TVET research. According to the co-occurrence network conducted, the biggest cluster of themes is "technical and vocational education and trainings" and "students" which consists of keywords such as "apprentices", "personnel training", "teaching", "teaching training", "learning systems", "education", "sustainable development" and others related keywords.