VISUALIZATION OF BIBLIOMETRIC ANALYSIS FOR MAPPING RESEARCH TRENDS IN THE ELECTRICAL ENGINEERING EDUCATION CURRICULUM IN THE INDUSTRIAL REVOLUTION 4.0 ERA

This study aims to conduct a bibliometric analysis visualized to map research trends in the Electrical Engineering Education curriculum in the Industrial Revolution 4.0 era, based on articles indexed in Scopus published between 2012 and 2021. Research distribution, knowledge base, and research boundaries for curriculum studies in Electrical Engineering Education in the Industrial Revolution 4.0 era were revealed using VOSviewer software and visualization technology. A total of 450 peer-reviewed papers from 76 countries published in 235 different journals have been identified. The United States is the most productive country, with 37.19% of all articles. The most active research journal is the ASEE Annual Conference and Exposition Conference Proceedings with 63 citations and 76 articles in the research field of the Electrical Engineering Education curriculum in the Industrial Revolution 4.0 era. Meanwhile, the organization that was cited the most was Old Dominion University, Norfolk, Virginia, United States of America. Specifically, our findings indicate that research issues regarding "learning tools", "robot automation", "technology utilization", "robotics techniques", "artificial intelligence", "robotics learning trends", and "technological innovation" form the knowledge base of research on the Electrical Engineering Education curriculum in the Industrial Revolution 4.0 era. The analysis results show that research in the field of Electrical Engineering Education curriculum in the Industrial Revolution 4.0 era still has the potential for further exploration, with indications that the number of documents can still be increased by exploring the characteristics of Industry 4.0 technologies related to the Electrical Engineering Education curriculum. This study also provides insight into the overall research trends in the Electrical Engineering Education curriculum during the Industry 4.0 era and can help us better understand this research field and predict its dynamic direction.