A BIBLIOMETRIC ANALYSIS OF DEEP LEARNING FOR EDUCATION RESEARCH

The purpose of this study was to determine the role, trend, and development of deep learning (DL) in education. The research method used is a bibliometric analysis method using the VOSviewer tool. VOSviewer is used to analyse the distribution of documents each year in various countries, institutions, journals, authors, and the relationship between keywords that appear. The results of this study show that the growth of publications on DL articles in the world of education increased by 31.69%, while the growth of DL articles as learning media increased by 11%. The most productive country in publishing articles related to DL in education is the United States with a total of 460 related documents and 13,162 citations. The most productive institution that researches DL in education is Stanford University with a total of 21 articles published. Furthermore, the most productive journal in IEEE Access with a total publication of 58,219 articles and a citation score of 4.8. The relationship between authors shows that the co-authoring network with Zhang Y. is the largest network with a total of 24 co-authored articles. The keyword that appears the most is the keyword "deep learning" which is directly related to "Data Analytics" and "AI". It is also seen that the topics that may arise for future research are topics related to the keyword "deep learning" which is related to "Virtual Reality" or "Educational Psychology". This research can be useful to find research gaps regarding the development or implementation of deep learning in the field of education to improve the quality of education and solving problems related to the world of education.