Identifying trends in recent publications using Data Visualization and Analytics

Abstract

There is an ongoing trend of applying various data analytics and visualization techniques, including AI algorithms to solve various problems. Technically in higher education defining the research gap and the research trends traditionally requires the researcher to read various articles and books in order to define what is a significant topic and one that represents a trendy topic that was recently explored and can be still explored. This process is time consuming and sometimes may lead to unnecessary overfitted results. In our previous paper we showed the importance of AI in research through a proposed model to increase the quality of research and improve the time spent and quality of content used for different research topics. This paper focuses on the same model but rather on data analytics and visualization applied on custom dataset from recent articles from IEEE Xplore to identify trends on educational research with focus on computer science.