学习分析主题结构研究及可视化分析

Topic Structure and Visualization Analysis of Learning Analytics Research

As an important part of educational data mining， learning analytics has drawn extensive attention among international scholars since its origin. To further explore the research on learning analytics， this paper， based on 674 articles on learning analytics between 2010 and 2015 from Web of Science， explored and revealed the international research status about learning analytics. In this study， we used the ＂Bicomb＂ word frequency analysis software， the ＂ Cites pace＂ citation analysis tool and ＂SCI2＂ tool and visualization technology to analyze the high-cited articles， the distribution of core authors， high prolific institutions and high frequency keywords. In addition， based on dissimilarity matrix of high frequency keywords， this paper further clarified the research scope using cluster analysis. Furthermore， by mapping out the strategic diagram graph ， the trend of the development orientation of learning analytics was further clarified in order to provide reference and suggestions for international research and practices on learning analytics. Results showed that the research topics had been greatly expanded and were more abundant during the 2011-2014 period. The learning analytics on behalf of communities suddenly rose and ranked to the top for four years ， which made it the hottest research area during those period of times. Learning analytics showed an increasing trend year by year， mainly related to information retrieval and education data mining. While， there is a split phenomenon of the visual analytics. It has two successors involving ＂Visual analytics＂ and ＂Machine learning＂ ， respectively as the representative of the theme. The two successors with the learning analytics become the three core research hotspots in 2015. From the results of the study， we can conclude that the learning analytics technology is still in the initial stage and the field of research is not balanced. Learning analytics research also face many challenges concerning data security， ethics ， and privacy. In general， although learning analytics technology has great application value and development potential ， there is still a long way to explore and practice in order for it to be widely applied in learning sciences.