Towards interactive visualization of time series data to support knowledge discovery

Abstract

Higher education institutions have a significant interest in increasing the educational quality and effectiveness. A major challenge in modern education is the large amount of time-dependent data, which requires efficient tools and methods to improve decision making. Methods like motion charts (MC) show changes over time by presenting animations in two-dimensional space and by changing element appearances. In this paper, we present a visual analytics tool which makes use of enhanced animated data visualization methods. The tool is primarily designed for exploratory analysis of academic analytics (AA) and offers several interactive visualization methods that enhance the MC design. An experiment is conducted to evaluate the efficacy of both static and animated data visualization methods. To interpret the experiment results, we utilized one-way repeated measures ANOVA.