Publication details
Towards Interactive Visualization of Time Series Data to Support Knowledge Discovery
| Authors | |
|---|---|
| Year of publication | 2015 |
| Type | Article in Proceedings |
| Conference | Progress in Artificial Intelligence - 17th Portuguese Conference on Artificial Inteligence - EPIA 2015 |
| MU Faculty or unit | |
| Citation | |
| Doi | http://dx.doi.org/10.1007/978-3-319-23485-4_57 |
| Field | Informatics |
| Keywords | animation;motion charts;visual analytics;academic analytics;experiment |
| Description | 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 provide efficient 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. AA is the business intelligence term used in academic settings and particularly facilitates creation of actionable intelligence to enhance learning and improve student retention. We evaluate the usefulness and the general applicability of the tool with a controlled experiment to assess the efficacy of described methods. To interpret the experiment results, we utilized one-way repeated measures ANOVA. |