Visual data analysis refers to highly advanced computational methods and graphics to make complex datasets easier to explore and visualize, revealing strong patterns and trends. It combines data analytics and data visualization techniques, given that these techniques help to see the big picture or to identify how datasets relate to each other.
Educators can, for instance, export user access reports from LMSs and use digital tools for visual data analysis. This can be very important to better understand the learners’ experience and to improve teaching and learning strategies. Examples of tools that educators can use are:
- Gapminder – used to identify misconceptions about important global trends based on reliable data to develop easy to understand teaching materials to rid people of their misconceptions;
- IBM Many Eyes – used for uploading, visualising, and discussing big data;
- FlowingData – used to make great charts easier to analyse through a collection of visualization resources (e.g., map-based clouds, charts, and graphs).