Collecting data is all the rage these days. But massive amounts of data in spreadsheets or tables won’t necessarily tell learners what they need to know. To thoroughly understand and tell stories with data—to communicate the importance or meaning of data—it’s necessary to use data visualizations in eLearning.
Understanding how to interpret and share the information that analytics data reveals enables eLearning developers to add impact and clarity to training tools.
What is data visualization?
Data visualizations display abstract information in visual, graphical formats. Statistical information, test scores, and other data commonly gathered about learners and their performance is abstract, but when analyzed and presented effectively, it can communicate detailed and relevant information about an individual employee’s or a department’s performance, about the effectiveness of training, or about how one person or training course is performing when compared with others.
A data visualization maps numbers—data points—onto spatial properties, such as lengths, heights, colors—hue or shade—positions, area, or size. Some visualizations enable readers to see a big-picture perspective, while others are better at showing precise comparisons and differences between values.
A single data visualization is rarely sufficient to describe and explore a dataset; often multiple visualizations, presented in different formats, are needed to fully illustrate a dataset. Hundreds of types of visualizations exist; common types include bar charts, pie charts, box-and-whisker plots, and bubble charts or maps.
It’s easy to get started: eLearning developers can create data visualizations using free or very low-cost tools, such as iNZight or Tableau Public. Data skills, such as knowledge of coding and statistics, enable developers to create more sophisticated visualizations.
Using data visualization in eLearning—and beyond
Exploring data and helping learners understand the stories it tells are clearly useful objectives: An L&D team with data visualization skills can add infographics, charts, and tables to eLearning courses and performance support tools to help learners understand the material. Data visualizations also offer a “plus one”—an additional format to consume and improve understanding of complex content.
Data visualizations also aid developers in achieving goals within the larger organization—outside of eLearning courses and tools—that are vitally important to many L&D teams. As companies increasingly seek to understand how eLearning and training add value, and L&D teams attempt to measure outcomes and determine the effectiveness of their training, enlisting data visualizations is an obvious step.
L&D teams routinely collect data on course completions, quiz results, activity performance, and content consumption. A data visualization that compares these metrics with key job-performance metrics will show how training correlates with improved results, for example. Clear, engaging, accurate visual representations of learning and performance data can help L&D teams “make their case” with managers far better than a verbal explanation alone ever could.