How Can You Help Stakeholders Better Understand and Use Significant Disproportionality Data? Part 2

In Part 1 of this blog post, we mentioned how one of the key goals for sharing education data is to build understanding, and we shared some raw numbers of a sample district’s significant disproportionality data.  In Part 2, we will explore how data visualization can be a powerful tool that you can use to better engage your stakeholders with this type of data.   Common forms of data visualization are graphs, charts, tables, and similar types of drawings.  However, because of the nature of significant disproportionality data, stakeholders can find it difficult to interpret the data even in a data visualization, so here are some effective strategies to enhance understanding.

1. Provide context within the visualization—Simple shapes, color coding, using patterns, and text boxes can turn a simple bar graph into a wealth of contextual information for your stakeholders. In the following example, shapes, colors, and a text box highlight several key concepts that can help stakeholders grasp the broader context for significant disproportionality, including what the state’s risk ratio trigger for significant disproportionality is, which disabilities the state considers significantly disproportionate, what type of risk ratio the state uses, and where equal representation should be.

2. Visualize the standard—One specific way you can provide context is by highlighting how certain groups compare to a specific standard or baseline, as shown in the following graphic. The previous graph displayed equal representation at 1.0, but how does that look when using a district’s data? In the following graph, adding a line to show which disability categories in this school district are above 1.0 provides a visual representation of the groups above the equal representation marker. In addition, with a circle, you can highlight disability categories that you may not consider significantly disproportionate according to the state’s definition but which may be “at risk” for significant disproportionality (e.g., a disability category with a risk ratio near 2.0).

3. Highlight the point—There are times when your stakeholders have either no time or desire to learn about significant disproportionality calculations, but they still need to make critical decisions based on the data. In this case, highlighting the main points for them, as seen in the following graphic, can support their engagement. However, you should never start with this type of visualization because significant disproportionality and its effects are too complicated to reduce to one graphic, and generally, your stakeholders need context to ensure they interpret the data correctly. A graphic such as this can be a powerful visualization for your stakeholders if you’ve taken the time to provide good context or a strong data story as a foundation for the visualization.

 The strategies above which best fit your needs will also be dependent on factors such as the message you are trying to send and the type of communication channel you are trying to use (e.g. a presentation, a social media post, etc.).  But creating data visualizations does not have to be a complicated or time-consuming activity. You can create the data visualization examples from this blog in Excel or PowerPoint using images or shapes readily available in those programs. But as always, we’re here to help! There are IDC experts who can help you review your data visualizations to ensure they build stakeholder understanding. IDC also has related resources, such as the Part B Indicator Data Display Wizard and the Data Meeting Toolkit, to assist you with creating visualizations and facilitating conversations around IDEA data.

Contact your IDC State Liaison if you need help using these resources, creating or reviewing your data visualizations for significant disproportionality, or assistance with any other IDEA data quality issue.

- Fred Edora