There are numerous well-written articles, books, and blogs about interpreting, using, and sharing assessment results. This page will serve as a compilation of several resources created by various individuals. Many of them are well known in the field of student affairs assessment and write with student affairs assessment in mind.
As a start, we have shared below an excerpt from the book, Assessment in Student Affairs, written by John H. Schuh, J. Patrick Biddix, Laura A. Dean, and Jillian Kinzie. The entire electronic book is made available to all UF students, faculty, and staff through the University of Florida Library (search ISBN 9781119051084). In Part II of this module, you will find links to resources that provide helpful tips about data visualizations.
Reading from “Assessment in student affairs”
Reference
Schuh, J. H., Biddix, J. P., Dean, L. A., & Kinzie, J. (2016). Assessment in student affairs. Retrieved from https://ebookcentral.proquest.com
General tips about Visualizations
Data visualization is one of the most critical components of reporting assessment results and bringing about change. Through a visual interpretation, you can articulate your findings to key stakeholders, analyze data through a new lens, and promote accountability for enacting your findings. Effective data visualization is the key to reporting results.
Tips for Using Tables and Graphs to Represent Information (Suskie, 2009):
• Give each table and graph a meaningful and self-explanatory title
• Label each part of a table or graph clearly
• Make each table/graph self-explanatory
• Group results together in a way that makes sense (ascending or descending order, etc.)
• Make it easy for readers to see differences and trends (changing the scale, order, etc.)
• Avoid putting too much information on a table or graph
• Present results in an order that makes sense to readers and helps convey your point
• Draw attention to the point that you want your table or graph to make
• Don’t assume a software generated table or graph is readable to everyone
Tables, Charts, and Graphs
Tables, charts, and graphs are all extremely helpful tools for data visualization. When using one of these to articulate your findings, they should accent the written words in your report of presentation, not provide new information to your audience. Regardless of which of these three tools you use to represent your data, it is always best to round any percentages up to the nearest whole percent and work with whole numbers, excluding decimals completely. When deciding which tool to use, it is critical to think about what will be easiest for your audience to read and what will most effectively illustrate the point that you are trying to make (Henning & Roberts, 2016).
Tables should be arranged in a logical order given the data that you are representing. In some cases, this may mean by ascending or descending means, alphabetically, or chronologically. It should be done in a way that would make sense to the reader and accentuate your point. If using color or shading within your table, it is important to limit the use of color, use muted colors that allow for the text to still be visible, and be aware that this can impact the readability of it for some populations. Color should only be used if it adds to the overall readability or accentuation of your point (Henning & Roberts, 2016). The Publication Manual of the American Psychological Association (American Psychological Association, 2020) provides specific guidance on creating table and charts.
“Charts are best for representing data, specifically when looking at change over time, frequency distributions, correlation, or relative shares of a whole” (Henning & Roberts, 2016, p. 211). Commonly used charts include pie charts, bar charts, and line charts, but there are many others that can be used. It is helpful to experiment with different charts to find one that meets your needs based on clarity, space, and the story your data need to tell (Henning & Roberts, 2016).
Graphs should include solid lines as opposed to dotted or patterned lines to increase readability for all audiences. Additionally, starting the y-axis at zero helps graphs be more easily understood by their audiences. It is also helpful to only accentuate points on the graph that are of specific value and to use a single unit of measurement per graph, and ensuring all labels are concise and readable. Graphs take up a large amount of space in a report when they are sized to be readable, so they should not be overused.