Making Sense of Assessment Data
“Collecting data is one thing, but making sense of them is something else. We want to use analytic techniques that are simple, direct, and effective” (Allen, M. J., 2004).
The most effective and useful techniques for analyzing your data do not involve complicated quantitative or qualitative analytic techniques. We encourage you to keep your analytic techniques simple. Doing so will not only make your own project more manageable, it will also increase the likelihood of sustained, long-term assessment efforts in your program.
This principle is so important, it deserves repeating:
The most effective and useful techniques for analyzing your data do not involve complicated quantitative or qualitative analytic techniques.
Purposes for analyzing assessment data
The purpose of assessment data analysis is to find patterns in student performance relative to your expectations of their learning. The goal is NOT to look to the data to find causes for the patterns. The data will tell you what the patterns are in student performance, but will not tell you why.
A second purpose of data analysis is to identify overall trends for all students involved in the inquiry project. This is not a process for evaluating the course, assignment, instructor, or students. The onus of responsibility for assessment results rests with the program. Look for overall trends that indicate wins and potential opportunities for improvement.
Goal of analyzing assessment data
Identify the "actionable n," which is the proportion of students' results that the program can work with to make a difference. Most of the time, basic proportions or percentages are the only mathematical tools you'll need to find the "actionable n" in your data. NOTE: The goal of analyzing assessment data is NOT to look for statistical significance. Remember that your data analysis should be simple, direct, effective, and sustainable.
“Most evidence of student learning can be summarized with simple tallies and percentages” (Suskie, 2018).
- Tallies/Counts (n): How many students performed at each performance level, for each PI.
- Percentages (%): The proportion of students with a score in the PI who performed at each performance level, for each PI.
To learn about analyzing assessment data, go to the
Program Assessment Resource Kit.
UC Davis login credentials required.
Using Results to Spur Action
At this stage, your role is to name and advocate for actions that can advance continuous and parity-driven improvements for your program. While some of the proposed actions may be out of scope, it is still important to name them in the present. Plan to advocate for implementation when conditions change.
Prioritize actions
After you identify all your possible actions, prioritize those that are:
- Specific - the actions are concrete, clear, and observable. That means you'll be able to see the action being taken.
- Realistic - the actions are achievable within reasonable time and resource constraints.
- Grounded in evidence - the actions align with assessment findings, as well as other insights, experiences, and/or discoveries you encountered during your assessment inquiry.
Act realistically for continuous improvement
Realistic action ideas can be further distilled into three categories: practical (doable within current program capacity); aspirational (doable with additional capacity and planning); and challenging (within your control, but requires substantial changes to capacity). Align your actions to your findings / observations from your assessment of student learning outcomes inquiry.
To learn more about analyzing & using assessment data, go to the
Program Assessment Resource Kit
UC Davis login credentials required.