Assessment Data Analysis
Assessment data provide a means to look at student performance to offer evidence about student learning in the curriculum, provide information about program strengths and weaknesses, and guide decision-making. Analyzing the data — in context — gives meaning to the information collected and is essential to appropriately utilize and communicate the assessment results.
Types of Assessment Data Analysis
Generally, data collected for program-level assessment fall into two categories: quantitative and qualitative.
- Quantitative data analysis relies on numerical scores or ratings and is helpful in evaluation because it can provide quantifiable results that are easy to calculate and display.
- Qualitative data consists primarily of words and observations, rather than numbers. Qualitative data can come from a variety of sources including open-ended survey questions, focus group notes, essay responses, and student portfolios, for example. Qualitative data can be useful for answering “why” and “how” questions about student performance, approach, motivation, or experience.
Note: Some textual data can be coded into a numerical form and analyzed as quantitative data. For example, rating scale data can be assigned values, such as: does not meet expectations = 1, partially meets expectations = 2, meets expectations = 3, exceeds expectations = 4.
Assessment Data Analysis Toolkit
The resources below are intended to help departments and programs summarize and display data collected about student learning as part of program-level assessment. They assume some familiarity with basic data analysis and with the academic program of interest. ACE is available to collaborate with undergraduate degree programs to analyze and create visual displays of assessment data to engage faculty in discussions of assessment results; contact us for additional information.
- Many of these resources contain strategies for organizing, analyzing, and presenting assessment data using Microsoft Excel. While other software can be used for assessment purposes, instructions for their specific use are not addressed.
- While these resources provide techniques and examples for many types of data and situations, it is up to the user to determine what methods are appropriate for their specific needs and type of data.
- Please contact ACE for assistance determining appropriate analysis methods or data collection practices for program assessment, or with other questions about using these resources.
Educational Research and Publication: While assessment utilizes many of the same qualitative and quantitative methodologies applied by traditional social science research, these resources are NOT designed for those who are interested in generating/publishing scholarly research from their assessment activities or findings. Please contact ACE if you have questions about distinguishing the data needs of program-level assessment and educational research, or about sharing results from assessment.
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|Data Organization||Quick Guide||ACE - WSU||Organizing Assessment Data for Analysis||PDF resource containing tips and suggestions intended to help faculty consider best practices and plan for organizing data collected about student learning|
|Quantitative Data Analysis||Quick Guide||ACE - WSU||Analyzing Quantitative (Numeric) Assessment Data||PDF resource containing tips and suggestions intended to help faculty consider best practices and plan for summarizing quantitative (numeric) data about student learning|
|Quantitative Data Analysis||Quick Guide||ACE - WSU||Strategies for Summarizing and Displaying Rubric Data||PDF resource intended to help faculty consider strategies for summarizing and presenting assessment data (with examples) collected from the evaluation of student work with a rubric|
|Quantitative Data Analysis||Template||ACE - WSU||Template for Creating Visual Displays of Rubric Data||Excel template intended to help faculty create visual displays of assessment data collected from the evaluation of student work with a rubric; Note: ACE recommends that you review our Strategies for Summarizing and Displaying Rubric Data PDF resource in conjunction with this template|
|Qualitative Data Analysis||Quick Guide||ACE - WSU||Analyzing Qualitative (Textual) Assessment Data||PDF resource containing tips and suggestions intended to help faculty consider best practices and plan for summarizing qualitative (textual) data about student learning|
|Sample Representation||Quick Guide||ACE - WSU||Quick Guide to Sample Sizes, Sampling, & Representation for Program Assessment||PDF resource offering sampling strategies and tips for determining sampling size and representation with examples|
|Data Stewardship||Quick Guide||ACE - WSU||Assessment Data Stewardship: Tips for Academic Programs||PDF resource with data stewardship tips for those collecting and managing degree program assessment data that align with WSU’s Executive Policy #8|
Additional Resources and Scholarship
Note: Please contact ACE to borrow a book.
Barkley, E. & Major, C. (2016). Learning Assessment Techniques: A Handbook for College Faculty. San Francisco, CA: Jossey-Bass.
Creswell, J. (2013). Qualitative Inquiry and Research Design: Choosing Among Five Approaches. Los Angeles, CA: Sage.
Krueger, R. & Casey, M. (2009). Chapter 6: Analyzing focus group results. In Focus Groups: A Practical Guide for Applied Research. Los Angeles, CA: Sage.
Suskie, L. (2018). Chapter 23: Summarizing and storing evidence of student learning. In Assessing Student Learning: A Common Sense Guide. San Francisco, CA: Jossey-Bass.