Data Analysis Strategies
Every assessment tool will produce particular forms of data. Matching, tool, data, and analysis strategy is critical to getting valuable information that will help you answer questions about what/how students are learning in your classes. See the table below for some common data types with corresponding data analysis strategies. Contact the director of assessment for help selecting assessment tools and/or analysis strategies.
| Data Type | Analysis Strategies |
|---|---|
| Test Questions | Spreadsheet of responses by category; percentage of students who responded in each |
| Writing Sample/Essay | Rubric; spreadsheet of responses; average score, range of scores |
| Self-Reflection | Thematic analysis: list key themes from across responses; relate to learning outcomes. |
| Performance-Based (presentation, project) | 1) Criterion-based 2) Rubric-based |
| Survey | Aggregation of survey responses; discussion |
| Interview | Thematic analysis: list key themes from across responses |
Keep in mind that, when we’re selecting assessment tools, we should work to address two key concerns of assessment research: Validity and Reliability. Effectively, Validity refers to the process of ensuring that we are measuring what we say we are measuring. This means the assessment tool needs to match the learning outcomes we expect students to demonstrate. Reliability, on the other hand, is the demonstration that our assessment is consistent over time. The measurement tool and the strategy for analyzing data are used the same way every time. This is done in an effort to build confidence in our data. For assessment to be reliable it must be consistently administered and provide results that can be thoughtfully interpreted.
Questions or comments?
Please contact the Office of the Provost (253)535-7126 or provost@plu.edu