Educational assessments can be used to support learning, as well as validate it. The type of assessment you choose should match the purpose behind the questions you’re trying to answer about student learning. With the numerous assessments available to educators comes the abundant streams of student assessment data. It can be tricky to figure out what data to use to make certain decisions.
What to do with all this rich assessment data? Good question! This list is a handy starting point for determining which data you should review to support an instructional decision or action.
1. Scores
- Offer at-a-glance insight into the strengths and weaknesses of student learning. Best paired with other sources of information, such as classwork, additional assessments (or quizzes) and communication to frame a complete picture of student understanding.
- Helpful when setting goals with students, monitoring student growth and identifying patterns over time.
2. Standard Error of Measurement (SEM) – describes the precision of a score from an assessment.
- SEM highlights how much confidence should be associated with a score. The smaller the SEM, the more likely the data is precise. Useful for determining how much confidence you can have in your scores. If a student has a higher than average SEM for their test, carefully consider what conditions may have impacted testing. If you’ve determined conditional or other factors may have negatively impacted the test, consider retesting the student for a more precise score.
3. Percentiles – reflect how a student’s score compares to other students in the same grade level.
- Useful to understand how students in a class are performing relative to their peers, particularly when setting goals with students, creating flexible groupings, discussing results with families or making program placement decisions.
4. Mean and Median – mean is the arithmetic average of a group of scores, and median is the middle score in a list of scores.
- Provides central points of reference when setting goals with students or reviewing performance of a group, whether a class, grade or larger sample.
- Valuable when comparing and organizing student assessment results to inform instructional groupings or programs.
5. Standard Deviation – the homogeneity/heterogeneity of the instructional level within a group of students. The higher the standard deviation, the more academically diverse the group.
- Can be useful when determining how diverse student performance is within a group. An important factor for understanding why an average (mean) score is higher or lower for a group, and whether whole group or small group instruction might be more effective.
Assessment data can provide real insight if you know the right type of data to use for each decision. Making data-informed decisions can be instrumental in moving student learning forward. Keep this as a handy reference and reminder when you have a key instructional decision to make and need to know what data to consult.
