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How do I compare data between two assessments?
How do I compare data between two assessments?

If you've given two different assessments and want to compare data between the two, this article is for you!

Erin Cooke avatar
Written by Erin Cooke
Updated over a week ago

On InnerOrbit, you can compare the dimensional data between 2 (or more) assessments. This is helpful when:

  • Comparing data between a "core" assessment and a "modified" assessment

  • Looking for "growth" between assessments

We'll discuss:

Filter for Assessment Data

Step 1: Go to "Reports" > "Dimensions"

Step 2: Scroll down to the filters on the left hand side, click on "Select Assessments"

Step 3: Click on the assessments you'd like to compare

  • EX: Select both the "core" assessment AND the "modified" assessment

  • You can select multiple assessments!

Step 4: The data that you will then see is the COMBINED data across the selected assessments.

  • To see each specific assessment's data, unselect other assessments, leaving the target assessment still checked.

Tip: Opening up one tab on your internet browser for each assessment helps if you're taking a deep dive into each assessment's dimension data!

Filter Data by Roster/Student

You can also filter a specific assessment's dimensional data by ROSTER (how did Period 1 do on the assessment versus Period 2?) by:

Step 1: Filter for the specific assessment (instructions in section above)

Step 2: Unselect all rosters EXCEPT for your target roster:

...or by STUDENT (how did Neil do on the dimensions for this assessment) by:

Step 1: Filter for the specific assessment (instructions in section above)

Step 2: Type and select the student name under "Specific Student"

Tips for comparing data and seeing "growth"

Keep in mind that assessment design significantly impacts dimensional data results.

If you're looking for dimensional growth between 2 or more assessments, it is imperative that the assessments are structured in the same way, including:

  • the same number of questions per Performance Expectation (PE) AND

  • the same question rigor (1D, 2D, and 3D)

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