Classroom Strategies: Using Data to Differentiate

Classroom Strategies:  Using Data to DifferentiateCris Tovani, in her book So What Do They Really Know: Assessment That Informs Teaching and Learning, has a great way of thinking about differentiation:

Differentiation is about adjusting my instruction to meet more student needs. It isn’t about each student doing an elaborate, individualized project.

If we look at data differentiation from this perspective, flexible grouping is just one strategy which allows us to meet more student needs.

When was the last time you used flexible groups in your classroom? What was the purpose? What data did you use to form the groups? How flexible were the flexible groups? Flexible grouping is a strategy often associated with differentiated instruction. Sometimes we get stuck on the flexible part. Let’s talk about ways that data might give you more flexibility.

On the last state assessment your data showed that this year’s math class was divided into 2 groups (proficient/not proficient) on the standard related to measurement. Although you received this data in August, as a starting point you could identify two groups the first week or two of school and do some quick assessments to try and get a clearer picture on what aspects of measurement were strengths and stretches. Now to get more specific information, your district uses an interim assessment which offers more detailed information about students and specific standards and sub-standards. Your plan for flexible grouping shapes up to look like this:

  1. Form 2 groups based on state assessment – proficient/not proficient.
  2. Administer short assessments focused on this year’s measurement standard to identify strengths and stretches within both groups.
  3. Form new groups based on results of short assessments.
  4. Students take the district’s interim assessment. Analyze those results and triangulate with the state assessment and your classroom assessments.
  5. Form new groups based on the triangulation of data. You may have two sets of groups, one that focuses on expanding students’ strengths and one set that focuses on addressing students’ stretches.

As you can see from the scenario above, we have formed and reformed groups at least three times in probably the first six weeks of school. Additionally as you get better at narrowing the instructional focus for these groups, students get better at learning what they need to know and to do, which causes you to flex the membership and focus of each group once more.

Differentiating with flexible groups works best when based upon data. You have a wide variety of data at your fingertips (as do students). Becoming data literate means that you can enhance your differentiation skills. While we want all students to meet the same success criteria, how they meet those criteria is the key to differentiation. In their book Data Driven Differentiation, Gregory and Kuzmich talk about a wide variety of data we can and need to collect in the classroom to successfully differentiate for student growth and achievement. They also discuss differences between ability, heterogeneous, random and constructed groups – all flexible and all formed by analyzing and acting upon the data.

What does this culture of using data to differentiate look like in your classroom from your perspective? From your students’ perspective? What strategies are you finding most useful? Share your thoughts in the comments section below.