CRCSD School Improvement

Got Data? Now What?

1. Question. What questions does your team have? What are you trying to find out? The data you need is related to the questions your team is exploring. What adult and student measures are indicated in your SIP?

2. Make Predictions. What do you think the data will show? What do you think you will see? This step gets us connected to the data and can surface assumptions. Consider facilitation of this: How will the conversation be structured (whole group, partners, individual, other)?

3. Go Visual. Consider the questions your team is trying to answer and the data source. Data should be able to be seen and touched by all members of the team. In order to have a discussion, the data must the accessible to all. Consider the collection and display of data: clearly labeled graphs, easy to understand data, print or electronic, each person or share, etc. These decisions can support or hinder data analysis.

4. Observe. What do the data show? Keep these factual. Consider again the facilitation of the conversation and the importance of engagement of the entire team. Your team might make observations in partners and then report out with the facilitator recording on chart paper for all to see.

5. Infer and Question. What insights do we have based on the data? What additional questions have surfaced? Are there additional pieces of information that the team needs to better understand?

6. After, and only after that process, the team can plan for action. Knowing what we know now, what is our collective recommended course of action?

BLT Session focused on Data Analysis

One of the BLT professional learning sessions was focused on just this topic.

These are the conversation starters teachers generated:


* What do you predict you will see in these data?

* What % do you think (will be proficient, have D/F, etc.)?

* What are you assuming?

* What % of students will improve....?

* How will/do you think group A will compare to group B?

* What change do you think we will see?

* Are there any things that might skew data?

* What trends do you expect to see?

* Why do you believe....?


* What trends do you see with the data?

* What, if anything, is surprising or unexpected based on our predictions?

* What are areas of strength? Weakness?

* Are there data points missing?

* How does A compare to B?

Question, Infer, and Wonder:

* How/Why is group A different that group B?

* What can we conclude?

* What might be the reason....?

* What about our teaching practices might contribute?

* Are there emerging patterns?

* Did we teach the skill/concept?

* Did we teach using best practice?

* What additional data might we need (subgroup, other data, etc.)?

* Has there been a system change that might impact these data?


* Do we have all the data/information that we need?

* How will we prioritize/focus our actions?

* What can we control?

* What have we done that is successful that we should continue?

* What, if anything, should we stop?

* What adult actions will we commit to?

* Where should we start? What's the first step?

* How do we share _____ with _____?

* When will (action steps) occur?

* Who is responsible for (action step)?

Additionally, if your team would like support in preparing for and planning data conversations, please contact any one of the teacher leaders in the Professional Learning Department; we are happy to help!

Want to know more? Add these to your summer reading list!