4 Ways to Improve Student Outcomes by Building a Data-Driven Culture

Data collection and review routines give you extraordinary power to shape student outcomes in your classroom and beyond.

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4 Ways to Improve Student Outcomes by Building a Data-Driven Culture
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4 Ways to Improve Student Outcomes by Building a Data-Driven Culture

Data collection and review routines give you extraordinary power to shape student outcomes in your classroom and beyond.

School data has the power to reveal student trends and empower schools to take action to improve student outcomes.

  • Data grounds your hunches about student performance to drive your decision making. 
  • Data can reveal patterns in student performance/behavior that might otherwise go unnoticed 
  • Data is a reflective tool to expose what power you have in impacting student trends. 

Data collection and review routines give you extraordinary power to shape student outcomes in your classroom and beyond.

What Kind of Data Culture Do you Have?

Take a moment to assess the data culture at your school. 

How does your school collect and use data?

Do you have conversations about the data collected? 

Who is in those conversations and what actions do they produce?

It can be helpful to classify a school’s data culture using the following categories as a guide:

A school with excellent data culture is one where data review is truly valued by all members of a school staff. Time is set aside within the school schedule to look at data and talk about what it means. Data is seen as a useful tool for decision-making: data that is surprising or goes against previously held beliefs leads to conversations and additional investigation. Conversations about data feel positive and solutions oriented.

Data only reaches a core group of administrators at a school with a developing data culture. In these schools, there is a select group of people who look at the data and are particularly passionate about using it to make decisions. While data might be used very well by certain individuals at the school, data routines are not uniformly valued and implemented and so the impact on student outcomes may be varied.

A data reticent school is a school that only collects data for operational purposes. Data is collected, but it is not reviewed regularly and there’s no coherent action plan that comes from it. A data reticent culture is hesitant to use the data as a conversation starter to drive change.

Benefits of Integrating Data into your Culture

Why should you aim for an excellent data culture? 

Schools are perennially busy, sometimes chaotic places where school staff are constantly trying everything they can to improve outcomes for students. Creating an excellent school data culture allows you to focus this work where it can make the biggest difference. You can more easily identify the areas in most need of intervention, thoroughly investigate the root causes of issues you are seeing throughout your school, and create action plans that directly address root causes. The key is building in time and space for routines for those who are in the best position to affect trends in different areas (e.g. teachers with the kids in their classrooms, ops teams with chronically absent students, deans with referral and suspension data, etc). An excellent data culture gives all the members of your team the tools they need to intervene where they have the most leverage.

Now that you know how an excellent data culture benefits you, there are four common pitfalls you need to avoid so you can effectively collect and use data to improve student outcomes. 

4 Pitfalls that Derail Excellent Data Culture

1. Not Knowing Where to Find Data –
If you don’t know where to find data easily, it’s hard to fully address the questions you’d like to answer like “how are referrals distributed by race?” or “are there certain students that struggle most with timely attendance to class?” It’s frustrating to be in a meeting where you spend the whole time looking for the right data and stakeholders can lose interest or faith in the process.

How to avoid it: A point person should find all relevant data in advance of data meetings and organize it in a way that is easy for all participants to access and read. Ideally, the meeting organizer should anticipate key questions that might come up, and make sure the answers to those questions are easy to find. DeansList can help! Our platform makes it easy to track things like attendance, classroom behavior, office referrals and family communication, and we can pull in things like grades. Then, you can use our analysis tools to share data during meetings. 

2. Pushing Back on the Data
– When data addresses sensitive topics, it’s not uncommon for people to push back on the results. For example, the data may reveal a gender or racial bias that you didn’t know existed. It’s understandable that seeing these realities in the data might make members of your team feel bad or get defensive, but conversations revolving around making excuses for why the pattern exists or pointing blame at individuals sidetrack teams from finding solutions.

How to avoid it: Educate staff on how the data will be used by setting expectations at the beginning of the meeting. More experienced staff can model how to look at their own data critically and without defensiveness. You can also scaffold the rate of sharing data. In your first few meetings, have staff look privately at their own dating so they can draw conclusions without feeling self conscious about oversight.

3. Varying Levels of Data Literacy – School faculty and staff have varying degrees of comfort analyzing data. Some will be more comfortable drawing conclusions from data than others.

How to avoid it:
Teach data literacy to those that struggle with it. Set up trainings at the beginning of the year to show your colleagues some easy ways they can view and explore their data. This helps get everyone acquainted with what the data will look like and what to look for. For people who are particularly excited about gaining additional data proficiency, give them time and opportunity to learn more about data analysis so they can be the “data champions” in your school’s break out groups (ex. grade level team, MTSS team) and teach others to get comfortable using data.

4. Feeling Overwhelmed
– Diving into your data can be overwhelming. Sometimes it can feel like all you’re doing is surfacing more problems without the time to come up with effective solutions. Data meetings that are too broad can leave people feeling like there’s nothing they can do to help students improve.

How to avoid it: Ask questions about the data that are relevant to every one who is in the meeting with you. It can be disempowering to look at data you have no power over. Instead, tailor the data you present so that it’s specific to your audience and sets the foundation for a solution. For example, share data with teachers specific to improving their classrooms, and share data with administrators about addressing overarching school themes. 

Building an excellent data culture takes time and buy-in from both administrators and teachers. When everyone is on board, data collection and analysis becomes routine and a powerful tool to make improvements year after year. 

Discover more ways to use data and improve student outcomes at deanslistsoftware.com

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