During a recent visit to Michigan State University’s (MSU) College of Education, State Superintendent Mike Flanagan said using data well is a common characteristic of turnaround schools. “In schools that have improved student achievement, everyone knows and understands weak spots, and tries to create strategies based on them,” Flanagan said.
Effective educators use data to reform and redesign their mission, and monitor progress. In addition, they understand the importance of collaborative use of data. Collaborative use of data for school improvement is supported by many education experts including Bruce Wellman of Lipton and Wellman’s Collaborative Learning Cycle and Kathryn Parker Boudett, director of the DataWise Project at Harvard School of Education. Strategies that support collaborative use of data for school improvement include district-school partnership, a strong vision, and data dialogues. Here are five tips to lead collaboratively with data for school improvement.
Encourage Collaborative Learning through Data Dialogue
Through data dialogue, school leaders structure and facilitate collaborative inquiry about data, giving coherence to school’s improvement program and creating a professional community where everyone takes charge. According to education consultant Bruce Wellman, a data dialogue addresses both data and collaboration, and encourages groups to explore approaches that enhance student learning.
MSU Office of K-12 Outreach suggests a three-phase process for Data Dialogues: activate and engage, explore and discover, and organize and integrate. This data dialogue process would help school leaders establish shared understandings of issues and goals. You can learn more about Data Dialogues on MI Toolkit.
Use Multiple Types of Data
The point of school improvement reform is to improve student learning. To do that, educators should look at multiple measures of data, including cultural as well as academic. Attendance, student demographic and drop-out data may tell more about the issues schools face than test scores or grade points. Victoria Bernhardt, executive director for the Education for the Future Initiative, suggests demographic data helps educators understand school’s current context and improve school improvement processes.
According to Patricia Edwards, distinguished professor in MSU’s College of Education, another important type of data is parent involvement. "Look into the parent involvement history at your school and how well it matches with your school's goals." Edwards said, adding that the data drive all school improvement measures only when school transformation teams address multiple types of data.
Focus Data on Instruction Improvement
Any good school improvement initiative focuses on instructional improvement, addressing the direct impact of instruction on student achievement. To improve instruction, educators must remember its three core elements: student, teacher and content. The instructional core framework consists of interaction between teachers and students in the presence of academic content. Systemically improving the instructional core is the only way to increase student learning over time, according to Harvard educator Richard Elmore.
Curriculum (the content) must be aligned at the district level and followed at the school level. In addition, school transformation teams should explore ways to evaluate and improve teacher-student interaction.
Employ a Step-by-Step Process
Start with baby steps and build up. Using a step-by-step process helps us see the big-picture objectives while maximizing limited resources, according to authors of Collaborative School Improvement.
Set up your own step-by-step process that aligns with your school’s mission, taking note of which steps are completed collectively at school level, and which could be productively completed alone or in pairs. Distinguishing effective ways to implement the school improvement plan helps the work fit into school’s larger goals.
Monitor School Improvement Efforts with Continuous Data Dialogues
Collaborative data dialogue is an ongoing process; keeping the momentum is just as important as initiating the dialogue. Meeting regularly with others to support implementation and provide feedback on one another’s strategies is critical to ongoing improvement. Collaborative data dialogues thrive when everyone takes charge.