Continuous Improvement Not Continuous Solutions: Leveraging Data and a Change Mindset

“Solutionitis” is a term being used more often—and appropriately—to describe how reform happens in schools and school systems, including our tendency as education leaders to jump quickly from identifying a problem to implementing a solution. There are several reasons why we opt for fast-paced implementation of new solutions. Chief among them are our urgent and ardent efforts to close achievement gaps and improve outcomes for the students we serve. Still, we know that a steady stream of new solutions can overwhelm teachers, stretch resources, lead to a “this too shall pass” mindset and, worst of all, prevent us from getting the results we seek. What can we do to create a new mindset focused on a cycle of continuous improvement?

The good news is that the Every Student Succeeds Act (ESSA) invites us to operate more effectively by adopting a continuous improvement focus. ESSA guidance calls on states, districts and schools to use multiple sources of data to focus on what is happening across the school system and then use those findings to:

1. Identify local needs.
2. Select evidence-based interventions that they have the capacity to implement.
3. Plan for implementation of those interventions.
4. Implement the selected interventions.
5. Examine and reflect upon how the intervention is working to address the local needs.

Nothing new here, right? Most school systems have—perhaps in a dusty notebook high on the shelf—an improvement model, needs assessment and strategic plan. While we’ve all considered local needs and implemented interventions, few have realized sustainable progress in areas that support student preparation for college, career and life. It’s time for a different approach. A continuous improvement model is needed, one that moves beyond a “once and done mindset” and includes regular cycles of data collection and analysis of progress, allowing us to deeply investigate the problem to be solved. The Plan, Do, Study, Act model embedded in Anthony Bryk’s improvement science framework incorporates these actions and serves as a good example.[1] This continuous improvement model has been successful in our work in Kansas districts and schools to improve reading and math performance. Principals in Hawaii are using it to test their change ideas.

Setting Ourselves Up for Success: Identifying Local Needs

The first, crucial step in any continuous improvement approach is to accurately identify local needs. To do so, district leaders are asked to examine relevant data to understand the most pressing needs and their potential root causes. This requires deep mining of many forms of data—including but extending well beyond academic data—to understand student learning patterns and the classroom, school, and district conditions that impact them.

Victoria Bernhardt[2] describes three data types beyond academic that should be considered in a needs assessment: Demographic, perception and contextual. A thorough analysis of these data can help us answer two essential questions to more clearly understand our most pressing problems.

1) Who is performing at standard and making gains?

 Academic data (both formative and summative) focus us on those students who are doing well and those that are not in reading, writing, mathematics, science and social studies as measured by key indicators of student success. This is often a state assessment but can include norm- referenced tests and formative assessments. Growth measures are also an essential part of this equation.

Demographic data help us to learn more about individual students. Data points explain students’ economic status, ethnicity, gender, special population status, and school attendance rates, for example.

2) Why are students underperforming or losing ground?

 Perception data collected through surveys and interviews can help us understand student and stakeholders’ values and beliefs and a school’s culture, or how students, teachers, and parents experience school. Unfiltered stories and perceptions from stakeholders give us a much more nuanced view of the issues we face. Perception data can be more challenging to generate and analyze and, as a result, is often dropped from our data lists, but it is an essential window into how we do business and how we can do it better.

Contextual data (another often overlooked data type) reveals the processes within the school and their impact on learning. We can, for example, examine the courses in which students are enrolled, the preparation of the teachers who teach them, the instructional materials and strategies used in a course, and the scheduling of learning opportunities. Classroom walk-through data are another useful tool for assessing instructional alignment and approaches.

We’ve supported schools and districts to select and follow a continuous improvement model and we’ve learned a great deal throughout each step of the cycle. Specifically, while conducting needs assessments to identify local needs we’ve learned that:

• Analyses of this scope and scale can’t be done by one or two people – districts are best served by involving a range of stakeholders in a needs assessment.
• Having the right mindset is also key. Working through something this complex requires that leaders approach the work as learners.
• To be successful, a needs assessment can’t be an exercise in blaming, excuse making, or penalizing, but an opportunity for stakeholders to understand core challenges and their underlying causes.
• Continuous improvement moves beyond the “once and done” improvement efforts of the past and requires multiple, structured cycles of study of whether or not changes are meeting our needs.

As we seek solutions to our most pressing problems and work towards continuous improvement in our schools and school systems, we must first use data to identify the problem and then investigate it deeply to understand the whole story before seeking solutions. We must hear all voices. We must embrace a new mindset, beyond the once and done to a cycle of data review and examination of progress toward the student success we seek.

[1] Bryk, A. et al. (2015). Learning to Improve: How America’s Schools Can Get Better at Getting Better. Harvard Education Press.

[2] Bernhardt, V.L. (2013). Data Analysis for Continuous School Improvement (Third Edition). New York, NY: Routledge