Some of the most common pitfalls for improvement data
- The data isn’t explicitly connected to the practice being changed
- The data focuses on vague or subjective outcomes
- The data is collected too soon, before change could reasonably occur
- The data is too resource-intensive to collect
- The data isn’t easily understood by the people using the data
- The data is shared too late to adjust implementation
- The data isn’t shared and used frequently within the planning team
Using data for continuous improvement is critical to changing teacher practice.
In the push to close the opportunity gap, one universal truth has emerged: teachers can have the greatest impact on student achievement (Darling-Hammond, 2000). In response, we’ve dedicated time and poured resources into improving teacher practice as a lever for improving student outcomes.
The job of building teacher capacity has never been more complex.
The increased urgency behind shifting instructional practice has ushered in an ever-increasing number of new curriculum methods that teachers and school districts are expected to implement. From Common Core to social-emotional learning to STREAM, we have an overwhelming number of new models and strategies for meeting a wide array of learning styles.
At the same time, school districts are making large “bets” on expensive, job-embedded learning methods that add complexity to the system. We’ve moved from single one-day workshops to professional learning that is continuous, job-embedded, and personalized to the adults it supports. This means the advent of coaching, population-specific strategies (like new teacher inductions or academies), and ongoing support models. Without a laser-like focus on aligning these supports around a common goal or outcome, there’s an even greater risk of not hitting any targets.
The pressure for demonstrating impact has increased.
The double whammy of new teaching methodologies and new intervention strategies results in a system that’s more complex from all angles—and the pressure to improve and demonstrate impact is growing with it. The Every Student Succeeds Act (ESSA) requires all interventions be evidence-based, while resources for professional learning like Title II-A are always at risk.
The demand for data is clear, and it goes beyond compliance. Gathering and using actionable data to continuously improve professional learning holds the key to solving three core problems: managing the complexity of professional learning, shifting teacher instructional practice, and demonstrating professional learning impact to ensure their sustainability.