SRI, together with the Data Wise project of the Harvard Graduate School of Education and New York University, conducted a study to develop and validate a toolkit to assess the effectiveness of instructional teams and professional learning communities engaged in various forms of collaborative data inquiry, data-driven decision making, and continuous improvement processes that rely on data.
The toolkit is designed for instructional leaders responsible for sustaining investments in data-driven decision-making training throughout their districts and schools. The final product is an adaptable, easy-to-use set of instruments designed to monitor uptake of collaborative data inquiry practices, identify areas of strength and opportunities for growth, and identify which instructional teams need targeted support to become more effective. The Collaborative Data Inquiry Practitioner Toolkit and related reports can be accessed below.
Teaching is a challenging, complex profession with high stakes for students’ future academic, professional, and civic engagement. In recent years, many districts have turned to data-driven decision-making and continuous improvement strategies that rely on data to support teachers’ professional development and to spur instructional improvement. We refer to these diverse approaches to leveraging data in teams as collaborative data inquiry (CDI). CDI models vary in sophistication, approach to data use, and ease of implementation.
Instructional leaders often observe that instructional teams can also vary in their sophistication and in their adoption of CDI practices. However, relatively little is systematically known about how instructional teams might vary and which aspects of collaborative data inquiry are most important for spurring improvements in instruction and student learning.
Collaborative Data Inquiry
In collaborative data inquiry teams, educators work together to improve instruction, using data to connect their teaching to student learning in continuous improvement cycles. When the CDI process is done well, discussions include multiple perspectives: teachers, who are closest to the work and will implement any desired instructional changes; coaches or other instructional experts, who support these changes; and school leaders, who can align the team’s work to the school’s needs and priorities.
To be successful, collaborative data inquiry requires strong team norms and structures, robust collaboration and data use, and individual team member investment and commitment to application of learning.
One widely implemented example of a CDI process is Data Wise, developed at the Harvard Graduate School of Education to help instructional teams collaborate around multiple data sources, surface evidence of students’ strengths and opportunities for growth, identify shared problems of practice, and pursue evidence-based solutions.
To implement Data Wise, schools and districts invest significantly in training their instructional teams. For example, Data Wise-trained teams complete 8-10 hours of pre-work and 5 days of in-person training, ideally followed by 1-2 years of monthly virtual coaching. Other CDI models require similar substantial investments in staff training and on-going support. The CDI Practitioner Toolkit is designed to help districts to scale and sustain collaborative data inquiry during and after this intensive training period, thereby maximizing the return on their investments in CDI interventions like Data Wise.
This Study
Funded by the Department of Education’s Institute of Education Sciences, this project developed and validated a toolkit to observe the quality of collaborative data inquiry in instructional teams. During the 2024-25 school year, SRI field-tested the toolkit in 35 schools in two mid-sized urban districts and tested the validity, reliability, concurrent validity of the toolkit on a range of teacher and student outcomes.
The toolkit will help instructional leaders monitor team progress to support scaling, sustainability, and district accountability for team effectiveness. It will measure team engagement with CDI practices and provide actionable feedback to instructional leaders. The toolkit will be designed for use after teams have had some engagement with data-driven practices and can be used at multiple time points to track progress.
The Collaborative Data Inquiry (CDI) Practitioner Toolkit
The CDI Practitioner Toolkit was developed to help instructional leaders and educators understand, identify, and evaluate the characteristics, processes, and behaviors of effective teams as they engage in CDI, data-driven decision making, and other continuous improvement processes that rely on data. The toolkit is designed to support districts, schools, and instructional teams engaged in many different forms of data inquiry, data-driven decision making, and continuous improvement cycles.
The toolkit measures team engagement with CDI practices and provides actionable feedback to instructional leaders. It is designed to enable school and district leaders to gain insights into team functioning, provide formative feedback, and plan for support and sustainability of CDI practices. The toolkit is intended for use after teams have had some engagement with data-driven practices and can be used at multiple time points to track progress.
The complete CDI Practitioner Toolkit as well as individual toolkit components can be downloaded for free by clicking the links below:
- Team Meeting Exit Ticket (PDF)
- Team Meeting Exit Ticket (Qualtrics Template)
- Team Reflection Protocol (PDF)
- Training Slide Deck (PDF)
Reports
This project began in 2020 as an efficacy study of Data Wise. When the COVID 19 pandemic precluded the recruitment of schools for a randomized control trial, the project was redesigned to focus on the development and validation of a toolkit to measure CDI team processes.
The study team published a report on the instruments developed for the original efficacy study, including a teacher survey and a team meeting log:
The study team will publish a report on the validity study in March 2026.
Associated SRI team members
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Katrina Laguarda
Senior Researcher, SRI Education
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Paul J. Burkander
Senior Education Researcher, SRI Education
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Selin Capan
Education Research Associate, SRI Education
Associated Team Member
- Kerry Schellenberger, Senior Data Scientist, SRI Education
