The long-term success of school leaders requires supportive conditions at all levels of the education system. In Leadership for Learning, The Wallace Foundation suggests three core elements of policy that largely determine the quality of school leadership and the environment in which they will either succeed or fail: (1) leader standards, (2) leader training and (3) system conditions. Conditions and incentives that heavily affect the long-term success or failure of leaders include: the presence or absence of necessary data to inform decisions; the authority and decision-making leaders either have, or lack; the ability to direct needed resources (people, time and money) to meet all students’ needs; and whether or not state and local policies affecting the recruitment, hiring, placement and evaluation of school leaders and teachers supports schools. Conditions that support data informed decisionmaking are described here.

At the district level, supportive conditions for data-informed decision-making include receiving timely data from state assessments and accountability systems; access to data warehouses that store and can help link data for decision-making; training in data use and data literacy; common or benchmark assessments aligned with state standards; school improvement planning processes that use data, predictive assessments such as those predicting college or work readiness; and, tools like the Balanced Scorecard that can provide district leaders with a wider range of data as well as leading indicators. Districts may develop or adopt their own assessments to diagnose, place and/or monitor student progress. Districts may collect and report a wide array of data beyond student achievement including budgets, how resources are allocated, staffing patters and staff qualifications and program information.

Data-Informed Decisionmaking: Leaders who use data to inform school improvement decisions know what goals to set and how close they are to achieving them. States, districts, and schools with easily accessible and comprehensive data systems provide accurate and timely data for informed decisionmaking. Summative data, such as those required by NCLB, are used primarily for accountability purposes. Formative data, such as those provided by district-level benchmark assessments, are used primarily for improvement purposes, since the data are more frequent and timely. Useful data can include student achievement results; predictive measures, such as student scores on college readiness assessments; indicators of teacher quality; student participation in early learning programs; and findings from tools like Balanced Scorecards, which provide leading indicators for school improvement.

Effective use of data requires training in data literacy for policymakers, district and school leaders, and stakeholders. Data displayed in easily understandable formats contribute to its use in school improvement planning approaches. Data can be used to identify promising practices that can be adopted to improve instruction and student learning. Cultures of inquiry -- involving ongoing, school-wide, and collaborative use of data -– help school leaders have conversations about the improvement of practice. When identified practice issues are identified and linked with effective, research-based interventions or changes in practice, student learning increases.

1. Essential Elements
The University of Washington report, Data-Informed Leadership, identifies several conditions that have an influence on how leaders can work with data:

• Focus on Learning Using Data – a persistent, public focus on learning improvement offers an especially important reference point for the leaders’ use of data, with emphasis on data concerning efforts to improve the quality of teaching and learning.
• Core Values and Theories of Action – five values are identified that focus on learning improvement:  ambitious standards for student learning, belief in human capacity, commitment to equity, belief in professional support and responsibility, and commitment to inquiry.
• Leader’s Data Literacy – how well the leader can understand the data reflects on their abilities to work with it.
• Available Data and Data Sources – includes student demographics, perceptions, student learning, school processes, teacher characteristics, behavior, and personal learning.
• Culture and Cycles of Inquiry – building a culture in your district that supports inquiry is important because it can reduce the risk of top-level leaders asking and answering questions about practice and performance; the leadership and support for inquiry must be distributed among the stakeholders of the organization.
• A policy environment - that includes investments in the development of leaders’ data literacy and investments in the development of data infrastructures, such as longitudinal data systems and data warehouses.

Supportive District Level Conditions
To support school leaders in using data, the following district-level conditions should be in place:

• District goals and standards that can be assessed. District goals are aligned to state goals.
• A balanced state and district level accountability system.  The state provides annual assessment results for accountability purposes and districts use common or benchmark assessments on a regular basis for monitor student progress.
• A school improvement planning process that uses data.
• District norms to support data use at the school board, district and school level.
• A data tracking system such as a longitudinal data system and data warehouse that is easy to use.
• Training in data use, including using data in cycles of inquiry.
• Transparency of data including public reporting of results and the engagement of stakeholders.

2. Promising Practices
According to Achieving with Data (Datnow & Wohlstetter, 2007) performance-driven school systems use six key strategies. These are:

1. Building a foundation for data-driven decision-making including measurable goals at the school, system, school and classroom level. They also monitoring the implementation of a system-wide curriculum that allowed them to gather, organize and act on data about student achievement.
2. Establishing a culture of data use and continuous improvement including expectations and norms requiring data use. Mutual accountability was fostered between the schools and central office which helped to build a commitment to continuous improvement.
3. Investing in an information management system to organize data in an accessible format and presenting it in a comprehensible manner. Data were timely and accessible and its use was supported by central office staff and school personnel.
4. Selecting the right data to guide improvement efforts included achievement data, instructional practice data, and goal implementation data. System-wide interim assessments aligned to standards providing timely data for interventions leading to improvements. Data were used to make instructional, curricular, resource allocation and planning decisions.
5. Building school capacity for data-driven decision-making occurred by investing in professional development, providing support for staff in how to use data and modeling data use, providing time for teacher collaboration, and connecting educators across schools to share data and improvement strategies.
6. Analyzing and acting on data to improve performance was accomplished by developing tools and processes to help all educators act on data. Tools included data analysis protocols and goal-monitoring reports for different role groups. Schools received immediate feedback to schools on student achievement and progress toward meeting their goals.

Elk Grove Unified School District near Sacramento, California was selected by the American Productivity and Quality Center (APQC) as a district that is exemplary in its use of data to close the achievement gap. As the fifh largest district in California, Elk Grove has 62,000 students, 62 schools, with 46% of the students receiving free and/or reduced lunch. Students come from homes that speak over 70 different languages. 

The state accountability system is the primary student achievement data monitored by the district. For all students, the district set a “bold goal” of 100% of the students meeting proficiency or advanced proficiency on all subjects assessed. The district has created many data charts and process questions that are shared with district leaders, school leaders and teachers. Principals are encouraged to look at their achievement gaps in detail, identifying achievement by ethnicity and trends over time. They are then encouraged to share this information with their community and engage parents in making sense of the data.

The district has also developed its own benchmark assessments that are administered several times a year in all grades and in reading and mathematics. Principals are asked to undertake a mid-year Assessment Data Analysis to inform instruction. The benchmark assessments are used to gauge progress and refocus on priority standards. A process template guides school leaders to identify units/lessons, identify supplementary resources and materials that might be used, adjust the instructional calendar and change instructional strategies to help students meet their achievement targets.

Resources are allocated to schools based on their needs through the use of site support teams. Every school has a support team comprised of district and school leaders who meet together monthly to identify school-specific strategies to close the achievement gap. These teams have “robust, honest dialogue” and make data-driven decisions to improve achievement across the board. Site teams align district professional learning resources, provide data systems and technology infrastructure and realign the resources of “time, talent, and treasure.”

Valley High School used the advice and help from its site support team. First, district curriculum specialists worked in partnership with school administrators and teachers to identify curriculum and instructional approaches for intervention classes. The district research department helped school leaders develop a placement matrix for 9th grade students in English and math based on student achievement data. The district professional learning staff provided targeted professional development based on closing the achievement gap. The school changed its schedule to double-block English and Algebra linked to a support class.  Teaching assignments were adjusted to place the most qualified teachers with students in need of the most support.

Sustained professional learning is based on an analysis of student achievement data. A trainer- of-trainers model is used in all schools to implement instructional strategies that engage all students. Elk Grove focused on two main areas: the first, teaching academic language to all students because of the ethnic diversity of the students, and second, providing more time for student-to-student interaction.

What’s been the result? Valley High School has made five years of continuous growth, moving from an Academic Performance Index score of 579 to 693.

3. Critical Questions
To ensure supportive conditions are in place for leaders to use data effectively, the following questions should be answered:

• Does your district have measurable goals and standards?
• Does your district use a balance of formative and summative assessments?
• Has your district identified multiple measures to assess all aspects of student achievement and system strategies related to raising student achievement?
• Does your district have a school improvement planning process?  That is understood and used by all?
• Does your district have access to a longitudinal data system and data warehouse that provides student level information for district leaders, school leaders and teachers?
• Does your district have benchmark assessments that provide timely data for intervention?
• Does your district administer predictive assessments (e.g., PSAT, EPAS) to ensure students will be ready for college and/or work?
• Are school leaders and teachers in your district trained in the use of data?
• Is a culture of inquiry supported by your school district, including time to collaboratively analyze data?
• Do school leaders receive timely data reports that are easy to understand?
• Does your district help link research-based interventions to student achievement results?
• Is there transparency of information that is shared with stakeholders?  Discussed?  Acted upon?
• Are data used to make personnel and resource allocation decisions?

4. District Resources

Most of these resources are from the UCLA/CRESST Assessment and Accountability Comprehensive Center Library.

Armstrong, Jane & Anthes, Katy. (2001). How data can help. American School Board Journal 188 (11), 38-41. Summary:This article highlights the key practices and attributes of six school districts in five different states that effectively used data to improve teaching and learning. All of the districts served low-income, transient and low-achievement populations of students and all were able to substantially improve student achievement through the use of data. Essential factors across these districts included: strong leadership; a supportive district wide culture for using data; a strong service orientation toward principals and teachers; partnerships with universities, businesses and nonprofit organizations; mechanisms for supporting and training personnel to use data; close monitoring of students’ performance on academic standards; and a well-defined, data-drive school improvement process.