DID Resource Kit for States, Districts and Schools


Overview: Conditions That Support School Leaders
In Using Data

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.

To be effective in using data for raising student achievement, school leaders need timely, comprehensible data to improve teaching and learning. Leaders need to be trained in how to use data and lead school teams in looking at individual, classroom, grade-level and school- wide data. Effective principals provide time to analyze data and develop “cultures of inquiry” in their schools around data. Schools use multiple sources of data such as student results on state assessments, results on district interim assessments, predictive assessments, diagnostic tests, teacher made tests and customer surveys. School leaders should be supported by access to a data warehouse where they can retrieve tailored information for their school. Schools also need a school improvement planning process that helps them undertake continuous improvement. Finally, schools should be supported by accessing intervention strategies linked to their data analyses.

1. Essential Elements

The University of Washington’s report, Data-Informed Leadership, identifies several conditions that influence 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.
  • Data Training and Infrastructure - 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 Conditions
To support school leaders in using data, the following school-level conditions should be in place:

  • Clear district goals and expectations for student achievement – translated to improvement targets for each school, classroom and student.
  • A principal or “data coach” who can help lead data informed decision-making within a school.
  • The availability of timely, accurate data that are displayed in formats that are easily understood. (This includes disaggregated data, and data that can be used to improve teaching and learning such as student demographics, grades, and curriculum information.)
  • The availability of data from multiple measures that includes state, district, school and classroom information.
  • A school culture of trust and high expectations in using data for continuous improvement.
  • A data warehouse where student progress is tracked over time and easily accessible to school leaders.
  • A school culture of inquiry where data are regularly analyzed, time is set aside for this purpose and school leaders and teachers are trained in using data to answer a clear set of questions.
  • A state or district system where data and data analysis are linked to school improvement planning.
  • A state or district system where results of data analysis are linked to appropriate, research-based interventions for improving teaching and learning – for individual students and teachers. This may include curriculum program alignment to assure all students meet standards. It also includes an ongoing, iterative process.


2. Promising Practices

At Dames Ferry Elementary School in Gray, Georgia, a data team was organized based on member's roles in supporting exceptional students, early intervention, training in Response to Intervention (RTI), and skill in differentiated instruction. Additional training in Max Thompson’s Learning Focused Schools was provided to this team, along with data analysis and application and K-2 literacy. The school team was trained in the Georgia Leadership Institute for School Improvement's model of school improvement. The goal was to improve 5th grade reading scores toward increasing the high school graduation rate so team members collaboratively compiled and shared data across the system.

By analyzing data, the team discovered that classrooms were not yet standards-based and that communication from the school to the community was limited and did not focus on improvement initiatives. Based on this analysis, they decided to focus on creating a standards-based curriculum, using tools to support data informed decisionmaking, focusing professional development efforts based on student results, aligning grade-level instructional practices, expanding stakeholder participation, and extending after-school programs.

The Dames Ferry Elementary data team then compared their practices to best practices. Based on this analysis they redesigned professional development to meet their objectives and developed a school improvement plan using the balanced scorecard. The balanced scorecard aligned with district and state goals, provided incentives for student attendance and informed the community of school programs in which their children could participate. Specifically, the team created a school schedule for grade-level planning time and motivational practices to address student attendance and behavioral concerns.

The principal then targeted teaching opportunities based on results, created monthly maps based on the state curriculum and developed benchmark tests against county-wide best practices. Teachers were provided additional training in the balanced scorecard, RTI, and lesson planning. Common planning periods were established for teachers in grades K-5.

The outcomes included grade-level teams operating as a more cohesive unit. Teachers learned about research-based strategies to use in the classroom and how to modify their instruction to meet the needs of struggling students. Intervention teachers improved achievement for at-risk students and student attendance and participation increased at school and after-school programs.  By the second year of the program student achievement results went from a baseline of 79% proficient to 95% proficient.

Under the leadership of principal Holly Fisackerly, Oleson Elementary School in Aldine, Texas has become one of the highest-performing elementary schools in Texas. In fact, in 2005 the school ranked in the top three elementary schools in the state in reading, mathematics and writing achievement. What makes Oleson’s success even more remarkable is that over 75% of the school’s 930 students are economically disadvantaged, over 80% are minorities and large numbers of students move frequently to different schools within the district.

Dramatic gains in student achievement occurred over three years, when the then new principal worked with teachers to align instruction to clearly defined district goals that set high expectations for all students.

“Let the data drive decisions” is an Aldine mantra. The district assesses student progress in both December and May, and then each spring reports the results of the state assessment – the Texas Assessment of Knowledge and Skills. Test results are disaggregated and reported by subgroup and individual student. Scorecards – including goals, measures, targets and results – are produced for the district, regional areas within the district and each school and classroom. Gaps between targets and results are used to pinpoint both student learning needs and teacher professional learning needs.

Based on student performance against district and state standards, the district develops annual goals. Schools then look at their student results and develop an action plan – organized by school, grade and classroom – to meet achievement goals. Targets and results are reported on scorecards, and reviewed every six weeks. If young students need more time to learn basic language, pre-reading skills or writing skills, they are retained – with parent permission – in kindergarten or 1st grade. As a result, students are rarely retained at the 3rd or 4th grade because their learning is well monitored earlier on.

Checkpoint tests also are given every five weeks to monitor student progress in grades K-4. In K-2, the Texas Primary Reading Inventory is administered to ensure all students are on track to be good readers. The district administers the Iowa Test of Basic Skills twice a year and looks for student progress against national norms and also checks to see if each child has made a year of academic growth. Data checkpoints in later grades help teachers to understand what students are learning and to use different instructional strategies if needed.

The district plays a strong role in supporting the school. District-organized teams identify benchmark targets aligned to state standards. These are sequenced in the curriculum and assessed by the checkpoint tests. The district also recruits a pool of highly qualified teachers.  Every teacher has a growth plan that is supported and monitored by the principal. Every teacher is required to have at least 40 hours of professional learning a year. Teachers are retained by offering a mix of above-average salaries, mentoring, extensive professional development and excellent working conditions.

3. Critical Questions

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

  • Does your school have a data leader?
  • Does your district provide data on students, their demographics and coursework?
  • Does your district administer and report data on interim assessments?  Predictive assessments?
  • Do the results from the state assessment arrive in time for planning?  Are they used in guiding instruction?  Curriculum revision?  Teachers’ professional learning?
  • Does your state provide a guide on how to use state assessment results and understand AYP?
  • Does your school collect and analyze its own data through teacher made tests, grades, student portfolios, and/or “walkthroughs.”
  • Is the school engaged in a school improvement planning process?
  • Is time made available for data teams to meet?
  • Is there a culture of inquiry supported by the school and school district?
  • Can school data teams analyze data and know how to improve instruction based on student results?  Align curriculum?
  • Does your district help link research-based interventions to student achievement results?
  • Are data shared with parents and other community members?
  • Is there an appraisal of leader effectiveness?  How are the results used?


4. School Resources

Bernhardt, Victoria L. (1994). The school portfolio: A comprehensive framework for school improvement. Larchmont, NY: Eye on Education. 978-1883001643. Summary: A school portfolio is an effective self-assessment tool that exhibits a school’s goals, progress, achievements, and vision for improvement. This book demonstrates how to develop a school portfolio tailored to a school’s continuous improvement efforts, using examples from schools that have successfully implemented the tool.

Boudett, Kathryn P. and Steele, Jennifer L. (2007). Data wise in action: Stories of schools using data to improve teaching and learning. Cambridge, MA: Harvard Education Press. Summary:A sequel to 2005’s Data Wise: A Step-by-Step Guide to Using Assessment Results to Improve Teaching and Learning, this book provides concrete examples and suggestions for how to implement the Data Wise process of using assessment results to improve instruction and learning. Case studies of eight schools that have implemented the improvement process offer insight into the challenges faced and strategies used in rolling out the process. The examples demonstrate how these schools adapted the process to fit their particular needs and illustrate how the Data Wise culture can begin with one school leader and spread outward.

Data Quality Campaign. (2008). Tapping into the Power of Longitudinal Data: A Guide for School Leaders. Summary: This short document provides an overview of the power of longitudinal data, making the distinctions between snapshot and longitudinal data. The last section provides action steps for school leaders to build and use longitudinal data systems.

Garmston, R.J. (2005). Group wise: Create a culture of inquiry and develop productive groups. JSD, 26(2). Summary: This article outlines three factors that are key to creating a culture of inquiry and developing productive groups: engaged leaders who continuously communicate and participate in practices; leaders who provide time and space for teacher collaboration; and the occurrence of continuing self-reflection following professional development. These collaborative efforts are focused on improving instruction, raising student achievement, and enhancing the professional community.

Halverson, R., Grigg, J., Prichett, R., & Thomas, C. (2005). The new instructional leadership: Creating data-driven instructional systems in schools. WCER Working Paper 2005-9, Wisconsin Center for Education Research, University of Wisconsin-Madison. Summary: This paper considers how school leaders develop data-driven instructional systems (DDIS) to facilitate the flow of information throughout their organizations.

Ingram, D., Louis, K.S., et al. (2004). Accountability policies and teacher decision making: Barriers to the use of data to improve practice. Teachers College Record, 106(6), 1258-1287.  Summary: This paper reviews findings from a longitudinal study of nine high schools nominated as leaders in Continuous Improvement (CI) that considers teacher willingness to use data to assess their own, as well as that of their colleagues and schools, effectiveness and ability to make improvements. It reveals inconsistencies between cultural assumptions and accountability policies, and barriers to the use of data in schools.

Lachat, M. A., & Smith, S. (2005). Practices that support data use in urban high schools. Journal of Education for Students Placed at Risk (JESPAR) 10(3), 333-349. Summary: This article presents initial findings of a case study focusing on data use in five low-performing urban high schools undergoing comprehensive school-wide reform. Study findings include several factors that contribute to data use in these study sites: the quality and accuracy of data; staff access to timely data; the collaborative use of data organized around clear objectives; and leadership structures that support the use of data.

Stiggins, R. J. (1994). Student-centered classroom assessment. New York: Macmillan College Publishing Company. Inc. 978-0134329314. Summary: This book provides information on student-involved and classroom-based assessment practices. It includes information on how educators can develop quality assessment procedures within the classroom setting. The author gives clear descriptions of various assessment methods and how to align them with relevant achievement goals.

Supovitz, J. & Klein, V. (2003, November). Mapping a course for improved student learning: How innovative schools systematically use student performance data to guide improvement. University of Pennsylvania Graduate School of Education: Consortium for Policy Research in Education. Summary: This report develops a framework to help educators build more efficient and effective systems for data collection and analysis, and explains how school leaders and teachers can use student performance data to guide instruction and decision making.

Symonds, K. W. (2003). After the test: How schools are using data to close the achievement gap. San Francisco: Bay Area School Reform Collaborative. Summary: The Bay Area School Reform Collaborative (BASRC) surveyed 32 K-8 schools in the San Francisco Bay Area in order to identify effective school-level policies and strategies of schools narrowing the achievement gap between higher- and lower-achieving groups of students. Findings from the study are grouped into three categories, including, teacher support for use of data, leadership for equity, and school focus. The authors recommend that schools need frequent and reliable data, teachers need support to use data, schools need to hire and promote people of color and opportunities for faculty to discuss how race and ethnicity affects students' experiences in school, and focus on ensuring that students are mastering reading and literacy skills that are the foundation of learning.

Wiggins, G. P. (1998). Educative assessment: Designing assessments to inform and improve student performance. San Francisco: Jossey-Bass, 978-0787908485. Summary: This book covers all aspects of assessment design, including how to craft performance tasks that meet rigorous educational standards, how to score assessments fairly, and how to structure and judge student portfolios. It also looks at how performance assessment can be used to improve curriculum and instruction, grading and reporting and teacher accountability.