With the passage of the Every Student Succeeds Act (ESSA), states gain considerably more authority and autonomy over the design of school accountability systems. This shift in responsibility creates the opportunity for states to reimagine new accountability models that align to goals of college and career readiness for all students and to move from a culture of compliance to one of continuous improvement.
This report provides a resource to inform design and implementation decisions as state policymakers embark on the task of creating their next generation accountability systems. The authors discuss the limitations of using a single composite accountability index, advance principles and a conceptual framework to drive next generation accountability, describe potential indicators of what they call an “Educational Quality and Improvement Profile,” and offer recommendations to guide the design and implementation of these new accountability systems.
Part One: The Significance of a Single Composite Index
Many states have relied on an accountability index for so long that policymakers may be unaware that reducing school performance to a single indicator hides more than it reveals about teaching and learning. Without a thorough understanding of measurement limitations, the response to ESSA may be to focus on the creation of a “better” indicator, by merely adjusting the formula used to rank or sort schools. Such a response ignores problems inherent in these systems and would not provide decision makers with the information they need to assess educational quality and improvement.
Four problems stand out as jeopardizing the accuracy and legitimacy of decisions made about schools based on composite indicators: poor conceptual alignment, hidden variance in student performance, misleading accounts of student growth, and the absence of explanatory evidence for making sense of school outcomes.
Part Two: Principles and Framework for Next Generation Accountability
First-generation accountability, in compliance with the prescriptions of the federal No Child Left Behind (NCLB) law, exposed vast, inequitable differences in student test scores across and within schools. Accountability systems, however, were not effective at informing capacity building within schools aimed at raising and equalizing achievement.
Next generation accountability is governed by three principles:
1. Shared Accountability. In a complex enterprise such as public education, performance responsibility is distributed across the system’s components and not left to any one group of actors or stakeholders.
2. Adaptive Improvement. Next generation accountability acknowledges that school capacities differ greatly and that systems must be flexible and responsive to particular school conditions.
3. Informational Significance. The information system designed to support next generation accountability needs to both comply with federal mandates and inform and enable school improvement. It should also reflect the different information needs of state and district policymakers, school site leadership, teachers, and parents.
In keeping with these principles, next generation accountability systems must both provide schools with useful information for their own improvement decisions and address the need for states to identify and support schools in need of improvement.
Part Three: An Educational Quality and Improvement Profile
The authors propose use of an Educational Quality and Improvement Profile (EQuIP), which reports data on school resources, processes, and outcomes in order to both assess school quality and focus school improvement efforts. They offer six guidelines for how data should be reported:
1. Outcome indicators should report achievement differences by student subgroup performance and changes in individual student performance over time.
2. Outcome indicators should be capable of identifying focus schools, priority schools, and reward schools consistent with criteria for federal waiver requirements.
3. Process and resource indicators should be scientifically defensible and tap conditions, attitudes, structures, and behaviors that can advance the goals of deeper learning and college and career readiness.
4. Indicators should be collected with appropriate frequency and minimal disruption to the learning process.
5. Indicators and measurement methods should have substantial evidence to support their validity and reliability, with the understanding that no single measure is perfect.
6. Indicators and measurement methods should change over time in response to the continuous evaluation and improvement of a state’s school accountability framework.
Part Four: Designing and Implementing Next Generation Accountability
The authors offer the following recommendations for state and local policymakers interested in pursuing this path to educational quality and improvement.
1. Do not use a single summative index to report accountability information.
2. Report outcome evidence in ways that clearly identify student performance toward deeper learning and college- and career-readiness standards, changes in student performance over time, and achievement gaps.
3. Include multiple indicators of capacity for quality improvement as part of a school profile.
4. Adhere to the Standards for Educational and Psychological Testing and write the policy in the least restrictive and prescriptive terms possible to allow for corrective action and improvement.
Alignment of Standards, Assessments, and Accountability: An essential first step in the development of a next generation accountability system is to make sure that curricular, assessment, and evaluation systems all align with and/or serve larger operational definitions of what it means to be a healthy, productive citizen.
School, District, and State Capacity Building: The authors identify the essential elements of the support infrastructure needed to build systemwide capacity: (a) state, district, and school leaders must create a systemwide culture grounded in “learning to improve”;
(b) learning to improve using EQuIP necessitates the development of strong pedagogical data-literacy skills; (c) resources in addition to funding—including time, access to expertise, and collaborative opportunities—should be prioritized for sustaining these ongoing improvement efforts; (d) there must be a coherent structure of state-level support for learning to improve, including the development of a strong Longitudinal Data System (LDS) infrastructure; and (e) educator labor market policy in some states may need adjustment to support the above elements.