The Myth of Accountability: How Data (Mis)Use is Reinforcing the Problems of Public Education
There is an ongoing tension in the American public education system between the values of excellence, equity, and efficiency. Accountability has emerged as a framework in education reform that promises to promote and balance all three values. Yet this frame is often contested due to disagreements over the role of incentives and penalties in achieving desirable change, and concerns that the proposed mechanisms will have significant unintended consequences that outweigh potential benefits. More fundamentally, there is widespread disagreement over how to quantify excellence and equity, if it is even possible to do so. Accountability rhetoric echoes a broader turn toward data-driven decision-making and resource allocation across sectors. As a tool of power, accountability processes shift authority and control to policymakers, bureaucrats, and test makers over professional educators.
Today, measurements of school performance have become so commonplace that they are an assumed part of education debates. As new forms of data are easier to collect and analyze, drawing on and interacting with information to measure the impact of programs and to inform decision-making and policy has emerged as a key strategy to foster improvement in public schools. But when did our national obsession with educational data start? What are the historic precursors to accountability as we now know it? What set of political, economic, cultural, and social conditions led to test scores becoming the main measure of a school’s success? How do current data-driven practices compare to historical data-driven practices and how have the terms shifted over time? Who does accountability serve? What are the incentive structures, and how is accountability gamed and resisted? In short, accountability of what, to whom, for what ends, at what cost?
The accountability movement reflects the application of free market economics to public education, a legacy of the Chicago School of Economics in the post-World War II era. As a set of policies, accountability was instantiated in the Elementary and Secondary Education Act (ESEA) of 1965, reauthorized as the No Child Left Behind Act (NCLB) of 2002, and reinforced by the Every Student Succeeds Act (ESSA) of 2015. ESSA gives more autonomy and flexibility to states than they had under NCLB through competency-based assessments, which could drive the development of personalized learning technologies. ESSA ’s accountability processes also require new types of data collection and disaggregation, including of non-academic indicators of school quality. Significantly, ESSA mandates the collection and reporting of per pupil expenditure data at the school level. Teach- ing and learning are increasingly being measured and quantified to enable analysis of the relationship between inputs (e.g., funding) and outputs (e.g., student performance) with the goal of maximizing economic growth and productivity and increasing human capital.
The accountability movement is built on a long history of standardized testing and data collection that privileges quantification and statistical analysis as ways of knowing. An underlying assumption is that learning can be measured and is an effect of instruction. This is an empiricist perspective descended from John Locke and the doctrine that knowledge derives primarily from experience. Accountability in education also holds that schools are fundamentally responsible for student performance, as opposed to families, neighborhoods, communities, or society at large. This premise lacks a solid evidentiary basis, as research shows that student performance is more closely linked to socioeconomic status. Finally, efforts to achieve accountability presume that market-based solutions can effectively protect the interests of society’s most vulnerable.
As has been true in other sectors when data-driven surveillance and assessment practices are introduced, outcomes may not be as expected. It is unclear whether this data push will promote equality of opportunity, merely document inequality, or perhaps even increase racial and socioeconomic segregation, as Pauline Lipman has argued in her work on neoliberal educational reform in Chicago. Furthermore, little is understood about the costs of increased assessment on the health and success of students and teachers, externalities that are rarely measured or considered in the march to accountability. States will need to generate stakeholder buy-in and think carefully about the metrics they include in their accountability formulas in order to balance mandates for accountability, the benefits that accrue to students from preserving teacher autonomy and professionalism, the social good of equal opportunity, and public calls for transparency and innovation.
In order to ground conversations about the use of data analytics in education, this paper examines what accountability allows us to see and what it obscures from our vision. As accountability has become a mainstay of public education, we must also consider how accountability instruments and related education reform platforms are themselves assessed and held accountable. Education reform and the battles over accountability are increasingly intersecting with new technologies, which are imagined to create new forms of accountability with little consideration for the longstanding history of current trends. Taking a step back is necessary to successfully move forward.
