Educational Policies and Their Impact on the (Un)Ethical Use of Data

• In Event: Data Ethics in Education: The Importance, Issues, and Use Cases

Abstract

Data are nothing new to educators. As long as we have had classroom instruction and teachers who care about what students learn, how fast they learn it and how deeply, we have mechanisms for measuring those outcomes. Although data have been a constant presence in classroom settings, their form, function, and prevalence have changed significantly over time—changes that are largely driven by an evolving educational policy landscape that mandates the use of data for making decisions about educational quality. In this presentation I trace American education policies of the last several decades and show how policy mandates for how data should be used has had deleterious effects on teacher practices and student outcomes.
In this presentation, I focus on what we have learned from decades of high-stakes testing practices initiated under the No Child Left Behind act of 2002. Although high-stakes testing was not new at the time, NCLB mandated the widespread adoption of the practice for all public school throughout the nation and has continued in some form for decades. Since its inception, we have learned a great deal about the effects of this practice. For example, we know that an over reliance on a single data point for making highly consequential decisions about schools, teachers, and students has had largely negative effects on instructional practices. When teachers feel pressured to make sure students do well on tests, they make instructional decisions to ensure resultant testing data are favorable—decisions that are in many cases questionable (e.g., cheating, teaching to the test).
Another result of these circumstances is that it has created a situation where ethical and unethical decision making becomes more difficult to disentangle. For example, there are examples of blatantly unethical actions such as cases where teachers cheat such as when they change students’ answers from wrong to right to ensure a higher score. However, there are also a host of other types of actions that are less clearly identified as “unethical” and instead might even be considered appropriate or noble. In short, the boundary between ethical and unethical decision making within high-stakes testing landscape is at times fuzzy. In the end, the complex array of possible (un)ethical behaviors underscores the necessity of ensuring all teachers, both present and future, are trained to understand the role, value, purpose, and consequences of data-driven decision making in their teaching.
Data are an important part of education. We need data to understand behavior, academic achievement, and other information to be able to assess how schools are functioning. However, we must also be very clear in how these data are used. As I will discuss, the more important a single data point becomes for decision making, the more likely we will see corruption and distortion in educational practices. Education policies and teacher training programs must guard against this situation or else we will continue to see problems in how we educate our students. This paper will discuss the implications of accountability on the ethical use of data.

Author

• Sharon L. Nichols, The University of Texas - San Antonio