Teacher Pay is Stagnating. Data and Analytics Could Give it a Boost

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In this special guest feature, University of San Diego Assistant Professor in Economics, Alison Sanchez, argues that economic questions like how to increase teachers’ pay can be answered through large-scale data analysis. A National Science Foundation Graduate Research Fellow, Alison Sanchez joined the University of San Diego School of Business in 2016 as an assistant professor of economics. Her interdisciplinary research combines behavioral economics with techniques and insights from neuroscience, psychology, information theory and machine learning. She holds a Ph.D. in Economics from UCSD.

Wage growth for workers in the United States economy has lagged over the past few decades. The Pew Research Center notes how, after inflation, today’s real average wage has the same purchasing power as it did four decades ago. For teachers, the wage situation is even more dire. Average weekly pay for public school teachers has actually decreased by $27 from 1996 to 2017, according to the Economic Policy Institute.

There is not one single answer or explanation behind this widespread salary drop for teachers, but data and analytics can reveal individual causes of teacher pay stagnation and provide customized solutions to address them.

How analytics can be used to address teacher pay gaps

In education, data and analytics are already being used to evaluate student performance and develop methods for academic improvement. Analysis of annual grade book data could reveal a certain teaching method or educational tool was successful or inefficient. Steps could then be taken to implement that successful initiative or remove the inefficient component on a larger level.

These same analytical steps and procedures could be applied to scenarios regarding teacher wage stagnation. For example, descriptive analytics can reveal what teachers may need higher salaries and which groups or demographics of educators are under performing. These analytics can reveal what caused stagnation in the first place, like new policies impacting wages or benefits.

Predictive and prescriptive analytics can show probable effects of certain policies or programs that were put into action, such as district-wide pay increases for teachers or individual performance-related initiatives. The district-wide pay increases could boost larger overall pay but ignore individual discrepancies within schools. The performance initiatives could help alleviate individual gaps but not the larger reasons why they exist. But we’re able to see the benefits and drawbacks of these potential initiatives through these analytics.

One doesn’t have to be an established data analyst with an advanced degree to uncover these insights. With a firm understanding of fundamental data and analytics procedures, teachers and education administration professionals can help evaluate this information alongside data professionals.

Next steps after insights are revealed

These insights can then be incorporated by education officials on the next decision-making level. For an individual school, that may be the principal or a school board. For a school district, it may be the superintendent or some larger government body or agency.

The insights are only valuable, however, if they compel decisionmakers to make actionable change. Policymakers may question if the economic benefit of a certain policy, such as raising teacher wages by $5.00 per hour, outweighs the initial cost of such a move, and leave what may have been a groundbreaking proposal on the table.

Those same policymakers may also question why it is so imperative to raise teacher wages. Here, analysts and education officials can present data and analysis that illustrates how the negative economic benefits of this pay stagnation extend beyond teachers themselves.

These can include how educators who take on side gigs to make ends meet can be overworked, or how lack of promising wages prevents the most talented candidates from seeking employment in the industry. And with teachers having less money to spend, that means less overall economic activity.

Take caution when using data and analytics

When using data and analytics to address teacher salary stagnation, no one-size-fits-all approach will do. The factors generating a wage gap in one school district may be completely independent and isolated from the elements perpetuating low wages in an educational community a few miles away.

Even with new policies guided by data in place, stagnation can still continue. Despite similar policies in business and healthcare to address wage stagnation, there are still workers being underpaid, with the larger forces that are contributing to their low wages being unacknowledged or unaddressed.

The data collection and analysis process takes time, as well as navigating the bureaucratic environments of education and government. New factors that impact teacher salaries could emerge while educators, administrators, and policymakers are still deliberating about how to address old causes of wage stagnation. With all this in mind, data and analytics are still beneficial as a new and alternative means of addressing teacher pay. Their ability to spot causes of pay discrepancies and to help develop solutions that remedy them, make analytics an invaluable component for policymakers at schools and within school districts.

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