Equity in education: Achievement gap demands good data

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Using data for good requires good data if we're going to close the achievement gap. Image by US Department of Education

The latest post in our Equity in Education series focuses on the achievement gap. National achievement data show that our public education systems work well for students with means. And not so well for disadvantaged students. Racial achievement gaps are found in the National Assessment of Education Progress (NAEP), also known as the “Nation’s Report Card.” On the 2015 NAEP Mathematics eighth-grade assessment, black students scored 32 points lower, on average, than white students.1

More alarming, the achievement gap between children from high- and low-income families is widening. It was roughly 30 to 40 percent larger among children born in 2001 than among those born in 1976.2 The socioeconomic status of a child’s parents has always been one of the strongest predictors of the child’s academic achievement and educational attainment. But it doesn’t have to be this way. I also lived on the poverty line, yet my public schools managed to help me reach the highest academic levels. The current equity agenda across state education agencies should help public school systems accomplish this for all students.

Conventional wisdom could prompt policymakers to focus on solving the poverty problem to improve academic outcomes. However, poverty is likely impossible to tackle in a four-year political term or average 3.2-year tenure of a chief state school officer.3 In the meantime, state leaders can strive for better performance measurement, find schools that are beating the odds, and use the strength of the evidence to guide expansion of the best programs, practices, and policies to shrink equity gaps.

States should strive for better performance measurement when looking at the contradictions in public education statistics. In 2014–2015, the U.S. high school graduation rate rose to an all-time high of 83.2 percent,4 yet various sources cite an average of 40 percent of college freshman as being not “college ready.” A 2011 report by the National Governor’s Association states that “approximately 40 percent of all students and 61 percent of students who begin in community colleges enroll in a remedial education course at a cost to states of $1 billion a year.”5 In these cases, students are paying full tuition for noncredit-bearing coursework—courses like Algebra I that they passed in high school in order to get a diploma but didn’t master.

While state test proficiency rates generally increased under No Child Left Behind (NCLB) accountability systems, this was in part due to many states lowering the proficiency bar, or cut scores. In contrast, 2016 NAEP results showed a drop in twelfth graders’ math scores and no improvement in reading—results unfortunately consistent with those previously released for fourth and eighth graders.

Looking globally, U.S. state standardized test scores rose under NCLB while our nation slipped on international benchmark tests such as The Programme for International Student Assessment (PISA). Out of 34 countries administering PISA in 2012, the U.S. ranked 27th in math, 17th in reading, and 20th in science.6 This reflects a drop in our nation’s ranking among 32 countries in 2000: 18th in math, 15th in reading, 14th in science.7

These contradictions provide a gut check. U.S. educators and policymakers need to get honest about student performance through better measurement. As states redesign accountability systems and school report cards under the Every Student Succeeds Act (ESSA,) they need to be designed with equity in mind so that they illuminate equity gaps in access to effective teachers, programs, resources, and opportunities. State leaders who think they already have measurement systems and data dashboards in place should to take a second look. It’s not just about providing more big data in a dashboard, but rather equipping our schools and teachers with data tools that can make a difference.  Performance metrics that illuminate equity gaps across districts, schools, and classrooms require some pretty sophisticated analytics. In order to use education data for good, decisions must be first based on good data that turn our attention to the most pressing inequities.

  1. Bohrnstedt, S. Kitmitto, B. Ogut, D. Sherman, and D. Chan, School Composition and the Black–White Achievement Gap (Washington, D.C.: U.S. Department of Education, National Center for Education Statistics, 2015), https://nces.ed.gov/pubsearch/pubsinfo.asp?pubid=2015018.
  2. Sean F. Reardon, . “The Widening Academic Achievement Gap Between the Rich and the Poor: New Evidence and Possible Explanations” (Stanford University/Russell Sage Foundation, 2011), https://cepa.stanford.edu/sites/default/files/reardon%20whither%20opportunity%20-%20chapter%205.pdf.
  3. Andrew Uijfusa, “Turnover, Growing Job Duties Complicate State Chiefs’ Roles,” Education Week (January 2015), www.edweek.org/ew/articles/2015/01/28/turnover-growingjob-duties-complicate-state-chiefs.html.
  4. Alyson Klein, “Graduation Rate Hits Record High of 83.2 Percent: Should Obama Take Credit?” Education Week (October 2016), http://blogs.edweek.org/edweek/campaign-k-12/2016/10/graduation_rates_hit_another_h.html
  5. Ryan Reyna, “Common College Completion Metrics,” National Governors Association, (2010), www.nga.org/files/live/sites/NGA/files/pdf/1007COMMONCOLLEGEMETRICS.PDF
  6. Andreas Schleicher and Michael Davidson, “Programme for International Student Assessment (PISA) Results from PISA 2012” (Paris, France: Organisation of Economic Co-operation and Development, 2012), https://www.oecd.org/pisa/keyfindings/PISA-2012-results-US.pdf.
  7. M. Lemke, C. Calsyn, L. Lippman, L. Jocelyn, D. Kastberg, Y. Liu, S. Roey, T. Williams, T. Kruger, and G. Bairu, “Outcomes of Learning: Results from the 2000 Program for International Student Assessment of 15 Year Olds in Reading, Mathematics, and Science Literacy” (Washington, DC: U.S. Department of Education, National Center for Education Statistics, 2002), http://nces.ed.gov/pubs2002/2002116.pdf.

 

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About Author


Senior Manager, Education Consulting

Hi, I’m Nadja Young. I’m a wife and mother of two who loves to dance, cook, and travel. As SAS’ Senior Manager for Education Industry Consulting, I strive to help education agencies turn data into actionable information to better serve children and families. I aim to bridge the gaps between analysts, practitioners, and policy makers to put data to better use to improve student outcomes. Prior to joining SAS, I spent seven years as a high school Career and Technical Education teacher certified by the National Board of Professional Teaching Standards. I taught in Colorado’s Douglas County School District, in North Carolina’s Wake County Public School System, and contracted with the NC Department of Public Instruction to write curriculum and assessments. I’m thrilled to be able to combine my Bachelor of Science degree in Marketing Management and Master of Arts degree in Secondary Education to improve schools across the country.

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