This is an excerpt from “E(race)ing Inequities: The State of Racial Equity in North Carolina Public Schools” by the Center for Racial Equity in Education (CREED). Go here to read the full report and to find all content related to the report, including the companion report Deep Rooted.
Attendance affects numerous educational outcomes. Absences are negatively associated with academic achievement, high school graduation, and standardized test performance (Ginsburg, Jordan, & Chang, 2014; Gottfried, 2009; Lehr, Hansen, Sinclair, & Christenson, 2003; Steward, Steward, Blair, Jo, & Hill, 2008). North Carolina defines chronic absenteeism as having missed more than 10% of school days enrolled in a given school year. National data based on similar definitions indicates that between 10-15% of K-12 students are chronically absent (U.S. Department of Education, 2016). Percentages are often much higher in districts that serve large proportions of students of color and students from lower socioeconomic backgrounds (Nauer, Mader, Robinson, & Jacobs, 2014). Researchers have warned of the devastating effect of chronic absenteeism on the life chances of individual students while noting reform efforts on the district, state, and national level to reduce chronic absenteeism (Balfanz & Byrnes, 2012; Ginsburg, Jordan, & Chang, 2014).
Addressing problems with student attendance has been a particularly vexing problem for researchers across numerous fields due to the many factors that impact attendance (Kearney & Graczyk, 2013). However, a growing body of literature explores the role that schools can play in preventing chronic absenteeism through early identification, intervention and progress monitoring, behavioral approaches, procedures to reduce academic obstacles, and team-based approaches for intervention (Sailor, Doolittle, Bradley, & Danielson, 2009).
Considering the documented negative effects and the role schools can play in its production and prevention, this report positions chronic absenteeism as an indicator of access and opportunity. Given its documented concentration in schools serving large proportions of students of color and students from lower socioeconomic backgrounds, chronic absenteeism may differentially expose these groups to the risk of school failure.
We examined the attendance records of over 1.1 million public school students in North Carolina during the 2016-2017 school year. Over 90,000 students, approximately 8%, were considered chronically absent. Unlike many previous studies, our data allowed us to separate out-of-school suspension (OSS) days from other absences, which may explain the difference between the lower percentage of chronically absent students in North Carolina (8%) as compared to the national averages (10-15%). While we did not include OSS days in our counts of chronic absenteeism, we do examine the relationship between race/ethnicity and OSS as a predictor of attendance below.
Figure 6.1 displays the proportion of chronically absent students by race/ethnicity. American Indian, Black, Hispanic, and Multiracial students are over-represented in chronic absenteeism, while Asian, Pacific Islander, and White students are under-represented.
We also built statistical models to predict the likelihood that a student would be chronically absent. In order to isolate the effect of different predictors, we used three models.
Model 1 included only race/ethnicity with Whites as a reference group. Model 2 included gender, language status, special education status, free/reduced lunch (FRL) eligibility, and giftedness. In the final model (Model 3), we included a variable indicating whether a student had received an out-of-school suspension at least once during the school year.
In Model 1, Asian students were approximately 60% less likely to be chronically absent compared to White students. Pacific Islanders were similarly likely as White students to be chronically absent. Black students were 38% more likely, Multiracial students were 34% more likely, Hispanics were 21% more likely, and American Indian students were 142% more likely than White students to be chronically absent.
The inclusion of additional predictors in Model 2 substantially changed the magnitude and direction of the effect of race/ethnicity for Black, Multiracial, Hispanic, and American Indian students. When controlling for gender, language status, special education status, free/reduced lunch eligibility, and giftedness, American Indian and Multiracial students were still more likely to be chronically absent than White students at 58% and 6%, respectively, although the magnitude of the effect was much smaller than Model 1. However, Black and Hispanic students switched from being more likely to be chronically absent than White students to being less likely to be chronically absent (by 8% and 14% respectively).
With the inclusion of a variable for whether a student had been suspended at least once in the final model, only American Indians were more likely than White students to be chronically absent (by 40%). Controlling for out-of-school suspension further reduced the likelihood of chronic absenteeism for Blacks in comparison to Whites.
The strength of suspension as a predictor of the likelihood of being chronically absent is also noteworthy. Recall that our counts of days missed in determining chronic absenteeism did not include out-of-school suspension days. Yet, after controlling for the effect of all other predictors (race/ethnicity, gender, language status, special education status, FRL status, and giftedness), receiving an out-of-school suspension increased the likelihood of chronic absenteeism by over 350%.
That is, regardless of race/ethnicity and other factors, receiving at least one suspension made students 3.5 times more likely to be chronically absent (not including the out-of-school suspension days) during the 2016-2017 school year.
Further, the effect of suspension was approximately double that of any other significant predictor in the model.
In the context of racial/ethnic equity, chronic absenteeism is something of an outlier. For the other access and opportunity metrics in this report, results tend to position Asians the best situated, with American Indian, Black, Hispanic, and Multiracial students less well-situated and Pacific Islanders similarly situated to their White counterparts. While this pattern holds for American Indians, Asians and Pacific Islanders in the context of chronic absenteeism, it is inverted for Black, Hispanic, and Multiracial students.
Overall, several conclusions flow from our analysis of chronic absenteeism. First, given their consistently higher odds, American Indian students appear to be uniquely exposed to a higher incidence of chronic absenteeism in comparison to other racial/ethnic groups. Secondly, White students as a racial/ethnic group appear to face significant challenges with chronic absenteeism. Third, although Black, Hispanic, and Multiracial students are over-represented in chronic absenteeism in comparison to their percentage of total student population, race/ethnicity does not appear to increase their odds of chronic absenteeism after controlling for other factors, particularly FRL status and special education status. Finally, our results suggest a powerful relationship between out-of-school suspension and chronic absenteeism across all student groups that warrants further empirical investigation. However, it suggests that policies and procedures intended to reduce the incidence of exclusionary discipline might also help diminish chronic absenteeism and the compounded effect of both on students’ educational outcomes.
Balfanz, R., & Legters, N. (2004). Locating the dropout crisis. Baltimore, MD: Johns Hopkins University.
Ginsburg, A., Jordan, P., & Chang, H. (2014). Absences Add Up: How School Attendance Influences Student Success. San Francisco, CA: Attendance Works. Retrieved from http://www.attendanceworks.org/wordpress/wp-content/uploads/2014/09/Absenses-Add-Up_090114-1-1.pdf
Gottfried, M. A. (2009). Excused versus unexcused: How student absences in elementary school affect academic achievement. Educational Evaluation and Policy Analysis, 31, 392-419.
Kearney, C. A., & Graczyk, P. (2014). A response to intervention model to promote school attendance and decrease school absenteeism. Child & Youth Care Forum, 43, 1-25.
Lehr, C. A., Hansen, A., Sinclair, M. F., & Christenson, S. L. (2004). Moving beyond dropout towards school completion: An integrative review of data-based interventions. School Psychology Review , 32, 342-364.
Nauer, K., Mader, N., Robinson, G., & Jacobs, T. (2014). A better picture of poverty: What chronic absenteeism and risk load reveal about NYC’s lowest income elementary schools. New York: Center for New York City Affairs.
Orfield, G., & Kornhaber, M. L. (2001). Raisings standards or raising barriers? Inequality and high-stakes testing in public education. New York, NY: Century Foundation Press.
Sailor, W., Doolittle, J., Bradley, R., & Danielson, L. (2009). Response to Intervention and Positive Behavior Support. In W. Sailor, G. Dunlap, G. Sugai, & R. Horner (Eds.), Handbook of positive behavior support (pp. 729–753). New York: Springer.
Steward, R. J., Steward, A. D., Blair, J., Jo, H., & Hill, M. F. (2008). School attendance revisited: A study of urban African American Students’ grade point averages and coping strategies. Urban Education, 43, 519-536.
Editor’s note: James Ford is on contract with the N.C. Center for Public Policy Research from 2017-2020 while he leads this statewide study of equity in our schools. Center staff is supporting Ford’s leadership of the study, conducted an independent verification of the data, and edited the reports.E(race)ing Inequities