Education and Socioeconomic Status Factsheet

Socioeconomic status (SES) encompasses not just income but also educational attainment, financial security, and subjective perceptions of social status and social class. Socioeconomic status can encompass quality of life attributes as well as the opportunities and privileges afforded to people within society. Poverty, specifically, is not a single factor but rather is characterized by multiple physical and psychosocial stressors. Further, SES is a consistent and reliable predictor of a vast array of outcomes across the life span, including physical and psychological health. Thus, SES is relevant to all realms of behavioral and social science, including research, practice, education and advocacy.

SES Affects Our Society

SES affects overall human functioning, including our physical and mental health. Low SES and its correlates, such as lower educational achievement, poverty and poor health, ultimately affect our society. Inequities in health distribution, resource distribution, and quality of life are increasing in the United States and globally. Society benefits from an increased focus on the foundations of socioeconomic inequities and efforts to reduce the deep gaps in socioeconomic status in the United States and abroad.

SES and Educational Issues

Research indicates that children from low-SES households and communities develop academic skills slower than children from higher SES groups (Morgan, Farkas, Hillemeier, & Maczuga, 2009). For instance, low SES in childhood is related to poor cognitive development, language, memory, socioemotional processing, and consequently poor income and health in adulthood. The school systems in low-SES communities are often underresourced, negatively affecting students’ academic progress and outcomes (Aikens & Barbarin, 2008). Inadequate education and increased dropout rates affect children’s academic achievement, perpetuating the low-SES status of the community. Improving school systems and early intervention programs may help to reduce some of these risk factors; therefore, increased research on the correlation between SES and education is essential.

SES and Family Resources

Literacy gaps in children from different socioeconomic backgrounds exist before formal schooling begins.

  • Children from low-SES families are less likely to have experiences that encourage the development of fundamental skills of reading acquisition, such as phonological awareness, vocabulary, and oral language (Buckingham, Wheldall, & Beaman-Wheldall, 2013).
  • Children’s initial reading competency is correlated with the home literacy environment, number of books owned, and parent distress (Aikens & Barbarin, 2008; Bergen, Zuijen, Bishop, & Jong, 2016). However, poor households have less access to learning materials and experiences, including books, computers, stimulating toys, skill-building lessons, or tutors to create a positive literacy environment (Bradley, Corwyn, McAdoo, & García Coll, 2001; Orr, 2003).
  • Prospective college students from low-SES backgrounds are less likely to have access to informational resources about college (Brown, Wohn, & Ellison , 2016). Additionally, compared to high-SES counterparts, young adults from low-SES backgrounds are at a higher risk of accruing student loan debt burdens that exceed the national average (Houle, 2014).

Research indicates that school conditions contribute more to SES differences in learning rates than family characteristics do (Aikens & Barbarin, 2008). Researchers have argued that classroom environment plays an important role in outcomes.

  • Students who were randomly assigned to higher quality classroom in grades K-3 earned more, were more likely to attend college, saved more for retirement, and lived in better neighborhoods (Chetty et al., 2011).
  • A teacher’s years of experience and quality of training are correlated with children’s academic achievement (Gimbert, Bol, & Wallace , 2007). Children in low-income schools are less likely to have well-qualified teachers (Clotfelter, Ladd, & Vigdo, 2006).
  • The following factors have been found to improve the quality of schools in low-SES neighborhoods: a focus on improving teaching and learning, creation of an information-rich environment, building of a learning community, continuous professional development, involvement of parents, and increased funding and resources (Muijs, Harris, Chapman, Stoll, & Russ, 2009).
  • Schools with students from the highest concentrations of poverty have fewer library resources to draw on (fewer staff, libraries are open fewer hours per week, and staff are less well rounded) than those serving middle-income children (Pribesh, Gavigan, & Dickinson, 2011).
SES and Academic Achievement

Research continues to link lower SES to lower academic achievement and slower rates of academic progress as compared with higher SES communities.

  • Children from low-SES families enter high school with average literacy skills five years behind those of high-income students (Reardon, Valentino, Kalogrides, Shores, & Greenberg, 2013).
  • In 2014, the high school dropout rate among persons 16–24 years old was highest in low-income families (11.6 percent) as compared to high-income families (2.8 percent; National Center for Education Statistics, 2014).
  • The success rate of low-income students in science, technology, engineering, and mathematics disciplines is much lower than that of students who do not come from underrepresented backgrounds (Doerschuk et al., 2016).
  • According to the U.S. Census Bureau (2014), individuals within the top family income quartile are 8 times more likely to obtain a bachelor’s degree by age 24 as compared to individuals from the lowest family income quartile.
Psychological Health

Increasing evidence supports the link between lower SES and learning disabilities or other negative psychological outcomes that affect academic achievement.

  • Low SES and exposure to adversity are linked to decreased educational success (McLaughlin & Sheridan, 2016). Such toxic stress in early childhood leads to lasting impacts on learning, behavior, and health (Committee on Psychosocial Aspects of Child and Family Health et al., 2012).
  • Children from lower SES households are about twice as likely as those from high-SES households to display learning-related behavior problems. A mother’s SES is also related to her child’s inattention, disinterest, and lack of cooperation in school (Morgan et al., 2009).
  • Perception of family economic stress and personal financial constraints affected emotional distress/depression in students and their academic outcomes (Mistry, Benner, Tan, & Kim, 2009).
SES and Career Aspirations

Social class has been shown to be a significant factor in influencing career aspirations, trajectory and achievement.

  • Diemer and Blustein (2007) found that racial, ethnic, and socioeconomic barriers generally hinder individuals’ vocational development. Career barriers are significantly higher for those from poor backgrounds, people of color, women, those who are disabled, and LGBTIQ-identified individuals (Blustein, 2013).
  • A study showed that individuals from a lower social class generally had less career-related self-efficacy when it came to vocational aspirations (Ali, McWhirter, & Chronister, 2005).
  • Those from higher social class backgrounds tend to be more successful in developing career aspirations and are generally better prepared for the world of work because of access to resources such as career offices, guidance counselors, better schools, high level “social actors,” and familial experience with higher education (Diemer & Ali, 2009).
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References

Aikens, N. L., & Barbarin, O. (2008). Socioeconomic differences in reading trajectories: The contribution of family, neighborhood, and school contexts.  Journal of Educational Psychology, 100, 235-251. http://dx.doi.org/10.1037/0022-0663.100.2.235

Ali, S. R., McWhirter, E. H., & Chronister, K. M. (2005). Self-efficacy and vocational outcome expectations for adolescents of lower socioeconomic status: A pilot study. Journal of Career Assessment, 13(40), 40-58. doi:10.1177/1069072704270273

Bergen, E., Zuijen, T., Bishop, D., & Jong, P. F. (2016). Why are home literacy environment and children’s reading skills associated? What parental skills reveal. Reading Research Quarterly, 52, 147-160. doi:10.1002/rrq.160

Blustein, D. (2013). The psychology of working: A new perspective for career development, counseling, and public policy. Abingdon-on-Thames, England: Routledge.

Bradley, R. H., Corwyn, R. F., McAdoo, H. P., & García Coll, C. (2001). The home environments of children in the United States Part I: Variations by age, ethnicity, and poverty status. Child Development, 72, 1844-1867. doi:10.1111/1467-8624.t01-1-00382

Brown, M. G., Wohn, D. Y., & Ellison, N. (2016). Without a map: College access and the online practices of youth from low-income communities. Computers & Education, 92, 104-116. doi:10.1016/j.compedu.2015.10.001

Buckingham, J., Wheldall, K., & Beaman-Wheldall, R. (2013). Why poor children are more likely to become poor readers: The school years. Australian Journal of Education, 57, 190-213. doi:10.1177/0004944113495500

Chetty, R., Friedman, J. N., Hilger, N., Saez, E., Schanzenbach, D. W., & Yagan, D. (2011). How does your kindergarten classroom affect your earnings? Evidence from Project STAR. The Quarterly Journal of Economics, 126, 1593-1660. https://doi.org/10.1093/qje/qjr041

Clotfelter, C. T., Ladd, H. F., & Vigdor, J. L. (2006). Teacher-student matching and the assessment of teacher effectiveness. Journal of Human Resources, 41, 778-820. doi:10.3368/jhr.XLI.4.778

Committee on Psychosocial Aspects of Child and Family Health, Committee on Early Childhood, Adoption, and Dependent Care, Section on Developmental and Behavioral Pediatrics, Shonkoff, J. P., Siegel, B. S., Dobbins, M. I., …Wood, D. L. (2012). Early childhood adversity, toxic stress, and the role of the pediatrician: Translating developmental science into lifelong health. Pediatrics, 129(1), e224-31. doi:10.1542/peds.2011-2662

Diemer, M. A., & Ali, S. R. (2009). Integrating social class into vocational psychology: Theory and practice implications. Journal of Career Assessment, 17, 247-265. doi:10.1177/1069072708330462

Diemer, M. A., & Blustein, D. L. (2007). Vocational hope and vocational identity; Urban adolescents’ career development. Journal of Career Assessment, 15, 98-118. doi:10.1177/1069072706294528

Doerschuk, P., Bahrim, C., Daniel, J., Kruger, J., Mann, J., & Martin, C. (2016). Closing the gaps and filling the STEM pipeline: A multidisciplinary approach. Journal of Science Education and Technology, 25, 682-695. doi:10.1007/s10956-016-9622-8

Gimbert, B., Bol, L., & Wallace, D. (2007). The influence of teacher preparation on student achievement and the application of national standards by teachers of mathematics in urban secondary schools. Education and Urban Society, 40, 91-117. doi:10.1177/0013124507303993

Houle, J. N. (2014). Disparities in debt: Parents’ socioeconomic resources and young adult student loan debt. Sociology of Education, 87(1), 53-69. doi:10.1177/0038040713512213

McLaughlin, K. A., & Sheridan, M. A. (2016). Beyond cumulative risk: a dimensional approach to childhood adversity. Current Directions in Psychological Science, 25, 239-245. doi:10.1177/0963721416655883

Mistry, R. S., Benner, A. D., Tan, C. S., & Kim, S. Y. (2009). Family economic stress and academic well-being among Chinese-American youth: The influence of adolescents’ perceptions of economic strain. Journal of Family Psychology, 23, 279-290. http://dx.doi.org/10.1037/a0015403

Morgan, P. L., Farkas, G., Hillemeier, M. M., & Maczuga, S. (2009). Risk factors for learning-related behavior problems at 24 months of age: Population-based estimates. Journal of Abnormal Child Psychology, 37, 401-413. doi:10.1007/s10802-008-9279-8

Muijs, D., Harris, A., Chapman, C., Stoll, L., & Russ, J. (2009). Improving schools in socioeconomically disadvantaged areas: A review of research evidence. School Effectiveness and School Improvement, 15, 149-175.

National Center for Education Statistics. (2008). Percentage of high school dropouts among persons 16 through 24 years old (status dropout rate), by income level, and percentage distribution of status dropouts, by labor force status and educational attainment: 1970 through 2007. Retrieved from  http://nces.ed.gov/programs/digest/d08/tables/dt08_110.asp

Orr, A. J. (2003). Black–White differences in achievement: The importance of wealth. Sociology of Education, 76, 281-304. http://dx.doi.org/10.2307/1519867

Pribesh, S., Gavigan, K., & Dickinson, G. (2011). The access gap: Poverty and characteristics of school library media centers. The Library Quarterly, 81(2), 143-160.

Reardon, S. F., Valentino, R. A., Kalogrides, D., Shores, K. A., & Greenberg, E. H. (2013). Patterns and trends in racial academic achievement gaps among states, 1999-2011. Retrieved from https://cepa.stanford.edu/content/patterns-and-trends-racial-academic-achievement-gaps-among-states-1999-2011

U.S. Census Bureau. (2000). Current population survey: Design and methodology. Retrieved from www.census.gov/hhes/socdemo/education/index.html.

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