Starting School Early Affects Educational Attainment
A singular cutoff point for school entry results in age differences between children of the same grade. In many school systems, September-born children, begin compulsory education in September of the year in which they turn five, making them relatively older than summer born children who begin school aged four.
Research on these annually age-grouped cohorts reveal relative age effects (RAEs) that convey the greater achievements accrued by the relatively old (RO) students compared to the relatively young (RY) students. RAEs are pervasive. Across OECD countries, in fourth grade, RY students scored 4–12% lower than RO students, while in eight grade the difference was 2–9% lower. RAEs are most evident in early formal education and can diminish as children mature. In 2016 for instance, Thoren, Heinig, and Brunner published a study on three grades attending public school in Berlin, Germany, and showed that the RAE in disappeared for reading by grade 8 and was reversed for math in favor of RY students.
Investigating the mechanisms involved is important because RAEs can remain evident in high-stakes exams taken at the end of compulsory education. RAEs may impact educational attainment, which is defined as an individual’s highest educational qualification (i.e., compulsory schooling, apprenticeship, or university education). For example, research by Sykes, Bell, and Rodeiro found that 5% less August-born GCSE students than September-born GCSE students chose at least one A level. Likewise, August-born students were 20% less likely to progress to university than September-born students. RO students also outperformed RY students on college admission tests to a university in Brazil, which significantly impacted the probability of being accepted to that university. Moreover, in Japan the percentage of graduates (aged 19–22 and 23–25) was two points greater for those born in April than those born in March. Collectively, these findings indicate that RAEs impact educational attainment because of their direct link to students’ acceptance to higher education. Since much of children’s development occurs within compulsory education, a natural question is whether educators act to alleviate or exacerbate RAE.
RAEs emerge primarily because of within-group maturity differences among RO and RY children (age-at-school-entry effect). RO children, have a one-year developmental advantage over RY children when they sit exams (age-at-test effect). Based on these advantaged test scores and maturation, RO children receive special opportunities from educators to excel in school. Using attainment, program participation, and attendance data from 657 students aged 11–14 from a secondary school in North England, a study by Cobley, McKenna, Baker and Wattie found that RO students were more likely than RY students achieve high scores across various subjects and be admitted to gifted programs. Even if RO students accepted to gifted programs are not actually gifted, the prestige of attending such programs would help them to foster strong positive self-esteem, which can persist over time. In turn, RO students may experience enhanced learning and praise long after small age differences are important in and of themselves.
Conversely, teachers lower their expectations of RY students because RY students appear less developed and intelligent than RO students. Interestingly, having RO classmates can prompt a spillover effect that boosts RY students’ grades, but also increases the probability that RY students will to be pathologized. This research suggests that RAEs emerge as a consequence of maturity differences but are maintained by the magnitude and persistence of social factors, such as educator-student interaction. Another study also reported RAEs in the diagnosis and treatment of ADHD in children aged 6–12 in British Columbia. Incorrect diagnosis can unnecessarily limit RY students’ academic performance by diminishing their self-esteem and task involvement, which are school achievement predictors.
If these inequalities decline over time, the influence of RAE on educational attainment is arguably minimal. However, if relative advantages such as skill accumulation persist in favor of RO students throughout formal education, RAEs translate into academic disadvantages for RY students. For instance, RY students’ negative self-perceptions of academic competence and learning disability can mediate the relationship between depressive symptoms and school dropout in adolescence. In turn, lack of formal education or poor academic performance makes entry to higher education arduous. Research illustrates with 16-year-old RY students scoring 0.13 standard deviations lower than RO students. This test score predicted that RY students would have a 5.8% higher potential dropout rate from high school and a consequently 1.5% lower college admission rate than RO students. Initial gains for RO students partly explain why they have a 10% greater probability of attending top-ranking universities and why they are more likely to graduate from university than RY students.
Research on the impact of RAE on educational attainment is not as straightforward as discussed thus far. Cascio and Schanzenbach used experimental variation by randomly assigning students to classrooms. Results showed improved test scores for RY students up to eight years after kindergarten and an increased probability of taking a college-entry exam. These positive spillover effects are evident when RY students, in a relatively mature peer environment, strive to catch up with higher-achieving RO students and end up surpassing them. Since RO students may strain under the expectations placed on them to be top of the class, RY students have an opportunity to catch up. Alternatively, RO students may not have the same incentive as RY students to work hard for academic success because RAEs already work in their favor. To overcome RAEs and succeed academically, RY students need greater persistence and attention than RO students in their schoolwork, which helps them gain a motivated mindset that benefits lifelong learning. For example, RY students in high school are more likely than RO students to study and compensate for poor academic achievement in middle school.
At a university in Italy, RY students obtained better grades than RO students. This reversal effect was also reported at university in the UK. The researchers postulated that due to RAEs, the RY students developed social skills more slowly. Therefore, RY students had less active social lives and more time to concentrate on educational attainment. The impact of RAEs on educational attainment is, subsequently, probabilistic not deterministic. Although research by Abel, Sokol, Kruger, and Yargeau indicated that RAEs do not affect the success of either RO or RY students’ university applications, they reported that more RO than RY students applied to medical school. In addition, Kniffin and Hank’s study did not find RAEs that influence whether a university student obtains a PhD. These two studies suggest that RAEs do not have such an important influence on college acceptance or educational attainment once in college. Instead, RAEs are a salient influence in so far as students in compulsory education obtain the necessary grades to apply to university in the first place.
The acquisition of higher mental functions and schooling over time helps normalize the student population by minimizing the attainment gap between RO and RY students, which helps explain why RAEs lessen in university. In addition, universities are often learning environments with great diversity in age (i.e., mature and repeat students), culture (i.e., international students), and academic achievement (i.e., doctorate/master’s students). Perceived developmental parities are inherently less important in university because classroom composition becomes heterogeneous, mitigating and masking the remaining relative age differences. Given this knowledge, greater classroom heterogeneity could be applied to compulsory education to minimize RAEs. Students in mixed-grade classrooms in Norwegian junior high schools, for example, outperformed students in single-grade classrooms on high-stakes school finishing exams. With this classroom composition, it is not disproportionately skewed in favor of younger/older students, the losses for RO students following class mixing would not outweigh the gains of the RO students. With more heterogenous classes, educational attainment could subsequently become less influenced by RAEs and a more equalized pursuit.
Since mitigating the impact of RAE on educational attainment depends partly on the strength of compensating investments such as classroom environments, streaming remains controversial. Academic streaming involves separating students according to innate ability. In reality, streaming is based on students’ prior academic performance, which is an imperfect measure of ability that can lead to misallocations. Streaming in early education can be particularly unfair because RY students do not get the opportunity to more closely approximate older classmates’ mental and physical development when sitting exams. In Germany for instance, being relatively old increased test scores by 0.40 standard deviations, increasing the probability of attending the highest secondary school track (gymnasium) by 12%. RY students are also at risk of being unfairly streamed into lower-ability classes because they are more likely than RO students to be diagnosed with behavioral problems and learning disabilities. Streaming thereby provides students with unequally differentiated educational experiences of teaching, competition, and opportunity that limit their academic exposure. Therefore, postponing streaming can reduce the impact of RAEs on educational attainment by ensuring that any developmental gaps have time to narrow.
Unequal educational experiences can limit RY students’ educational attainment. In 2015, the average number of 25–64-year-olds with tertiary education was greater for countries who exhibit almost no streaming, such as Ireland (42.8%), compared to the OECD average (35%). Is it the case that streaming at multiple stages can rectify initial misallocations while still enhancing academic achievement? In Austria, children are streamed in grade five (aged ten) and in grade nine (aged fourteen). In one study, RY students in grade five were 40% less likely to be streamed into higher classes, but the second streaming, in grade nine, helped mitigate RAEs by giving students the opportunity to upgrade to a higher stream. In a complex interplay, streaming and RAEs can reinforce and be reinforced by existing socioeconomic inequalities. In this vein, the researchers concluded that RAEs only disappeared for students with favorable parental backgrounds in the second streaming. In contrast, RY students with unfavorable parental backgrounds were 21% less likely than RO students to move to a high-ranking school. As previously mentioned, learning at the wrong academic level can strain academic achievement and reduce the chances of continuing to higher education.
Socioeconomic status is the extent to which learning opportunities are disadvantaged as a result of low-income. Socioeconomic status can exacerbate the impact of RAEs on educational attainment. Huang and Invernizzi’s research examined a cohort of 405 students in a high poverty, low performing school from the beginning of kindergarten until the end of grade two. Results concluded that early-age literacy achievement gaps between RO and RY students narrowed over time but did not fully close by the end of grade two. Similarly, a Madagascar-based study by Galasso, Weber, and Fernald indicated that differences in home stimulation are dependent on the wealth gradient and accounted for 12–18% of the predicted gap in early outcomes between advantaged and disadvantaged children. At least in early education, these findings suggest that diminished academic performance and exacerbated RAEs are in direct proportion to socioeconomic status. Thus, greater flexibility regarding age at entry in compulsory schooling could help lessen the impact of RAE on academic performance.
Suziedelyte and Zhu published a “Longitudinal Study of Australian Children” and reported that starting school early benefits children from low-income families who, compared to children from high-income families, have limited access to learning resources at home and formal pre-school services. However, a three-month postponement of the cutoff enrollment date (increasing grade age) can increase both academic success and the likelihood of repeating a grade. Similarly, a one year delay in school enrollment (redshirting) can produce a 0.303 standard deviation decrease in test scores and lead to significantly lower math scores for students identified with a disability when compared to nonredshirted students with disability. These mixed findings suggest that equalizing educational attainment opportunities among RO and RY students, by implementing a flexible entry cutoff point, varies as a function of individual difference. Therefore, managing and mitigating RAEs requires greater sensitivity to confounds such as socioeconomic status.
The impact of starting school early on educational attainment is mediated by social factors, school policy, and socioeconomic factors, resulting in individual differences in learning outcomes. RAEs fade throughout formal schooling and can even reverse in higher education. The relative age phenomenon, nevertheless, caveats that ascribing merit to students based on relative age can lead to the provision of unequal learning opportunities and harmful pathologies. Unfortunately, the mechanisms that underpin the impact of RAEs on educational attainment are currently quite speculative and inconclusive. In this sense, existing findings warrant further empirical research and reveal the need for more comprehensive methods for determining an appropriate school entry cutoff point.
Abel, E., Sokol, R., Kruger, M., & Yargeau, D. (2008). Birthdates of Medical School Applicants. Educational Studies, 34(4), 271-275. http://dx.doi.org/10.1080/03055690802034302
Barrett, P., Davies, F., Zhang, Y., & Barrett, L. (2015). The Impact of Classroom Design on Pupils’ Learning: Final Results of a Holistic, Multi-Level Analysis. Building And Environment, 89, 118-133. http://dx.doi.org/10.1016/j.buildenv.2015.02.013
Bedard, K., & Dhuey, E. (2006). The Persistence of Early Childhood Maturity: International Evidence of Long-Run Age Effects. Quarterly Journal Of Economics, 121(4), 1437-1472. doi:10.1162/qjec.121.4.1437
Billari F., & Pellizzari, M. (2011). The Younger, the Better? Age-Related Differences in Academic Performance at University. Journal Of Population Economics, 25(2), 697-739. doi:10.1007/s00148-011-0379-3
Cascio, E., & Schanzenbach, D. (2016). First in the Class? Age and the Education Production Function. Education Finance And Policy, 11(3), 225-250. doi:10.1162/edfp_a_00191
Cobley, S., McKenna, J., Baker, J., & Wattie, N. (2009). How Pervasive are Relative Age Effects in Secondary School Education?. Journal Of Educational Psychology, 101(2), 520-528. doi:10.1037/a0013845
Crawford, C., Dearden, L., & Greaves, E. (2011). “Does When You are Born Matter? The Impact of Month of Birth on Children’s Cognitive and Non-Cognitive Skills in England.” IFS Briefing Note: BN 122, Institute of Fiscal Studies.
Crawford, C., Dearden, L., & Meghir, C. (2010). When You Are Born Matters: The Impact of Date of Birth on Educational Outcomes in England. Institute for Fiscal Studies, 2-4, 21-22. doi:10.1920/wp.ifs.2010.1006
Elder, T., & Lubotsky, D. (2009). Kindergarten Entrance Age and Children’s Achievement: Impacts of State Policies, Family Background, and Peers. Journal Of Human Resources, 44(3), 641-683. doi:10.1353/jhr.2009.0015
Fortner, C., & Jenkins, J. (2017). Kindergarten Redshirting: Motivations and Spillovers Using Census-Level Data. Early Childhood Research Quarterly, 38, 44-56. doi:10.1016/j.ecresq.2016.09.002
Galasso, E., Weber, A., & Fernald L. C. H., (2017). Dynamics of Child Development: Analysis of a Longitudinal Cohort in a Very Low Income Country. The World Bank Economic Review, lhw065.
Huang, F., & Invernizzi, M. (2012). The Association of Kindergarten Entry Age with Early Literacy Outcomes. The Journal Of Educational Research, 105(6), 431-441. doi:10.1080/00220671.2012.658456
Kniffin, K., & Hanks, A. (2015). Revisiting Gladwell’s Hockey Players: Influence of Age Effects upon Earning the PhD. Contemporary Economic Policy, 34(1), 21-36. doi:10.1111/coep.12114
Leuven, E., & Rønning, M. (2014). Classroom Grade Composition and Pupil Achievement. The Economic Journal, 126(593), 1164-1192. doi:10.1111/ecoj.12177
Matta, R., Ribas, R., Sampaio, B., & Sampaio, G. (2016). The Effect of Age at School Entry on College Admission and Earnings: A Regression-Discontinuity Approach. IZA Journal Of Labor Economics, 5(1). doi:10.1186/s40172-016-0049-5
Matsubayashi, T., & Ueda, M. (2015). Relative Age in School and Suicide among Young Individuals in Japan: A Regression Discontinuity Approach. PLOS ONE, 10(8), e0135349. doi:10.1371/journal.pone.0135349
Morrow, R., Garland, E., Wright, J., Maclure, M., Taylor, S., & Dormuth, C. (2012). Influence of Relative Age on Diagnosis and Treatment of Attention-deficit/hyperactivity Disorder in Children. Canadian Medical Association Journal, 184(7), 755-762. doi:10.1503/cmaj.111619
N.A. (2015) Education attainment – Adult education level – OECD Data. Retrieved 10 April 2017, from https://data.oecd.org/eduatt/adult-education-level.htm
Nam, K. (2014). Until When Does the Effect of Age on Academic Achievement Persist? Evidence from Korean Data. Economics Of Education Review, 40, 106-122. doi:10.1016/j.econedurev.2014.02.002
Pehkonen, J., Viinikainen, J., Böckerman, P., Pulkki-Råback, L., Keltikangas-Järvinen, L., & Raitakari, O. (2015). Relative Age at School Entry, School Performance and Long-term Labour Market Outcomes. Applied Economics Letters, 22(16), 1345-1348. doi:10.1080/13504851.2015.1031864
Pekrun, R., Lichtenfeld, S., Marsh, H., Murayama, K., & Goetz, T. (2017). Achievement Emotions and Academic Performance: Longitudinal Models of Reciprocal Effects. Child Development. doi:10.1111/cdev.12704
Peña, P. A. (2015). Creating Winners and Losers: Date of Birth, Relative Age in School, and Outcomes in Childhood and Adulthood”, unpublished manuscript.
Puhani, P., & Weber, A. (2006). Does the Early Bird Catch the Worm? Instrumental Variable Estimates of Early Educational Effects of Age of School Entry in Germany. Empirical Economics, 32(2-3), 359-386. doi:10.1007/s00181-006-0089-y
Quiroga, C., Janosz, M., Bisset, S., & Morin, A. (2013). Early Adolescent Depression Symptoms and School Dropout: Mediating Processes Involving Self-Reported Academic Competence and Achievement. Journal Of Educational Psychology, 105(2), 552-560. doi:10.1037/a0031524
Roberts, S., & Stott, T. (2015). A New Factor in UK Students’ University Attainment: The Relative Age Effect Reversal?. Quality Assurance In Education, 23(3), 295-305. doi:10.1108/qae-01-2013-0008.
Robertson, E. (2011). The Effects of Quarter of Birth on Academic Outcomes at the Elementary School Level. Economics Of Education Review, 30(2), 300-311. doi:10.1016/j.econedurev.2010.10.005
Schneeweis, N., & Zweimüller, M. (2014). Early Tracking and the Misfortune of Being Young. The Scandinavian Journal Of Economics, 116(2), 394-428. doi:10.1111/sjoe.12046
Suziedelyte, A., & Zhu, A. (2015). Does Early Schooling Narrow Outcome Gaps for Advantaged and Disadvantaged Children?. Economics Of Education Review, 45, 76-88. doi:10.1016/j.econedurev.2015.02.001
Sykes, E., Bell, J., & Rodeiro, C. (2009). Birthdate Effects: A Review of the Literature from 1990-on (pp. 3-4). Cambridge, England: University of Cambridge.
Thomas, J. (2012). Combination Classes and Educational Achievement. Economics Of Education Review, 31(6), 1058-1066. doi:10.1016/j.econedurev.2012.07.013
Thoren, K., Heinig, E., & Brunner, M. (2016). Relative Age Effects in Mathematics and Reading: Investigating the Generalizability across Students, Time and Classes. Frontiers In Psychology, 7 (n/a). http://dx.doi.org/10.3389/fpsyg.2016.00679
Zhang, S., Zhong, R., & Zhang, J. (2017). School Starting Age and Academic Achievement: Evidence from China’s Junior High Schools. China Economic Review. doi:10.1016/j.chieco.2017.03.004
This guest article originally appeared on the award-winning health and science blog and brain-themed community, BrainBlogger: How Does Starting School Early Impact Educational Attainment?.
Guest Author, P. (2018). Starting School Early Affects Educational Attainment. Psych Central. Retrieved on June 2, 2020, from https://psychcentral.com/blog/starting-school-early-affects-educational-attainment/