It’s normal. There are a lot of track athletes, but a lot of different events. Different people run different distances, and some may not finish their race. It is the same with education - from pre-K and K8 programs, to high-school and graduation, to college.
As shown in our data-driven education dashboard, there are some interesting trends over time. Looking at enrolment since 1965, K9-12 shows a more level trend, but we can see a higher relative uptake in pre-K enrolment, and a marked rise in college access. In comparison, over a shorter period of time, adult education enrolment has decreased since 2009.
Over this period the share of the education sector between public and private has remained reasonably stable, but there are marked differences in the proportion of private provision at the different levels of school. Over this period, 12% of children from pre-kindergarten up to 8th grade attended private school, but this drops to 9% for the core years of grades 9-12, while rising to nearly a quarter of total provision for the college years.
Looking at the population as a whole, we can compare the qualification levels that people reached, the distances they ran. Predictably, we can see a reduction in numbers from high school graduation (3) to bachelor’s degrees (6) to graduate and professional qualifications (7), and a gender gap in the uptake of certain qualifications (associate’s degrees - 5). This reduction in numbers from level to level is mirrored in a rise in financial benefits (median salary, avoidance of poverty) in the step from one qualification group to another.
These overall trends and groupings are not the whole story, of course. One factor with which we can break down the numbers is location. How do different states act, and perform, and how are those things linked? In terms of investment, expenditure per pupil will be affected not just by policy, but practical considerations (the highest spend per capita is in the state with the smallest student body - DC - so economies of scale and minimum expenditure levels on infrastructure will have an effect). But what can we tell about investment and its impact on results?
With the exception of the out-lying DC result, when comparing expenditure per pupil with K12 graduation rates, we can see a cluster of states graduating less than 75% of students which are at the lower end (up to $12k per pupil) in expenditure terms. However, by adding in another metric - the percentage of 5-17-year-olds in the state below the Census Bureau’s poverty rate, we can see not only that this cluster is in the states with the highest poverty rate (red), but also another cluster at the next level (yellow), which seems capped around the 80% mark (Ohio the highest performers at 81%), even with New York having the second-highest expenditure rate. There will presumably be a link between the incidence of poverty in a state and the amount that states can afford to spend on education, but the interaction of these measures suggests that education achievement is affected by a broader range of financial factors than direct spend.
We can also look at the importance of early years education and basic skills as a platform for success later on. Using the NAEP (National Assessment of Educational Progress) benchmarks for proficiency in reading and mathematics, this investment, at 4th and 8th grade level, can be plotted against eventual K12 graduation. Here again there is a clear trend in the distribution, although Tennessee shows that lower scores (28% and 26% proficiency, but an 80% graduation rate) can be recovered from, and which they do with a relatively low spend ($9k per pupil).
The mirroring of qualification levels with financial benefits mentioned above can clearly be seen in two ways; first, the median earnings at each qualification level (benchmarked against the overall working population), and secondly in the incidence of poverty in each group. Those who did not graduate high school are twice as likely to be in poverty as those who did (26.5% v 13.1%), and over six times more likely than someone who went on to gain a bachelor’s or further degree (4.1%).
These figures also show a gender split, in that at every level, men’s median earnings are above the overall median. For example, for people with bachelor’s degrees, men’s median earnings are roughly 120% of the overall ($61k v $50k) whereas women’s are roughly 80% ($41k), and this variance is mirrored for other groups. Contributory factors such as time spent out of the workforce to have children would have an impact here, but the difference is pointed.
The dashboard analyzing the US educational system shows both patterns and outliers drawn from a broad range of publicly available data, and also identifies other datasets (overall population figures, years in the workforce) that could be brought in to add further depth to the view. Thus, education can educate itself to identify and gather the data to discover - through analysis - the patterns that can help it to help their students to succeed.
Discover these trends and many more by yourself in our data-driven education dashboard.