Immigrant students build STEM skills more than US-born students
Marie Donlon | January 09, 2019
According to research from Duke and Stanford Universities, U.S. immigrant children study more STEM subjects than U.S.-born students, resulting in their greater representation in STEM occupations.
According to the research, roughly 20% of U.S.-born college students major in STEM-related subjects, while 36% of immigrant students — those who arrived in the U.S. after age 10 and from a non-English speaking country — majored in STEM-related subjects.
Immigrant students earn 20% more high school credits in math-intensive courses than in English-intensive courses, according to researchers, a trend that follows those students to college and explains, in part, the higher representation of immigrants in STEM careers.
"Most studies on the assimilation of immigrants focus on the language disadvantage of non-English-speaking immigrants," said Marcos Rangel, assistant professor at Duke's Sanford School of Public Policy. "We focus instead on the comparative strength certain immigrant children develop in numerical subjects, and how that leads to majoring in STEM subjects in college."
"Some children who immigrate to the U.S., particularly older children from a country where the main language is very dissimilar to English, quite rationally decide to build on skills they are relatively more comfortable with, such as math and science," said Rangel.
The study appears in the Proceedings of the National Academy of Sciences.
Following the links to supporting data leads one down a rabbit hole of unbelievable assumptions, substitutions, estimations, obfuscations and downright vagueness which is compounded by the degrees of hierarchal footnoting. It is a house of cards built on sand. The first footnote is an example "In the data-preferred model, there is a small but significant degree of imperfect substitutability between natives and immigrants which, when combined with the other estimated elasticities, implies that in the period from 1990 to 2006 immigration had a small effect on the wages of native workers with no high school degree (between 0.6% and +1.7%). It also had a small positive effect on average native wages (+0.6%) and a substantial negative effect (−6.7%) on wages of previous immigrants in the long run." If that is not enough try reading footnote 22 Levenshtein VI (1966) Binary codes capable of correcting deletions, insertions and reversals. Sov Phys Dokl 10:707–710. OpenUrlGoogle Scholar
This study is differentiating correlation and causation using conditional probability. As any statistician knows correlation does not imply causation (Statistics 101). The assumption that language skills or lack thereof is a causal effect in the choice of STEM vs Language courses is extremely narrow and does not address more pervasive possibilities such as culture base importance of education and the current trend in US schools of social promotion.
By their own statistics comparing age at time of immigration they show that the longer someone is in another countries school system the better they do at the more rigorous study of STEM, which requires lots of reading to understand the mathematical relationships if you are to understand what they represent. Anyone who has had an exposure to higher level Engineering studies can verify this.
Before I can take any of this as being remotely causal the authors need to examine not just the language but also the country of origin and the value that they place on education. My reasoning being that lumping in 3rd world countries where survival outweighs education to a country such as Hungary (whose language has no Latin origins) which places a high value on education is an obfuscation that is polluting the data. Why they would overlook this obvious multivariable approach is a question to be asked, as any investigator worth there salt uses multivariable analysis. My experience in the past have shown that when single variable analysis is used there is a preconceived hidden agenda that they wish to support. Or it could be naivety or a requirement for tenure or dissertation where complex words, long sentences and many footnotes imply rigor.
"There are liars, damned liars and statisticians." - Mark Twain
"Do not put your faith in what statistics say until you have carefully considered what they do not say." - William W. Watt
“Against stupidity the gods themselves contend in vain.” ― Frederich Schiller