I recently read an article from the Wall Street Journal. According to their research, for non-STEM fields the prestige of the institution mattered significantly for starting and mid-career salaries. For STEM fields, the prestige did not have so much of an effect on the resulting salaries for graduates.
The authors propose one theory that this difference occurs because of the logical, progressive nature of STEM fields as opposed to non-STEM fields. For STEM fields, there is a fixed body of knowledge that has been standardized for every graduate in one of those fields. Whether you go to a prestigious institution or a non-prestigious one, you will get roughly the same skills in the basic, required areas.
This is in contrast with the non-STEM fields, where the requirements are much less structured. There, the extra prestige can ensure that a student has the necessary skills. Without the well-known difficulty of prestigious programs, the student could have breezed through trivial programs.
In one of their examples, going to a school like UPenn for engineering would cost $167,000 more than a university like Texas A&M and only provide a $1000 benefit in salary. By those numbers, it would take 167 years to pay off the extra college tuition.
The numbers they present are very telling if you are looking for monetary return-on-investment for various schools. If you care primarily about what the optimal way to turn school into salary, then those charts would suggest you should go to a prestigious school for a non-STEM field and to a non-prestigious school for a STEM field. If you are solely focused on money, then you should just discount the non-STEM fields entirely as their salaries are far too low, especially because you have to spend the additional money attending a more prestigious university.
Following further along, why are non-STEM fields even offered? It makes no monetary sense for individuals to study non-STEM fields. Without any demand for those fields, they would just disappear from college curricula everywhere.
Except, there’s just one problem. The very existence on non-STEM fields indicates there must be something wrong with the conclusion. As the logic is sound, there must be an issue with the assumption: that students are looking primarily for a monetary return-on-investment.
Therein lies the fundamental issue with quantification of poorly-quantifiable situations. The choice of major and college is far too complicated an issue to be reduced to a computational model. The end of the article touches on the finer aspects; however, the article as a whole is arguing about using the monetary ramifications as a primary source of optimization.
There is nothing inherently wrong with using quantitative data as a source of optimization. In many instances, quantitative optimization is the best way to achieve good results. Those instances are those when the success is measured accurately by the quantitative function.
Is college and major choice one of those instances? Is the main point of college to optimize our salary after graduation?
But … but … isn’t the point of college to learn? It’s called higher education, after all.
When you go to college, you seek to deepen your understanding in your chosen field and broaden your understand in other fields. When someone is educated, we typically expect them to have a basic understanding in all sorts of disciplines; not to be an expert, but enough to be able to understand a conversation about them.
Rationalizing the non-STEM majors is far easier with that model of thought. If college exists for students to learn about a major they are passionate about, then it makes perfect sense for colleges to offer all of those majors. Without those areas of study offered, how could students deepen their understanding about them?
These ideas help support the other supposed nonsensical decisions like going to a prestigious school for STEM fields. When going to college is about learning, your main optimization strategy is to choose a college where you will learn as much as possible.
The classic model of learning is with a professor lecturing to many students about a topic. Then, those students internalize the topic and are able to reproduce it for use on command. Using this model, the curriculum is the main determining factor on how much you will learn. If you know the curriculum at a prestigious college is more rigorous than one from a less-prestigious college, you would prefer to go to the prestigious school. This mirrors the found justification from the quantitative analysis. However, if you know the curriculum will be identical between the two colleges, there should be no reason to choose one over the other. This appears to be the case in STEM fields, where there is the certain body of knowledge that all students must master.
Where that model of learning falls short is in the seemingly instantaneous nature that the students absorb and are able to reproduce the material that they learn in lecture. Almost nobody has that ability. The real learning occurs elsewhere, on the assignments that are intended to be difficult.
When you have an assignment that you are unable to solve after many hours of attempts, you need to turn to your teachers or your peers. It is economically infeasible for the schools to have enough professors that all students can turn to their professors every time they have a question. The remaining choice, that students need to turn to their peers for help, is the reason the original model breaks down.
Possibly more important than the professors, the people you work with while you are studying play a key role in how much you learn. Having good peers to lean on will significantly benefit your learning. They are much more available for assistance than single professors that have to divide their time among the students, and you will often have to reciprocate the assistance by teaching of your own. This teaching further improves how well you understand the material.
The difference between the prestigious schools and the non-prestigious ones for STEM fields lies not primarily in the body of knowledge that each student must be exposed to. The difference lies in the other students at that school. If you go to a prestigious institution, you are much more likely to find other students that highly motivated and wanting to learn.
Optimizing which college to go to based on return-on-investment entirely sidesteps the real reason why you are going to college in the first place. Choosing where to go to college should be focused on finding out where you will learn the most, whether from your peers or your professors.