What’s the potential of on-line education?

About MOOC

The hip term in academia for online education is MOOC (massively open online courses). MOOC’s medium (the internet) isn’t really a new thing, however what is new is the fact that it is free, and that top universities have started to roll out this free content on the internet.  These courses generally have very large cohorts of students, and although the completion rate is fairly low, it is still significantly large in aggregate terms. This logically implies that the average quality of teachers on the web is much higher than the average teacher (assuming the internet picks the best teachers). As MOOCs expand, they offer terrific possibilities for developing countries, the only requirement for this free knowledge is access to internet. A 16 year old Indian who has never been to school could potentially know more math than an MIT graduate. The only real advantage offline courses offer is direct contact with the teacher though this is not necessarily as important as it may first appear; it could be that the forums created will become extensive enough to answer every possible question a student might have (especially with some advanced algorithms we can produce today) but in terms of thesis feedback and supervision, there would be complications, and there are also some limitations on more practical subjects being mastered online.

Economic theories of education

Before discussing online education we must first lay down the ground work for why people get educated.

The first theory is the theory of human capital, which basically says that people go to school or university to improve their skills or knowledge. Improving themselves makes them more valuable to companies, and as long as your value capacity is higher than what the employer has to pay you then you should be able to get a job.

A second theory is signalling, here people don’t go to university or school to get better, they merely go there so that they can prove to employers that they have certain skills. For instance, getting a degree might signal that you are more intelligent or that you work hard, which are traits the employers desire. This theory could imply a limited capability for social mobility since signalling accreditation is not accessible to all.

Finally the third main theory is the status theory; this is people going to Universities because of cultural or societal ranking purposes. This is not very different from attending a church, though this model could imply a networking effect which boosts earnings.

The literature I am familiar with seems to indicate signalling is the more prominent one. The specific measurements seem to indicate that depth of education is secondary to selection criteria and brand value of the university, which both lean towards signalling.

edit: An example of how researchers try to separate human capital from selection is by looking at those who got accepted into top universities but did not attend, some studies .

Generally my ball park estimate for the value found from attending University is something like 80% signalling and a close match between the other two, human capital is probably slightly more important than good status.  This split isn’t the same in all degree types of course, humanities rely more on signalling; technical skills could be more reliant on human capital and MBA programs more reliant on status.

Application to online education

Under all three theories, online education has a place, however its potency differs. Under signalling dominating there is likely to be a wage premium for attending regular Universities since a large portion of their value is their selection criteria which are diluted when there is an online system. However if a shift should occur and human capital becomes more important, that is, people attending Universities to improve their skills, then that spells a bust for traditional universities.

Making online education also appeal to signalling will require a way to make testing credible by being exempt from plagiarism, it might seem plausible to just have screen sharing settings on or webcam active at all times during testing but it’s very hard to say who would watch these, it is perhaps better if an automated process is found. If credibility is attained in online education it may be possible for it to signal things that regular universities don’t, such as discipline, initiative, independence or even entrepreneurship.

Demand and Supply

In my mind there are two main types of demand for these MOOCs, mainly seeking mental stimulation (perhaps old retirees) and career advancement. There are likely to be cases where the human capital model applies for career advancement, as some jobs might offer on-site testing but it’s perhaps better if centers for testing were established that people can just show up for and use their knowledge to gain accreditation and then not have to re-take endless amounts of tests. In any case if the goal is accreditation the cost will generally be higher, but if the goal is the acquisition of skills or recreational purposes, it’s very cheap to provide since no involvement with test centers and diplomas is required.

A special demand market that the flexibility of online education can tap into is people who are full time workers. This pool of people is likely to be gigantic and the talent endless, these people are people who are so valuable to companies that the company cannot afford to let them off for a year to do an MBA or specialist program. Let’s also not forget that this extra choice for students will create competition with Universities, and with competition, there won’t be as strong of ability for Universities to select the very best candidates since the pool of people they will be selecting from will be smaller. This will dilute their selection criteria, and subsequently their signalling value.

On the supply side, the business model of providers this will shift attention to the lecturers, probably significantly cutting down non-lecturer staff of universities. It could be argued that if some of these fields being taught online aren’t expanding(I want to say fields like Anthropology generally evolve slower) enough every couple of years, the maintenance of updating the videos will be very low resulting in very few lecturers being required. For instance it could be that the same videos of mathematics will be watched 100 years from now, essentially killing the market for math lecturers. This could result in a winner take all effect, such as the music industry has witnessed, but not likely to be as prevalent since the language barrier might be important, this is because it is the main source of communication (where as music today barely relies on language).   This winner take all effect could be monetized through textbooks, although the market for textbooks will shrink in aggregate because of MOOC’s (controlling for shifts from developing to developed). This is an inevitable consequence of the winner take all effect, it is likely that successful textbooks will be boosted as the reputation of its author (who is an MOOC lecturer) rises and offers higher brand value to the University hosting the lecturer, which can also be monetized in a number of ways. This also implies much fewer universities being around unless people still value other things about them such as the cultural or extra-curricular aspect, but it is also just possible people meet that demand by participating more in their local clubs.  There are also legal boundaries preventing such supply shifts from occurring, such that you need to be accredited by government agencies and I am not certain how that affects online courses.

Present and future structures

Imagine a moving platform that holds a product and goes through different points to add new elements to the product. Now imagine that those elements are dependent on the previous one’s being properly installed. Well that’s how I view education as it is right now, only the products are people. This method causes way too many defects, and not necessarily by being more efficient either, since the energy expended to make sure each sequential piece was properly placed would be given by the people themselves. So the main cost is the switching cost, the initial cost of change. It doesn’t make sense for someone (regardless of their age) who hasn’t mastered a subject to move on to a more advanced subject that has the un-mastered subject as a prerequisite.  I don’t really need to produce evidence that it’s harder for a child that hasn’t learned the power rule to apply the chain rule.

It seems the easiest step to take in making education more dynamic is pushing it online, students have the ability to rewind, fast forward and pause and really go at their own pace, the Khan Academy model also seems fairly effective, they have a quiz after each concept is introduced, making sure students have mastered a concept by acing a quiz before being recommended to move on, so all students are A students. Not to mention that the world would be much more efficient if degrees were given out for every concept mastered, like that, people would not get over or under educated.

Perhaps the most backwards mechanics we apply is grading on curves that is giving x% of a class an A or a B. This gives no indication of mastered material, and makes the goal to be better than the rest as opposed to learning the material. This relative grading passes on an information cost to employers since they have to employ capital to learn what different kinds of grades mean, to see if they meet an absolute qualification and to see how they fare compared to graduates of other systems. An employer knows very little if an A or a B was received in a curved class and his only way of knowing how much stuff they learned in these classes is by knowing something about the school or university which channels money to the elite who have an already established reputation and costs the employers less. This is in part why it’s good to have national/international wide testing (eg. GCSE, IB, AP etc) that is widely accepted, so we can compare people. However this information cost must still be borne when comparing people who took different types of tests and in the case of Universities, the lack of such test types makes it very hard to compare students.

The structure of education needs to be taken into account, especially in government funding; it could be funneling us to towards some of these theories. For instance the French education system which I previously discussed has government pushing the status and signalling theories, which could amplify inequality. Online degrees probably haven’t had enough time to be able to project degree type value, in the future the mere fact that you have an online education could signal things like discipline and initiative to employers, and may probably offer value in that people can boost their job experience whilst simultaneously boosting their education credentials but these things will likely emerge over time.

As a final note, let’s not forget that online education is today much cheaper, which allows students to more flexibly choose their career, whilst traditional graduates will have to choose things that will repay their loans, even if their career advancement prospects in this given position are limited. However this cannot be properly observed without specific econometric techniques to get rid of the selection bias of people who did not attend regular university.

Price System: some assumptions

This randomly came up today and I got to thinking about when the price system is the best way to distribute things, I should mention that this is off the top of my head so it might not be a textbook complete answer. This is related to my other post about price gouging.

So the assumptions i’m going to talk about are going to be in order of ascending rarity: unequal utility; limited resources; limited wealth inequality; and rational people.

Unequal utility, this assumption is the easiest to meet, its hard to even think of a situation where utility is the same. This is because not everybody values things in the same way, even if its their life you are talking about, some people may be suicidal, whilst others might be willing to kill a hundred babies to live. The trick here is an element of perception of utility, one might perceive a higher or lower utility than the actual one he will get and that might distort things, but this is probably more relevant in the rational people section.

Limited resources, this is also fairly easy to assume, there’s never an infinite amount of resources. If you have an infinite amount of television sets available to people then they will maybe use the first 3 to watch 3 channels at once, maybe more if they handle more than that, then, the next couple will be for backup, then maybe you would like to use the next couple as chairs around the house, then the couple maybe for releasing stress by dropping them off the 7th floor. The point is that there is diminishing marginal utility from these televisions but since they are free you have no reason to stop getting them. Of course what matters is not whether or not the resource is infinite, but whether your access to it is infinite.

Limited wealth inequality is touched on in my last post but its also an important assumption. Relatively more money allows for relatively more leisure, if there is a heart for sale and someone only has 10 dollars and is willing to use it all to purchase this heard because his is about to expire. But someone else who is in fine shape whose heart is only 0.1% likely to fail him in the next decade but who has a trillion dollars, would maybe be willing to pay 1000 dollars to buy the heart and freeze it somewhere as insurance. Here excessive inequality has led to the item in question not being used to its highest utility.

I should mention that the wealth doesn’t have to be a liquid asset, even a house or future promises to achieve something, maybe even offering yourself up to be a sex slave, in this case even gender creates inequality, since if the vendor is a straight man, then females will have an extra option to exchange for the heart.

Rational people is in my mind the most far reaching assumption. This is because you might have people who use morals, religion, or have some other irrational mechanism with which they make decisions. There are many cases of people not adapting to their environment to offer up the service or product required to achieve their end means because of morals. You might be desperate for food and find someone selling a loaf of bread for 1000 dollars and think that he is ripping you off and so you decide to wait for someone cheaper to come along, without knowing if this cheaper vendor even exists.

Worse yet, even if there is perfect equality, and a given person x has a higher utility than everyone else and there is only a single unit of the product that will save him, and he knows that there is only one unit and only one chance to buy it(heck it could even be free), he might still decide to forego it due to religious reasons.

We must also assume rationality from the vendor’s side, although its perfectly rational to accept only cash if you don’t trust the people around you. If he does trust everyone to a good degree then he should be able to accept illiquid forms of cash as long as the time value of money is taken into account in the form of interest. It is also true that for the vendor to perfectly utilize the price system he must be able to analyze and calculate the perfect price for his product at any given time in order to make sure that he sells it at the highest price where it is going to be sold out. Even if you sell a bottle of water for 100 dollars, you would have been better off selling two for anything over 50, so its important to be able to price things as optimally as possible.

Do hospitals make you sicker?

Selection bias is often a very destructive force when trying to determine what works and what doesn’t, it’s often impossible to evaluate if programmes are a success or not unless you’re under something extreme like a totalitarian regime.

Let’s take hospitalization for instance; if you were to ask people coming out of the hospital how their health status was, it would probably be worse for people coming out of the hospital rather than randomly selected people from the population.

So let’s assign some simple terms here then.  First let’s have the treatment dummy:

So its 0 if they don’t get treated and 1 if they do get treated. Then we observe the actual outcome (health status) for each individual with Y.

So to actually measure how much of an effect treatment has we need to compare people receiving treatment to those not receiving it.

Yet the world presents problems since what we actually observe in the real world is:

So there is no one number that represents what actually happens. We can measure the, the average effect of treatment on the treated (ATT), average effect of treatment on the untreated (ATU) or the average treatment effect (ATE).

In public institutions there is this top down selection problem and the more private an institution is the more bias comes from self-selection.

The ATT can tell us the effect of going to the hospital on the people who went to the hospital. The first part of the equation is the observed part, where we measure the health status of individuals who went to the hospital had they went to the hospital. The second part is unobserved because it measures the potential health status of patients who went to the hospital had they not gone to the hospital.

ATT can show us how much people gain from going to the hospital. In the real world private enterprises are much more likely to survive if people notice that there is a positive effect and so the market eliminates a low output hospital. A government hospital on the other hand might have trouble eliminating waste because it will receive customers who might not necessarily think the hospital is any good but will still go just because it is free.

The ATU tells us the expected effect of going to the hospital on someone who did not go to the hospital. The unobserved portion is the effect of the hospital on those who did not go. Second part which we observe is the effect of the hospital on those who went to the hospital.

So it seems pretty obvious that in the real world ATU and ATT are very close to impossible to measure accurately. However what we can measure accurately is the average treatment effect. This is represented by:

To accurately measure this we must make sure to apply a RCT (randomized control trial), in other words randomly allocate if people will go to the hospital or not, and here a paradox arises. We can understand if something works if we randomly allocate it, but if we randomly allocate it we are not maximizing the use of the hospital since we are sending in healthy people. Yet if we don’t randomly allocate it we cannot observe if the hospital is working.

This also is the case with control areas if we decide to do something differently in one country/state/city and leave the rest untouched we can then compare them to see if the area where we applied the new method is better off. So what’s the next step? If they are better off then we mass produce this method to the control areas and we can no longer see if it’s working(think long term effects), and if we don’t mass produce it then those control areas are not benefiting from this new method that could be improving their standard of living.

So the paradox here is between knowing something works versus making it work for everyone. Whether we apply a randomized control trial or use control groups, chances are we are not helping out the best we can, and if we do not apply these methods then we are ignorant as to whether the program is helping people at that specific period in time. To properly understand treatment effects we need a sacrificial lamb to exist. Though what’s generally done is to assume that if something worked in the past, it will keep doing so.