Since Udacity is not exactly forthcoming on exactly what their business model will be, could you add some insight to exactly what the great business model is? Right now, I see the MITx and Stanford programs being a small loss per student compared to the normal amount universities spend on instruction, but a small loss a hundred thousand times over doesn't exactly turn a profit.
If you are going the freemium route (free content, pay for testing/credentialing) you have the classic freemium dilemma, what is your conversion percentage from free to paid and what is your margin on the paid version. If you anchor your product pricing at zero, you can't exactly charge hundreds or thousands for testing. Plus, the vast majority of students in the Stanford experiment were overseas which makes the paid option at a recognized testing center much more difficult.
It's all a percentage game. Revenue = Total Students * percent who complete the class * percent who can pay for testing * percent who do pay for testing * margin on testing. We ran the numbers in a number of different number of scenarios when we looked at going that exact same route and found time and time again that even if you can break even at a small number of very popular classes, the chances of being able to build out a broad curriculum of classes with less mass appeal was not good.
To use some realistic numbers, let's take the Intro to Databases class and make up some inputs:
Number of students: 90,000
Percent who completed the class: 7.2%
Percent who could take tests at approved centers: est 40%
Percent conversion from free to paid: Classic freemium less than 5%. Hugely optimistic: 20%
So, we have a probable range of $1,300 - $26,000 based on some real numbers and some educated guesses. $26,000 may sound like a lot, but that amount can easily be absorbed just in the professors time prepping and managing the class. Now add on the rest of the overhead of high paid SV engineers, offices, support, etc...
The end result, an enormous amount of things have to go just right in order to cover your base costs. Even if those things go just right, you still have a huge amount of pressure to create classes with the broadest possible appeal with the highest possible number of students completing the course (in order to have a chance of testing revenue). Those market pressures do not coexist well with academic integrity and high standards. They also don't support classes that might "only" have a few thousand students.
There other ways to get to free education for all (we're on that path ourselves), but starting out as free without the backing of a large university is a tough proposition.
The business model of Ivy league free courses is protect the market, destroy competition, preserve monopoly.
At the moment Uni education is a pretty open market, there is Ivy league, there are top state colleges, there are 3rd tier and then the Phoenix type places - you pay your money and take your choice.
The real tough competition, at least in technical subjects, is between ivy league and top state schools. The students can save a lot of money by going to UCB over Stanford, learn exactly the same stuff and get exactly the same job - why pay the extra $100k for a Stanford t-shirt?
What these free courses are saying to the students headed to state Uni outside the top 10, and in fields that don't require a paper qualification (like software) is: don't bother paying to go to UCLA, do a startup or do opensource AND do our courses for free and you will get the same job.
Gradually (at least in CS) UCLA etc will disappear from the market and the employer radar who then see MIT/Stanford vs self taught.
It's really no different from why Nike pay Tiger Woods a zillion $. The idea is to put in the minds of the consumer (or CS student and employer) that there is only Nike or nothing.
Not to be too self promotional, but we're probably the closest to what you are describing. The biggest limitation is our course catalog is very small to start (bootstrapping). Over the next 12-18 months we should have a much more complete curriculum (Masters in CS/SE focused) as we prep for regional accreditation.
Flexibility? All classes are truly self paced (start immediately, work through the material as fast as you are capable) and include genuine interaction with the professor and real human grading.
Expensive? Basically, $50/$100 per credit depending on whether you need the credentialing and human grading portion. In your situation, our MSE program would end up being less than $4,000 plus books.
We're also Silicon Valley based, and are building the program to exceed the very high standards in the area.
Having done my fair share of laser marquetry, let me first tell you that I truly appreciate the amount of work that goes into the whole process, and really respect what you are doing. The intricacy of these types of patterns makes for a very high level of difficulty.
That being said, it appears to my somewhat trained eye that you are using Photoshop (or other CG) mockups on some of the product pages (http://woodcutmaps.com/146 for example), without saying explicitly that that's what they are. I know how difficult straight on photography is with these textures, but if those are indeed Photoshop generated, you run the risk of increasing expectations beyond what is technically possible with the process.
Excellent work either way, as I can tell from the genuine product shots. Like I said, not easy stuff.
OU was a big inspiration for us. The bar we personally use is building a system designed for Silicon Valley. Pacing and availability are critical, as is maintaining a very high standard for classes. Right now, OU doesn't meet either requirement. (their SE program, for example, is little more than a few intro to Java classes and some SE theory)
I was hoping this comment would come up, actually. The real difference in just in time vs. just in case has to do with delivery, sequencing and retention. A broad, solid foundation sounds great on paper, but there are some hard realities that sink in shortly after graduating. First, within about 6 months the amount of actual knowledge you retain from this foundation is probably going to be between 5 and 7%. That's 5-7% of the total from a not very efficient 4 or 5 years of dedicated study. How not efficient? Well, if you look at the in major portion of your degree, you probably had about 450 hours in real classroom instruction, or a little under 2 hours a week. So, of those 450 hours, you will probably retain less than 30 or 40 hours worth of real useful knowledge. you may dismiss this as hyperbole, but trust me, all that work dissolves incredibly quickly. I remember Big O, a couple of formulas, and the ability to order a sandwich (or was it a donut) in German.
More importantly, though, is the fact that since you only have 40 or so classroom hours in any class, and you have to teach to the average, it is extremely difficult to build up to a properly high level of skill in any particular subject. It feels hard while you are doing it, but after you graduate, you realize the people who have been focusing on the subject for a couple years are light years ahead of you. It's even more difficult to chain subject together to reach that high level. The closest thing we have is a generic 100,200,300 level system with some prerequisites.
How does this relate to just in time vs just in case? Even if you assume an identical breadth of knowledge, being able to sequence classes together in series instead of having semester and scheduling gaps means you go into the next class with more knowledge retained from the previous, which means you can build on your foundation in a more logical and efficient way and reach those higher levels that you just can't in a fragmented system. You can approach this from the ground up (building on higher and higher concepts), but the very nature of a JIT system means you can also approach it from the top down. That is, you can define the ends result or top level class, and then sequence each course to build up the fundamentals you need, just before you need them.
The point? If you are defining a broad base of skills, JIT allows you to master each one quicker and sequence them together to reach higher levels of mastery. If you need skills in the real world, JIT is the quickest and most efficient way to build those skills. The reason I consider disagreeing to be dangerously wrong, is that JIT is so much more effective at real education that those who bank on JIC for their future (students, schools, or countries) will find themselves left in the dustbin of history.
Thanks for the thorough reply. It seems we agree on a few key points:
1) Retention sucks in the current model of higher education.
I've been thinking about this one a lot lately. I've been doing a one year masters where I'm taking two courses a semester and doing research. The depth with which I am learning things is night and day compared to the depth with which I learned my undergrad material. During undergrad, I was drinking from a firehose and just trying not to drown. I would turn in unfinished problem sets, not having learned the material, and move on with my life. I would sleep through classes out of sheer exhaustion.
Now, with just two classes, I'm able to learn things almost well enough to teach them. So one way to improve retention is just to take things slower.
Another model comes to mind if we consider how people study at Cambridge, Oxford, etc. I have not experienced it myself, but according to students who went there as exchange students (and students from there who came here (here being MIT)) it's pretty different. Students here are overwhelmed with constant work. There, it is a lot more self paced, with a set of final examination at the end (someone please correct me if I am not doing it justice).
So perhaps self-pacing and working smarter, not harder leads to more retention.
Do you know of any sources for retention statistics such as those you cited? Some of them don't match my experience (for example, I would say that I spent 8-10 hours a week in classes related to my major).
2) Courses need to happen in a logical sequence so that they can build on one another.
When I first read your post I thought you were suggesting that students should, by themselves, pick what to learn based on what they want to build, in lieu of being guided through a logical curriculum.
The point about scheduling gaps is interesting. Scheduling gaps happen because it's hard to satisfy the constraints of so many student and faculty schedules. If you could take courses on demand, that would fix things.
3) Results driven learning can be excellent for motivation and retention.
When one talks about results, there is a fundamental issue of time scale.
Courses that say things like "When you're done, you will have built an autonomous mobile robot" are great.
But there are many fundamental things to learn, over a long period of time, whose benefits
* you might not see for a long time
* are broader than you could have ever imagined (and hence the benefit would seem artificially low to you)
If you as a student get to pick the desired result yourself all the time, you might be tempted to pick shorter-term results. This can be catastrophic to your education.
I believe in forcing people to learn fundamentals of their chosen field --- fundamentals whose power they might not appreciate until later. Learning fundamentals (that you might choose not to learn if you weren't forced to) is fruitful in powerful and unexpected ways.
Take pure math classes. You learn analysis. Then you learn measure theory. Then you learn measure-theoretic probability theory. Then you learn stochastic processes. All of a sudden, financial mathematics becomes easy to grasp. But so do a host of other things. Signal processing, computer vision, statistical mechanics, complex multiagent systems, epidemic modeling, control systems.
I suppose you could have started on this path because you wanted to learn financial mathematics. But it probably would have seemed way too complicated and difficult. But if someone says they want to be an applied mathematician (a much "broader" and more long term goal than just learning financial mathematics), then they'd better take a ton of pure math.
1) There have been a few different experiments with self pacing and retention at schools like Oxford (and a college in Iowa of all places). The typical result is a significant increase in retention with lower stress. The problem, and fundamental reason why this isn't the norm, is simple logistics. Trying to build a serial system of education that still uses classrooms is massively difficult. The closest you can get is a compromised 6 week class system that is still extremely difficult to pull off. Parallel is just easier and more cost effective to administer. It's also easier and more cost effective to administer on an online system which is why the push for MOOC. The difference for us is that we care more about optimizing the learning process itself and real evaluation and guidance, and are willing to bet that enough students also care about those points to give us a chance at proving it at a large scale. Our system costs a little more than free, sure, but the difference in results can be dramatic, as you are seeing with your masters program.
As for in-major hours, it may vary a bit by school (and MIT has a higher percentage than most), but here is the breakdown for UT. In-major credits required for a CS bachelors: 45. Average credits per class: 4. Weeks in a semester: 14. Average classes per week: 3. Total estimated lecture hours per class: 42ish. Total in major lecture hours for 45 credits: about 500. Subtract intro days, quiz and final days plus time for class to get settled, etc.. and you have somewhere around 400-450 hours left, or 100 per year, 2 per calendar year week or 3.5 per school year week. Some semesters you might not have any in major, some you might have 2 or 3, so remembering 8 hours in a week of classes is not outside of the data set.
2) A student should not have to know the exact set of skills necessary to build up to the higher level concepts. This is one of the problems with the self directed learning attempts in traditional schools. But, if the student has a clear end goal in mind (say, the goal of becoming a search engineer at Google), then a JIT system that can build a sequence of courses based on the concepts within the course is more effective and targeted than a standardized fire-hose curriculum. Speaking of fire-hose, I'm working on a post covering context switching in a parallel educational system that addresses exactly why this is such a problem.
3) This comes back around to the top down (or goal oriented) approach, and gets even more interesting with a mentor guided approach. Imagine a hybrid apprentice/mentor system where the mentor can define a sequence (or collection) of high level concepts which the learning system could then take and generate a path to master those concepts. All the while, the mentor could provide direct guidance and assistance where needed and help answer the tough questions that arise without having to dedicate all their time to the actual instruction. There are many, many, variations on this pattern that work extremely well with JIT systems but really don't work at all in JIC.
The best way we can attract our first users is with having a course that is so valuable for our students that accreditation concerns become secondary. In this case, if you are looking for a high level class in Web App for Mobile, you probably will never find it in the coursera, mitx, udacity or khan catalogs. They have no interest or incentive to put that sort of course together.
If you look at the value proposition for a student, our web app class is extremely high. The material covered in that class can have a direct impact on job prospects, billing rates, or internal promotion opportunities, and it is such a difficult area to self teach that saving tens or hundreds of hours fighting though online tutorials is well worth the $200 or $400 that the class costs.
How do I know it's high quality, though? $400 is a significant amount of money. Without user testimonials or reviews, am I supposed to take it on blind faith that it will be worth my $$?
I'm not slagging you, by the way. Just offering my initial reaction as someone who would be interested in such a class, who is doing a CS degree at a traditional university, and who would like to see someone disrupt the higher education model.
As soon as we have users, we'll have user testimonials and reviews. It's part chicken and egg, I know, but it's the same problem any new product has. Someone has to be the first.
Other than user reviews (and the free preview and money back guarantee), what could we do to convince you (or other prospective students in your position) that it's worth the risk? Would a google hangout with Dr. Ostrowski (something we have been talking about) make a difference ?
Thanks for the advice, We'll definitely work on making our guarantee more prominent.
I've been considering an AMA on Reddit, even though I actually had to quit the site three months ago to get to where we are. AMAs on HN are a little tricky as the commenting system is so...unique.
Either way, I'll add your email and keep you updated.
HN AMAs unfortunately seem to be a non-starter. I can definitely sympathize with blocking reddit for productivity reasons, but it's a connection with your target market that shouldn't be ignored.
I like your idea, and I love your goal, but it's going to take more than that to make me a customer who forks over hundreds of dollars. You've got the attention of the technorati; I'd first focus on how you can convert them to paying customers, then deal with the plebs later.
Well, the courses start at $200, we have a generous refund policy, and you can actually try the system and class out for free right now with a guest account. We don't even require a real email.
Also, we have thought very seriously about the business model of offering classes for free (Udacity model) and charging for certification/one on one. The numbers we see for that model just don't work, even at a large scale. You have to focus in introductory classes with the broadest possible appeal, reduce the difficulty of the course so you don't get 10,000 complaint emails from students who can't keep up, use a MOOC structure that is more about cost control than maximizing learning. Plus, the conversion from free to paid user may or may not be enough to cover the cost of course development. Our model, on the other hand, allows us to pay our professors quite generously for classes that may not have 100,000 students attending and focus more on building our catalog instead of just building the user base.
We actually have to focus on results first and foremost. By the time we can even apply for accreditation (probably 3 years out) the issue of accreditation for reputation will be moot.
But, you have to look at what the larger impact can be with accreditation and Title IV. Even though we are strongly against student loans, being able to work with state and federal governments for grant and work study funds is the best and most direct way we have at hitting "free education for all" status. It's also the quickest way to move out of the relatively small group of students who don't care about accreditation to reach the much larger group that does. It's only by being a reasonable alternative to this group of students that we can apply real pressure to the current system. As long as we aren't accredited, the existing institutions can simply point to that fact and write us off and most people will listen to them.
If you are going the freemium route (free content, pay for testing/credentialing) you have the classic freemium dilemma, what is your conversion percentage from free to paid and what is your margin on the paid version. If you anchor your product pricing at zero, you can't exactly charge hundreds or thousands for testing. Plus, the vast majority of students in the Stanford experiment were overseas which makes the paid option at a recognized testing center much more difficult.
It's all a percentage game. Revenue = Total Students * percent who complete the class * percent who can pay for testing * percent who do pay for testing * margin on testing. We ran the numbers in a number of different number of scenarios when we looked at going that exact same route and found time and time again that even if you can break even at a small number of very popular classes, the chances of being able to build out a broad curriculum of classes with less mass appeal was not good.
To use some realistic numbers, let's take the Intro to Databases class and make up some inputs:
Number of students: 90,000
Percent who completed the class: 7.2%
Percent who could take tests at approved centers: est 40%
Percent conversion from free to paid: Classic freemium less than 5%. Hugely optimistic: 20%
Margin from a paid testing center: $10-$50 (est)
90,000 * .072 * .4 * .05/.2 = 130/520 estimated paid students
So, we have a probable range of $1,300 - $26,000 based on some real numbers and some educated guesses. $26,000 may sound like a lot, but that amount can easily be absorbed just in the professors time prepping and managing the class. Now add on the rest of the overhead of high paid SV engineers, offices, support, etc...
The end result, an enormous amount of things have to go just right in order to cover your base costs. Even if those things go just right, you still have a huge amount of pressure to create classes with the broadest possible appeal with the highest possible number of students completing the course (in order to have a chance of testing revenue). Those market pressures do not coexist well with academic integrity and high standards. They also don't support classes that might "only" have a few thousand students.
There other ways to get to free education for all (we're on that path ourselves), but starting out as free without the backing of a large university is a tough proposition.