The Education Bubble

It is possible that you have heard of the concept of an "Education Bubble". We have seen a Tech Bubble that burst in 2001-2002. We have also seen a Housing Bubble that burst in 2007-2008. Some people are now predicting an Education Bubble is the next thing that will burst. I didn't really like this term when I first heard it, but recently I have come around to accepting it. This term is used to describe something that I have been worried about for a while, a devaluation of standard college education. This blog post will present my views on this issue and what I think schools, like the one I teach at, need to do to make sure they aren't destroyed when this bubble bursts.

First off, I should explain why I didn't like the term "Education Bubble". I think that a college education is extremely valuable. Studies such as What's it Worth? show that those with a college education earn more than those without, and for many majors, the difference is easily large enough to justify the expense. In addition, those with a bachelors degree are far less likely to be unemployed than those without. In fact, if you look at the plot linked to in the previous sentence, you probably notice that even having college without a degree seems to have moved away from the college degree curve since the last recession.

The reason I didn't like the term was that it implied to me that the value of college education was going to drop. I don't see that. If anything, I feel that the value of high levels of education is going to increase. One thing I do see changing is that just having a degree in whatever you want is no longer sufficient. I'll come back to this point later.

So if I don't think that the value of college level education is going down, why did I say above that I foresee a devaluation of a standard college education? The reason is that I see a rise in the availability and quality of non-standard forms of education that will cost a lot less. As prices are set by marginal utility, the devaluation I see isn't of the product itself, but how much it provides you above and beyond much cheaper alternatives. From the standpoint of what the market will bear when it comes to tuition, it doesn't matter if the pressure is devaluation from above or increased valuation of lower-cost products, either way, tuition costs will have to come down.

Where the Pressure Comes From
The source of the pressure that I think colleges should be feeling comes from new technology that allows education on a much broader scale. One of the more well known agents in this is the KhanAcademy. With funding from the Gates Foundation, KhanAcademy has made some waves. Most people think of it as a tool for teaching elementary kids arithmetic, but if you visit the site you will see they have a lot more going on. The math goes well into the college curriculum with differential equations. They also have more diverse topics like science, finance, and art history. All of these videos are free to watch. It is also free to do testing that verifies what you have learned for many of the topics.

Of course, KhanAcademy isn't really gunning to replace colleges. Other sites like Udacity and Coursera are. Those two sites were born in late 2011-early 2012 out of Stanford, and both offer full courses online. They include evaluation in addition to lectures. Udacity was co-founded by Sebastian Thrun who is probably best known for his involvement in the Google autonomous car project. In the fall of 2011 he offered his Stanford AI course to the world online and over 100,000 students signed up and 20,000 finished the course. A detailed look at this can be found in an article from Wired. There are three significant features I want to point out.

• Thrun left his tenured position at Stanford to found Udacity. That is how much he believes in this model.
• Students stopped coming to his lecture at Stanford to watch the videos because that felt more personal to them.
• "Fifty years from now, according to Thrun, there will be only 10 institutions in the whole world that deliver higher education."

These aren't your standard online courses and things have moved well beyond OpenCourseware.

Speaking of OpenCourseware, MIT has seen this Stanford based "threat" and has answered with MITx. Their goal is to be able to offer certification for completing MIT courses and they want the entire MIT curriculum on there. This type of thing is already being utilized by some people. Today there are questions of acceptance by employers and others, but I don't think it is likely those obstacles will slow things down too much.

Another recent entry into the fray is the Minerva Project. Their goal is a bit different. They want to be an affordable, elite institution that uses material from top faculty from around the globe. In some ways, this shows that people are still feeling about for what will really work. However, it is likely that something will gain traction, and all of these are reducing the margin between what one can get for a low cost (possibly free), and what one gets in the standard college experience.

Current Impact
These new challengers are just starting up, but hard economic times have already forced a number of institutions to make changes. The motivation for change can be seen in declining enrollment and rising discount rates. Basically, it is getting a lot harder to pull in students, especially those who will pay the money that higher education is currently asking for. Some schools are already responding to this by cutting tuition. Even more have chosen to freeze tuition or take other measures.

What it comes down to is that the competition for students and student dollars is getting more fierce. It isn't just an economic problem either. It has moved full force into the political arena as well. State schools have been feeling it for a while as their state funding gets cut. Having the federal government turn an eye to it means that private institutions might have to deal with this as well. Honestly, having state school defunded helps private institutions as it closes the tuition gap. Losing national funding from grants and the like won't be so helpful.

Needed Changes
So what needs to happen? The short answer is that tuition needs to come down. Even if the economy picks back up enough that individuals and families are willing and able to pay higher tuition, The availability of real alternatives at much lower cost or no cost will eventually push people away from standard colleges unless they drop their price.

How much does tuition need to drop? My gut feeling is that tuition needs to drop to almost nothing. Room and board plus the opportunity cost of being in college is probably going to be a significant hurdle even without additional tuition. I can see some tuition as being needed for various psychological reasons, but I can't see it being a big part of the budget for a college or University. That's going to be a real problem for schools that currently get the vast majority of their budget from tuition. I don't see much hope for those schools in 20 years, perhaps even in 10. The timescale depends as much on social momentum as it does on technology changes. Schools with large endowments have a chance to restructure themselves so that their endowment covers the majority of their budget. That isn't going to happen overnight though. That is where the bubble part comes in. Schools which start making changes in advance can restructure their budgets in a smooth transition and survive. Those who fail to do this will have to rush at the last moment to make the changes and I expect most will burst and fail.

Making this Happen
So how can a school make this happen? I can only talk to this in a limited way as college budgets are far from my area of specialization. In the case of Trinity I believe that ~55% of our budget currently comes from tuition. That is a lot of money to shave off. However, if that can be dropped to ~25% in 10 years it would, IMO, be a significant step in the right direction and at that point we would definitely have a clearer picture of how much more needed to be done. For this to happen, tuition needs to drop, but having a bigger endowment would certainly help as well.

So how can a University lop off ~30% of their operating budget in 10 years? I have no idea on the details. My hope is that someone reading this will know more about that and come up with something. However, I can talk to aspects related to faculty and technology.

The bottom line is that we need to be more efficient, and do more with less. This has been a mantra for businesses through most of the economy. However, it hasn't hit education. Indeed, we have gone the other way. We typically push for lower student/faculty ratios. Trinity is now down to 10:1. We tout that  as a benefit in our recruiting. There is no doubt it is a great thing in many ways. There is also no doubt that it is extremely expensive to maintain that ratio. Doing more with less in education really means finding a way to give students the feel of an individualized educational experience with good access to faculty without having 10:1 student/faculty ratios.

In order to do this, we have to re-evaluate how we teach everything. I think we need to take some notes from our upcoming competition as well. If you read the article from Wired linked to above, Thrun mentions that students stopped coming to lecture in favor of the videos. Today's students often consider watching a video in their room to be a more intimate and individualized interaction than being in even a small lecture hall with the professor. This points to one easy change: faculty should not be full time lecturers. We should take advantage of things like online videos, even making them ourselves. Time spent face-to-face with students should be spent using formats that exclusively can't be done with prepared videos, like answering questions, providing critique, and moderating discussion.

In many ways, making students watch videos is not that much different from asking them to read. I believe that the videos work better, but only partly because they are videos. (The dynamic nature of video can definitely help with some topics.) What makes them really successful is having them done in short segments (10-15 minutes is ideal) and having them followed by questions that help a student identify if he/she understood the material. That can be done for reading too, but making it work requires utilizing technology.

That is the other half to doing more with less. Education has been very poor at making good use of technology. Many different approaches have been tried. Few have been really successful in changing the fundamental nature and efficiency of the education process. I feel like we have finally hit the point where that can change. Electronic evaluation gives us the ability to place little sign posts that students have to go past and check off. These don't have to be a primary form of evaluation, just something strong enough to serve two purposes. They have to tell the student if he/she is really grasping the material and they need to allow the faculty member to check that students are doing each of them. The technology exists to do this today. It takes more prep-time, but once created, it is useful for many years and allows faculty to focus more on efforts that are very individualized. That is the one edge a traditional campus has over something like Udacity, and we have to find ways to maximize it.

It is probably already apparent at this point, but I feel that I have to explicitly mention that any movement to reduced teaching loads is moving in the wrong direction. To cut 30% off a University budget is going to require increased teaching loads. Faculty might balk at that, but keep two things in mind. I really am talking about working smarter, not just harder. In addition, if the education bubble does burst and we haven't done this, faculty become unemployed and most will have little chance of re-employment.

The World Keeps Changing
Now to the other topic that I feel is closely related, and which I know many of my colleagues will probably be upset to hear me say. I feel that we are moving out the the window of time where "a college degree in anything" insures a job. In an earlier blog post I wrote about differences between what is happening today and the industrial revolution. In regards to education and jobs, prior to the 1920s, people could safely drop out of primary school and still get employed. When the industrial revolution rewrote the rules of American farms, that changed. Somewhere around the 1950s I believe the rule had become that a high school diploma was what you needed to make sure you had a good job. For all of my life, ~1980-2010, the rule of thumb has been that a college degree, regardless of what it is in, is the path to a good job and a good life. I think we are moving out of that phase.

This is part of the education bubble. This is the reason you have people like Peter Thiel telling students that they should simply skip college. I personally still see a huge value in college education. However, there is a gain of truth in what Thiel has to say. I think it is possible today to get a college education that doesn't serve you well later in life. Regardless of what you major in, you have to make certain you pick up certain skills that will benefit you after graduation. All too often, college students under the impression that "any degree will do" search for the easiest route. I think what Thiel is really pointing out is that the world is constantly growing more competitive and those who seek the easy way out are dooming themselves to failure, even if they complete a college degree.

Maybe I am Wrong
Of course, it is always possible that I am wrong. It is possible that companies will decide that credentials from places like Udacity have no meaning. Maybe colleges don't have to lower tuition or can even raise it and students will continue to walk through our doors and pay whatever we demand. I don't think I'm willing to bet my career on that assumption though.

I would like to thank Bryan Alexander for ideas and some of the links in this post.

Value of Skills in 2022

This post continues my thoughts on curricular issues. I said the last one might upset some people. This one could probably cause various things to be thrown at me the next time I walk across campus if many people read it.

The year 2022 in the title was not selected just because it happens to be 10 years in the future, it was selected because Trinity is currently redoing the curriculum with the charge of considering the needs of the graduate of 2022. As this is another post that some might disagree with I repeat my request that if you do, start a discussion. That way we might both learn something.

Skills vs. Content
There are many ways of classifying things that one feels students should learn. For this post I am going to use a skills vs. content division and focus on the skills side. When looking at this division, skills are things like reading and writing. They are separate from content in that they are broadly applicable to many different content areas. Every class should be making you read. Every class should also be making you write to some extent. Content can be divided up into its own set of categories. I am going to ignore those because what I want to focus on is a few possible areas of skills that an institution of higher education, such as Trinity, might want to make sure students have command of before they graduate. I want to look briefly at their value today and then look at how that might change by 2022.

Here are the categories of skills I want to consider:

• Reading
• Writing
• Quantitative/Numeric
• Foreign Language (Natural Language)
• Basic Programming (think of this as Foreign Language: Artificial Language)

All of these have the characteristic that they can be valuable in conjunction with many types of content. In addition, they are often challenging to teach without associated content, with the possible exception of foreign language where conversational usage provides an automatic application.

Current State of Affairs

The way things stand today, reading, writing, and quantitative skills start with primary school and continue on through college. In the state of Texas now, all students have to take 4-years of English, Math, Social Studies, and Science in high school. When they go to college, all students continue to read and write, though perhaps with less explicit instruction.

Many students pretty much stop taking quantitative courses. There is generally some minimum core requirement for math and science which will have quantitative elements. Students outside of STEM majors are very prone to take nothing above the minimum for that. Having taught introductory astronomy to classes which are mostly composed of students who are taking it to avoid other courses they perceive as harder, and who will often say they haven't done any math in years, I feel fairly confident in saying that by the time they leave college, a great many students have very poor skills at the level of algebra and above.

Foreign language in the US is not introduced until middle school or high school normally, and most colleges have a minimum requirement for that as well. The minimum requirement for foreign language can be anywhere from 2-4 semesters (that would be 2-4 years of HS study). Depending on the details of how it is implemented, many students will never have to take a foreign language in college as long as they took enough while they were in high school.

Then there is programming. In the US it is not generally even offered before high school. Not all high schools offer it, and even when they do, it isn't required for anything so few students take it. At the college level, it is generally not a requirement except in some STEM majors. (At Trinity, the introductory programming course is required by CS, Engineering, Math, and Physics, it is an option for Biology and Geoscience, and it is not mentioned in the Chemistry degrees. No other department requires it, and it is not a University requirement, though it can satisfy one course in the Common Curriculum.)

The standard explanation for this is that programming is not as fundamental a skill as the others. While I would disagree with that even in 2012, I will argue that in 2022 it could be the most fundamental of these skills after reading and be on par with quantitative skills.

Why Coding Instead of Application Usage?

Some readers might find it interesting that my skill is for programming, not application usage. Indeed, many schools in the US have gone through times where application usage was either required or was at least taught to large fractions of students. While that likely made Microsoft very happy (and I'm sure they donated the software to help make it happen), proficiency in particular pieces of software is extremely non-fundamental. It is something that changes a lot, all the time. How do you pick what software to teach? Why chose one vendor over another for similar programs?

The reality is that knowing how to use a particular application might be helpful in life or even in completing your homework. However, it does not open new vistas in terms of your thinking. The ability to read allows you to acquire knowledge in ways that are completely closed to the illiterate. The ability to do math allows you to approach many problems with a formalism that leads to exact answers in ways you can't do without it. In this same way, the logical formalism of learning how to program opens your mind to new ways of approaching problems. It also gives you access to a completely general problem solving tool that can do things that are impossible for the unaided human.

Teaching a kid to use Microsoft Word is like giving a hungry man a fish. Teaching that kid how to program is like teaching the kid to fish. It gives him/her a new perspective on all problems as well as on what is going on in every program he/she ever uses. Given how much of modern life is spent using computers and software, it is a bit surprising how few people have any clue what is going on inside those magical little boxes. (Indeed, they are magic little boxes to anyone who doesn't have any idea what is going on inside of them.)

Existing Technology and Trends

Of course, technology is ever changing. Computers are getting exponentially faster so the rate of change of computing power is also exponential. What is cutting edge today will be mainstream in less than five years. In ten years you will have small devices running things that would only be possible today on a supercomputer, or which haven't even been written today because there is no market as the mainstream machines can't handle them.

So how is current cutting edge technology impacting the skills mentioned above? 

Reading - This one doesn't even need to go cutting edge. Have you seen a headline for a topic of interest and clicked on it expecting an article, only to find a video? Videos and audio are everywhere. You really don't have to read much to get information these days because technology has made information in others forms fairly ubiquitous. In the case of education, consider sites like the KhanAcademy, where you can pick from hundreds of video lectures. TED-Ed, YouTube > EDU, and many other venues are adding great educational material using the dynamic medium of video.vSure you have to read some words in the video, but that is pretty low-level reading.

At the cutting edge we are beginning to see a real move from standard textbooks to electronic textbooks. The impetus is that the newer forms of electronic textbooks can be highly dynamic with integrated video and other features that bring the contents to life. Sure they still have writing and you still read, but compare the reading that happens in those books to an old textbook you might pick up from several decades ago. The nature of reading has already changed a lot and will continue to do so.

Writing - The impact of technology on writing at the cutting edge today is probably best seen in Narrative Science. This is a company that makes software to write news stories. Here is one article of many that have been written about the company. You can see the products of the program at Forbes, where Narrative science has their own blog. The simple message of this is that writing has been automated. The robotic author is not just part of the future, it is part of the present. It isn't yet general enough to work on everything, but what they are doing works off of nothing but machine readable data. It isn't hard to imagine a program that takes an outline and some basic information from an "author" and produces an essay or short paper in full prose.

Quantitative - Quantitative skills have been part of technology for decades. These days a lot of the instruction for arithmetic is done expecting the use of calculators. Even this has taken significant steps recently with things like the ability to do 3-D plots in Google. Probably the best demonstration of cutting edge though is Wolfram Alpha. This website, set up by the creators of Mathematica, gives you remarkable abilities when it comes to quantitative data. For example, it is a simple matter to get answers for many different mathematical problems, whether symbolic or not. You can even have it look up data sets for you and do math on them, like this search showing the ratio of corporate profits to GDP in the US.

Foreign Language - One of the main goals of knowing a foreign language is to facilitate communication with people who speak other languages. Your smartphone can do that now. There are many different apps that you can put on your phone that will translate your speech to text in a foreign language. Some of the newer work on this includes a Microsoft project that uses your voice to speak the translated text.

Coding - Everything listed above was created by people writing code. You are reading this on a computer that is running an OS that includes hundreds of millions of lines of code using a browser that is code. Computer code/programs are everywhere in 2012. Computing is ubiquitous. There are a number of educational tools like Scratch and Alice, which are designed to make coding more accessible to the novice. However, there really aren't any tools that automate the fundamental process of writing code. 

There are two main reasons for this. First, natural languages contain many ambiguities and code can't. You have all seen examples of English that has been written explicitly to be non-ambiguous. That is what you see on tax forms. It is painful, ugly stuff. So even if you create a tool that goes from English to code, the user still needs to have some basic knowledge of how to help the program remove ambiguities.

The second reason is the halting problem. From the early days, computer scientists have known that there is no way to universally automate coding. This doesn't mean we can't create programs that write other programs as well as humans. This does mean that we can never write a program that can write any other program we desire and be able to demonstrate it is correct.

Where All This Leads in 2022

Math and numeracy are probably the best examples of the fact that just because technology has made it so you don't need to be able to do something, there is still value in knowing how to do it. Calculators have made doing arithmetic by hand obsolete for quite a while now. However, they are garbage in, garbage out devices so if you don't have any idea what the operations really are, you have no feel for the numbers and you don't realize when answers that you get are completely absurd. In addition, symbolic manipulation is probably the more important quantitative skill to have, and it too requires some type of feel for operations for it to make sense. So just because technology can do something, even if it does it better than humans, there can still be a value in humans learning how to do it.

However, the relative values of reading, writing, and foreign language skills are going to take a significant hit in the coming decade as the usage of those skills declines with computers filling in the gaps. To see this, start with foreign language. There are cognitive advantages to knowing more than one natural language and there are advantages to understanding other cultures in ways that are hard to do without knowing the language. In 2022 though, it is likely that a small device will be able to fit into your ear that works like Douglas Adams's babblefish and allows you to hear translated speech of those around you with minimal delay. In effect this means that there is almost no advantage to learning a foreign language in terms of communicating with other people. In addition, I see globalization of markets decreasing for various reasons (which would take a full post to describe, but think 3-D printers and increasing transportation/energy costs) so that will also reduce the impetus for studying a foreign language relative to today.

When it comes to writing, people will need to know how to do it, but I expect a lot of the dirty details will be handled by computers. A human will lay out ideas, and a computer will be able to stitch them together into complete prose. The human can proof them or tweak them, but most of the time probably won't bother. This doesn't apply to poetry or certain other types of artistic writing, but that is a small fraction of what people write today and if anything I see it shrinking, not growing. Narrative Science could probably do most technical writing in under five years. No need to wait until 2022 for that.

Should you even bother writing things if people won't read them? I still expect many things will be read. It will still be a vital skill. However, kids know how to read by the end of primary school. Little instruction beyond that really focuses on the mechanics of reading. At that point reading becomes mostly a tool to use to get information. Even though reading will be needed, it wouldn't surprise me if the amount it is actually done goes down. Why bother reading a static book when other media can present dynamic concepts so much better? What is more, it isn't hard to imagine a Heads-Up Display (HUD) that integrates functionality like Google Goggles that can not only analyze the items you are looking at and give you back information, it can read things to you too. Having it read in your native language might not be something most people want, but having it read things in foreign languages could be extremely helpful.

What about quantitative? This is a hard one for me. I feel like there will continue to be a general need for numeracy, symbolic manipulation, and the general rigor of working within the formal systems that are part of mathematics. This list doesn't explicitly include arithmetic. My gut feeling is that arithmetic is needed for the numeracy, but perhaps someone will find a way around that. The need to do arithmetic is going to decline even further in the future as the ubiquitous computers are very good at arithmetic and they will be always at hand to do it for us. Still, I feel there is a need to understand it at some level so you know what operations connect to different meanings.

Of course, if code is ubiquitous in 2012, it will be far more so in 2022. Does everyone need to know how to write code? No, not everyone, but anyone who wants to be successful in life probably does. This position is probably best laid out by the article "Now Every Company is a Software Company" in Forbes from 2011. My view can be summed up this way, if you think that computers are magic little boxes in 2022, and you have no idea what is happening inside them, you have already lost.

Closing Notes: The Rise of Other Skills

In writing this post, it has occurred to me that while the need for some skills falls, others will rise. One of the current buzzwords in computing is "big data". That is how Narrative Science works today. By 2022 it is possible that everything will be "big data" in one way or another. The sciences are pretty much there today. Politics and economics are too. Digital humanities will pull in the rest of academia. What skills are needed to deal with that? It isn't just coding.

In addition, as reading and writing fall, I see a possible rise of the value of oral communication. The ability to speak to others in ways that entertains and makes your case is important today. It might be absolutely essential in 2022.

What are your thoughts? Let me know what you agree and disagree with.

Option for 4-4, 2-2 at Trinity

This post is rather specific to teaching at Trinity, but it has elements that might interest others in higher education,. Plus I figure that many of the people who see my posts are former students who might at least find this interesting, and might even want to provide feedback. Warning, this post contains a few of my opinions that might not make me popular on certain parts of campus. I would suggest that instead of getting offended, a reader who disagrees should try to turn that energy into comments that can lead to constructive discussion. Present why you disagree and elaborate. I typically find that I learn most about things when I can have reasoned discussions with people who have very different viewpoints. It makes me think outside of my comfort zone.

Background
Currently Trinity has a teaching load of 9 contact hours/semester and as most classes are 3-hour courses, this leads to what we call the 3-3 teaching load. In addition, students take roughly 5 courses each semester of these 3-hour courses. A number of faculty have pushed for going to a 4-4 course load where students take only 4 courses each semester. To make this work those courses should be 4 contact hours each. (Note that apparently some schools had been basically cheating on this and newer laws make it so that such courses must be 4-hour courses. The schools doing this were often considered good schools that rank highly, which is why they are often cited in discussions.)

The goals of such a change are two fold. First, students are not as spread thin and distracted by so many different topics. Second, faculty can have fewer preps because fewer courses need to be offered. Both can be valid arguments, though I'm not sure I buy either one. For the first one, the reality is that students at Trinity have lots of time to pursue fun activities. Even those taking 18+ hours can generally participate in a fair number of hours each week of various recreational activities. If faculty find that students aren't focused enough on their course, perhaps the faculty need to work on making their courses harder so students have to focus.

As for the faculty, my message is similar. I regularly do overloads above a 3-3. I still find time to do my research, write a 900 page textbook, and do things with my wife and kids. I also have students coming by not only for office hours to get help, but just to shoot the shit and talk about cool stuff. Would I enjoy having less work to do? Perhaps, though as most of my work is self-inflicted, that is a position that might be hard to argue for. However, the reality is that the world is a competitive place and it is only getting more so. For students who don't want to lose their social time I point to Occupy protesters who have degrees and no jobs. You need to be better than them. For faculty, my future post on the "Education Bubble" will hopefully make it clear why I think we need to be working our butts off to make sure our entire institution is still relevant in 20 years. Asking for higher wages and lower teaching loads feels to me like a step in the wrong direction. Instead, I think we need to try to move toward having extremely low tuition and the ability to "live" off of little more than the endowment.

The division on support of the 4-4 seems to be reasonably clear through departments. Departments in STEM (along with Business and Music), which have a lot of hours in their graduation requirements say it isn't feasible. Departments in the humanities and the social sciences with under 40 hours of requirements typically like it. Computer Science is a big major and we barely staff things as is. We also wish we could add more courses to the major, not fewer. You can tell from this where I stand.

Having said all of that, I do have an idea for those who really want to go 4-4.

A Simple Proposal
Seriously, this isn't rocket science. If your department wants to go 4-4, do it. Start teaching 4 hour courses. The normal teaching load will be two four hour courses. Every so often you throw in something else so you have an average of 9 contact hours. (Maymester and the like would help with that last part.)

The only problem with doing this today is that Trinity's class schedule does not support it. We have blocks of time set up for 3-hour courses. So the second part of this proposal is a change in the time blocks. Right now we have 15 normal time blocks with 9 MWF/MW and 6 TR. Here are two alternatives. In both of these the blocks are changed to 4-hours, but I expect many 3-hour courses will still be taught. They just leave a bit more free time between sections.

First, to please the faculty who would like to have a day set aside for things like outside speakers, we do MR and TF with blocks of 8:00-9:45, 10:00-11:45, 12:00-1:45, 2:00-3:45, 4:00-5:45, and so on. Most courses will use these blocks. This leaves Wednesday completely open. Unfortunately, there are only 10 time blocks before 6pm instead of the current 15. That is probably too big a drop for the scheduling to work out, but maybe I'm wrong and it could happen. It could be modified so that Wednesday we allow 3-hour courses until noon. That way there could be MWF courses at 8:00-8:50, 9:00-9:50, 10:00-10:50, and 11:00-11:50 that only allow 3-hour courses. That could cause scheduling nightmares, but it might be enough to make this work, and I have great faith in technology when it comes to scheduling. Computer programs should be building University wide schedules IMO. The way we do it today is silly.

The alternative does not leave Wednesday free at all and looks more like our current schedule. You have TR blocks like those from above on 2-hour increments. You have MWF blocks that have students in class 1:10 each day with 10-minute breaks. 8:00-9:10, 9:20-10:30, 10:40-11:50, 1:00-2:10, 2:20-3:30, 3:40-4:50. (The last two could be modified to MW only to preserve Friday afternoon meeting times.) These six blocks, plus the five from TR give 11 blocks to play with. I still don't know if that will be enough. Going to 4-4 only reduces course offerings by 20-25% even if fully adopted. I am not pushing for complete adoption here. Whether 60% adoption would be sufficient to make the schedule work is not clear to me.

They Better Really be 4-hour Courses
One argument that I have heard for the 4-4 was that students in courses from the humanities and social sciences often need more time to dedicate to a class. I am extremely skeptical of this as my experience is that students wind up spending more time on science and math courses than just about anything else. However, the argument was that when a student gets pressed for time, they skip the reading in the humanities course and do the assignment in the science/math course because they might be able to get by without having done the reading, but they can't get by without turning in something. There might be some truth to that. However, if that is the reason, I don't see the 4-4 being a fix, I see the 4-4 being a path for students to spend less time on academics and more time playing.

If departments do adopt a 4-4, I feel there has to be extreme pressure on the departments and faculty who go that direction to make sure that their courses truly are rigorous enough to warrant four hours of credit.

What do you think? Should Trinity go 4-4? What would be the benefits? What are the shortcomings? What will really happen if we make this transition and only 60% of departments start teaching 4-hour courses?

Open Ended Courses

This blog post describes an idea that occurred to me recently. It was largely prompted by quotes from the creator of KhanAcademy about learning naturally vs. what normally happens in the classroom. Given changes that are happening in the educational marketplace, I feel that schools are going to have to change things to address this. One thought that has occurred to me is the introduction of open ended courses that don't have the normal time restrictions that have been part of the teaching for decades.

Bicycles and Unicycles
The story that Sal Khan likes to use is one of teaching a kid to ride a bike. You don't have a certain day where you test him/her on the bike, and if the student falls you give a D and move on to unicycles. However, that is what we do in classes. I have ~15 weeks to cover a certain amount of material. At certain dates that I pick in advance, I give tests. Based on how much the student has learned by those dates and their ability to communicate that learning on the test, they get an appropriate grade. After that, I move on. Those students who did poorly can redouble their efforts, but they are then left trying to learn what they didn't get down previously along with the new material we are moving into. In Khan's analogy, they are practicing both bicycle and unicycle at the same time.

Is there any way to fix this? I think that the problem comes from two aspects of the current course. The most obvious is that there is a definite time limit, and generally it is a fairly short one. All courses march in this lock step of one semester/quarter to the next with grades given out at the end.

The other part of the problem is that the standard lecture format has a distinct lack of personalization. At a school like Trinity, I get to have classes that are generally in the 10-20 student range. If students choose to, they can spend a lot of time with me outside of class. That is good. That does allow personalization. However, my lectures and tests are universal for all students in a given course. They happen on the same day and cover the same material, regardless of how fast an individual student is moving.

I can make arguments that this isn't a problem. In the "real world" there are deadlines and things have to be done by certain times. However, I still find Khan's analogy to be persuasive and the honest truth is, learning is different from real world application. Should I care so much when a student learns things or should I focus on the fact that the student can learn them?

This has led me to the idea of open ended courses. Students sign up with a professor to learn a certain amount of material. Assessment is done individually. The only end date might be something like the graduation date. Transcripts would probably need to indicate what has been completed as well as what has been signed up for, but not completed. There is no lock step though. Students finish a course whenever they decide they are done and demonstrate as much mastery as they have attained at that time.

Anyone who teaches and is reading this might well say that is an interesting idea, but how do you actually pull it off? In some ways, it just seems impractical. I think the answer to this is demonstrated by what Sal Khan has put together in the KhanAcademy.

Inverted Lectures
Video lectures have been moving into University classes for a while now. There are terms like "inverted lecture" to describe ways of using them. Teachers know that asking students to read books outside of class and show up with the knowledge generally fails. Part of that is because books are so non-dynamic. Video lectures are more dynamic, and they can be paired with automated assessment so that students have an idea of how much they have really learned before trying to move on.

I am working to build a set of these types of lectures for my textbook, "Introduction to the Art of Programming Using Scala". My hope is that by fall 2012 I will have over 100 short lecture videos up at the book website and that I will be able to organize my own courses largely using the inverted lecture format.

I don't think it is a huge step from the inverted lecture format to open ended courses. There can still be meeting times and an intended pace. the meeting times aren't filled with logic, they are filled with application or discussion of material. In my own courses, I intend to present problems and ask students to apply what they have learned to write programs to solve those problems. I will critique their solutions and optimally I would like for students to work in pairs and see code written by other students.

The main hurdle is not delivering content, but assessment. One has to create a method of assessment that students can do when they are ready, on what they are ready to approach. I really believe that the ideal form of assessment in most areas is the oral exam. So I might dedicate several hours each week to giving oral exams. Students could sign up for times in advance and each course would have a certain number of exams that students have to get through to complete the course. In CS it would certainly also be possible to have some automated assessment where students have to write code to solve problems. That type of system could be set up fairly easily and used both for student practice and for formal assessment.

Still Need to Teach
Less anyone thinks that the inverted lecture is a way for faculty to get out of teaching, I can assure you that I will spend several times as much time preparing video lectures as I would delivering lectures in a semester. What makes this different from just pointing students to KhanAcademy or Codecademy is the time spent in class. Faculty become more like learning coaches, especially for courses taken by many students.

For example, anyone who adopts my textbook, inside or outside of Trinity, could use my video lectures. That does remove the burden of content creation from them. Then again, most faculty don't write their own textbooks so that isn't a huge change. The real change is in how they spend their time with students. They can spend it doing things that are more individualized. They can look over what the students are doing and provide feedback individually because they are not spending their time lecturing to students en masse. I also think that they will spend a lot more time on individualized assessment, doing things like oral exams.

No Traction
The one place where I threw the idea of the open ended course out among my peers, it got no traction. Even though it was a group looking to change curricula, it didn't go anywhere. I think it might be a bit too big a departure from the status quo for many to accept. However, given the possibility of an "Education Bubble", I think all ideas should be on the table. In case you aren't familiar with the idea of the education bubble, I'll write another post about that with evidence for and against, as well as my thoughts on what colleges need to do to make sure they aren't destroyed by it bursting.

Of course, one could do just about everything I've described here on a rigid semester schedule. Indeed, I plan to start moving that way next year. However, I think the approach really takes off if it is applied to a large number of classes on a campus, and we do remove the artificial time bounds.

Show me the Money
This has some interesting implications for both colleges and students when it comes to money. Currently students pay for courses. At Trinity a full-time student pays a fixed amount for anywhere between 12 and 18 hours. Taking fewer or more leads to paying per hour of credit. In this open ended course model you don't pay per course. Instead, you pay to be on campus and have access to the resources. Students can go through the curriculum at their own pace, but then it is a matter of cost. Top students might fly through and graduate in two years. Other students take longer. Taking longer is a luxury they would pay for. They will want to focus on subjects they learn more quickly in. If there is a subject a student finds very challenging though, they can go for the minimum grade to get it off their plate or they can push through using more time until they have mastered it for full marks.

What do you think? Should college courses be open ended? What implications do you see that having that I haven't mentioned here?

Modern Automation, Similarities and Differences to the Industrial Revoltuion

Setting the Stage
I write a fair bit in this blog about how technology is disrupting the world, including the role of automation in the economy. Some comment discussions on Google+ and Facebook have led me to some new thoughts comparing and contrasting the current situation with what happened around the 1920-1930s in the US as the industrial revolution automated agriculture. Prior to that time, the majority of the workers in the US worked in the field of agriculture. When automation changed that, it caused serious economic hardship, and it took a significant period of time for people and the economy to adjust.

Things Did Adjust
When you talk about technological unemployment, many economists seem to like to point to the industrial revolution as the classic example of how the disruptions of technology cause temporary pain, but lead to greater overall economic growth. The purpose of this post is to look a bit closer at some features of how that worked, and compare it with the current situation.

The bottom line is that the economists are correct in their statements about the industrial revolution. The economy did adjust to automation and become more robust in the end. However, I think a major part of that adjustment was in the form of education. If you were living in rural America in 1910 (as the majority of Americans did at that time), you probably didn't get past 8th grade if you even made it that far. There simply wasn't a need to. You were going to work on a farm. You probably wouldn't need to read, much less use algebra or trigonometry. What is more, the people you trusted, like your parents, were probably telling you that you would be better off leaving school and starting to develop "real world skills" for those jobs on the farm. They didn't lie to you, that was sound advice is 1910.

Between 1910 and 1930, the industrial revolution moved into agriculture and that advice stopped working. The jobs in agriculture went away. One man with a tractor could do the work of 100 without. As economists love to point out, new jobs were created. Those new jobs were in factories in cities. The problem was, those jobs required a bit more education. You definitely needed reading and there were a growing number that did require algebra and trig. The people designing the machines, and there were a reasonable number of them, required a lot more than that too. So now people needed more education to get the jobs.

Down, But Not Out
People don't learn overnight though. You had a bunch of people from out on the farms who are in the wrong place and have the wrong skills. It takes a while both to move those people and teach them a new skill set. I want to focus on the learning part as that is more my area. It takes a number of years to get a kid from 5th grade level to 8th or 12th grade level. It really isn't faster for adults either. So you have a period where there aren't enough people with the right skills and a lot of people with the wrong ones. It takes time to build a more educated workforce and things sucked in the meantime.

What really sucked was to be one of the last group of kids who were told to drop out and learn to farm in 4th grade only to find a few years later that all the local farms were automated and your skill set wasn't needed anymore. If that was you, you had to put in a lot of effort to build the skills needed for these new jobs. You were down, but you didn't leave school in 4th grade because you were incapable of going further, you left because you were told you didn't need to go further. So with some effort you could gain that knowledge and pick yourself back up.

Changing Advice on Education
The thing is, in 1930, there was a lot of potential in the US public for improving skills through education. Most people were undereducated. They hadn't reached their potential because they didn't need to and were advised against it. Somewhere around the 1950s, kids were being told that they really needed to graduate from High School to find jobs. By the 1980s, you needed to go to college to get a good job. By 2000, college wasn't seen as the key to the good jobs, it was the key to almost every job. We had moved into the information age and High School counselors were telling students that if they didn't get some college they were doomed to lower-end jobs.

One result of this is that the US is probably close to maxed out on education. There are inevitably some things that can happen to help certain students go further. There are definitely things that can be done to make the whole process more efficient. However, I don't think this is an area of huge untapped potential. I don't see any technology that is going to take current High School dropouts and turn them into Ph.D.s in STEM fields.

New Round of Automation
Automation has been ongoing since the beginning of the industrial revolution. We now have a mere 2% of the US population working in agriculture. Automation in factories did to certain segments of manufacturing what the tractor had done to agriculture. However, none of these later moves to automation have had quite the same impact as the automation of agriculture did around 1930, because none of them have hit such a broad segment of the population. Nothing has hit since then with the ability to disrupt 30+% of the population in such a short period of time. Nothing until today that is.

I personally believe we are at the leading edge of a decade that will disrupt the jobs of close to 50% of the population. It isn't a single product like the tractor that will do it. Instead, it is the combination of more capable computer AI software with more functional robotics. The single biggest aspect is that the AI is becoming able to handle the unexpected, and make the robotics work in unpredictable environments. The details of this argument make a whole separate blog post. What I want to focus on here is the impact of this and how society can or can't adapt.

Not a Repeat of the Past
I think the stories from the Occupy movement of people who had degrees and couldn't find jobs are a parallel to the kid in the 1920s who was told to drop out of school and start working the farm. While it is easy to take a condescending view of the 20-somethings who racked up a whole bunch of debt majoring in some field from the Humanities and can't find a job today, doing so is not only non-productive, it really isn't fair. Those kids grew up being told that they should get a college degree in something they loved and that would get them a job. That advice has worked for decades. The people giving the advice didn't lie, they simply didn't have 20/20 foresight into the future. (Something it is impossible to blame people for.)

There is a difference between today's occupiers and the unemployed farm hand of 1930 though, the unemployed farm hand had a lot of untapped potential when it came to education. The youth of today typically don't. Yes, they could go learn something different to give them more desirable skills, but I fear that doesn't scale the same way. Plus, many of these people chose the direction they went because they found that those other areas (which might be better for jobs) didn't work well for them.

Where Does This Leave Us?
So if you buy the argument above, we are hitting another time of significant disruption when large fractions of the US population will be put out of jobs, much like they were 80 years ago when the economy underwent huge change. Unlike 80 years ago, we can't just send them all back to school to further their educations, most people have basically maxed their education potential. This seems like a bleak outlook. What makes it even worse is that I'm not even throwing out the idea that computing power is growing exponentially and that if people do try to retrain, they will have a hard time learning enough of what they need before the AI becomes capable of the job they were training for.

My own thoughts on where this leaves us have changed a fair bit over the last 8 months. In some future blog posts I'll go through a few ideas of things I see as possibilities. The interesting aspect of these possibilities is that many of them are quite positive and lead to people having a better overall life.

Proving the Value of Higher Education

Last year, 2011, a law went into effect requiring colleges and universities to post a cost calculator on their web pages. (http://www.usatoday.com/news/education/story/2011-10-19/college-cost-calculator/50830080/1) The goal being that people planning to go to college should be able to make an informed choice and understand their likely costs. In this blog post I am going to propose another law that goes a step forward.


In many ways, the costs of college have always been fairly transparent. However, I know people in admissions think that the cost calculators could have as big an impact on recruiting as rankings had when they were first introduced. What is far less transparent about college is what you get out on the other end. The What's It Worth? study showed correlations between degrees and earnings across the nation, but modern technology should allow this to go much further. Most importantly here, it should allow us to get measures of what people earn after leaving different schools with different degrees.


I learned about the cost calculator in a meeting of the admissions committee at Trinity University. The cost calculator is a big deal for us because Trinity is not cheap. The standard argument is that a liberal arts education prepares students to go on to very successful lives. What struck me as unfortunate is that we can do little more than provide anecdotes to that effect. While most Universities, including Trinity, have active alumni associations, it simply doesn't fly to ask everyone how much money they make. However, thanks to modern computing technology I think that with very minimal support from the federal government, it would be possible to get that information in a reliable and anonymous way.


The scheme I have in mind relies on the fact that colleges and universities have the Social Security Numbers of their graduates. It also requires that the IRS help out a bit. The colleges would request income information for groups of people. Ideally I see these being groups based on major and years of graduation. The IRS would provide only a median income level for the group, and perhaps quartiles if the group is large.


To preserve anonymity, groups need to have no fewer than 50 people and the IRS need only provide information back if it has data for at least 30 of them. I feel like groups should also include at least one full major for at least a five year window. Smaller schools and smaller majors will need to group things to make the 50 person rule. They might choose to group several related majors or to make windows of 10 years instead of just 5.


Requests for data could only come from accredited institutions, and there would be significant penalties for falsifying anything. That would prevent an institution from putting a single person into more groups than they should be part of to bump thing up. The use of median and quartiles instead of mean is also significant here. The exact levels of income at the top and the bottom are unimportant so a single billionaire can't throw things off.

Of course, this would only track income in the US so it couldn't follow people who go to work abroad. I'm sure there are a number of other possible pitfalls as well. However, it seems to me like a very plausible, low cost way to really show the value, or lack thereof, in the higher education provided by a particular institution. If the federal government is forcing schools to provide cost calculators with the idea of helping to inform and protect the consumer, this seems to me like the next logical step to provide actual information on financial benefit. What is more, the cost to the IRS would be extremely minimal and the cost to colleges and universities should not be all that high either. The information is already being stored in computer systems capable of far more complicated tasks. Even the software required would be simple to write.

What do you think? If you like the idea, suggest it to your US congress people or maybe just send this blog post to WhiteHouse.gov.

My Actor Epiphany

One of the great strengths of Scala is that is contains support for multiple different forms of parallelism. You have access to the Java thread libraries for anything that you want to do at a low level. However, you also have built-in data parallelism through the parallel collections and support for the actor model as well. At a certain level, the actor model is fairly simple, an actor is like an object that can have a thread associated with it so that different actors can be doing things at the same time. It was a model that I had imagined using without really knowing about it. However, having a description of something isn't the same as really understanding it. A few weeks ago, while working on project descriptions for my book, the real implications finally clicked.

Before going into the details of the moment of epiphany, let's dig a bit deeper into the actor model. With normal objects, you make the object do something by calling a method. For actors, you send a message. The syntax can be similar, and they sound very similar, but there is a huge difference in semantics. When you call a method on an object, the current thread moves over to run the code in that method. When you send a message to an actor, the current thread stays with the current actor. The message will be processed by another thread. Typically, messages do not have "return values." They can, but this impairs the parallelism so you want to avoid it is possible. The message gets placed on a queue for the actor and that actor will get to the message in the order of the messages it has received. If a response is needed, a message can be sent back to the original actor.

To make the actor model work, one of the key aspects is that if you are going to have mutable data, it exists in a single actor. You never allow two separate actors to mutate the same data at the same time. That way you avoid race conditions. In Scala this is often done by making sure that all messages are immutable and you never call methods on other actors. Actors only interact by sending immutable messages (typically case classes).

This was all in my head, and it all made sense. However, I can say that I didn't really grok it until I started picturing the MUD project using actors. For those who are not old enough or weren't geeky enough when they were younger, a MUD (Multi-User Dungeon) is multi-user text-based RPG. Normally a MUD was pretty hack-and-slash. There were other things like MOOs that were more about the role-playing part. Think of World of Warcraft with text instead of graphics.

The normal object-decomposition of a MUD has characters, rooms, items. Characters move between rooms and pick up items. The simplest implementation of this uses one thread to handle the networking part of logging in and a second thread to run the game loop. You keep a sequence of characters and run through them. You could also have a priority queue and use events for scheduling. The bottom line of this approach is that it has one very busy thread and one thread that is mostly asleep. It does not scale up.

So my naive thought on making it actor based was to make the characters into actors. After all, they are the things moving around and doing stuff. If they are actors, they each get their own thread and things start happening in parallel. There is only one problem, what happens when two players do something at the same time that deals with the room they are in? For example, they both go to pick up the same object at the same time. That is a classic race condition. Now, it really isn't a problem when one character or the other gets the item. In fact, threads are probably more fair than the normal loop where the order of the sequence will determine who actually gets the item. The problem is that if you make normal method calls on the room, then you can have a situation where both characters get the item because the race condition overlaps the activities. That is not acceptable. Putting in standard synchronization seems the wrong way to go. Actors are supposed to have to prevent you from doing that.

The answer is, of course, very simple. make the rooms into actors as well. This isn't mind blowing, but when the full implications sunk in for me, it really helped me see how the actor model works in general. Now when two characters go to pick up the same items, they send messages to the room. Those messages get queued in a particular order. When the first is handled, it removes the item from the room and sends a message back to that character saying they got the item. When the second message is handled, it finds that item is no longer present and sends back a message to that effect. The end result is exactly what we want. All threading problems go away and the system can now scale to very high concurrency. The key idea here is that you need to broaden the image of what should be an actor. Actors are not just the things that are active. They are also anything that might be acted upon by two actors at once.

I'm still trying to figure out if I can do rings simulations using actors. Perhaps I'll try that some this summer using Akka 2.0. If I find anything that works, I will definitely blog on it.