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:
- 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.