Posts tagged ‘economics’
Disturbing but fascinating piece linked below that suggests that the “super efficient” meritocracy of the United States quickly sorts out those with talent, who then marry each other, and over time, the gap between the upper classes and the lower classes becomes more than just opportunity. The suggestion in this interview is that schools can’t really do much to fill in that gap. The piece by Roschelle et al that I mentioned a few weeks ago suggests that schools can help the lower-performing groups improve their performance, but there is some question as to whether schools can really bridge the gap, or will the better-performing students just accelerate even more than the lower-performing?
And is that school’s jobs at all? On my way out of Heathrow last Sunday morning, I read a news piece and an op-ed in The Telegraph, outraged that schools were accepting poorer children who did not have the grades to get in on their own. Explicitly, the heading complained that the schools were engaged in “social engineering.” In the US, we do talk about education as a leg-up, a way of enhancing social mobility. But maybe that’s not a necessary role for school, and Murray would argue, school can’t achieve that goal anyway.
But this assumes that academic ability—whether defined as intelligence, or non-cognitive skills and character traits, or whatever else—is randomly distributed across the population. Which, Murray argues, was probably once true but is no longer. Because of the ferocious sorting of the meritocratic machine, talented people have been finding and marrying one another, and giving birth to a super-class of highly gifted children. (Murray said at our event that it “doesn’t matter” whether these gifts are bequeathed by nature or nurture. What matters is the strong link between the talents of parents and the talents of their offspring.) And, as David Brooks pointed out today, after years of bedtime stories, trips to the zoo, vocabulary-packed conversations, and other “enrichment” activities, these children enter school miles ahead of the rest of their peers—including the poor kids that are the focus of so many education reforms.
Of course, as Murray says, this phenomenon plays out in terms of group averages. If we live in a meritocracy where intelligence and other talents lead to success,* then the children of the highly successful (the Elite) will, on average, be more talented than the children of the somewhat successful, who will, on average, be more talented that the children of the not successful (i.e., the children of the poor). On average.
Understandably, we don’t much like to discuss this possibility. It gives cover to educators who look at a classroom of low-income children and diminish their expectations—thinking that “these kids” aren’t capable of much, educators who don’t buy the mantra that “all children can learn.” But would we be shocked to find that the average intelligence level of such a classroom is lower than a classroom in an elite, affluent suburb?
Most of the computing education research papers and proposals that I read make an economic justification for the work. Sometimes the work is a response to “Rising above the Gathering Storm (RAGS),” and the goal is to generate more computing innovation to improve national competitiveness. Maybe the concern is that our modern economy needs more and better computing workers to fuel our information-driven businesses, so we are exploring novel curricula to create better learning. Maybe we want to have greater representation for women and under-represented minorities in order to provide great economic impact, so we strive to improve student attitudes about and engagement with computing among middle and high school students. I’ve made all of these arguments myself.
I recently read “Eight issues for learning scientists about education and the economy” (Journal of the Learning Sciences, 20(1), 3-49, Jan 2011) by Jeremy Roschelle, Marianne Bakia, Yukie Toyama, and Charles Patton. It has dramatically impacted my perception of these issues. Jeremy and his colleagues dive into the economic literature, to understand the education research impact that economists can actually support. The result helps me to think about why we do what we do.
To start with, economists have found that education researchers’ overall impact on the economy appears to be bounded. For example, 1/3 of all new jobs predicted by the BLS from 2006-2016 do not require formal education. Instead, they “are projected to fall into the short-term on-the-job training category.” 40% of all job openings require less than one month of on-the-job training. Most of those aren’t STEM jobs. A 2006 study “found a relatively small positive association between math and science academic achievement and economic growth.” Later studies (in 2007 and 2008) reanalyzed the data with varying results, but found that statistically significant results “which are most plausible with a 15-year time lag between educational improvement and economic benefits.” So pushing for better STEM (with Computing in there) learning might have an impact on the economy, but we won’t see it for 15 years.
Part of the problem here is confounded variables. If you have a nation-state with a strong interest in developmental policies, and the political will and economic might to put those policies into place, then good things are going to happen to the economy anyway — and far sooner than 15 years.
Let’s consider the competitiveness angle, which comes up often in computing education research. There is certainly evidence that the United States test scores ranks far behind countries like Finland and Singapore. But Roschelle et al. present evidence that the US is producing enough top scientists and engineers to support innovation, and the US’s poor showing is more a factor of size than of educational quality. “Furthermore, in the United States, is is possible to find regions the size of Singapore and Finland that also score as well as Singapore and Finland (Guarino, 2008; SciMathMN, 2008).” Our bigger challenge is to reduce the variance in scores, which is the real reason for the low overall international performance. They argue that reducing inequities in education “is good for equipping all students for not only better access to valued jobs in a knowledge economy but also for democratic participation.” If you want to make the US more competitive in terms of international test scores, then don’t worry about the overall test score average — bring the bottom up, and the average will take care of itself. However, test scores may not actually have anything to economic competitiveness, because the economists that Roschelle et al. cite don’t really believe RAGS. We have enough top engineers and scientists, and the economy shows few signs of needing more. The US innovation engine is doing just fine. In fact, Roschelle et al. point out that Singapore sends delegations to the US to figure out what we’re doing right.
The part that most influenced my thinking was Roschelle et al.’s analysis of the STEM pipeline. We imagine a pipeline where:
- We modernize curriculum and pedagogy in K-12 which results in better prepared students and greater interest in STEM disciplines;
- These students then achieve more in STEM and pursue undergraduate degrees;
- Graduates with STEM degrees become scientists and engineers in the labor and academic force;
- Which results in greater national economic development.
Roschelle et al. consider each phase of the pipeline:
- Yes, better K-12 curriculum does lead to better student achievement. Teacher quality, however, may play an even larger role, and the distribution of high-quality teachers is uneven and inequitable. There is far more research effort in curriculum than teacher professional development. But even if you can improve all three of curriculum, pedagogy, and teacher quality, the results are surprisingly short lived because it’s a staged pathway, and the stages don’t communicate. (I’m reminded of Alan’s quote, “You can fix a clock, but you have to negotiate with a system.”) “This may be because credentials, not specific higher order abilities, get students into university, and once students are there professors expect only traditional textbook learning (and correspondingly do not leverage what students have learned from more progressive curricula).” (Italics were in original.) In other words: If you were in some terrific new 4th grade curriculum where you learned to do inquiry-based learning, that might raise your test scores that year, but you’ll get into college based on your SAT and ACT scores, and your university prof won’t assume you know how to do inquiry-based learning.
- This next part was quite surprising to me: Increasing student interest and achievement doesn’t change undergraduate STEM enrollment. “Lowell and Salzman (2007) found that although American high school students’ exposure to math and science has increased and their standardized test scores have increased over time, their interest in pursuing science and engineering majors has been stable…In other words, even with 20 years of steady improvements at the K-12 level, no increase occurred in the percentage of university students interested in majoring in STEM fields.” (p. 23) Despite our concerns about low scores, the references in Roschelle et al. say that the slope is upward. My guess is that improving interest and achievement is necessary, but not sufficient for undergraduate STEM enrollment. If students don’t understand science and they hate it, they won’t major in it. But loving STEM or computing doesn’t mean you want a career in it. Bigger factors preventing greater undergraduate STEM degree production are poor quality college STEM education (“e.g., large, lecture-based, fast-paced classes”) and poor access to high school “gatekeeper” courses. “Finishing a course beyond Algebra II, such as trigonometry or calculus, in high school more than doubled the probability that college-enrolled students would obtain their bachelor’s degree (Adelman, 1999.)” Getting more of those courses available involves (in part) fixing the problem of access to high-quality teachers.
- Surprisingly many students who graduate with STEM degrees don’t stick with STEM jobs. Within 4 years, 27% of science and engineering bachelors have moved on to unrelated jobs, and the percentage increases each year.
Overall, though, Roschelle et al. tell a story in favor of the importance of computing education research. Being able to use computing “in sense making” and for “information literacy” are on several education and economics groups’ lists of 21st century skills. Learning how to measure and improve those skills are among the top recommendations of their paper. And while the pipeline is not nearly as connected as we might like, it’s possible to have long term effects. For example, the Perry Preschool Program had dramatic effects on its participant, through Age 27.
Richard Hake had a related post recently. Why do we want to educate children and improve education overall? Hake argues with Roschelle et al. that competitiveness is not an important enough driver, and maybe there are even bigger issues than economics that we should be aiming toward.
Ravitch wrote: “. . . .the nation forgot that education has a greater purpose than preparing our children to compete in the global economy.” I agree with Coles and Ravitch that “global competitiveness” should not be the main driver of education reform. In a discussion list post “Is the ‘Skills Slowdown’ the Biggest Issue Facing the Nation?” at <http://bit.ly/9kIHAW>, I countered David Brooks’ claim <http://nyti.ms/LfJp1K> that it was, arguing the “Threat to Life on Planet Earth” was the biggest issue facing the nation. Likewise, I think the “Threat to Life on Planet Earth” and NOT “global competitiveness” should be the main driver of education reform.
I learned from reading the Roschelle et al. paper that it is hard for computing education research to impact the overall economy, but as Hake is pointing out, too — there are more important goals for us. People need computing skills in the 21st century. Our skills can help the individuals at the bottom half of the economy become more marketable and raise their economic status (and those of their children), but more importantly, computing skills can make them better citizens in a democracy (e.g., maybe as critical thinkers, or as people who know how to explore and test claims in the newspaper and made by politicians). We do need more and better curriculum, because that does have an achievement impact, but we have a greater need to produce more and better teachers.
Low-income students and schools are getting better, according to this study. They’re just getting better so much more slowly than the wealthy students and schools. Both are getting better incrementally (both moving in the right direction), but each increment is bigger for the rich (acceleration favors the rich).
We heard something similar from Michael Lach last week. The NSF CE21 program organized a workshop for all the CS10K efforts focused on teacher professional development. It was led by Iris Weiss who runs one of the largest education research evaluation companies. Michael was one of our invited speakers, on the issue of scaling. Michael has been involved in Chicago Public Schools for years, and just recently from a stint at the Department of Education. He told us about his efforts to improve reading, math, and science scores through a focus on teacher professional development. It really worked, for both the K-8 and high school levels. Both high-SES (socioeconomic status) and low-SES students improved compared to control groups. But the gap didn’t get smaller.
Despite public policy and institutional efforts such as need-blind financial aid and no-loan policies designed to attract and enroll more low-income students, such students are still more likely to wind up at a community college or noncompetitive four-year institution than at an elite university, whether a member of the Ivy League or a state flagship.The study, “Running in Place: Low-Income Students and the Dynamics of Higher Education Stratification,” will be published next month in Educational Evaluation and Policy Analysis, but an abstract is already available on the journal’s website.“I think [selective colleges] very much want to bring in students who are low-income, for the most part,” said Michael N. Bastedo, the study’s lead author and an associate professor of higher education at the University of Michigan. “The problem is, over time, the distance between academic credentials for wealthy students and low-income students is getting longer and longer…. They’re no longer seen as competitive, and that’s despite the fact that low-income students are rising in their own academic achievement.”
I looked up Justin Reich based on Betsy DiSalvo’s comment last week. Justin argues that the affluent benefit more from free and open learning technologies (like WikiSpaces) than do lower socioeconomic class students, so free and open learning technologies actually widen the gap, more than shrink it. His video op-ed, linked below, makes this case with data based on use of WikiSpaces, showing that lower socioeconomic schools have less capacity to pick up and use these technologies.
But what to do? I liked both of the initiatives that Justin mentions, but I was disappointed that both of them are outside school. His study is on school use, but his recommendations are for out-of-school use. Is there nothing we can do in poorer schools to make things better?
The NYTimes had an article on Saturday on “Computer Science for the Rest of Us” which was all about broad introductory computing classes at the college level. I exchanged email with the author before the column came out, pointing out several sources and mentioning Media Computation. Randy felt that Georgia Tech’s experience with computing for everyone was less compelling, because Georgia Tech is an “engineering school.” He said that he was more interested in programs that cater to humanities majors — which is what MediaComp is, because we developed it to reach Liberal Arts, Architecture, and Management majors.
More interesting is the whole section of The Guardian focused on computing education. I learned about it from Nick Falkner’s post on CS as a fundamental 21st century skill, and then from other readers who forwarded me the link — thanks! I was most impressed by the open letter to the UK Secretary of State for Education, Michael Gove, “A manifesto for teaching computer science in the 21st century.” John Naughton really gets why CS in K-12 matters, and understands (better than most programmers) that teaching computing is not about threatening the programmer elites.
[T]hey are not the most important justification, which is that in a world shaped and dependent on networking technology, an understanding of computing is essential for informed citizenship.
3. We believe every child should have the opportunity to learn computer science, from primary school up to and including further education. We teach elementary physics to every child, not primarily to train physicists but because each of them lives in a world governed by physical systems. In the same way, every child should learn some computer science from an early age because they live in a world in which computation is ubiquitous. A crucial minority will go on to become the engineers and entrepreneurs who drive the digital economy, so there is a complementary economic motivation for transforming the curriculum.
A rather provocative title from the Jezebel site leads to some interesting statistics. If you follow the link to the NYTimes site, you find that CS still has men paid 2% more than women. IT is the winner, where women make more than men. What I find it interesting that few women choose IT for a career, despite the obvious economic advantages: Lots of jobs, high-paying jobs, and jobs where women get paid better than men. That suggests that decision away from IT is not an economic one — there are other factors at play.
According to the Times’ Catherine Rampell, it looks like a woman’s choice of college major may determine her future income equality. Rampell analyzed information provided by salary data-collecting company PayScale and found that a surprising number of majors actually eliminate much of the discrepancy between male and female pay. Women who majored in Mechanical Engineering or Management Information Systems, for example, earn identical salaries to their male counterparts, even when controlled for demographic differences. Women who studied Electrical Engineering, Civil Engineering, Communications, English, Sociology, Graphic Design, or Psychology earn only 1% less than men doing the same job. And women who studied Information Technology in undergrad and didn’t go to grad school actually outearn similarly educated men by 1%.
I don’t understand the claim of this study, which makes it hard for me to believe it. I can sort of see how it’s possible that average taxpayers are providing subsidies to elite public schools. While the state contribution to elite state universities are decreasing, because the elites are so much more expensive, they probably still take a larger part of state taxpayer dollars than other institutions in the state. But elite private schools? How? Through Pell Grants and other federal programs? How can that be more than the non-profits and middles?
An October study by the American Enterprise Institute (AEI) entitled “Cheap for Whom?” showed one way that the university system is rigged in favor of the rich. It said: “Average taxpayers provide more in subsidies to elite public and private schools than to the less competitive schools where their own children are likely being educated…. Among not-for-profit institutions, the amount of taxpayer subsidies hovers between $1,000 and $2,000 per student per year until we turn to the most selective institutions . . . Among these already well-endowed institutions, the taxpayer subsidy jumps substantially to more than $13,000 per student per year.”
I found the article below in this summer’s Harvard Education Letter, then had to hunt to find the reference US Department of Education report. It’s a meta-analysis that came out in October 2010. They do find that online plus face-to-face seems to be the best combination for student learning: The meta-analysis found that, on average, students in online learning conditions performed modestly better than those receiving face-to-face instruction. The difference between student outcomes for online and face-to-face classes…was larger in those studies contrasting conditions that blended elements of online and face-to-face instruction with conditions taught entirely face-to-face. The Harvard piece is pointing out that that’s changing the online schools’ practice. In times of rising higher-education costs, that probably should be changing brick-and-mortar institutions’ practice, too.
Fast forward to 2011. Connections Academy operates in more than 20 states and serves more than 30,000 students. And it’s not alone. In just one decade, virtual learning has exploded, with two massive statewide full-time virtual schools in Florida and North Carolina, and more on the way.
But just as online learning is taking off, new research is finding that it may not be the most effective way to teach children, and virtual companies have begun to see that a purely virtual approach has its limits.
A key report put out by the U.S. Department of Education in September 2010 demonstrated that a blend of face-to-face instruction and online learning produced the greatest academic gains. Now, not only are traditional schools looking for more online options, but virtual schools in turn are adding bits of brick and mortar to their offerings.
Interesting set of studies that argue that US teachers work a lot, but aren’t so productive (in terms of student achievement). How could more of teachers not correlate with better students? An interesting argument here suggests that the low salaries of US teachers are at fault. Are we attracting the most productive possible teachers?
Among 27 member nations tracked by the Organization for Economic Cooperation and Development, U.S. teachers work the longest hours, the Wall Street Journal reports. This seems particularly impressive as the U.S. has long summer vacations, and primary-school teachers only spent 36 weeks a year in the classroom, among the lowest of the countries tracked. Yet the educators spent 1,097 hours a year teaching, in the most recent numbers from 2008. New Zealand, in second place at 985 hours, had schools open for 39 weeks a year. The OECD average is 786 hours…
One conclusion to be drawn from this is, as the Journal writes, “American teachers are the most productive among major developed countries.” But it also notes that “student achievement in the U.S. remains average in reading and science and slightly below average in math when compared to other nations in a separate OECD report.”…
There is something strange about this finding that countries where the teachers work fewer hours produce better educated students. Although the Journal does not address this in its article, the issue is energetically taken up elsewhere. To some it is a salary issue. Business Insider reported that in comparison to other developed countries, American educators work the most hours of all industrialized nations, but are the fifth lowest paid after 15 years on the job. Finland, the company ranked highest in international tests, has teachers that work the fifth fewest hours, and are the ninth lowest paid.
Thanks to Barry Brown for the link! The graphs in these articles really tell the story — highly recommended perusing:
What accounts for the higher G.P.A.’s over the last few decades?
The authors don’t attribute steep grade inflation to higher-quality or harder-working students. In fact, one recent study found that students spend significantly less time studying today than they did in the past.
Rather, the researchers argue that grade inflation began picking in the 1960s and 1970s probably because professors were reluctant to give students D’s and F’s. After all, poor grades could land young men in Vietnam.
They then attribute the rapid rise in grade inflation in the last couple of decades to a more “consumer-based approach” to education, which they say “has created both external and internal incentives for the faculty to grade more generously.” More generous grading can produce better instructor reviews, for example, and can help students be more competitive candidates for graduate schools and the job market.
This is exactly the problem that Alan Collins was describing in his AERA talk this last Spring. The Internet is deeply divided along economic lines. His concern was that open learning created opportunities for the rich but not the poor, and removed the “compulsory” subjects that created a sense of civic duty.
A study from the University of California, Berkeley, suggests the social Web is becoming more of a playground for the affluent and the well-educated than a true digital democracy.
Despite the proliferation of social media — and recent focus on sites like Twitter and Facebook playing pivotal roles in such pro-democracy movements as the Arab Spring — most blogs, Web sites and video-sharing sites represent the perspectives of college-educated, Web 2.0-savvy affluent users, a UC Berkeley release said Tuesday.
“Having Internet access is not enough. Even among people online, those who are digital producers are much more likely to have higher incomes and educational levels,” said Jen Schradie, a doctoral candidate in sociology at UC Berkeley and author of the study.
This makes economic sense. The rising value of the CS degree does lead to the ability to charge more for the CS degree, though that raises the possibility that students may avoid CS to avoid the additional cost.
I am most interested in carrying this idea through to high school, on the supply side. If we’re going to charge more for CS education, we ought to be able to pay high school CS teachers more, because what they are teaching has such high economic value. Raising CS teacher’s salaries would improve our odds of competing with industry. If you know enough to teach Java in AP CS, you also know enough to get a better paying job than teaching high school. We can never truly compete with industry salaries, but we can make high school teaching more economically attractive.
With a hot market for their skills and employers who offer top-notch salaries and benefits, should computer science students pay more for their bachelor’s degree than theater or history majors? In Washington state, the answer could soon be yes.
I’ve heard the argument that the Bayh-Doyle act was the downfall of undergraduate education in America. By allowing universities to keep the intellectual property rights to sponsored research, an enormous incentive was created for universities to push faculty into research, and away from education. A recent Supreme Court ruling may have placed a limit on the Bayh-Doyle Act, by ruling that an individual researcher’s rights supersede the university’s. The New York Times editorial linked below is disappointed by this ruling, predicting increased tension between universities and faculty.
Looking for a silver lining, I wonder if this ruling might not create the opportunity to get back to education. Rich DeMillo continues to point out in his blog how research is a losing proposition for universities. Could this ruling reduce the incentive for universities to push research, by raising the costs (and lowering the potential benefits) of faculty research? (Rich’s latest blog post on the point directly addresses the nay-sayers who say that research only makes money for universities – a recommended and compelling read.)
Although the decision is based on a literal reading of a poorly drafted initial agreement between Stanford and the researcher, it is likely to have a broader effect. It could change the culture of research universities by requiring them to be far more vigilant in obtaining ironclad assignments from faculty members and monitoring any contracts between researchers and private companies. Relationships between the university and its faculty are likely to become more legalistic and more mercantile. By stressing “the general rule that rights in an invention belong to the inventor,” the majority opinion of Chief Justice John Roberts Jr. romanticizes the role of the solo inventor. It fails to acknowledge the Bayh-Dole Act’s importance in fostering collaborative enterprises and its substantial benefit to the American economy.
This recent article in Slate addresses an old problem in economics: Why hasn’t the computer led to a dramatically new economy? Why hasn’t it led to a boost in productivity? A new book on The Great Stagnation suggests that the American economy hasn’t faltered — rather, the American boom in previous years was due to “low-hanging fruit,” and all of that is gone now. What I’m more interested in is what The Great Stagnation and another recent book The Lights in the Tunnel: Automation, Accelerating Technology and the Economy of the Future suggest about the role of technology in the future economy.
In general, it’s not a pretty picture. Their idea is that computers replaced physical labor, and now are taking on more cognitive labor. For example, in the future, you won’t need as many legal clerks, because a law-aware version of Web search will do the job so much better. These economists argue that our ability to create new jobs won’t grow as quickly as technology’s ability to take over jobs, and with relatively few people creating the job-stripping technology — these economists argue that it doesn’t take many programmers to serve the needs of the IT industry. Thus, these economists predict a future world with 30% unemployment.
I wonder what role computing education might play in the productivity paradox and in these future visions of the technology and economy. I’m not arguing that bad computing education is causing the productivity paradox — rather, I wonder what role that better computing education could play in improving productivity with computing, in ways that computers can’t take over. Alan Kay has argued many times that the real computer revolution hasn’t happened yet. We use very little of the computer’s potential in our daily lives. Certainly, part of the problem there is the lack of enough good, usable software that taps into the real power of the computer (e.g., other than what-if games on Excel, what everyday-usable software has people building models and simulations?). Another way to look at the problem is that maybe we haven’t taught people how to use the computer well. In our computer science courses, we focus so much on how to build scalable, robust software that meets others needs, but we spend relatively little time on how to write small, throw-away programs that meet our needs — and maybe those little bits of programs would lead to a major productivity boost (especially if the languages were better suited to meet those needs, e.g., not public static void main(String args)). I’ll bet that learning to write those little, useful bits of code would lead to transferable learning that could have a major boost in productivity. Employees who know how to use more of the computer’s potential, without waiting for the next release of Microsoft Office, may be employees who keep their jobs.
Could it be that economists have found no productivity boon in the printing press is because there was too little literacy when the press was first created? The press created a reason to become literate, and that literacy led to a productivity boost. Similarly, the computer may create a reason to become computationally literate (maybe even more mathematically literate), and those new literacies could lead to a major productivity boom — but maybe not for another 100 years, as education and society changes.
Consider the case of Gutenberg’s printing press. Though the technology radically transformed how people recorded and transmitted news and information, economists have failed to find evidence it sped up per-capita income or GDP growth in the 15th and 16th centuries.
At one point, some economists thought that an Internet-driven golden age might have finally arrived in the late 1990s. Between 1995 and 1999, productivity growth rates actually exceeded those during the boom from 1913 to 1972—perhaps meaning the Web and computing had finally brought about a “New Economy.” But that high-growth period faded quickly. And some studies found the gains during those years were not as impressive or widespread as initially thought. Robert Gordon, a professor of economics at Northwestern, for instance, has found that computers and the Internet mostly helped boost productivity in durable goods manufacturing—that is, the production of things like computers and semiconductors. “Our central theme is that computers and the Internet do not measure up to the Great Inventions of the late nineteenth and early twentieth century, and in this do not merit the label of Industrial Revolution,” he wrote.
Gordon’s work leads to another theory, one espoused by Cowen himself. Perhaps the Internet is just not as revolutionary as we think it is. Sure, people might derive endless pleasure from it—its tendency to improve people’s quality of life is undeniable. And sure, it might have revolutionized how we find, buy, and sell goods and services. But that still does not necessarily mean it is as transformative of an economy as, say, railroads were.
That is in part because the Internet and computers tend to push costs toward zero, and have the capacity to reduce the need for labor.
Interesting piece by Nobel prize-winning economist Paul Krugman. Read all the way to the bottom where he points out that just giving workers degrees won’t restore middle class society. Krugman’s argument makes sense, but he makes the same mistake that most education administrators make. The real advantage to the individual of computing is not in using computers. That doesn’t require any particular education, as Krugman points out.
Krugman misses that the economic advantage goes to those who know how to create with computing. Those who can program (which does require education) have (a) an advantage which enables innovation and (b) the ability to marshal the resources of what used to take many human laborers, thus increasing productivity.
Why is this happening? The belief that education is becoming ever more important rests on the plausible-sounding notion that advances in technology increase job opportunities for those who work with information — loosely speaking, that computers help those who work with their minds, while hurting those who work with their hands.
Some years ago, however, the economists David Autor, Frank Levy and Richard Murnane argued that this was the wrong way to think about it. Computers, they pointed out, excel at routine tasks, “cognitive and manual tasks that can be accomplished by following explicit rules.” Therefore, any routine task — a category that includes many white-collar, nonmanual jobs — is in the firing line. Conversely, jobs that can’t be carried out by following explicit rules — a category that includes many kinds of manual labor, from truck drivers to janitors — will tend to grow even in the face of technological progress.