We Need an Economic Study on Lost Productivity from Poor Computing Education

March 19, 2013 at 1:27 am 11 comments

How much does it cost the American economy that most American workers are not computer literate?  How much would be saved if all students were taught computer science?

These questions occurred to me when trying to explain why we need ubiquitous computing education.  I am not an economist, so I do not know how to measure the costs of lost productivity. I imagine that the methods would be similar to those used in measuring the Productivity Paradox.

We do have evidence that there are costs associated with people not understanding computing:

  • We know from Scaffidi, Shaw, and Myers that there are a great many end-user programmers in the United States.  Brian Dorn’s research on graphic designers identified examples of lost productivity because of self-taught programming knowledge.  Brian’s participants did useless Google searches like “javascript <variablename>” because they didn’t know which variable or function names were meaningful and which were arbitrary.  Brian saw one participant spend a half an hour studying a Web resource on Java, before Brian pointed out that he was programming in Javascript which was a different language.  I bet that many end-users flail like this — what’s the cost of that exploration time?
  • Erika Poole documented participants failing at simple tasks (like editing Wikipedia pages) because they didn’t understand basic computing ideas like IP addresses.  Her participants gave up on tasks and rebooted their computer, because they were afraid that someone would record their IP address.  How much time is lost because users take action out of ignorance of basic computing concepts?

We typically argue for “Computing for All” as part of a jobs argument. That’s what Code.org is arguing, when they talk about the huge gap between those who are majoring in computing and the vast number of jobs that need people who know computing.  It’s part of the Computing in the Core argument, too.  It’s a good argument, and a strong case, but it’s missing a bigger issue.  Everyday people need computing knowledge, even if they are not professional software developers.  What is the cost for not having that knowledge?

Now, I expect Mike Byrne (and other readers who push back in interesting ways on my “Computing for Everyone” shtick) to point out that people also need to know about probability and statistics (for example), and there may be a greater cost for not understanding those topics.  I agree, but I am even harder pressed to imagine how to measure that.  One uses knowledge of probability and statistics all the time (e.g., when deciding whether to bring your umbrella to work, and whether you can go another 10K miles on your current tires). How do you identify (a) all the times you need that knowledge and (b) all the times you make a bad prediction because you don’t have the right knowledge?  There is also a question of whether having the knowledge would change your decision-making, or whether you would still be predictably irrational.  Can I teach you probability and statistics in such a way that it can influence your everyday decision making?  Will you transfer that knowledge?  I’m pretty sure that once you know IP addresses and that Java is not the same as JavaScript, you won’t forget those definitions — you don’t need far-transfer for that to be useful.  While it is a bit of a “drunk under the streetlight” argument, I can characterize the behaviors where computing knowledge would be useful and when there are costs for not having that knowledge, as in Brian and Erika’s work.  I am trying to address problems that I have some idea of how to address.

Consider this a call to economics researchers: How do we measure the lost productivity from computing illiteracy?

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11 Comments Add your own

  • 1. Seth Chaiken  |  March 19, 2013 at 10:14 am

    These anecdotes about people wasting time are interesting to start with, but to analyze economic productivity, one needs data about the long term efficiency of workers after they are habituated to their tasks. When someone is required by their supervisor to take on a new IT task, one would expect that, perhaps after the floundering that the Google searches are evidence of, the worker’s need for training will become apparent and the supervisor will bring in a trainer. The training might be just rote, but will make the worker productive until the next new assignment comes along.

    Reply
  • […]  People know even less about computing than they do about finance.  We don’t know the costs are of that ignorance, but we do know that it has been difficult and expensive to provide enough education to correct […]

    Reply
  • […] for CS in schools, including this NPR piece.  I believe that the strongest argument is that most professions need computing, so it makes sense to build up that literacy.  But it’s a hard argument to sell, and we keep […]

    Reply
  • […] Influence countries’ economic competitiveness.  There might be a stronger argument here.  Elementary school is about general literacy.  There is likely an economic cost to computing illiteracy. […]

    Reply
  • […] of how the cloud works and how other digital technology in their world works.  Applications purposefully hide the underlying technology. Coding is a way of reaching a level lower, the level at which we want students to understand. In […]

    Reply
  • […] My colleague, Amy Bruckman, wrote a blog post about the challenges that nonprofits face when trying to develop and maintain software.  She concludes with an interesting argument for computing education that has nothing to do with learning programming that everyone needs.  I think it relates to my question: What is the productivity cost of not understanding computing? (See post here.) […]

    Reply
  • […] that it’s not really that big of a deal if Wikipedia stores your IP address (see story about Erika Poole’s research).  There is evidence that learning one programming language will likely transfer to another one […]

    Reply
  • […] this is another example of the productivity costs of a lack of ubiquitous computing literacy (see my call for a study of the productivity costs).  We spend a lot on technology in schools.  If teachers learned more about computing, they […]

    Reply
  • […] in the non-CS majors, the ones who learn computing because it makes them more productive (see where I make that argument) or because they want to make themselves more marketable (see Eric Robert’s post) or because […]

    Reply
  • 11. Michole Washington  |  September 12, 2019 at 2:50 pm

    I ask for caution when pushing anything as “ubiquitous” or “for all” as it is hardly ever that. Historically, every “for all” movement has been cruxed by the ingenuity of those in power.

    For example, around the 19th century when White Southerners’ were against universal schooling for Blacks they would enforce anti-literacy laws with harsh consequences. HOWEVER, there were also some laws stating that slaves could learn basic arithmetic just so that they can fulfill roles such as carpenter or dressmaker. There was an interest-convergence. It was to the benefit of slave masters to permit slaves’ limited access to basic mathematics as long as it was not evolve into a threat to their power (where actually it did, but that has been an up and down battle for decades now).

    This issue of interest-convergence is still seen in present day with issues such as tracking where students’ non-academic characteristics (e.g. race) are just as good of predictors of math track placement as their previous academic achievement. Then once they are in a track they are stuck doing the same redundant calculations with the same unmotivated teachers. Those with less power (i.e. underestimated groups) are butted with the low-hanging fruit that is replaceable by a basic battery-operated calculator.

    So I want to squeeze somewhere in this post just a very strong push for accessible culturally relevant computer science alongside the ubiquitous. Which I think ironically contributes a nice additional layer to your question: How do we measure the lost productivity from barriers mediating computing illiteracy?

    (can supply citations upon request)

    Reply

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