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"Many teachers may already be teaching these skills."
Russ Abbott's profile photoBarry Kort's profile photoJames Salsman's profile photo
I would give this video a - if I could. It is not about computational thinking. It is broadly about how computers and the Internet are changing the world. It's not wrong in that regard -- although it's superficial. But to call what they say here computational thinking is very misleading.

Most people are able to understand the concepts in this video. Computational thinking involves being able to develop software at some level or another. It requires a special way of thinking to do that. Most people can't seem to think in that way--at least not intuitively. Teaching everyone what it means to write software may or may not be possible. The dream of teaching computational thinking is to do just that. It is still an open question whether that will succeed. As it stands most teachers are not competent in computational thinking.
+Russ Abbott one particular instance of computational thinking we need to solve is the payback for tuition subsidy as suggested by the second paragraph and graph at

Here's a law review article on the laws that established California's public universities in 1973:
Here is some related mathematics:
Here is a very brief summary of some subset of related points:

cc +Barry Kort also I want to cc +Baratunde Thurston because his name came up when I tried to +-mention Barry and I am fascinated by his opinion on this question: how much do the taxpayers get for each $1 invested in tuition? (Less and less if the colleges and universities keep hiking tuition ahead of inflation, and that might be much if not most of the real problem right there.)
Very interesting papers. (I didn't real them through thoroughly.) I like the approach. It would be very useful if the Congressional Budget office scored government spending in those terms. Investment in infrastructure would presumably result in a net positive return over 10 years. To make that widely acceptable, though, would require very rigorous studies and analysis. If that approach to govt. spending could become institutionalized  it would make it much easier to understand which spending items provide a return and which don't. That would be terrific.

Unfortunately, that sort of approach (which is sometimes called dynamic scoring) is what Republicans generally refer to when they claim that tax reductions produce a net benefit to the government because of the marginal increase in GNP. So it's important to be very careful about how it is done and to stick to very well established results. 

One thing struck me about the comparison of subsidizing English majors to community college-level training. The article claimed that English majors are expected to earn only $40,000/year. Where did they get that? Many English majors go on to law school and earn quite a bit more. So again, for this approach to be believable requires very rigorous analysis and data collection. But if this approach could be established, it would serve the country well.
I think I first heard the word "investment" used for government spending during the Clinton administration. I took it as his way of not saying government spending. He could make a case that it's investment, but I never heard the case actually made in any concrete way. It seemed more like a way to relabel government programs so that they would seem less undesirable to people who don't like government spending in general. But it would be quite useful if this approach to govt. spending as investment could be established and defined rigorously.
+James Salsman. It's amazing that you find all these references. I'm impressed.  Wrt scoring govt. investment in tuition assistance or anything else, I'm afraid I don't have either the economics expertise or access to the required data. Someone should do it, but I'm not qualified. 
+Russ Abbott you would think that every university's development department in the world would be making infographics at least yearly on the details of this, wouldn't you?
They all create ads about their schools and about how well selected alumni do. But to develop a rigorous payback model is another thing. They don't have the data or expertise to do that.
Computational thinking calls for a lot of mathematical abstractions.  In the early days, the abstractions were mathematical algorithms that could be translated into working computer programs using suitable languages like Fortran, Algol, or PL/I.   Later on, it became essential to understand concepts like finite state automata which could be instantiated with object-oriented programming.  It's not clear to me how practical it is to get these abstractions across to the general public.
The public probably has a greater need to understand risks, probability, and statistics than to understand differential calculus.  Our high-tech culture is built on a lot of mathematical abstractions which the general public has a woefully limited understanding or appreciation of.
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