Computational Thinking: AP Computer Science Vs AP Statistics?

theodp writes: "What if learning to code weren't actually the most important thing?" asks Mother Jones' Tasneem Raja. "Rather than increasing the number of kids who can crank out thousands of lines of JavaScript, we first need to boost the number who understand what code can do." Computational thinking, Raja explains, is what really matters. So, while Google is spending another $50 million (on top of an earlier $40 million) and pulling out all the stops in an effort to convince girls that code and AP Computer Science is a big deal, could AP Statistics actually be a better way to teach computational thinking to college credit-seeking high school students? Not only did AP Statistics enrollment surge as AP CS flat-lined, it was embraced equally by girls and boys. Statistics also offers plenty of coding opportunities to boot. And it teaches one how to correctly analyze AP CS enrollment data!

Broken priorities

[Shadow of Eternity]

We throw tens if not hundreds of millions of dollars at girls and women to get them to choose technology or engineering as a major, but completely ignore that they're already a majority to an overwhelming majority of graduates in literally every other major and dominate every level of education. Evidently it's more important that women not be a mere ~5% less of a program that's already only 10% of the degrees conferred in the US than it is to do something about the fact men are barely 1/3rd of college graduates in the first place.

Because, yknow, that's not going to be unhealthy for society at all.

Re:AP Statistics isn't really computational thinki

[Registered Coward v2]

Statistics is indeed quite important, and whether AP CS or AP Statistics is a more useful use of a high-school student's time is a useful question (assuming they have to choose, which maybe they don't?). But AP Statistics is not teaching computational thinking; it's teaching statistical thinking, which is not the same!

While I agree statistical think is different than computational thinking, to answer your question I think it is a better use of a students time to teach statistics. Properly taught, it teaches you to think about how to formulate a question, what data you need and how to analyze it. In short, it is as much about the problem as the answer.

Computational thinking, or to use an older term, procedural literacy, is the idea that people should understand how to think in terms of processes, procedures, etc..

SNIP

Many people can't do that: even leaving aside that they don't know C or Java or Lisp, they also don't really understand what an algorithm or a computer program is conceptually, and have absolute no idea what kinds of things can be computed and what kinds can't, or which are easy or harder to compute. They lack the ability to interact meaningfully with non-code representations of computation and algorithms as well, like flow charts or (natural-language) instruction sequences.

Again, I concur with you comments. That's why code monkeys are cheap and those who can actually develop a solution valuable; and the skills you mention don't become obsolete when a new language comes along. Unfortunately, far to many people equate the ability to code with being a computer scientist or engineer. That's not to say we don't need good coders but focusing on coding and forgetting the how and why behind it is doing them a disservice. I've also found the ones who can really write elegant code generally also think conceptually as well. Maybe I was lucky but when I took CS in high school the teacher made us explain and diagram what we are trying to do before coding, and rewarded accomplishing tasks in as few lines of code as possible. A she put it, "anybody can write a program with 100 lines to accomplish what can be done in 2."

Statistical thinking is quite a bit different, more about proper use of data, quantification of evidence and uncertainty, etc. It can be complementary to computational thinking, but it isn't the same skill.

True, but faced with learning statical thinking or how to write code I think the former is more valuable.

Re:What about statistics vs calculus

[ShanghaiBill]

It's not really a new debate, but the assumption that high school students will on average be better served by taking calculus instead of statistics could use some scrutiny.

Students should learn calculus, but it could be compressed, and maybe even merged with physics. My class spent a lot of time learning how to do things like integrate the square root of the reciprocal of the co-secant. That is not useful. Students already get quite a bit of exposure to statistics and probability in math classes, although there is usually not a class solely focused on that topic.

Practically speaking, basic familiarity with statistics is also a form of civics - teaching kids when to call BS on bogus claims

Indeed. I have long felt that we should be teaching "bullshit math" where rather than getting a problem and finding a solution, the students are presented with a political advocacy statement, and tasked with identifying the logical and mathematical flaws, unstated assumptions, and missing information. This sort of critical thinking skill, along with learning basic economics, could lead to a better functioning democracy.

If you build stats from a practical standpoint,

[jpellino]

then it's a lot more like computational thinking. A team of us - 3 college math profs (goals) , 6 HS math teachers (reality check) and 2 scientists (applications) were asked to craft a HS math series from scratch. We were able to condense most of traditional HS math into three years, then allow for a year of electives. What we came up with as the start of the three years was to "force the card" onto the students with some evocative event, like the teacher walks into the room and declares "boys are taller than girls". And that's when the battle starts. "I'm taller than him!" "Yeah, but look at these four tall boys and those five short girls." Etc. So the socratic stuff starts, and they go through the developmental history of statistics in order to find the tools needed to solve problems (i.e., arguments about numbers). It leverages all the arithmetic they learned K-8 and some of the geometry, they need to think hard about why a stdev can be more sensible than a variance, why diagrams and structures are important in dealing with numbers, why arrays and variables and sorting and the procedures involved in mean/median/mode etc. have to be thought out thoroughly. Add in testing, logic, thresholds, and you pretty much have the basis of many of the skills you want a programmer to have when they're tackling an actual problem in context. Put a Ti-83-ish in their hands, and have them use it all along. Far less whining about "like will we ever use this" and a glimpse of what a career can be doing this sort of thing.