On 2/16/07, Daniel C. <[EMAIL PROTECTED]> wrote:
I've always been confused about the motivation for learning pure _Science_, especially when dealing with something like computers. What's the point of learning theory if you don't know how to apply it? So you can get a job teaching theory to other people, who will go on to get jobs teaching theory...?
One of my professors here at BYU was talking about this a couple of months ago. As he put it (and I agree 100%) if you want to learn to write code you go to ITT or whatever tech school has a less painful, less long program and learn how to write code. You will learn how to code on current tools and write currently applicable software. The idea behind learning Computer _Science_, at least in the view of this professor, is that if you learn to think about computing and why we do things the way we do, and learn how to code as you do so you are prepared to solve new problems by applying the theory. If the current standard had ever been "good enough" the computing landscape we live in today would be very different. The folks at Xerox PARC were not people who learned to code to make a living. They were folks who thought a lot about the theory of what was or would be possible. The same holds for the people who are doing the research in AI and machine learning, NLP, and other fields that will change the landscape of computing we will have in the future. I'm going to go out on a limb and say that there is a level of software engineering that you can only reach with a solid understanding of the theory. If you don't know that a certain problem can be solved, or the principles on which it can be solved, you can't code up a solution. -- Alex Esplin /* PLUG: http://plug.org, #utah on irc.freenode.net Unsubscribe: http://plug.org/mailman/options/plug Don't fear the penguin. */
