One hundred percent of my family is technologically literate. No, really. I’ve got the numbers to back that up. #

Here’s how I would report that to the Department of Education: #

Number of members of my family: 4 #If you know me or my family at all, I suspect that you would challenge my numbers. Why? Because two of the four members of my immediate family are children. Young children. One’s three. The other’s a ten-month-old. How in the world are they technologically literate? #Number who are technologicaly literate: 4. #

See, what I did back there, and what most folks who collect statistics do all the time, is that I got to define my terms. For the purposes of this data reporting, I have defined technologically literacy as the ability to turn the TV in our living room off with the remote control. Everyone in my family has accomplished this action – although not all of them deliberately so. #

I was reminded today, as I sat through a conversation about data reporting now and data reporting to come, that reporting a number in a column or a data field seems like such a simple thing. How many computers do you have? (Easy to answer – you can count.) How many 8th graders do you have? (Easy to answer.) How many of them are technologically literate? (Um. Well. That one’s harder.) #

That last one all depends on how you’re defining technological literacy. And how to assess it. And we’re not all in agreement about the best way(s) to do that. The devil continues to be in the details. (Oh, and while we’re kind of on the subject, here’s an analysis of many of the different definitions of 21st Century Skills, which Nancy White happened to tweet along while I was in the other conversation. We’ve got lots of definitions, and now definitions of the definitions, but we still don’t know how to teach the blasted things. Nuts.) #

When you see a statistic, I hope that you are looking past the number and seeking the definitions and the methodology. I hope you’re teaching your students to do so, too. I continue to be worried that, for all the data we’ve got, it isn’t any good. #

I just blogged about this same subject and then found your post. You said it better and I like the analysis of different definitions, which I will add to my delicious links.

Back when I was a bit jockey, and “technologically literate” meant that you could actually write the software that ran on your computer, we knew that

data != information.

All the fooferaw about “data” these days makes me thing we’ve forgotten that.

I agree totally with Mr. K’s comment about data not being the same as information.

Also, I would like to think we could still consider technologically literate to require some understanding of code. Especially with the focus on Web 2.0, we are at a time when more than ever students are able to “go to the code” (just right click and ‘view source code’), and yet current tech standards say almost nothing about programming ability.

I tend to agree with Guido van Rossum, creator of the Python programming language:

“…while many people nowadays use a computer, few of them are computer programmers. Non-programmers aren’t really “empowered” in how they can use their computer: they are confined to using applications in ways that “programmers” have determined for them.”

http://www.python.org/doc/essays/cp4e.html

It seems to me that there is no other way (besides teaching the fundamentals of programming) that students will ever be able to reach the standard you quoted:

“VI. Technology Operations and Concepts

Students demonstrate a sound understanding of technology concepts, systems and operations. Students:

A. understand and use technology systems.

B. select and use applications effectively and productively.

C. troubleshoot systems and applications. ”

I can’t see students reaching those three standards without knowing how programs are made.

I always am a little leery of statistics for the reasons you mention, and others. For example, the statistic that half of new teachers quit within five years is often held up to show the state of our schools. I’ve never see statistics about how long a typical college graduate stays at a non-teaching job. Is it similar to teachers? Higher? Lower? Without that piece, the other piece of information doesn’t mean much.

The example I always give to my students about how statistics can be manipulated is as follows: A company notices that 40% of all sick days are taken on a Monday or Friday, so they assume that staff aren’t sick, they’re taking advantage of sick time to have a long weekend. They clamp down on sick time and start harassing their employees, only to discover later that if sick days were randomly taken all five days of the week, that would be 20% each day. Any two days added together would be 40%. Statistics can be very tricky. Especially for folks like me who have never taken a statistics course.

[…] really think a post by Bud the Teacher is appropriate for this discussion: Lies. Statistics. Whatever. Let him and the rest of us know what you think! Posted on April 14, 2008 in State of Illinois, […]

As Mark Twain said, ” There are three kinds of lies: white lies, damned lies, and statistics.”

It does hinge upon definition and then the spin of the interpretation.