Our Own Private Kitchen Strainer

In his book Too Big To Know, David Weinberger makes this excellent observation about information filters,information overload

First, it’s unavoidably obvious that our old institutions are not up to the task because the task is just too large: How many people would you have to put on your library’s Acquisitions Committee to filter the Web’s trillion pages? We need new filtering techniques that don’t rely on forcing the ocean of information through one little kitchen strainer.

It may be obvious to Weinberger and others that our old expert-based systems for filtering information are no longer adequate, but not to the leadership here in our overly-large school district (and, I suspect, elsewhere in the American education system).

We have some very specific kitchen strainers that attempt to inhibit teachers and others from using most digital resources until they have been blessed by the right people. A process that often takes months, discourages most teachers from even making the attempt, and is roundly ignored by many.

Part of that process includes very small teams of specialists who spend a lot of time carefully collecting and analyzing resources for a list of approved instructional products, or writing and editing materials lovingly added to the “curriculum assessment resource tool”, our homemade database for “approved” instructional materials (and magic test generator). Everything, of course, must be filtered through the specific classification schemes for classifying the knowledge dispensed in the classroom, as established by the district or state.

Although this year a section was added to that database allowing teachers to share materials they’ve created, which is a step in the right direction, it has not been particularly popular.1 I suspect a large part of that is due to the fact that teachers who really want to share their work and ideas already have found much better tools available on the open web.

When presented with a choice, a rigid and very closed environment really won’t appeal to those educators who have already discovered the value of sharing in the world outside their schools.

Interpreting the Data

This past week the owner of the Tesla electric car company got into a fight with a reporter for the New York Times over a somewhat negative article about his road test of the vehicle. To prove his point that the reporter had not conducted a fair test, the owner released all the telemetry data the car had collected during the trip.

Which might have been the end of things except that a writer for the Atlantic looked at the same data and came up with a different interpretation. And the Times own public editor weighed in with analysis looking at both sides and not necessarily supporting either of them.

Although I saw a little of this story pass by in my info stream, the larger point of all this didn’t really register until reading David Weinberger’s post yesterday.

But the data are not going to settle the hash. In fact, we already have the relevant numbers (er, probably) and yet we’re still arguing. Musk [Tesla owner] produced the numbers thinking that they’d bring us to accept his account. Greenfield [the Atlantic reporter] went through those numbers and gave us a different account. The commenters on Greenfield’s post are arguing yet more, sometimes casting new light on what the data mean. We’re not even close to done with this, because it turns out that facts mean less than we’d thought and do a far worse job of settling matters than we’d hoped.

Electronic data tracking on a car – where it went, how fast it got there – yields very straightforward numbers and, in this case, still produces different interpretations of the meaning of that information.

Now I’m sure the Tesla is a very complex piece of technology. But it’s not nearly as complicated as understanding and managing the growth and learning processes of a human being, especially kids in K12 schools.

However, using much less precise measuring systems than those in the car, we collect far fewer data points on each student here in the overly-large school district during each year.

We then accept those numbers as a complete and accurate representation of what a student has learned and where they need to go. That very narrow information stream also leads to even more narrow judgements on schools (success/failure) and now we’re starting to use the same flawed data to assess the quality of teachers.

In his post, Weinberger is celebrating the open and public way in which the dispute between Tesla and the Times is being played out, with many different parties lending their voice to the discussion of how to interpret the data.

How often do we ask even the subjects of our testing to analyze the data we’ve gathered from them? Why are then not included in the development of the assessment instruments? When do we include at least a few of the thousands of other factors that affect student learning in our interpretations?

I’ve ranted before in this space about the increasing amount of resources being poured into data collection and analysis here in the overly-large school district (and elsewhere). But it’s the absolutist approach to the analysis of those numbers that may be an even larger disservice to our students than wasting their time.

Insanely Inadequate

David Weinberger on copyright in 2012.

I think our current copyright system is insanely inadequate for the new ecology, and that it has the opposite effect that its best-spirited defenders want it to have: the current copyright laws (and mindset) are impeding the greatest cultural flowering in our history, and if those copyright laws are taken to their proposed maximum, they will kill culture dead.

He goes on to discuss how he and the musician whose post inspired his comments both depend on copyright to make a living (at least part of it) but still believe the system is broken.

Slightly off the topic of our screwed up intellectual property system, I’m in the middle of reading Weinberger’s new book Too Big to Know and highly recommend it. It’s an interesting read about how information is moving beyond an expert-driven system to a world of knowledge where networks are the experts. For those of us in education, his ideas have many implications.

Learning From Twitter

David Weinberger offers 4.5 Things Twitter Teaches Us, in which he makes some interesting observations about the microblogging system/current-mainstream-shiny-bauble.

His basic premise is that Twitter is a simple, extensible communications tool in which users themselves determine how best to use it.

Something that’s true about every successful web 2.0 application.

After you’ve finished with this crappy summary, go read the whole thing.

Whatever Will We Call It?

David Weinberger, author of the excellent Everything is Miscellaneous, says he is often asked what web 3.0 will be.

Good question. But don’t expect a concrete answer.

Weinberger’s reply is that we don’t know and really can’t know.

In fact, it’s likely we’ll never get to something that can be tagged with the next increment like software.

Web 2.0 also makes it less likely that a single change will sweep the entire Net, for Web 2.0 makes it easier to diversify the Web’s offerings. So Web 2.0 may also spell the end of giving the Web point revision numbers.

With any luck he’s right and we can figure out a name for all this stuff that makes more sense to people outside this echo chamber.