Ignition for Education

In a previous post, I commented on “the quantitative tyranny in education”—the evaluation of learning, and of teachers and schools, through standardized tests. I argued that these tests can only measure a limited range of skills at best, and that they might measure only the students’ test taking skill and mentality. Yet great store is set in them because they are easy and cheap to administer. People don’t have to be sent, or paid, to go to schools, conduct interviews, sit in classrooms, review students’ work, and learn what is actually happening.

And, best of all, standardized tests give results in the form of easy numbers. The numbers might not tell us what’s actually going on. But who cares? They’re numbers. You can make graphs with them. So, they’re science, right?

Wrong. They are merely measurement—a component of scientific enquiry, for sure, but not synonymous with it.

Earlier, I wrote about intelligence. I argued that it is simply the ability to handle complexity. But people want to gage it through IQ scores. An IQ tests involves various tasks, each of which reveal the ability to handle complexity in some form. However, an overall IQ number is not a valid measure of intelligence because it averages the test takers proficiency on each of the tasks, rather than taking their performance on the task at which they are most capable as indicative of their intelligence.

It’s a bit like scoring people on their ability to read, calculate, paint, sing, lift weights, dance, and cook, averaging those scores, and calling and calling the result Ability Quotient, or AQ. A person’s ability level, if it were even sensible to try and gage such a thing, would have to be gaged on the basis of their strengths.

Furthermore, IQ testing prioritizes speed of processing over depth, and it probably measures test-taking ability and mentality, and test conditions, over either speed or depth in at least some cases.

But an IQ test delivers a single number between 1 and 200, or, if one looks closer, a set of numbers between 1 and 200. So, what’s not to love?

These are what, from now on, I’m going to call “lazy numbers.” They are numbers that don’t actually represent what they purport to represent. They are an alternative to serious investigation or analysis that people rely on because they prefer to have a simple set of numbers than to have a complex picture. And because, to the undiscerning reader or listener, numbers make one sound credible.

Please feel free to comment on this post with your favorite example of a lazy number.