June 28, 2006

Growth models, technocracy, democracy, and algebra

I had thought that my being anxious and out of sorts for several days was from that line-drive hit into my leg two weeks ago and the resulting swelling and discomfort. But no—it was from the interruption of the book-writing for other things that are quite valuable (the journal, the article on migration and graduation estimates, and a few other tidbits) but that stopped my writing momentum. I think I have it back now, and I'm much happier. I know—I should be delighted that I've accomplished so much with even a minor injury. But I have a compulsion (hopefully not a disorder!) to get this book done.

Current status: I have a contract I need to sign with one publisher (hurrah! I'll add that information as soon as I receive my completely-signed copies), and I'm on chapter 2 right now. That's the chapter on the relationship between technical expertise and democracy, one that explores the politics of accountability statistics and how that is rooted in a long-term tension between technocracy and democracy. The first section of the chapter explores the Progressive-Era origins of prestigious technical expertise and the ambivalence our society has with expertise (with IQ testing as a prominent example). The second section of the chapter explains the organizational life of testing and how the fragility of the world of testing undermines our ability to use high-stakes testing with confidence. I suspect I need to add a separate section on some of the stuff that didn't fit in the first chapter, on the civil-rights meme that's only just emerged as a major rationale for high-stakes testing.

This morning, I'm working on the last section, on growth modeling. I've discussed growth models before. It's a paradigm* of the dilemma in balancing both technocracy and democracy. My goal is to describe both the technical difficulties with growth measures and the way that the holy grail of growth has obscured the political questions involved: how we set expectations for schools and students.

Addendum (added after a few minutes' thought waiting in a coffee line): the tricky part of this chapter is figuring out what technical discussion is necessary without going over the heads of the potential audience. What can I assume? Practically speaking, I think I need to assume some knowledge of plain multivariate regression. These days, principals and superintendents need some statistical reading skills (though I won't call it statistical literacy) not to be bowled over by waves of school accountability statistics and bad research.

And there's another place where algebra has some use in everyday life. If you understand a linear equation, you can understand multivariate regression. This means that administrators, and any teacher (at any level!) who wants to be an administrator, needs to know algebra.

* Paradigm is now associated with Thomas Kuhn's (mis)usage of the word to mean "social model." I'm using the older meaning.

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Posted in Accountability Frankenstein on June 28, 2006 9:57 AM |