Another Word For It Patrick Durusau on Topic Maps and Semantic Diversity

July 7, 2012

Measurement = Meaningful?

Filed under: Data Science,Education,Measurement — Patrick Durusau @ 4:37 am

A two part series of posts on data and education has started up at Hortonworks. Data in Education (Part I) by James Locus.

From the post:

The education industry is transforming into a 21st century data-driven enterprise. Metrics based assessment has been a powerful force that has swept the national education community in response to widespread policy reform. Passed in 2001, the No-Child-Left-Behind Act pushed the idea of standards-based education whereby schoolteachers and administrators are held accountable for the performance of their students. The law elevated standardized tests and dropout rates as the primary way officials measure student outcomes and achievement. Underperforming schools can be placed on probation, and if no improvement is seen after 3-4 years, the entire staff of the school can be replaced.

The political ramifications of the law inspire much debate amongst policy analysts. However, from a data perspective, it is more informative to understand how advances in technology can help educators both meet the policy’s guidelines and work to create better student outcomes.

How data measurement can drive poor management practices is captured in:

whereby schoolteachers and administrators are held accountable for the performance of their students.

Really? The only people who are responsible for the performance of students are schoolteachers and administrators?

Recalling that schoolteachers don’t see a child until they are at least four or five years old and most of their learning and behavior patterns have been well established. By their parents, by advertisers, by TV shows, by poor diets, by poor health care, etc.

And when they do see children, it is only for seven hours out of twenty-four.

Schoolteachers and administrators are in a testable situation, which isn’t the same thing as a situation where tests are meaningful.

As data “scientists” we can crunch the numbers given to us and serve the industry’s voracious appetite for more numbers.

Or we can point out that better measurement design could result in different policy choices.

Depends on your definition of “scientist.”

There were people who worked for Big Tobacco that still call themselves “scientists.”

What do you think?

No Comments

No comments yet.

RSS feed for comments on this post.

Sorry, the comment form is closed at this time.

Powered by WordPress