Alexander Russo flagged this interesting article by the New Yorker's James Surowiecki about Jeremy Lin and how NBA teams' biases (skinny, Asian Harvard grad) led them to ignore the hard data about him, which showed he had NBA potential. But I disagree 100% with Russo's take on how it applies to evaluating teachers. Here's what Russo wrote:
This is a problem that education has already, and which may not be solved by value-added ratings or other numerical schemes. Teacher ratings will likely be ignored when they don't conform with other visual or personal experience, just like research, which is routinely ignored in the creation of public policy, and school ratings, which are belittled when they don't fit public perceptions of a school. This is good news for those who don't believe in the ratings and a worrisome problem for those who are putting so much stock in the power of numbers.
To me, the article underscores how critically important it is to use hard data because many teachers APPEAR to be good – they're nice, love children, maintain order, work well with colleagues, put in extra hours, etc. – but are simply no good at imparting knowledge to children. This reminds me of what Howard Fuller calls "happy schools," which are actually a FAR bigger problem than obviously horrible schools like the one my friend describes above. Happy schools (mostly elementary schools) are ones in which the students are happy, the parents are happy, the teachers are happy, the principal is happy – EVERYONE is happy. So what's the problem? The vast majority of the kids CAN'T READ!!! In other words, the schools appear fine to a casual observer, but THERE'S LITTLE TO NO LEARNING GOING ON! Keep this in mind as you read the next two articles.