Building an IQL Course From the Data Out

I'm meeting with a quite a few people doing interesting things around quantitative literacy, and I can't help but be amazed with the audacity of what they are attempting. If any of you are reading this post, know that you all are my heroes.

It occurs to me though that many people developing IQL start building courses from a different direction than I would start. Usually the course is nearly fully developed before the professor begins to try to seek out publicly available data for the students to use to defend or attack quantitative propositions. And very often that data turns out to be spotty, shallow, or not directly manipulable with the tools that students have access to (data, for instance, that is locked up in PDF charts).

This is understandably frustrating -- it's difficult to push students to do real analysis when the data is limited.

That's where the concept of building a course "from the data out" comes in.

When you build a course from the data out, you identify the data sources you will use early in the course design process. Say you want to teach a quantitative literacy course, and you would like it to be on the general topic of poverty and health. When you design from the data out you start by doing an inventory of public data sources pertaining to the subject.

Looking at the data you can ask yourself these sort of questions:

• What sort of activities could students do with the available data?
• Are there opportunities here fro original analysis?
• Is the data rich and varied enough to support multiple viewpoints?
• Will the data work with free visualization tools?
• Are there collaboration or crowdsourcing opportunities?

In other words, start by building rich authentic activities and projects around the data, and then start to work backwards to the larger course structure which will help give meaning and relevance to the activities and projects, and your job will be a lot easier.