Advisor Jake Carlson on data literacy

Our advisor Jake Carlson has posted to the e-Science blog about our recent work weekend where we convened our entire national team. An excerpt is below:

As someone who generally works primarily with graduate students, I don’t get a lot of exposure to what the expectations are for high school students around data literacy. In the interviews we conducted with graduate students in the Data Information Literacy project they indicated that their data management skills were primarily self-taught. Although I don’t see High School students needing to learn how to manage and curate research data sets necessarily, I am interested in how students could be better prepared for assuming these types of responsibilities as they progress in the education.

Earlier this month I participated in a three day, all-hands meeting for the project where we discussed aspects of data literacy and contemplated possible directions to support High School education. The meetings were intense and wide ranging, but I want to share a few items of that I found particularly interesting.

How much do you need to know to teach data? Many librarians do not have a background in the sciences or math (myself included) which could make teaching data literacy topics intimidating. However statistics and data are not math, or at least there are aspects of data literacy that transcend math, that students need to know and librarians are potentially well suited to teach.  Applying data in arguments effectively and ethically and being an intelligent consumer of data are just two areas where the knowledge and skills of a librarian could easily be applied. The bottom line is that while we may not be able to teach students everything about data literacy, we can teach them some important things to further their education.

Many issues in information literacy are relevant for data literacy. Evaluating the quality and appropriateness of materials, for example, is a concern in both information and data literacy requiring the development of critical thinking skills in students. For example, the Reuters news agency produced an egregiously bad chart implying that gun deaths had decreased in Florida since the “Stand Your Ground” law was enacted (they’ve actually increased), citing Florida’s Department of Law Enforcement as the source. Even when the data are sound, the presentation of the data may be suspect. Evaluating data could present particular difficulties for high school students as understanding the context and methodologies behind the data may overwhelm them.

This segues into another issue that was frequently brought up, the difficulty of teaching data literacy in a way that high school students could understand and apply. There are a number of fairly easy to use online tools available to analyze or visualize data that could be used to introduce high school students to working with data by taking a lot of the guess work out of the process. However, focusing on a tool may hinder a student’s ability to understand the underlying concepts of data analysis or visualization and limit their cognizance of the data itself. Schools librarians noted that students will often write their assignments and then seek out the data they need to support their arguments instead of the other way around.

In closing, participating in this project has renewed my admiration for school librarians. Everyone I met was incredibly passionate about the work that they are doing as educators and fully committed to extending their work into data. I can’t wait to see how school librarians will make use of the products with the materials produced from this project.

Thanks, Jake!

About Kristin Fontichiaro

Kristin Fontichiaro is the principal investigator of this IMLS-funded project and a clinical associate professor at the University of Michigan School of Information.