by Rebecca Hyde, Research & Instruction Librarian, Associate Professor, Pius XII Memorial Library
“Data literacy” is used to mean many different things, but I recently came across a simple definition that really resonated with me: Data literacy is “the ability to interpret, evaluate, and communicate statistical information” (Beauchamp 2015). I like this broad definition because it encompasses the basic skills that are important for everyone, while also touching on the more advanced analytical skills we expect students and researchers dealing with data to master.
This concept is nothing new, and is sometimes called “statistical literacy” or “quantitative literacy,” but the basics of it can be easily overlooked as assumed knowledge in the classroom. With data becoming an ever more present part of our lives, this skill is crucial for our students to become educated consumers and users of data, even if they will not end up as researchers whose grasp of data creation and usage is essential to their scholarship.
Many of you probably already know of ICPSR (Inter-university Consortium for Political and Social Research) as a place to go for research data and maybe even as a place to archive your own data. ICPSR also has started to create resources for instructors interested in incorporating data literacy into their classrooms. There are multiple levels of resources, including some for students with little or no experience working with data, as well as for more advanced students who have experience with statistical analysis. All of these resources are freely available to anyone at an ICPSR member institution, including Saint Louis University.
The most basic level classroom exercises are the Data-Driven Learning Guides which provide an easy way to introduce working with data to your students. Most of the legwork is done for you, including links to data analysis for specific variables, interpretive questions for students to answer, and a bibliography of related articles. These guides are especially useful when you want to engage students in a deeper conversation on a relevant topic, while also giving them some exposure to using and thinking about data in an academic setting.
While these guides were created with the social sciences in mind, the topics are broad enough that they may be useful in a variety of classrooms. For example, the guide on “Attitudes about Racial Discrimination and Racial Inequality in the US” might be relevant in many classrooms and can inform a discussion about what conclusions students can and can’t draw from the data presented and how the data might relate to discussions on race in St. Louis and the U.S. at large.
For classes with more advanced students, there is the Crosstab Assignment Builder, which allows instructors to choose specific variables from a dataset for students to work with using an online application. This removes the need for students to learn statistical software in order to access and analyze the data and can simplify datasets by limiting the variables available to students. There also are more advanced exercise sets created with research methods courses or other advanced courses in mind.
If this post has gotten you excited about using data or statistics in your course, take a look at ICPSR’s list of resources for teaching undergraduates and their collection of videos related to data literacy and teaching. If you want other options for more simplified statistical data (or databases to point your students to), check out DataPlanet Statistical Datasets or the ProQuest Statistical Abstract of the United States. Please get in touch with me if you’re looking for suggestions or would like help navigating any of these resources!
Beauchamp, A. (February 12, 2015) What is Data Literacy? Databrarians. http://databrarians.org/tag/teaching-data-in-higher-education/
Rebecca Hyde is a faculty research & instruction librarian at Pius XII Memorial Library. She is the subject librarian for Government Information, Political Science, the Center for Sustainability, and the School for Professional Studies.