Making Data Literacy Qualitative
Hello colleagues!
In For the Public Good: Reimagining Arts Graduate Education in Canada, we draw on Joseph Aoun’s concept of the three “new literacies”: human literacy, technological literacy, and data literacy. Human literacy is, in its simplest form, what we also call ‘people skills.’ Technological literacy is facility with, you guessed it, technology; not necessarily building it, but being able to understand its underlying principles and to use it effectively. But I want to talk here about data literacy, because we feel Arts graduate education has a lot to contribute, and where there is both much potential and much misunderstanding.
For many, “data” is an inherently quantitative concept, and so “data literacy” in terms of graduate curriculum sounds like a synonym for “learn more stats.” Aoun himself frames data literacy as “the capacity to understand and utilize Big Data through analysis.”
However, we suggest a broader understanding that encompasses both quantitative and qualitative data and the use of mixed methods and multi-methods approaches to analyze data, both big and small. Statistics Canada has a useful definition of “data literacy” as follows:
Data literacy is the ability to derive meaningful information from data. It focuses on the competencies involved in working with data including the knowledge and skills to read, analyze, interpret, visualize and communicate data as well as understand the use of data in decision-making.
Data literacy also means having the knowledge and skills to be a good data steward including the ability to assess the quality of data, protect and secure data, and their responsible and ethical use.
This definition is particularly useful because, even though it’s from Canada’s leading statistical research body, it doesn't reference quantitative approaches specifically. Data simply means facts and pieces of information, and so data literacy really means being able to handle and make sense of multiple bits of information. And this is a powerful concept that should be more expressly applied to structure Arts graduate programs.
Not all research involves data. Arts researchers still analyze singular items of information, like a book or work of art. But much research involves collecting and analyzing different bits of information, whether quantitative or qualitative. This is data analysis. The digitization of information, such as archives, parliamentary debates, and census records, allows more opportunities than ever to work creatively and discern patterns and connections in data.
In the age of “I did my own research,” the critical and thoughtful use of data is more important than ever. At the undergraduate level, we have a responsibility to teach basic data literacy skills: discernment; how to use a search engine effectively; how to identify reputable and reliable sources; and how to determine what questions can be answered by what data. (See Loleen Berdahl’s “Skills Agenda” column on teaching undergraduate data literacy). At the graduate level, the mission is advanced: how to develop skills in collecting and analyzing data on their own; how to review the quality of others’ data and analysis; and the effective communication of complex data into clear conclusions.
Furthermore, Arts disciplines critically reflect on the use of data and its normative implications. Remembering the StatsCan definition, “data literacy” emphasizes both the direct use of data but also reflections on the use of data, and this is where the Arts have their greatest value. Data security and preservation is also a critical part of data literacy, and again is widely found in the Arts; we may all not be adept in advanced statistical techniques, but the principles of what information to secure and why are central to the Arts.
The challenge is that while some Arts graduate programs are doing some of these things already, we’re not necessarily articulating them well. Part of the blame can be put on the narrow perspective that “data” is solely about numbers, and “empirical analysis” and “statistics” are the same thing — a narrow perspective that can lead both quantitative (“more stats!) and qualitative scholars (“less stats!) to dismiss each other. And while it’s not hard to require and agree on the parameters of an introductory statistics course in most programs, it’s more difficult to formulate a “data literacy” course that covers “everything else”, from archival research to participatory ethnography to elite interviewing.
But our larger concern is that Arts programs are not being systematic about data literacy as a primary, rather than secondary, objective. Whether quantitative or qualitative, students mostly pick up analytical skills and techniques along the way as needed for a specific course or their dissertation project. In For the Public Good, we propose sample graduate programs that incorporate data literacy as a primary learning outcome in its own right, exposing students to systematic thinking and understanding of why and how to analyze data, even if they may not use a particular approach for their own research. (And yes, that may include learning more about stats!)
Returning to Aoun’s overall three literacies, the objective is not necessarily to become an expert in everything; it’s to be literate, in the sense of being able to comprehend and understand them at a general level. Arts graduate education has always prided itself on equipping students on a broad scale. Let’s be more systematic about it.
On behalf of my For the Public Good: Reimagining Arts Graduate Programs in Canadian Universities coauthors and myself, thanks for your continuing interest in improving Arts graduate education. What are your own thoughts about data literacy? Please let us know in the comments below.
One more thing before we go: now that For the Public Good: Reimagining Arts Graduate Programs in Canadian Universities is published, we welcome opportunities to work directly with units – including yours! – to support your efforts to update and reimagine your social science and humanities graduate programs. Contact us at Reimagining.Grad.Education@gmail.com for details. And if you would like to write a guest post for the Reimagining Graduate Education newsletter, please contact us at the same address. We look forward to hearing from you!
Stay well, colleagues!
Help advance broader discussion of graduate education! Ask your university and local libraries to order a copy of For the Public Good: Reimagining Arts Graduate Programs in Canadian Universities.
Praise for For the Public Good: Reimagining Arts Graduate Programs in Canadian Universities:
“It is the kind of quietly good book we need to see more of. … This book provides a very solid description of the process of defining and developing excellent, sustainable arts programs that serve students rather than academics. And not only is it dead-on in terms of its recommendations about how to design and evaluate programs, it has a lot of helpful matrices and worksheets to help those who are put in positions requiring them to do exactly that … More like this, please." – Alex Usher
“Nearly half the book is dedicated to charting a transformative course for liberal arts departments.... If For the Public Good can provide the impetus for social sciences and humanities departments to refine their graduate studies programs, the career outcomes for tens of thousands of grad students will be the better for it. That alone would move the needle on Canada’s public good problem." – Literary Review of Canada
Related articles:
Arts graduate education in Canada should be redesigned around students’ and society’s needs (May 2024)
Arts graduate programs have an opportunity and a need to focus on talent development (June 2024)
Canada actually needs more arts graduate students. We’ve just been doing it wrong (paywall, The Globe and Mail) (August 2024)