Data Literacy in the Real World: Conversations & Case Studies

Introduction

Every day, your students are immersed in data, whether they’re reading their textbooks, viewing infographics in their social media feed, or making sense of the day’s news with their families. Data — millions of little “bits” of numbers and information — may be collected, aggregated, and analyzed to determine which coupons their family receives when they show their customer card at the grocery store, whether their family qualifies for a mortgage, the level of energy efficiency in their home, or even what election ads they see on Facebook.

Knowing how to recognize the role data plays in their lives is critical to navigating today’s complex world. Yet few high school students are exposed regularly to the kinds of practice with statistics, visualizations, and real-world issues — particularly in the digital age. Graphs in math class, where the y-axis always starts at zero, don’t always function the same way in news stories, where the y-axis may be truncated to fit in limited space. If students don’t know to “stop, look, and listen” when they confront even the simplest visualizations, their prior experience may contribute to misunderstanding. We assume that today’s students can move fluidly between online sites and portals, but they may not realize that their Facebook posts are being scanned by algorithms to determine what they see in their feed. The ease with which our thermostats, exercise trackers, and Instagram accounts collect information about us belies the reality that they may be used to construct hidden profiles about who we are, what we value, and where we shop. Daily, we leave behind bread crumb trails that can be used to adjust the pricing of our merchandise, airline tickets, and more.

Data literacy — the ability to “read” and “write” effectively with data — is critical to success in the 21st century. We want our high school students to graduate being able to understand and make conscious choices about the ways in which they approach data. We recognize that data is not constrained to any particular subject area: in fact, it pervades all subject areas. Additionally, the high school day is tightly regimented, with little room to add coursework in data literacy. We saw a need for nimble just-in-time interventions, mini-lessons, and other strategies that librarians and their classroom colleagues could insert into existing curriculum.

With that in mind, we launched the project Supporting Librarians in Adding Data Literacy Skills to Information Literacy Instruction. Made possible in part by the Institute of Museum and Library Services RE-00-15-0113-15, our goal was to develop the capacity of high school librarians and others to gain skills that they could deploy as-needed across curriculum areas and beyond the classroom and into the wild.

Beginning in 2015, we convened conversations between those who were already fluent in data skills and highly-skilled curriculum leaders to work on three projects:

• The 4T Virtual Conference on Data Literacy (http://dataliteracy.si.umich.edu/conference), was a pair of free online conferences for high school librarians and educators (and, as we discovered, over 80 other types of professionals!). In 2016 and 2017, topics included data and voting, basic statistics strategies, sources of raw data, infographics creation, citizen science as a pro-social use of Big Data, personal data management, and more.
• Creating Data Literate Students (a free book at http://datalit.sites.uofmhosting.net/books/book/ or available for purchase at cost at https://www.amazon.com/Creating-Literate-Students-Kristin-Fontichiaro/dp/1607854244 ), our 2017 publication in which our experts unpacked their experiences navigating data with high schoolers. Chapters ranged from a discussion of the most valuable statistical strategies to teach to how to create engaging infographic units to how to find data and conduct basic analysis with Microsoft Excel.
• This book, in which we focus on building the professional learning of high school librarians and educators.

The book you are reading now is divided into two sections.

In Part I, you’ll be able to access the archived sessions from the 2016 and 2017 4T Virtual Conference on Data Literacy. We’ve designed these to be “out of the box” professional learning experiences for you and your colleagues and hope you will view these with colleagues in a variety of settings, including professional learning communities, inservice events, and in other small groups. These webinars follow our project’s seven themes:

• Data and statistical comprehension - Our experts have sifted through statistical practices and identified the most impactful things we need to know about understanding numbers so that we can share that information with our students.
• Data in arguments - From the op-ed page to Congressional hearings to essays in English class, data is used to support arguments and thesis statements. How can we help students read more critically and use data to bolster their own arguments effectively?
• Data visualizations - Arguably the most popular theme in our project, data visualization ranges from creating simple pie charts to developing complex infographics. The critical questions here are how we “read” and “write” with data in visual form.
• Big Data - “Big Data” is an umbrella term referring to the process of collecting large amounts of numerical or informational data and then using algorithms (computer processes) to draw conclusions. Often perceived as infallible, educators and their students need to be aware that algorithms may be purposefully or accidentally skewed and have intended or unintentional consequences.
• Citizen science - In the digital era, scientists can now generate and collect incredible amounts of data. Whether that data manifests as weather data, photos of animals, or lab documents, the volume is too great for any one person to analyze. Online portals make it possible for high schoolers to contribute to prosocial projects that embrace the best of the Big Data era ... but what should we be aware of?
• Personal data management - From a young age, individuals begin generating data. From social media clicks to browser information, from activity trackers to digital assistants, what should we know so we can help high schoolers be aware of what they should be aware of and can make conscious choices about the degree to which they want to share their data with others?

After viewing each webinar, you’ll find discussion questions and activities that you can use to bridge webinar content with your own classroom experiences. (You can also find links to the videos and accompanying materials at http://datalit.sites.uofmhosting.net/books/data-literacy-in-the-real-world/webinar-discussion-sheets/ .)

In Part II, you’ll find over 45 case studies related to data “in the wild.” These aren’t hypotheticals — they’re pulled from the news. We invite you and your colleagues to read the resources provided (hint: you can find a list of each case study’s links at

http://datalit.sites.uofmhosting.net/books/case-study-links/) and engage with the discussion questions. We’ve taken care to avoid being didactic here: you won’t find us saying that certain tools or practices are good or bad — those are decisions each individual should make for him or herself.

We’ve organized these case studies into four themes:

• Personal data management
• Citizen science
• Big Data
• Ethical data use

Once you have tried these in professional learning settings, you may wish to bring some of them into your classroom.

Throughout the text, you may encounter long URLs separated with a hyphen at the end of a line. In that case, don’t type or include a hyphen when visiting those web pages.

Our work with educators and librarians over the past two years has solidified our belief that these are ideas and concepts worth grappling with, first as professionals and secondly with our students, and we are eager to hear how you are using your newfound knowledge with your students. We encourage you to drop us a line at [email protected] with your insights.