The first 4T Virtual Conference on Data Literacy is this week Thursday, July 14, and Friday, July 15. Join us to learn about building the data and statistical literacy of high school students. Attendance is free, and all are welcome!
Please complete the registration to attend or receive information about archived sessions.
See the Frequently Asked Questions for more information about attending.
We are looking forward to seeing you in our online sessions soon!
Looking for something to read? Are you seeking to brush up on data literacy basics?
Everydata: The Misinformation Hidden in the Little Data You Consume Everyday by John H. Johnson and Mike Gluck is a nice introduction to developing critical thinking skills for data. It is full of bite-sized examples from everyday life, as Fast Company‘s review points out. At the end of each chapter, there is a handful of tips on how to apply the topics in the chapter.
For example, Johnson and Gluck shed light on self-reported data:
How many times did you eat junk food last week?
How much TV did you watch last month?
How fast were you really driving?
When you ask people for information about themselves, you run the risk of getting flawed data. People aren’t always honest. We have all sorts of biases. Our memories are far from perfect. With self-reported data, you’re assuming that “8” on a scale of 1 to 10 is the same for all people (it’s not). And you’re counting on people to have an objective understanding of their behavior (they don’t). (p. 20-1)
Johnson and Gluck acknowledge that “[s]elf-reported data isn’t always bad…. It’s just one more thing to watch out for, if you’re going to be a smart consumer of data.” This salient point is easy to keep in mind when looking at sources with students, reading the newspaper, browsing the web, listening to the radio on the way home from work, etc.
Everydata isn’t about the math; it’s about understanding the data and numbers that you encounter. Take a look at it for more practical tips like that one!
Source: Johnson, John H., and Mike Gluck. Everydata: The Misinformation Hidden in the Little Data You Consume Every Day. Brookline, MA: Bibliomotion, 2016.
Image: “Photo 45717” by Dom J, on Pexels. CC0 License.
Awareness is growing that students need instruction on interacting with data, as our project is helping librarians teach. In the prevalence of data, technology, the Internet, and digital resources, data literacy is a competency that equips students to navigate information. Education Week recently highlighted this need, including the skills to use data as arguments and understand data privacy.
How do you teach good online research skills to students who use mobile technology?
Librarians are observing that students approach research differently on mobile technology. Infinite scrolling makes re-finding difficult. The abundance of information has led to differing ideas about what sources are credible. Our team member Wendy Stephens wrote about these issues on School Library Journal. Included in her piece are insights from our team member Tasha Bergson-Michelson.
Wendy writes:
Evaluating information is necessarily a more time intensive and complicated process than retrieving information in a networked environment, but teens have demonstrated shifting notions about what makes a source valuable. Pickard, Shenton, and Johnson (2014) found that the young people they surveyed at an English secondary school, when presented with a list of particular evaluative criteria for online research, were not interested in traditional authority of information. Those students instead prioritized currency and topicality, lack of mechanical errors, and verifiability. The last item in particular suggests that young people find recurring information, shared in a variety of places, to be a hallmark of authenticity at odds with earlier notions of authorial attributions.
“Search is a garbage in, garbage out process,” says Tasha Bergson-Michelson, instructional and programming librarian at Castilleja School in Palo Alto, CA. “Choosing search terms is hard. If you have the right words, you can find the data.”
Transferring research standards to current technology is necessary, as Wendy concludes:
The topics may differ and the sources might look different, but online research still points to many of the hallmarks of an established process. Contextualizing the acquisition of search skills, as Martin suggests, and refining search terms as Bergson-Michelson advocates, reiterate principles of bibliographic instruction grounded in print research. But the necessary authenticity of the research task will remain integral, and this is where librarians are key in championing and supporting inquiry projects of students’ own devising, helping young people connect to a range of resources to inform their particular passions.
These points connect to data literacy because knowing how search works is part of responsible digital citizenship and, relatedly, personal data management. Thanks, Wendy and Tasha!
Image: “Apple Iphone Smartphone Technology Mobile Phone,” by Pexels on Pixabay. CC0 Public Domain.
School Library Journal recently highlighted our upcoming 4T Virtual Conference on Data Literacy in an article by Linda Jacobson. Our new online conference on July 14 and 15 will provide guidance for librarians and educators teaching data literacy to students. We are excited to be featured in SLJ and to launch our conference!
As SLJ’s article describes, the 4T Virtual Conference on Data Literacy will provide support for teaching data literacy skills to students. Statistics and data are everywhere, but do students understand and effectively use them? Building students’ skills will help them be good consumers of data and statistics. From our conference, librarians and educators can gain skills to equip their students. Conference sessions will focus on high school, and all are welcome to attend. Interested? Register on our website here!
This online conference is not the only part of our work! 4TDL is a piece of our two-year project. We will publish a handbook with rules of thumb and mini-lessons about data literacy for librarians and educators. Team member Connie Williams and Co-Principal Investigators Kristin Fontichiaro and Jo Angela Oehrli reflect on our project in SLJ:
Connie Williams, a teacher librarian at Petaluma High School in Petaluma, CA, and one of the educators working on the project, says that understanding data is important for using grading systems and looking at standardized test results.
“It’s important to be able to ask the right questions so that we can get the answers that inform great changes,” she says, adding that teaching students to properly evaluate the data they see every day is a “huge part” of media literacy. “In today’s connected world there are so many memes, data points, and headlines that promote arguments, persuasions, or points of view, and kids have to be able to sift through the numbers and beautiful graphics to gather the evidence that supports the argument.”
In addition to two virtual conferences—this year and next—the project will also provide librarians with a handbook of background information, basic rules for using data and mini-lessons developed by teams of data and curriculum experts. The intent is to give librarians ideas that they can easily weave into the lessons they are already teaching.
A mini-lesson might “cover a quick intro to a census data tool so that students could find reliable population stats,” says Jo Angela Oehrli, a co-principal investigator and an associate librarian in the University of Michigan Library. “Another lesson might be an infographic-of-the-day lesson where students dissect the meaning of a visualization.”
In each chapter of the handbook, Fontichiaro adds, authors are providing “quick recipes” for how educators can include data and statistics into their practice. “So whether you have five minutes, 30 minutes or multiple days, you’ll have ideas for how you can build your students’ skills over time,” she says.
Professional development materials, such as webinars and discussion questions, will also be developed as part of the project.
“If even one librarian says ‘I don’t tell students to skip the statistics part of articles anymore,’” Fontichiaro says, “we’ll have done our job.”
Join us for 4TDL!
Having some quick, go-to strategies that students can adopt to structure their visualized data into infographics and other forms can really raise the intentionality and outcome of student work. We recommend this video that introduces graphic designer Richard Saul Wurman’s five methods of organizing information visually. It can help inspire and focus students when they are stumped about how to design visualizations — take a look!
With summer fast approaching, here’s a book suggestion!
I just finished The Internet of Us: Knowing More and Understanding Less in the Age of Big Data. It offers an interesting commentary on how people interact with information and big data.
Author Michael Patrick Lynch takes a philosophical approach to issues in the information age. He writes about the difference between knowing and understanding. Have you ever been concerned about big data’s focus on the “what,” rather than the “why?” And how people say that sometimes the “what” is enough for understanding trends? Lynch recognizes this concern. He points out issues with this practice of only considering what is happening, of looking at correlations only.
Lynch asserts that three aspects compose big data:
He also discusses the dangers of decreased privacy owing to the creation of data through our activities and the use of it by companies.
Data analysis is impossible without context, according to Lynch. This point feeds his conclusion that knowing how parts connect with the whole is key to being a responsible “knower.” People need to see how information that they find online fits with their broader knowledge and the world. Seeing this bigger picture allows them to be creative. As he writes:
…our digital form of life tends to put more stock in some kinds of knowing than others. Google-knowing has become so fast, easy and productive that it tends to swamp the value of other ways of knowing like understanding. And that leads to our subtly devaluing these other ways of knowing without our even noticing that we are doing so–which in turn can mean we lose motivation to know in these ways, to think that the data just speaks for itself. And that’s a problem–in the same way that our love affair with the automobile can be a problem. It leads us to overvalue one way to get to where we want to go, and as a result we lose sight of the fact that we can reach our destinations in other ways–ways that have significant value all their own. (p. 179-80)
The Internet of Us shows both the pros and cons of technology and big data. It is not an anti-technology book. Instead, Lynch raises awareness of modern practices. Lynch’s distinction between knowing by searching online and actually developing skills is something that’d we’d all do well to remember. For those of you who are looking for inspiration — and points to make when students wonder why they have to learn something when they can just find the information online — this book is for you!
Source: Lynch, Michael Patrick. The Internet of Us: Knowing More and Understanding Less in the Age of Big Data. New York: Liveright Publishing Corporation, 2016.
Image: “Photo of Holloways Beach, QLD, Australia” by Alexander Khimushin, on Wikipedia. CC BY-SA 3.0.
This post is Part 2 in a two-part series highlighting our team members’ work with Choose Privacy Week. This initiative of the American Library Association puts a spotlight on issues of privacy in today’s digital world, such as tracking in online searches. Knowing how your data are used is a component of data literacy, and we are excited to feature our team members’ blog posts on these topics.
Debbie wrote with Rigele Abilock about online privacy policies and data collection on the Choose Privacy Week blog. Data collection by vendors can affect students, as they explain:
Reconciling big data opportunities with healthcare privacy concerns is the same dilemma we face in education. Instructors want to support personalized learning, instruction, and classroom management with online offerings – but the data of underage patrons hangs in the balance. Just as health profiling based on longitudinal data collection raises red flags, so does educational performance profiling. Ethically and practically, youth will always be our Achilles Heel.
Knowing what data vendors are collecting can be difficult to discern. Debbie and Rigele advise a close examination of their Terms of Service and Privacy Policy:
The Privacy Policy is an on-the-ground description of how the vendor operates its site, and should be read in conjunction with the Terms of Service. A link to the Privacy Policy must be placed on the vendor’s homepage and/or product page. The Privacy Policy is a working picture of the company’s current and expected practices related to data use, collection, and sharing, as well as marketing, advertising, access, and security control. While a Privacy Policy lacks the contractual element of a click-through signature, it remains the primary declaration of the company’s privacy practices, and thus may be enforceable against a vendor that breaches those standard practices. Through a close reading of the Privacy Policy, you should be able to learn a great deal about a vendor’s privacy standards; if the language is overly complex or contorted, treat that as indicative of what a vendor may want you to know, or not.
And so we come to intention. Close reading of a Terms of Service and Privacy Policy must be augmented by your common-sense evaluation of a vendor’s corporate intention. Both for-profit and non-profit entities may choose to embed trackers into Web pages to collect information such as navigation patterns and preferences. Certain trackers, such as Facebook’s “like” thumb and Twitter’s blue bird, are visible, but most are hidden. Sometimes these trackers follow the user to other sites to gain additional insight, in order to create a better user experience. Specifically, trackers may run tests on differences in language and image use, look for ways to improve navigation, and fix technical problems.
Check out their post for some practical tips on monitoring what information vendors collect!
Image: “Freedom from Surveillance — Choose Privacy Week 2012,” American Library Association, on Choose Privacy Week
This post is Part 1 in a two-part series highlighting our team members’ work with Choose Privacy Week. This initiative of the American Library Association puts a spotlight on issues of privacy in today’s digital world, such as tracking in online searches. Knowing how your data are used is a component of data literacy, and we are excited to feature our team members’ blog posts on these topics.
Connie wrote about the traces that online actions leave and how they affect teens on the Choose Privacy Week blog. Here is an excerpt from her piece:
…there are universal norms that our students must know about their online presence: what you post can describe you, once a post leaves your device it is no longer in your control, and there is indeed, a digital footprint that gets left behind.
What this means for children and teens is that their online lives can follow them through their offline lives. If they post provocative things or mean things or negative things, they will be perceived by their online friends as those things; even if they are none of those things in their offline lives. One of the hardest ideas for teens to grasp sometimes is the idea that they are often creating a ‘body of work’ that can define them to others.
Online work can certainly have broad implications. Being active online, and managing privacy at the same time, are not always easy, though. Connie suggests establishing norms:
…it is important that we begin thinking about how we will allow our growing children online access while still keeping them protected. While online security is not a typical survival necessity, it is one that can impact our children. As adults, the information we share about our children with our own friends and families is the first step to modeling positive online behavior. Setting up norms that children learn to follow and understand – ‘hand holding’ – will allow parents and educators to loosen that grip, enabling them to expand their access as they grow and demonstrate their abilities to participate positively.
Instruction on best practices for students can take a variety of forms, and Connie goes on to provide examples. Thanks, Connie!
Image: “Choose Privacy Week 2013,” American Library Association, on Choose Privacy Week
One of the first things that I learned for this project was that correlation does not imply causation. While it is easy to be critical of misrepresentations of causation, it is much trickier to apply the concept myself! This week, I was composing a research proposal and struggling to design my experiment so that it tests causation. My first iterations would have only revealed correlations. After working with a research professor to redesign my proposed experiment, I added a qualitative test to determine the effect of the independent variable on the dependent variable. This change would hopefully show causation if it existed. My experience taught me what a slippery concept causation is!
To improve my understanding, I revisited one of the books that our whole team read to grow in our data literacy. Naked Statistics by Charles Wheelan covers basic statistics with real-world examples. Wheelan offers a clear explanation of the difference between correlation and causation:
…a positive or negative association between two variables does not necessarily mean that a change in one of the variables is causing a change in the other. For example, I alluded earlier to a likely positive correlation between a student’s SAT scores and the number of televisions that his family owns. This does not mean that overeager parents can boost their children’s test scores by buying an extra five televisions for the house. Nor does it likely mean that watching lots of television is good for academic achievement.
The most logical explanation for such a correlation would be that highly educated parents can afford a lot of televisions and tend to have children who test better than average. Both the televisions and the test scores are likely caused by a third variable, which is parental education. I can’t prove the correlation between TVs in the home and SAT scores. (The College Board does not provide such data.) However, I can prove that students in wealthy families have higher mean SAT scores than students in less wealthy families. (p. 63)
This illuminating passage helped me grasp the distinction between correlation and causation. Televisions do not cause higher test scores but are correlated with them. Digging deeper reveals other variables — parental education and family wealth — that do affect test scores.
From learning how to apply these concepts and going back to a resource, I now have a much deeper understanding of correlation and causation!
Source: Wheelan, Charles. 2014. Naked Statistics: Stripping the Dread from the Data. New York: W.W. Norton.
Image: “Family watching television 1958” by Evert F. Baumgardner on Wikimedia Commons. Public Domain.