Library Guides: Teaching Information Literacy: Resources for Faculty: Data Literacy

Introduction to Data Literacy

Introduction to Data Literacy (Datacamp)
Course Description: Data is all around us, which makes data literacy an essential life skill. It is a skill that empowers you to ask the right questions about data and choose the right tools to read, interpret and communicate data. This non-technical course will equip you with the necessary knowledge and skill to feel confident around data and understand how data can be used to gain actionable insights and drive change.

Through hands-on exercises, you’ll learn how to get from data to insights, how data drives decision-making, how to collect and manage data, the four types of analytics and how to use storytelling and visualization to improve your data communication, and more.
Gartner Data Literacy Defined
Gartner defines data literacy as the ability to read, write and communicate data in context — with an understanding of the data sources and constructs, analytical methods and techniques applied — and the ability to describe the use-case application and resulting business value or outcome.
What is Data Literacy (Michelle Knight-Feb. 16, 2022)
Data literacy describes the ability to read, work with, analyze, and argue with data.
Data Information Literacy
Welcome to the working space for the Institute of Museum and Library Services (IMLS) funded research project investigating data information literacy (DIL) needs of e-scientists. With the continued evolution of technology driven research or "e-science" impacting the skills necessary for effective data management and curation, a curriculum designed to effectively prepare the next generation of scientists for the dynamic nature of research becomes necessary. This project, consisting of research teams from Purdue University, the University of Minnesota, the University of Oregon, and Cornell University, aims to develop and implement a DIL curriculum in conjunction with university faculty to address these needs.
Data Literacy (Ivy Wigmore) TechTarget
Data literacy is the ability to derive meaningful information from data, just as literacy in general is the ability to derive information from the written word.
Strategies for Teaching Data Literacy (Berkley School of Information)
Teachers’ Ability to Use Data to Inform Instruction: Challenges and Supports
Research published by the U.S. Department of Education on teachers' ability to use data. The report recommends specific learning outcomes for teachers themselves, who may then use many of those same objectives to measure data literacy among students: .

The U.S. Department of Education research on Teachers' Ability to Use Data to Inform Instruction recommends specific learning outcomes for teachers themselves, who may then use many of those same objectives to measure data literacy among students:

Location: finding relevant pieces of data from the original source.
Comprehension: understanding how the data was collected and what it means.
Interpretation: figuring out what the data means and why it matters.
Analysis: asking questions about the data to identify findings and implications.
Integration: linking data to classroom practice for instruction and assessment.
Collaboration: working together with other analysts or with multiple datasets.
Communication: being able to share insights and information from the data.

Tools and Utilities

Kaggle
Open access to datasets, code, courses, and more
OpenRefine
An open source utility for data manipulation

Library Guides on Data Literacy

Data Literacies (Washington University in St. Louis)
The amount of data produced, the democratization of data, and the increase of data tools have increased the need for data literacy among the general population and in organizations. Data literacy means the ability to find, evaluate the source and quality of the data, be able to understand the data, manipulate it, ask questions of it, make an argument from it and assess the arguments of others.
Data Literacy Library Guide (Eastern Michigan University Library)
A guide for faculty interested in learning about data literacy.
SEE TEACHING TOOLS FOR VIDEO TUTORIAL ON DATA LITERACY
Information Literacy: 21. Data Management
Provides several graphics describing data literacy

Data Literacy and the Academic Library

Data Literacy in Academic Libraries by Julia Bauder (Editor)
Call Number: ebook
ISBN: 9780838937495
Publication Date: 2021-06-22
The strategies and initiatives detailed in this book will empower data librarians, information literacy instructors, library liaisons, and reference staff to successfully incorporate data literacy into their work. We live in a data-driven world, much of it processed and served up by increasingly complex algorithms, and evaluating its quality requires its own skillset. As a component of information literacy, it's crucial that students learn how to think critically about statistics, data, and related visualizations. Here, Bauder and her fellow contributors show how librarians are helping students to access, interpret, critically assess, manage, handle, and ethically use data. Offering readers a roadmap for effectively teaching data literacy at the undergraduate level, this volume explores such topics as the potential for large-scale library/faculty partnerships to incorporate data literacy instruction across the undergraduate curriculum; how the principles of the ACRL Framework for Information Literacy for Higher Education can help to situate data literacy within a broader information literacy context; a report on the expectations of classroom faculty concerning their students' data literacy skills; various ways that librarians can partner with faculty; case studies of two initiatives spearheaded by Purdue University Libraries and University of Houston Libraries that support faculty as they integrate more work with data into their courses; Barnard College's Empirical Reasoning Center, which provides workshops and walk-in consultations to more than a thousand students annually; how a one-shot session using the PolicyMap data mapping tool can be used to teach students from many different disciplines; diving into quantitative data to determine the truth or falsity of potential "fake news" claims; and a for-credit, librarian-taught course on information dissemination and the ethical use of information.

Koltay (2017) Data literacy for researchers and data librarians

Books for Possible Purchase???

Data Literacy: A User′s Guide 1st Edition (Herzog)
2016 Sage
Extensively illustrated, step-by-step instructions within a concise, yet comprehensive, reference will help readers identify, obtain, evaluate, clean, analyze and visualize data. A concluding chapter introduces more sophisticated data analysis methods and tools including database managers such as Microsoft Access and MySQL and standalone statistical programs such as SPSS, SAS and R.
The Data Literacy Cookbook (2022) ALA
Kelly Getz and Meryl Brodsky
Today’s students create and are confronted with many kinds of data in multiple formats. Data literacy enables students and researchers to access, interpret, critically assess, manage, handle, and ethically use data.

The Data Literacy Cookbook includes a variety of approaches to and lesson plans for teaching data literacy, from simple activities to self-paced learning modules to for-credit and discipline-specific courses. Sixty-five recipes are organized into nine sections based on learning outcomes

Creating a Data Literacy Course

Cooking Up a Data Literacy Course by Claire Nickerson MLIS, Fort Hays State University
Abstract
This asynchronous online course, Interdisciplinary Studies 815: Introduction to Data, was developed for graduate students in the information analysis and communication concentration of the Fort Hays State University master of liberal studies degree. The course is designed for professionals who need to make data-driven decisions such as educators, policy makers, and nonprofit employees. It is a survey course, so it does not go into great depth on any of the topics covered but rather provides a basic grounding for developing further data literacy skills. It exclusively uses zero-cost resources, including openly licensed content, library-licensed e-books and articles, and free online content. The course uses weekly mini-assessments as well as three major assignments: a data memo, a data visualization, and a final video presentation.

Online Courses and Tutorials

Data Literacy Online Courses and Tutorials (Rutgers)
This is a collection of information resources on data literacy. Users can find links to courses, workshops, tools, tutorials, videos, webinars, and other resources related to data literacy.
Data Literacies
In this workshop we will be discussing the basics of research data, in terms of its material, transformation, and presentation. We will also engage with the ethical dimensions of what it means to work with data, from collection to visualization to representation. This workshop is taught by Di Yoong. They are currently a PhD candidate in Critical Social/Personality Psychology at CUNY, The Graduate Center (GC).

Teaching Information Literacy: Resources for Faculty: Data Literacy

Work in Progress