Information And Data Literacy
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Author | : Julia Bauder |
Publisher | : American Library Association |
Total Pages | : 176 |
Release | : 2021-07-21 |
Genre | : Language Arts & Disciplines |
ISBN | : 0838937500 |
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.
Author | : Jake Carlson |
Publisher | : Purdue University Press |
Total Pages | : 282 |
Release | : 2015-01-15 |
Genre | : Language Arts & Disciplines |
ISBN | : 1612493521 |
Given the increasing attention to managing, publishing, and preserving research datasets as scholarly assets, what competencies in working with research data will graduate students in STEM disciplines need to be successful in their fields? And what role can librarians play in helping students attain these competencies? In addressing these questions, this book articulates a new area of opportunity for librarians and other information professionals, developing educational programs that introduce graduate students to the knowledge and skills needed to work with research data. The term "data information literacy" has been adopted with the deliberate intent of tying two emerging roles for librarians together. By viewing information literacy and data services as complementary rather than separate activities, the contributors seek to leverage the progress made and the lessons learned in each service area. The intent of the publication is to help librarians cultivate strategies and approaches for developing data information literacy programs of their own using the work done in the multiyear, IMLS-supported Data Information Literacy (DIL) project as real-world case studies. The initial chapters introduce the concepts and ideas behind data information literacy, such as the twelve data competencies. The middle chapters describe five case studies in data information literacy conducted at different institutions (Cornell, Purdue, Minnesota, Oregon), each focused on a different disciplinary area in science and engineering. They detail the approaches taken, how the programs were implemented, and the assessment metrics used to evaluate their impact. The later chapters include the "DIL Toolkit," a distillation of the lessons learned, which is presented as a handbook for librarians interested in developing their own DIL programs. The book concludes with recommendations for future directions and growth of data information literacy. More information about the DIL project can be found on the project's website: datainfolit.org.
Author | : Michael Bowen |
Publisher | : |
Total Pages | : 171 |
Release | : 2014 |
Genre | : Graphic methods |
ISBN | : 9781938946035 |
Here's the ideal statistics book for teachers with no statistical background. Written in an informal style with easy-to-grasp examples, The Basics of Data Literacy teaches you how to help your students understand data. Then, in turn, they learn how to collect, summarize, and analyze statistics inside and outside the classroom. The books 10 succinct chapters provide an introduction to types of variables and data, ways to structure and interpret data tables, simple statistics, and survey basics from a student perspective. The appendices include hands-on activities tailored to middle and high school investigations. Because data are so central to many of the ideas in the Next Generation Science Standards, the ability to work with such information is an important science skill for both you and your students. This accessible book will help you get over feeling intimidated as your students learn to evaluate messy data on the Internet, in the news, and in future negotiations with car dealers and insurance agents.
Author | : David Herzog |
Publisher | : SAGE Publications |
Total Pages | : 240 |
Release | : 2015-01-29 |
Genre | : Language Arts & Disciplines |
ISBN | : 1483378675 |
A practical, skill-based introduction to data analysis and literacy We are swimming in a world of data, and this handy guide will keep you afloat while you learn to make sense of it all. In Data Literacy: A User's Guide, David Herzog, a journalist with a decade of experience using data analysis to transform information into captivating storytelling, introduces students and professionals to the fundamentals of data literacy, a key skill in today’s world. Assuming the reader has no advanced knowledge of data analysis or statistics, this book shows how to create insight from publicly-available data through exercises using simple Excel functions. 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.
Author | : Neil Smalheiser |
Publisher | : Academic Press |
Total Pages | : 284 |
Release | : 2017-09-05 |
Genre | : Science |
ISBN | : 0128113073 |
Data Literacy: How to Make Your Experiments Robust and Reproducible provides an overview of basic concepts and skills in handling data, which are common to diverse areas of science. Readers will get a good grasp of the steps involved in carrying out a scientific study and will understand some of the factors that make a study robust and reproducible.The book covers several major modules such as experimental design, data cleansing and preparation, statistical analysis, data management, and reporting. No specialized knowledge of statistics or computer programming is needed to fully understand the concepts presented. This book is a valuable source for biomedical and health sciences graduate students andresearchers, in general, who are interested in handling data to make their research reproducibleand more efficient. - Presents the content in an informal tone and with many examples taken from the daily routine at laboratories - Can be used for self-studying or as an optional book for more technical courses - Brings an interdisciplinary approach which may be applied across different areas of sciences
Author | : Kristin Fontichiaro |
Publisher | : Maize Books |
Total Pages | : 0 |
Release | : 2017 |
Genre | : Education |
ISBN | : 9781607854524 |
Knowing how to recognize the role data plays in our lives is critical to navigating today's complex world. In this volume, you'll find two kinds of professional development tools to support that growth. Part I contains pre-made professional development via links to webinars from the 2016 and 2017 4T Virtual Conference on Data Literacy, along with discussion questions and activities that can animate conversations around data in your school. Part II explores data "in the wild" with case studies pulled from the headlines, along with provocative discussion questions, professionals and students alike can explore multiple perspectives at play with Big Data, data privacy, personal data management, ethical data use, and citizen science.
Author | : Ellen B. Mandinach |
Publisher | : Teachers College Press |
Total Pages | : 177 |
Release | : 2016-04-01 |
Genre | : Education |
ISBN | : 0807757535 |
Data literacy has become an essential skill set for teachers as education becomes more of an evidence-based profession. Teachers in all stages of professional growth need to learn how to use data effectively and responsibly to inform their teaching practices. This groundbreaking resource describes data literacy for teaching, emphasizing the important relationship between data knowledge and skills and disciplinary and pedagogical content knowledge. Case studies of emerging programs in schools of education are used to illustrate the key components needed to integrate data-driven decisionmaking into the teaching curricula. The book offers a clear path for change while also addressing the inherent complexities associated with change. Data Literacy for Educators provides concrete strategies for schools of education, professional developers, and school districts.
Author | : Serap Kurbanoglu |
Publisher | : Springer |
Total Pages | : 686 |
Release | : 2013-12-13 |
Genre | : Education |
ISBN | : 3319039199 |
This book constitutes the refereed proceedings of the European Conference on Information Literacy, ECIL 2013, held in Istanbul Turkey, in October 2013. The 73 revised full papers presented together with two keynotes, 9 invited papers and four doctoral papers were carefully reviewed and selected from 236 submissions. The papers are organized in topical sections on overview and research; policies and strategies; theoretical framework; related concepts; citizenship and digital divide; disadvantaged groups; information literacy for the workplace and daily life; information literacy in Europe; different approaches to information literacy; teaching and learning information literacy; information literacy instruction; assessment of information literacy; information literacy and K-12; information literacy and higher education; information literacy skills of LIS students; librarians, libraries and ethics.
Author | : Kevin Hanegan |
Publisher | : |
Total Pages | : 268 |
Release | : 2020-11-27 |
Genre | : |
ISBN | : 9780578639871 |
This book presents a 6-phase, 12-step process to help those at all levels of an organization use their knowledge, skills, and experience to make data-informed decisions that can help transform their companies-and sometimes, even the world.
Author | : Ben Jones |
Publisher | : |
Total Pages | : |
Release | : 2020-07-03 |
Genre | : |
ISBN | : 9781733263429 |
The vast majority of people in the world today do not receive a formal education that adequately prepares them for the level of data literacy required of them in their careers and by their communities. As a result, many are being left behind by the transition to data-driven dialogues and decisions all around them, and they're seeking ways to break down the barriers that are preventing them from participating. Data Literacy Fundamentals covers foundational topics such as the overall goal of data, various ways of measuring and categorizing the world, five different forms of data analysis and when they apply, pros and cons related to how we display data in tabular or graphic form, and the way teams work together to convert data into insight.This book has been written for anyone who is just getting started with data and who wants to feel more confident in their understanding of what it is, what it isn't, and what it's used for. This invaluable resource will cure you of your "dataphobia", teach you the basic concepts of data, and set you on a path of learning that will ultimately result in fluency in the language of data.