The Basics of Data Literacy
The Basics of Data Literacy

Author: Michael Bowen

Publisher:

Published: 2014

Total Pages: 171

ISBN-13: 9781938946035

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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.

Learning to See Data
Learning to See Data

Author: Ben Jones

Publisher: Data Literacy Press

Published: 2020-12-15

Total Pages: 1

ISBN-13: 1733263454

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This book is associated with the 'Data Literacy Level 1' on-demand online course: https://dataliteracy.com/courses/data-literacy-level-1 For most of us, it's rare to go a full day without coming across data in the form of a chart, map or dashboard. Graphical displays of data are all around us, from performance indicators at work to election trackers on the news to traffic maps on the road. But few of us have received training or instruction in how to actually read and interpret them. How many times have we been misled simply because we aren't aware of the pitfalls to avoid when interpreting data visualizations. Learning to See Data will teach you the different ways that data can be encoded in graphical form, and it will give you a deeper understanding of the way our human visual system interprets these encodings. You will also learn about the most common chart types, and the situations in which they are most appropriate. From basic bar charts to overused pie charts to helpful maps and many more, a wide array of chart types are covered in detail, and conventions, pitfalls, strengths and weaknesses of each of them are revealed. This book will help you develop fluency in the interpretation of charts, an ability that we all need to hone and perfect if we are to make meaningful contributions in the professional, public and personal arenas of life. The principles covered in it also serve as a critical background for anyone looking to create charts that others will be able to understand. "This book is clear and evocative, thorough and thoughtful, and remarkably readable: a marvelous launchpad into the world of data." –Tamara Munzner, Professor, University of British Columbia Computer Science "Everyone of us needs good data literacy skills to survive in the modern world. Without them, it's hard to succeed at work, or survive the onslaught of information (and misinformation) across all our media. Ben's book provides the necessary building blocks for a strong foundation. From that foundation, Ben's approach will inspire you to own the process of developing your skills further." –Andy Cotgreave, Technical Evangelism Director, Tableau

Gender Differences in Computer and Information Literacy
Gender Differences in Computer and Information Literacy

Author: Eveline Gebhardt

Publisher: Springer

Published: 2020-09-11

Total Pages: 73

ISBN-13: 9783030262051

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This open access book presents a systematic investigation into internationally comparable data gathered in ICILS 2013. It identifies differences in female and male students’ use of, perceptions about, and proficiency in using computer technologies. Teachers’ use of computers, and their perceptions regarding the benefits of computer use in education, are also analyzed by gender. When computer technology was first introduced in schools, there was a prevailing belief that information and communication technologies were ‘boys’ toys’; boys were assumed to have more positive attitudes toward using computer technologies. As computer technologies have become more established throughout societies, gender gaps in students’ computer and information literacy appear to be closing, although studies into gender differences remain sparse. The IEA’s International Computer and Information Literacy Study (ICILS) is designed to discover how well students are prepared for study, work, and life in the digital age. Despite popular beliefs, a critical finding of ICILS 2013 was that internationally girls tended to score more highly than boys, so why are girls still not entering technology-based careers to the same extent as boys? Readers will learn how male and female students differ in their computer literacy (both general and specialized) and use of computer technology, and how the perceptions held about those technologies vary by gender.

Data Literacy
Data Literacy

Author: David Herzog

Publisher: SAGE Publications

Published: 2015-01-29

Total Pages: 240

ISBN-13: 1483378675

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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.

Big Data in Education
Big Data in Education

Author: Ben Williamson

Publisher: SAGE

Published: 2017-07-24

Total Pages: 281

ISBN-13: 1526416328

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Big data has the power to transform education and educational research. Governments, researchers and commercial companies are only beginning to understand the potential that big data offers in informing policy ideas, contributing to the development of new educational tools and innovative ways of conducting research. This cutting-edge overview explores the current state-of-play, looking at big data and the related topic of computer code to examine the implications for education and schooling for today and the near future. Key topics include: · The role of learning analytics and educational data science in schools · A critical appreciation of code, algorithms and infrastructures · The rise of ‘cognitive classrooms’, and the practical application of computational algorithms to learning environments · Important digital research methods issues for researchers This is essential reading for anyone studying or working in today′s education environment!

Data Analysis, Interpretation, and Theory in Literacy Studies Research
Data Analysis, Interpretation, and Theory in Literacy Studies Research

Author: Michele Knobel

Publisher: Myers Education Press

Published: 2020-04-17

Total Pages: 249

ISBN-13: 1975502159

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Novice and early career researchers often have difficulty with understanding how theory, data analysis and interpretation of findings “hang together” in a well-designed and theorized qualitative research investigation and with learning how to draw on such understanding to conduct rigorous data analysis and interpretation of their analytic results. Data Analysis, Interpretation, and Theory in Literacy Studies Research demonstrates how to design, conduct and analyze a well put together qualitative research project. Using their own successful studies, chapter authors spell out a problem area, research question, and theoretical framing, carefully explaining their choices and decisions. They then show in detail how they analyzed their data, and why they took this approach. Finally, they demonstrate how they interpreted the results of their analysis, to make them meaningful in research terms. Approaches include interactional sociolinguistics, microethnographic discourse analysis, multimodal analysis, iterative coding, conversation analysis, and multimediated discourse analysis, among others. This book will appeal to beginning researchers and to literacy researchers responsible for teaching qualitative literacy studies research design at undergraduate and graduate levels. Perfect for courses such as: Literacy Research Seminar | Introduction to Qualitative Research | Advanced Research Methods | Studying New Literacies and Media | Research Perspectives in Literacy | Discourse Analysis | Advanced Qualitative Data Analysis | Sociolinguistic Analysis | Classroom Language Research

Digital Literacy
Digital Literacy

Author: Paul Gilster

Publisher: Wiley

Published: 1998-04-03

Total Pages: 292

ISBN-13: 9780471249528

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"Readers leery of ramping onto the information highway and surfers suffering Internet overload will value the solid advice supplied by Gilster." --Booklist. "Paul Gilster's intelligent, sobering look at the Internet is a breath of fresh air." --Amazon.com "This book sheds light on the skills that Web surfers need to separate the digital garbage from the golden nuggets of good data. It's a good place to start for adult newcomers to the information highway." --Courant Now in paper! Digital Literacy provides Internet novices with the basic thinking skills and core competencies they'll need to thrive in an interactive environment so fundamentally different from passive media. PAUL GILSTER (Raleigh, North Carolina) is the author of The Web Navigator and Finding It on the Internet which have sold over 200,000 copies.

Data Literacy in Academic Libraries
Data Literacy in Academic Libraries

Author: Julia Bauder

Publisher: American Library Association

Published: 2021-07-21

Total Pages: 176

ISBN-13: 0838937500

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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.

Data Literacy
Data Literacy

Author: Neil Smalheiser

Publisher: Academic Press

Published: 2017-09-05

Total Pages: 284

ISBN-13: 0128113073

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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

Data Literacy Fundamentals
Data Literacy Fundamentals

Author: Ben Jones

Publisher:

Published: 2020-07-03

Total Pages:

ISBN-13: 9781733263429

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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.