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Data Driven Approaches in Digital Education

Author: Élise Lavoué

Publisher: Springer

Published: 2017-09-04

Total Pages: 621

ISBN-13: 331966610X

This book constitutes the proceedings of the 12th European Conference on Technology Enhanced Learning, EC-TEL 2017, held in Tallinn, Estonia, in September 2017. The 24 full papers, 23 short papers, 6 demo papers, and 22 poster papers presented in this volume were carefully reviewed and selected from 141 submissions. The theme for the 12th EC-TEL conference on Data Driven Approaches in Digital Education' aims to explore the multidisciplinary approaches thateectively illustrate how data-driven education combined with digital education systems can look like and what are the empirical evidences for the use of datadriven tools in educational practices.

Big Data in Education

Author: Ben Williamson

Publisher: SAGE

Published: 2017-07-24

Total Pages: 257

ISBN-13: 1526416344

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This cutting-edge overview explores big data and the related topic of computer code, examining the implications for education and schooling for today and the near future.

Data-Driven School Improvement

Author: Ellen B. Mandinach

Publisher: Teachers College Press

Published: 2008

Total Pages: 296

ISBN-13: 0807775509

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The first comprehensive examination of the field, this book brings together stakeholders representing a variety of perspectives to explore how educators actually use data and technology tools to achieve lasting improvement in student performance. Contributors: David V. Abbott, Carrie Amon, Jonathan Bertfield, Cornelia Brunner, Fred Carrigg, Jere Confrey, Katherine Conoly, Valerie M. Crawford, Chris Dede, John Gasko, Greg Gunn, Juliette Heinze, Naomi Hupert, Sherry P. King, Mary Jane Kurabinski, Daniel Light, Lisa Long, Michael Merrill, Liane Moody, William R. Penuel, Luz M. Rivas, Mark S. Schlager, John Stewart, Sam Stringfield, Ronald Thorpe, Yukie Toyama, Jeffrey C. Wayman, and Viki M. Young. If you want to understand usable knowledge, read Data-Driven School Improvement. Ellen Condliffe Lagemann, Harvard University It is reassuring to know that at least some of the data being generated in our data-driven age are being used to make wiser decisions. We can all learn from these illustrative accounts. David C. Berliner, Mary Lou Fulton College of Education, Arizona State University Replete with examples from real schools and districts, this volume provides a multi-layered portrait of what it takes to establish a culture of data use. Readers will come away with an appreciation of the systemic changes needed to reap the full potential of data-driven decision making. Barbara Means, Center for Technology in Learning, SRI International

Data-Driven Decision Making

Author: Chris O'Neal

Publisher: International Society for Technology in Education

Published: 2012-02-21

Total Pages: 149

ISBN-13: 1564844609

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This workbook will serve as your guide to incorporating the data-driven decision making process into your organization’s culture and behavior. O’Neal leads you through setting up teams; warehousing, accessing, and examining data; and finally reflecting on your process. Understand what’s happening in your school environment and how you can make better decisions that will keep you on a path to success.

Contemporary Technologies in Education

Author: Olusola O. Adesope

Publisher: Springer

Published: 2018-11-08

Total Pages: 268

ISBN-13: 3319896806

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This edited volume provides a critical discussion of theoretical, methodological, and practical developments of contemporary forms of educational technologies. Specifically, the book discusses the use of contemporary technologies such as the Flipped Classroom (FC), Massive Open Online Course (MOOC), Social Media, Serious Educational Games (SEG), Wikis, innovative learning software tools, and learning analytic approach for making sense of big data. While some of these contemporary educational technologies have been touted as panaceas, researchers and developers have been faced with enormous challenges in enhancing the use of these technologies to arouse student attention and improve persistent motivation, engagement, and learning. Hence, the book examines how contemporary technologies can engender student motivation and result in improved engagement and learning. Each chapter also discusses the road ahead and where appropriate, uses the current trend to predict future affordances of technologies.

Transforming Teaching and Learning Through Data-Driven Decision Making

Author: Ellen B. Mandinach

Publisher: Corwin Press

Published: 2012-04-10

Total Pages: 280

ISBN-13: 145228346X

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Connect data and instruction to improve practice Gathering data and using it to inform instruction is a requirement for many schools, yet educators are not necessarily formally trained in how to do it. This book helps bridge the gap between classroom practice and the principles of educational psychology. Teachers will find cutting-edge advances in research and theory on human learning and teaching in an easily understood and transferable format. The text’s integrated model shows teachers, school leaders, and district administrators how to establish a data culture and transform quantitative and qualitative data into actionable knowledge based on: Assessment Statistics Instructional and differentiated psychology Classroom management

OECD Digital Education Outlook 2021 Pushing the Frontiers with Artificial Intelligence, Blockchain and Robots

Author: OECD

Publisher: OECD Publishing

Published: 2021-06-08

Total Pages: 252

ISBN-13: 9264904646

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How might digital technology and notably smart technologies based on artificial intelligence (AI), learning analytics, robotics, and others transform education? This book explores such question. It focuses on how smart technologies currently change education in the classroom and the management of educational organisations and systems.

Data Driven Differentiation in the Standards-Based Classroom

Author: Gayle H. Gregory

Publisher: Corwin Press

Published: 2014-05-22

Total Pages: 329

ISBN-13: 1483332500

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Collect the data you need to reach every student! Veteran educators Gregory and Kuzmich provide user-friendly techniques for data-gathering, helping you to differentiate instruction. This informative book is now fully updated to support the Common Core and other key standards, and includes: Step-by-step guidance on gathering data to improve classroom dynamics, pinpoint student learning styles, adjust lessons for different learners, and inform diagnostic teaching and assessment Techniques for using data to refresh and strengthen curriculum, including numerous unit and lesson plans fully linked with the Common Core A wealth of templates for fast and simple data collection Updated differentiation strategies for the Common Core and other key standards, including the Career and College Readiness Standards and the Standards of Mathematical Practice

Data-Driven Science and Engineering

Author: Steven L. Brunton

Publisher: Cambridge University Press

Published: 2022-05-05

Total Pages: 615

ISBN-13: 1009098489

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A textbook covering data-science and machine learning methods for modelling and control in engineering and science, with Python and MATLAB®.

Educational Data Science

Author: Alejandro Peña-Ayala

Publisher: Springer Nature

Published: 2023

Total Pages: 299

ISBN-13: 9819900263

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This book describes theoretical elements, practical approaches, and specialized tools that systematically organize, characterize, and analyze big data gathered from educational affairs and settings. Moreover, the book shows several inference criteria to leverage and produce descriptive, explanatory, and predictive closures to study and understand education phenomena at in classroom and online environments. This is why diverse researchers and scholars contribute with valuable chapters to ground with well-sounded theoretical and methodological constructs in the novel field of Educational Data Science (EDS), which examines academic big data repositories, as well as to introduces systematic reviews, reveals valuable insights, and promotes its application to extend its practice. EDS as a transdisciplinary field relies on statistics, probability, machine learning, data mining, and analytics, in addition to biological, psychological, and neurological knowledge about learning science. With this in mind, the book is devoted to those that are in charge of educational management, educators, pedagogues, academics, computer technologists, researchers, and postgraduate students, who pursue to acquire a conceptual, formal, and practical landscape of how to deploy EDS to build proactive, real- time, and reactive applications that personalize education, enhance teaching, and improve learning!