Data Driven Approaches in Digital Education

2017-09-04
Data Driven Approaches in Digital Education

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  • Author: Élise Lavoué
  • Publisher: Springer
  • ISBN: 331966610X
  • Category : Education
  • Languages : en
  • Pages : 621

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.

Data-Driven School Improvement

2008
Data-Driven School Improvement

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  • Author: Ellen B. Mandinach
  • Publisher: Teachers College Press
  • ISBN: 0807775509
  • Category : Education
  • Languages : en
  • Pages : 296

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

2012-02-21
Data-Driven Decision Making

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  • Author: Chris O'Neal
  • Publisher: International Society for Technology in Education
  • ISBN: 1564844609
  • Category : Education
  • Languages : en
  • Pages : 142

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.

Big Data in Education

2017-07-24
Big Data in Education

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  • Author: Ben Williamson
  • Publisher: SAGE
  • ISBN: 1526416344
  • Category : Education
  • Languages : en
  • Pages : 257

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.

Transforming Teaching and Learning Through Data-Driven Decision Making

2012-04-10
Transforming Teaching and Learning Through Data-Driven Decision Making

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  • Author: Ellen B. Mandinach
  • Publisher: Corwin Press
  • ISBN: 145228346X
  • Category : Education
  • Languages : en
  • Pages : 280

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

Intelligent Systems and Learning Data Analytics in Online Education

2021-06-15
Intelligent Systems and Learning Data Analytics in Online Education

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  • Author: Santi Caballé
  • Publisher: Academic Press
  • ISBN: 0128231270
  • Category : Computers
  • Languages : en
  • Pages : 427

Intelligent Systems and Learning Data Analytics in Online Education provides novel artificial intelligence (AI) and analytics-based methods to improve online teaching and learning. This book addresses key problems such as attrition and lack of engagement in MOOCs and online learning in general. This book explores the state of the art of artificial intelligence, software tools and innovative learning strategies to provide better understanding and solutions to the various challenges of current e-learning in general and MOOC education. In particular, Intelligent Systems and Learning Data Analytics in Online Education shares stimulating theoretical and practical research from leading international experts. This publication provides useful references for educational institutions, industry, academic researchers, professionals, developers, and practitioners to evaluate and apply. Presents the application of innovative AI techniques to collaborative learning activities Offers strategies to provide automatic and effective tutoring to students’ activities Offers methods to collect, analyze and correctly visualize learning data in educational environments

Data Driven Differentiation in the Standards-Based Classroom

2014-05-22
Data Driven Differentiation in the Standards-Based Classroom

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  • Author: Gayle H. Gregory
  • Publisher: Corwin Press
  • ISBN: 1483332500
  • Category : Education
  • Languages : en
  • Pages : 329

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

Educational Data Science

2023
Educational Data Science

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  • Author: Alejandro Peña-Ayala
  • Publisher: Springer Nature
  • ISBN: 9819900263
  • Category : Artificial intelligence
  • Languages : en
  • Pages : 299

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!

Enhancing Education With Intelligent Systems and Data-Driven Instruction

2024-03-04
Enhancing Education With Intelligent Systems and Data-Driven Instruction

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  • Author: Madhulika Bhatia
  • Publisher:
  • ISBN:
  • Category : Education
  • Languages : en
  • Pages : 0

In the dynamic environment of education, the traditional methods employed by educators are struggling to keep pace with the evolving needs of students in the 21st century. The challenge lies in fostering an environment that not only engages students but also equips them with the skills essential for the modern world. Teachers find themselves navigating a complex terrain where outdated pedagogical approaches fall short of unlocking the full potential of diverse learning styles and unique talents within their classrooms. Enhancing Education With Intelligent Systems and Data-Driven Instruction is a groundbreaking book that goes beyond the constraints of conventional teaching methods, offering a comprehensive guide that inspires and equips educators with innovative tools and approaches. From integrating innovative technology to cultivating collaborative learning environments, the book provides a roadmap for educators to reimagine their teaching practices. By embracing student-centered approaches, fostering diversity, and utilizing digital tools effectively, this book empowers teachers to transform their classrooms into dynamic hubs of inspiration, motivation, and empowerment.

Data-Driven Design for Computer-Supported Collaborative Learning

2021-08-11
Data-Driven Design for Computer-Supported Collaborative Learning

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  • Author: Lanqin Zheng
  • Publisher: Springer Nature
  • ISBN: 981161718X
  • Category : Education
  • Languages : en
  • Pages : 162

This book highlights the importance of design in computer-supported collaborative learning (CSCL) by proposing data-driven design and assessment. It addresses data-driven design, which focuses on the processing of data and on improving design quality based on analysis results, in three main sections. The first section explains how to design collaborative learning activities based on data-driven design approaches, while the second shares illustrative examples of computer-supported collaborative learning activities. In turn, the third and last section demonstrates how to evaluate design quality and the fidelity of enactment based on design-centered research. The book features several examples of innovative data-driven design approaches to optimizing collaborative learning activities; highlights innovative CSCL activities in authentic learning environments; demonstrates how learning analytics can be used to optimize CSCL design; and discusses the design-centered research approach to evaluating the alignment between design and enactment in CSCL. Given its scope, it will be of interest to a broad readership including researchers, educators, practitioners, and students in the field of collaborative learning, as well as the rapidly growing community of people who are interested in optimizing learning performance with CSCL.