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Learning Analytics Goes to School : A Collaborative Approach to Improving Education - Andrew Krumm

Learning Analytics Goes to School

A Collaborative Approach to Improving Education

By: Andrew Krumm, Barbara Means, Marie Bienkowski

Paperback | 25 January 2018 | Edition Number 1

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Learning Analytics for Educational Improvement presents a framework for understanding how to conduct new forms of education research and enact new approaches to improving education practice made possible by big data. Although application of big data techniques to learning and education is quite new, learning analytics and educational data mining have been growing rapidly, fueled by the visible successes of applications of data analytics in the commercial and political realms. This book serves as a one-stop reference for a variety of learning analytics tools and techniques and makes those methods meaningful by describing their application in a wide range of real-world education contexts.
Industry Reviews

"Learning Analytics Goes to School provides a clear and practical overview of how to harness excitement over big data and learning analytics in education for educational improvement at scale. The approach outlined by the authors provides concrete guidance for how research-practice partnerships can use large data sets, new analytic techniques, and methods of improvement science to design and test solutions to problems of practice. It is a must read and great reference book for those new to educational data science, as well as those seeking to embrace a more collaborative approach to education research."

-William R. Penuel, Professor of Learning Sciences and Human Development, University of Colorado, USA

"Learning Analytics Goes to School is for anyone interested in understanding the growing use of data pertaining to students and their digitally-mediated learning activities. This book provides a thorough and thoughtful discussion of the primary issues related to educational data, and a step-by-step guide to addressing these issues by implementing a process called 'Collaborative Data-intensive Improvement' (CDI). The authors demystify jargon, lay out the basic concepts of data science for education, and provide a roadmap for creating research-practice partnerships aimed at producing reliably positive outcomes for all students. Written in a style that is both professional and accessible, this will be a valuable resource for teachers and administrators as well as researchers."

-Stephanie D. Teasley, Research Professor in the School of Information at the University of Michigan, and President of the Society for Leaning Analytics Research (SoLAR), USA

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