Learning Analytics Goes to School: A Collaborative Approach to Improving Education

Author:   Andrew Krumm ,  Barbara Means ,  Marie Bienkowski
Publisher:   Taylor & Francis Ltd
ISBN:  

9781138121836


Pages:   178
Publication Date:   25 January 2018
Format:   Paperback
Availability:   In Print   Availability explained
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Learning Analytics Goes to School: A Collaborative Approach to Improving Education


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Full Product Details

Author:   Andrew Krumm ,  Barbara Means ,  Marie Bienkowski
Publisher:   Taylor & Francis Ltd
Imprint:   Routledge
Weight:   0.272kg
ISBN:  

9781138121836


ISBN 10:   1138121835
Pages:   178
Publication Date:   25 January 2018
Audience:   College/higher education ,  Professional and scholarly ,  Tertiary & Higher Education ,  Professional & Vocational
Format:   Paperback
Publisher's Status:   Active
Availability:   In Print   Availability explained
This item will be ordered in for you from one of our suppliers. Upon receipt, we will promptly dispatch it out to you. For in store availability, please contact us.

Table of Contents

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 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


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


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


Author Information

Dr. Andrew Krumm is Director of Learning Analytics Research at Digital Promise, a nonprofit organization that brings together the expertise of educators, researchers, and technology developers in the interest of improving teaching and learning. Dr. Krumm has launched multiple research-practice partnerships and his research addresses the use of data-intensive research techniques to improve learning environments. Dr. Barbara Means is Executive Director for Learning Sciences Research at Digital Promise. Formerly the founder and director of the Center for Technology in Learning at SRI International, Dr. Means is a nationally recognized expert in defining issues and approaches for evaluating the implementation and efficacy of technology-supported educational innovations. Dr. Marie Bienkowski is Director of the Center for Technology in Learning at SRI International, a nonprofit research and development organization based in Silicon Valley that takes innovative ideas and technologies from the laboratory to the end-user and marketplace. Dr. Bienkowski is a computer scientist and education researcher leading efforts to improve student learning, effective teaching, and meaningful assessment.

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