Learning analytics goes to school : a collaborative approach to improving education
- Responsibility
- Andrew Krumm, Barbara Means, and Marie Bienkowski.
- Publication
- New York : Routledge, Taylor & Francis Group, 2018.
- Copyright notice
- ©2018
- Physical description
- xi, 178 pages : illustrations ; 23 cm
At the library
Education Library (Cubberley)
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| Call number | Status |
|---|---|
| LB1028.43 .K78 2018 |
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Description
Creators/Contributors
- Author/Creator
- Krumm, Andrew, author.
- Contributor
- Means, Barbara, 1949- author.
- Bienkowski, Marie, author.
Contents/Summary
- Bibliography
- Includes bibliographical references and index.
- Contents
-
- 1. Introduction
- 2. Data Used in Educational Data-Intensive Research
- 3. Methods Used in Educational Data-Intensive Research
- 4. Legal and Ethical Issues in Using Educational Data
- 5. Foundations of Collaborative Applications of Educational Data Mining and Learning Analytics
- 6. Supporting Conditions for Collaborative Data-Intensive Improvement
- 7. Five Phases of Collaborative Data-Intensive Improvement
- 8. Lessons Learned and Prospects for the Future.
- (source: Nielsen Book Data)
- Summary
-
Learning Analytics Goes to School presents a framework for engaging in education research and improving education practice through the use of newly available data sources and analytical approaches. The application of data-intensive research techniques to understanding and improving learning environments has been growing at a rapid pace. In this book, three leading researchers convey lessons from their own experiences-and the current state of the art in educational data mining and learning analytics more generally-by providing an explicit set of tools and processes for engaging in collaborative data-intensive improvement.
(source: Nielsen Book Data)
Subjects
Bibliographic information
- Publication date
- 2018
- Copyright date
- 2018
- ISBN
- 9781138121829 (hardback)
- 1138121827 (hardback)
- 9781138121836 (pbk.)
- 1138121835 (pbk.)
- 9781315650722 (ebk)
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