Editors:
- Provides insights into how higher education institutions adopt learning analytics and data mining studies
- Contributions from distinguished international researchers
- Considers theoretical perspectives, innovative technologies,
- implementation, and assessment strategies for learning analytics in higher education
- Includes case studies showing innovative approaches for learning analytics in higher education
Part of the book series: Advances in Analytics for Learning and Teaching (AALT)
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Table of contents (21 chapters)
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Front Matter
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Focussing the Organisation in the Adoption Process
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Front Matter
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Focussing the Learner and Teacher in the Adoption Process
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Front Matter
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Cases of Learning Analytics Adoption
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Front Matter
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About this book
The book aims to advance global knowledge and practice in applying data science to transform higher education learning and teaching to improve personalization, access and effectiveness of education for all. Currently, higher education institutions and involved stakeholders can derive multiple benefits from educational data mining and learning analytics by using different data analytics strategies to produce summative, real-time, and predictive or prescriptive insights and recommendations. Educational data mining refers to the process of extracting useful information out of a large collection of complex educational datasets while learning analytics emphasizes insights and responses to real-time learning processes based on educational information from digital learning environments, administrative systems, and social platforms.
This volume provides insight into the emerging paradigms, frameworks, methods and processes of managing change to better facilitate organizational transformation toward implementation of educational data mining and learning analytics. It features current research exploring the (a) theoretical foundation and empirical evidence of the adoption of learning analytics, (b) technological infrastructure and staff capabilities required, as well as (c) case studies that describe current practices and experiences in the use of data analytics in higher education.Editors and Affiliations
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Curtin University, Perth, Australia
Dirk Ifenthaler
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University of Mannheim, Germany
Dirk Ifenthaler
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Curtin Learning and Teaching, Curtin University, Perth, Australia
David Gibson
Bibliographic Information
Book Title: Adoption of Data Analytics in Higher Education Learning and Teaching
Editors: Dirk Ifenthaler, David Gibson
Series Title: Advances in Analytics for Learning and Teaching
DOI: https://doi.org/10.1007/978-3-030-47392-1
Publisher: Springer Cham
eBook Packages: Education, Education (R0)
Copyright Information: Springer Nature Switzerland AG 2020
Hardcover ISBN: 978-3-030-47391-4Published: 11 August 2020
Softcover ISBN: 978-3-030-47394-5Published: 12 August 2021
eBook ISBN: 978-3-030-47392-1Published: 10 August 2020
Series ISSN: 2662-2122
Series E-ISSN: 2662-2130
Edition Number: 1
Number of Pages: XXXVIII, 434
Number of Illustrations: 30 b/w illustrations, 74 illustrations in colour
Topics: Educational Technology, Learning & Instruction, Higher Education