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Adoption of Data Analytics in Higher Education Learning and Teaching

  • Book
  • © 2020

Overview

Editors:
  1. Dirk Ifenthaler

    1. Curtin University, Perth, Australia
      University of Mannheim, Germany

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    You can also search for this editor in PubMed   Google Scholar

  2. David Gibson

    1. Curtin Learning and Teaching, Curtin University, Perth, Australia

    View editor publications

    You can also search for this editor in PubMed   Google Scholar

  • 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)

  1. Front Matter

    Pages i-xxxviii
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  2. Focussing the Organisation in the Adoption Process

    1. Front Matter

      Pages 1-1
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    2. Adoption of Learning Analytics

      • David Gibson, Dirk Ifenthaler
      Pages 3-20

    3. The Politics of Learning Analytics

      • Reem Al-Mahmood
      Pages 21-38

    4. A Framework to Support Interdisciplinary Engagement with Learning Analytics

      • Stephanie J. Blackmon, Robert L. Moore
      Pages 39-52

    5. The Framework of Learning Analytics for Prevention, Intervention, and Postvention in E-Learning Environments

      • Muhittin Şahin, Halil Yurdugül
      Pages 53-69

    6. The LAVA Model: Learning Analytics Meets Visual Analytics

      • Mohamed Amine Chatti, Arham Muslim, Manpriya Guliani, Mouadh Guesmi
      Pages 71-93

    7. See You at the Intersection: Bringing Together Different Approaches to Uncover Deeper Analytics Insights

      • David Paul Fulcher, Margaret Wallace, Maarten de Laat
      Pages 95-111

    8. “Trust the Process!”: Implementing Learning Analytics in Higher Education Institutions

      • Armin Egetenmeier, Miriam Hommel
      Pages 113-134

  3. Focussing the Learner and Teacher in the Adoption Process

    1. Front Matter

      Pages 135-135
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    2. Students’ Adoption of Learner Analytics

      • Carly Palmer Foster
      Pages 137-158

    3. Learning Analytics and the Measurement of Learning Engagement

      • Dirk Tempelaar, Quan Nguyen, Bart Rienties
      Pages 159-176

    4. Stakeholder Perspectives (Staff and Students) on Institution-Wide Use of Learning Analytics to Improve Learning and Teaching Outcomes

      • Ann Luzeckyj, Deborah S. West, Bill K. Searle, Daniel P. Toohey, Jessica J. Vanderlelie, Kevin R. Bell
      Pages 177-200

    5. How and Why Faculty Adopt Learning Analytics

      • Natasha Arthars, Danny Y.-T. Liu
      Pages 201-220

    6. Supporting Faculty Adoption of Learning Analytics within the Complex World of Higher Education

      • George Rehrey, Marco Molinaro, Dennis Groth, Linda Shepard, Caroline Bennett, Warren Code et al.
      Pages 221-239

    7. It’s All About the Intervention: Reflections on Building Staff Capacity for Using Learning Analytics to Support Student Success

      • Ed Foster, Rebecca Siddle, Pete Crowson, Pieterjan Bonne
      Pages 241-256

    8. Experiences in Scaling Up Learning Analytics in Blended Learning Scenarios

      • Vlatko Lukarov, Ulrik Schroeder
      Pages 257-282

  4. Cases of Learning Analytics Adoption

    1. Front Matter

      Pages 283-283
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    2. Building Confidence in Learning Analytics Solutions: Two Complementary Pilot Studies

      • Armelle Brun, Benjamin Gras, Agathe Merceron
      Pages 285-303

    3. Leadership and Maturity: How Do They Affect Learning Analytics Adoption in Latin America?

      • Isabel Hilliger, Mar Pérez-Sanagustín, Ronald Pérez-Álvarez, Valeria Henríquez, Julio Guerra, Miguel Ángel Zuñiga-Prieto et al.
      Pages 305-326
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Keywords

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

  • Curtin University, Perth, Australia

    Dirk Ifenthaler

  • University of Mannheim, Germany

    Dirk Ifenthaler

  • 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

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